"\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2021, e-ISSN: 2811-3594 \n\n\n\n\n\n\n\n\n\n\n\nOFFICIAL JOURNAL \n\n\n\nRESEARCH ARTICLE \n\n\n\nPage 16 of 22  \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nPolymorphism Survey between Mahsuri Mutant and Tetep using \nSSR Markers \n\n\n\n \nSiti Nurdiyana Yusof 1,2, Faiz Ahmad1,2, Waitulfifika Asrapil1, Siti Norvahida \n\n\n\nHisham1,2, Affrida Abu Hassan2, Nor\u2019 Aishah Hasan3, Noraziyah Abd Aziz \nShamsudin1 and Abdul Rahim Harun2 \n\n\n\n\n\n\n\n1 Department of Biological Sciences and Biotechnology, Faculty of Science and Technology,  \n\n\n\nUniversiti Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia \n2 Agrotechnology and Biosciences Division, Malaysian Nuclear Agency,  \n\n\n\nKajang, Selangor, 43000, Malaysia \n3 Faculty of Applied Science, Universiti Teknologi MARA, Cawangan Negeri Sembilan  \n\n\n\nKampus Kuala Pilah, Negeri Sembilan, Malaysia. \n \n\n\n\n*Corresponding author: faiz@nm.gov.my  \n\n\n\n\n\n\n\n\n\n\n\nIntroduction \nRice blast, which is caused by the fungus \nMagnaporthe oryzae (M.oryzae), is one of the most \ndevastating rice diseases worldwide. Blast disease is \na plant disease that occurs in rice plants through the \nformation of diamonds around the leaves and other \nparts of the plant and thus causes  \n \n \n \n \n \n\n\n\nthe plant to die. This occurs when spores of \nM.oryzae are spread over the leaves and the \nprocess of germination takes place (Aishah, H. et al., \n2017). The rice blast infection can damage almost \nall parts of the plant at various growth stages \n(Vasudevan, K et al., 2015) especially vegetative and \nreproductive stages. Loss from this disease can \nsingle-handedly feed 60 million people, equivalent \nto 30% of human population in the world. Though \nthe yield potentiality of rice is 10 tons-ha whereas \nfarmers on an average harvesting about 5 tons ha-1. \nThis yield difference is due to diseases in rice. \n\n\n\n \nAbstract \n\n\n\nGlobally, food security is in need to be maintained while facing climate change. Climate change has \nseverely affected the production of crops either through biotic or abiotic effects. Rice blast is one of the \nbiotic effects that threatens the performance of rice production all over the world. The occurrence of this \nparticular disease is caused by a fungus named Magnaporthe oryzae. Current way out to this problem is \nthrough chemical as well resistance rice variety. The evolution of microorganism becomes extra challenge \nin overcoming this disease. A variety originated from Vietnam, Tetep is resistance to blast and have been \nstudied in depth for its resistance gene. Most of the resistance genes cloned come from this variety. \nMahsuri Mutant is the first mutant rice produced in Malaysia through EMS and gamma radiation, \nperformed on a traditional variety Mahsuri. This mutant has better performance in resisting blast disease \nand longer kernel length compared to its original variety. However, no specific linked-gene is reported in \nMahsuri Mutant that resistant to blast till now and not many studies have been done on this variety. This \nstudy is to identify the polymorphic markers that linked to blast resistance gene between Mahsuri Mutant \nand Tetep as part of the allelic study. A polymorphism survey using SSR molecular marker between these \ntwo varieties was done using a total of 60 primers. 9 (15.5%) polymorphic markers were obtained \n(RM224, RM6324, RM317, RM136, RM314, RM336, RM562, RM7102, RM17708) and 3 out of 9 markers \nare linked to blast resistance gene. The markers from this study will help in further understanding on blast \ngene and future breeding program. \n\n\n\nKeywords: Mahsuri Mutant; Tetep; SSR and Magnaporthe oryzae \n\n\n\n\n\n\n\n*Corresponding author: Faiz Ahmad, Agrotechnology and \nBiosciences Division, Malaysian Nuclear Agency, \nBangi, 43000 Kajang, Malaysia \n\n\n\nEmail: faiz@nm.gov.my \n\n\n\n \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2021, e-ISSN: 2811-3594 \n\n\n\n\n\n\n\n \nPage 17 of 22 \n\n\n\nAmong the biotic stresses blast disease is the most \nharmful threat to high productivity of rice (Miah, G. \net al., 2013). The fungus is able to develop \nresistance to both chemical treatments and genetic \nresistance which is continuous threat to the \neffectiveness of blast-resistant rice varieties. Hence, \nit is urgent to find out strategies for developing \ndurable resistance varieties to the disease \n(NurulNahar et al., 2020; Aishah, H. et al., 2017; \nJiyong et al., 2017) By being one of countries that \nstaple food is rice (Oryza sativa), Malaysia does not \nexclude from being affected by this particular \ndisease. Presently, Malaysia has recorded 30 million \npopulation and is expected to reach 50 million in \n2070 thus, the source of food for this country has to \nbe well managed and prepared (Nurhaziqah et al., \n2019). The first report of rice blast in Malaysia is \nback in 1945 with estimation 20% of average yield \nloss and 30% plot yield on Jaya variety. Rice blast is \ncategorized as major rice disease and the \nemergence of superior pathotype in Malaysia is due \nto continuous planting of mega varieties like MR219 \nand MR220 which covered 90% of the Peninsular \nMalaysia. Almost 50% planting of MR220CL2 and \nMR263 may alter the dominancy of blast pathotype \nto P0.0, P1.0 and P9.0 (Siti Norsuha and Latiffah \n2019). Lots of resistance variety during first \nreleased becoming susceptible in every coming \nseason like MR219 which has been declared by \nMalaysia Agriculture Research Development \nInstitute (MARDI), to lost its ability to resist blast \npathogen and eventually to stop planting by \nfarmers (MARDI 2021). \n \nAccording to Jiyong et al., (2017) over 100 blast \nresistance genes on rice chromosomes has been \nmapped and recognized already. The resistance \ngenes are produced either into qualitative or \nquantitative with qualitative resistance genes are \nprone to be selected due to its sensitivity and \noverall resistance given from different allele while \nquantitative resistance genes operated as \nadditional resistance comes from different allele \nwhich is hard to use in breeding despite its being \nmore durable in resisting the disease. Presently, 350 \nquantitative traits loci (QTLs) related to blast \nresistance gene has been identified (Xinglong et al., \n2018). Many blast resistance genes have been \nidentified present in both japonica and indica rice \nlike Tjina (Pib), Tetep (Pib, Pi1 and Pita), Pai-Kan-Tao \n(Pi3), Moroberekan (Pi5 and Pi7), 5173 (Piz-5 = Pi2), \nTKM1 (Piz-t), Tadukan (Pita), Zenith (Piz), and LAC23 \n(Pi1). For further assist in breeding strategies, many \ngenes have been clones Pib, Pita, Pid2, Piz-5, Piz-t, \nPi9, Pi36, and Pi3. Usage of QTLs or selection of \ngenes is very vital in breeding new variety through \ncloning and functional studies. Xinglong et al. (2018) \nstated that effectivity of major genes in resisting can \nbe observed from rice variety with more than one \n\n\n\nresistance QTLs and the combination of major R \ngenes and QTLs will give better resistance effect \nagainst M. oryzae. \n \nDevelopment of technology helps in aiding the gene \nidentification available in plants and living things.   \nMolecular marker is the selected tool for this due to \nability in usage with no information of crop \nbeforehand.  Simple sequence repeat (SSR) markers \nhave high polymorphism and stability with added \nvalue by being simple in technical aspect and fast \nassay while stay natural and co-dominant and easily \nrun using Polymerase Chain Reaction (PCR). At the \nsame time, this tool helps in evaluating genetic \ndiversity of both wild and cultured rice species, \nquick in disclose genetic polymorphism and \ncontrast in genotypes. SSRs are majorly being used \nto map, identify and introgress agronomically \nimportant QTLs into well-known varieties \n(Nurhaziqah et al., 2019). \n \nReasons for this study are because there is no \nspecific linked-gene reported in Mahsuri Mutant \nthat resistant to blast and the need to identify \nwhether Mahsuri Mutant is allelic to linked gene \nthat resistance to blast in Tetep. From this research, \nthe comparison in availability of blast resistance \ngene information in Mahsuri Mutant and Tetep will \nbe proven. The finding of this research may help in \ninformation addition related to blast resistance \ngene in rice and future use of this gene information \nwill boost the process of creating disease resistance \nvariety. \n\n\n\n \nMethodology \n \nDNA Extraction \nThe extraction of DNA for both Mahsuri and \nMahsuri Mutant is done using CTAB based on \nAboul-Maaty (2019) with slight changes. About 0.1 \ng of fresh leaves at young stage was grinded with \n500 mL CTAB buffer. The solution then transferred \ninto a 2.0 mL microcentrifuge tube before \nincubated in the water bath at 65\u2103 for 20-30 \nminutes. Then, 500 \u03bcL of chloroform:isoamyl \nalcohol 24:1 solution is added to the tube and shook \nfor 5 minutes. Next, the tube was centrifuged for 15 \nminutes at 13 200 rpm (max). Supernatant obtained \nwere transferred to new 2 mL tube and added with \n200 \u03bcL isopropanol before left to incubate at -20\u2103 \nfor 60 minutes. After that, samples were \ncentrifuged for 15 minutes at the same rpm. The \nsupernatant was discarded before 70% ethanol was \nadded to it. Ethanol was discarded and the palette \nwas left to dry before adding 100 \u03bcL of TE buffer and \n1 \u03bcL of RNAse. The DNA were kept at -4\u2103 for \nfurther use. The DNA purity is checked using \nNanodrop spectrometer and the quality is further \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2021, e-ISSN: 2811-3594 \n\n\n\n\n\n\n\n \nPage 18 of 22 \n\n\n\nchecked using 1% agarose gel electrophoresis at \n80V for 40 min and viewed under GelDoc. \n \nAmplification of PCR \nPolymerase chain reaction was performed in order \nto amplify the DNA with all SSR markers. The \namplification of SSR markers were carried out with \n20\u00b5l total volume of product. Products consisted of \n1\u00b5l of 25ng/\u00b5l DNA template, 4\u00b5l of 5x PCR Buffer, \n1\u00b5l of each primer pair, 0.4\u00b5l dNTPs \n(Deoxynucleotide triphosphates), 2.4\u00b5l MgCl \n(Magnesium chloride), 0.1\u00b5l Taq polymerase and \n10.10\u00b5l of distilled water PCR process consists of 5 \nstages: (1) pre-denature of DNA template at 95\u00b0C \nfor 4 min; (2) denature of DNA template at 95\u00b0C for \n\n\n\n15 sec; (3) annealing at 55\u00b0C for 15 sec; (4) \nextension at 72\u00b0C for 30 sec and (5) post-extension \nat 72\u00b0C for 7 min. PCR products were viewed in 2% \nagarose gel electrophoresis with buffer 1X TBE in \n60V for 50 min and visualised using GelDoc. \n \nParental Polymorphism Survey  \nA polymorphism survey was conducted using total \nof 60 SSRs markers linked to blast and other \ncommon markers which cover whole rice genome. \nInformation on markers was referred at Gramene \n(http://www.gramene.org) and previous studies. \nTable 1 showed list of SSRs markers used to find \npolymorphism between Mahsuri and Mahsuri \nMutant.\n\n\n\n\n\n\n\nTable 1. List of SSR markers used in polymorphism survey between Mahsuri Mutant and Tetep. \n\n\n\nMarker Forward Reverse Product \nsize (bp) \n\n\n\nChromoso\nme \n\n\n\nAnnealing \ntemp \n\n\n\n246 CGAGCTCCATCAGCCATTCAGC ACTTGAGAGCGAGATTGGGAAT\nCG \n\n\n\n116 1 55 \n\n\n\n6324 CTGTACAAGAACGGCAGCAACC GCACCACCAAACAGAGACAGAG\nG \n\n\n\n148 1 55 \n\n\n\n3235 ATCTAATTCCAGTGGCGCAGAGG TGGAGCTAAGTGAGAGCTAGTG\nATGG \n\n\n\n112 1 55 \n\n\n\n1090 CGATACAACGCTGTTACTGTGC TCCCTTGTGTCGTGTTGTATTAGG 176 1 55 \n\n\n\n462 CCGCGAATCCATTCAGACTGC TCTAGGAGGAGATGGCGGAGTA\nGC \n\n\n\n243 1 55 \n\n\n\n6464 CGAGGAGAATACTCGTTCGGTAG\nC \n\n\n\nCCCTTCTCCATCTCATCTCACTCC 146 1 55 \n\n\n\n12138 AGCTTGTTCAGCCGCCATAGCC GTCGAAGCGTTGGTGAGATTTG\nG \n\n\n\n95 1 55 \n\n\n\n122 GGGACTACTCGAGCAAGCTAATG\nC \n\n\n\nGTCCAATCTAATCGACCTCCAAG\nAGC \n\n\n\n227 1 55 \n\n\n\n336 ACTTACACAAGGCCGGGAAAGG TGGTAGTGGTAACTCTACTCCGA\nTGG \n\n\n\n154 1 55 \n\n\n\n562 GGAAAGGAAGAATCAGACACAG\nAGC \n\n\n\nGTACCGTTCCTTTCGTCACTTCC 243 1 55 \n\n\n\n513 CTATTGGGCGTTGGTCTAGTGG CAACGAAATCATCCCTAGCTTCC 262 1 55 \n\n\n\n594 TCGAGAGAGGGAGAGTGAGAAC\nATGG \n\n\n\nGCCTTCGCACATAAAGGATGAAC\nC \n\n\n\n300 1 55 \n\n\n\n279 CCTCTCACTCACGTGGACTCTCC CCTCACCCTAGGCTTTGATATGC 174 2 55 \n\n\n\n535 ATGAATGTCGTGCCGTTTCTGG AAGTTTGGACTGCCCAATCAGG 138 2 55 \n\n\n\n5862 CCTCCTGAAGGGTAAAGGATTGG TCCACACATGATCGCTACATCG 223 2 55 \n\n\n\n151 AGCAGTAGCTGCATCGAAGG GTATGTGCTCTTGCATTCTTGC 197 3 55 \n\n\n\n570 AGAAATGGTGAAAGATGGTGCT\nACCG \n\n\n\nCTGAATGTTCTTCAACTCCCAGTG\nC \n\n\n\n208 3 55 \n\n\n\n15875 AGGCCTCGATGAGGGTGAGG CTCCCTCCTCTTCTTCTCCAGTAG\nG \n\n\n\n237 3 55 \n\n\n\n15593 AGAGGAGGAGACGAGCGCAACG CGGGCACCACTCCCATTAAGACC 86 3 55 \n\n\n\n155 GCAACACATCAAACTGCTGAATC\nG \n\n\n\nCGTTAGGTGCGAACGAAGTTCC 155 3 55 \n\n\n\n527 TGGTCATTGATTACACCCTCAGC TTCAGATGAGAAGCAAGCACTCG 233 4 55 \n\n\n\n17180 GGAGACAACTCTGGTCTTGACAG\nC \n\n\n\nGGACCTCGCGTAGTTGAAGTCG 165 4 55 \n\n\n\n17600 CCTCGAAATGAATTGCAGTCGAA\nCG \n\n\n\nGTCTTGTGCCTTGTGCCGATGG 478 4 55 \n\n\n\n17501 CTGGAGAGGGTGGTTGGGATCG CAGCAGCAGCACGCGAAACC 167 4 55 \n\n\n\n\nhttp://www.gramene.org/\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2021, e-ISSN: 2811-3594 \n\n\n\n\n\n\n\n \nPage 19 of 22 \n\n\n\n317 CATACTTACCAGTTCACCGCC CTGGAGAGTGTCAGCTAGTTGA 155 4 55 \n\n\n\n17297 GGTCCCTCTCCCTCATGTCATCC TCCGCTTCGCTCCTAGCATGG 91 4 55 \n\n\n\n16541 AGGGCCTTTCACAACCTCTACC ACCTGAGCATTATCACCACAGC 521 4 57 \n\n\n\n17708 GCCATCGATCTGCTTCCTTCC CGCCTCCTTTCTGGTACATAGGC 165 4 57 \n\n\n\n303 ATCGATGTAGGTAGAGGGACAC\nC \n\n\n\nCAGATCTAGTCGACATGGTTGG 200 4 55 \n\n\n\n17079 GTGTGAATCTGGACATACCCTAA\nGC \n\n\n\nTTTCTTCCTCCTCATCTGGTTGC 674 4 NA \n\n\n\n7302 GGGAGAGAGGAAGGAGGAGCT\nTCG \n\n\n\nCGGGACCGGAACCTTTCAACG 180 5 55 \n\n\n\n574 AAACTAGCCACGGTTTGGTAGGG AGGGTGGCAGGGATGTAATTTCC 155 5 55 \n\n\n\n6317 GGAGACAGTGGAGAGGCTACTG\nG \n\n\n\nCATCATCAACTACCAACCCATCC 199 5 55 \n\n\n\n3790 CGATCAACCACCTCAACTACTGC TGTGCATGTGGACACGTAATGC 119 5 55 \n\n\n\n19157 GCATTCCTACCAGTGAAACAGAG\nC \n\n\n\nGTCATGCGTGAGGGAGACAGG 180 5 55 \n\n\n\n18862 AGGGCACGTGCATTCCTAGAGC GGAGAAGAAGGGCACATGCATC\nC \n\n\n\n149 5 55 \n\n\n\n18056 AGATCTCCTCTCAGAGTCTACCG CACTGAGTATAATCCCTGCAACC 295 5 55 \n\n\n\n440 CATGCAACAACGTCACCTTC ATGGTTGGTAGGCACCAAAG 128 5 57 \n\n\n\n18940 GATCGATCAGTCAACCAAGAAGC AGAAGAGGTATCCAAAGGCAAG\nG \n\n\n\n234 5 NA \n\n\n\n13 TCCAACATGGCAAGAGAGAG GGTGGCATTCGATTCCAG 141 5 NA \n\n\n\n136 AGAGCAGAAGTGAGCAATCATG\nG \n\n\n\nCACCTATCATCACTGGGCATGG 101 6 55 \n\n\n\n6836 GCGTGTTCAGAAATTAGGATACG\nG \n\n\n\nGATCTCGCCACGTAATTGTTGC 240 6 55 \n\n\n\n412 CACTTGAGAAAGTTAGTGCAGC CCCAAACACACCCAAATAC 198 6 55 \n\n\n\n494 GGGATCGAGATAGACATAGACC TCTGTACAGTGTCATTCCTTCC 203 6 55 \n\n\n\n19665 CGATGTCTTCGAGTCCCTTAACA\nGG \n\n\n\nACGGTTGGTGATGCTCTTAGGC 191 6 55 \n\n\n\n19743 CCGGTGACACTAATGGCTGGTAG\nC \n\n\n\nAACTCGATCTCATCGGCGTTCC 186 6 55 \n\n\n\n314 CTGGAGAGTGTCAGCTAGTTGA AACATTCCACACACACACGC 118 6 55 \n\n\n\n20638 AGGCAAGCTAGCATGGAGATGG CGTACGGATGGTCCAATGATGC 151 6 NA \n\n\n\n7153 AACCGATCAGCAACCATCCAAAG\nG \n\n\n\nGTTGCACGGTGGATGACGTTGG 154 7 55 \n\n\n\n21354 TATGCCATCCATACGAGGAAGC TATGCACCAAACTGGGTTAGGC 267 7 NA \n\n\n\n21258 TATCATTCCGGTCCAAAGTGTCG TCCGGTCCAAAGTCTCATTTGC 377 7 NA \n\n\n\n342 GTTGCCGGTGAAGGTCCATCC TGTCACCCTCATCAACATCAGTG\nG \n\n\n\n141 8 55 \n\n\n\n224 TCTCCCTCCTCCTCCTCCTACG GATTCAGCACAGCGATTGTTGC 157 8 55 \n\n\n\n7175 CGTGTCCATTGTGTGAAGCTACG ACGTGGTGCCTCCTTTCAAACC 105 9 55 \n\n\n\n4835 GGTTTGGTTCACCTACTCGTTTGC CTCTTCGCTCGCGTGTTTCG 183 10 55 \n\n\n\n484 TCTCCCTCCTCACCATTGTC TGCTGCCCTCTCTCTCTCTC 299 10 55 \n\n\n\n224 TCTCCCTCCTCCTCCTCCTACG GATTCAGCACAGCGATTGTTGC 157 11 55 \n\n\n\n7102 GGGCGTTCGGTTTACTTGGTTAC\nTCG \n\n\n\nGGCGGCATAGGAGTGTTTAGAG\nTGC \n\n\n\n169 12 55 \n\n\n\n\n\n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2021, e-ISSN: 2811-3594 \n\n\n\n\n\n\n\n \nPage 20 of 22 \n\n\n\nResult and Discussion \nThe percentage of polymorphism was calculated using the formulae: \n\n\n\n=    \n    \ud835\udc45\ud835\udc40 \ud835\udc43\ud835\udc5f\ud835\udc56\ud835\udc5a\ud835\udc52\ud835\udc5f\ud835\udc60 \ud835\udc46\u210e\ud835\udc5c\ud835\udc64\ud835\udc56\ud835\udc5b\ud835\udc54 \ud835\udc43\ud835\udc5c\ud835\udc59\ud835\udc66\ud835\udc5a\ud835\udc5c\ud835\udc5f\ud835\udc5d\u210e\ud835\udc56\ud835\udc60\ud835\udc5a\n\n\n\n\ud835\udc47\u210e\ud835\udc52 \ud835\udc61\ud835\udc5c\ud835\udc61\ud835\udc4e\ud835\udc59 \ud835\udc5b\ud835\udc62\ud835\udc5a\ud835\udc4f\ud835\udc52\ud835\udc5f \ud835\udc5c\ud835\udc53 \ud835\udc45\ud835\udc40 \ud835\udc5d\ud835\udc5f\ud835\udc56\ud835\udc5a\ud835\udc52\ud835\udc5f\ud835\udc60 \ud835\udc62\ud835\udc60\ud835\udc52\ud835\udc51\n    \ud835\udc65   100 \n\n\n\nTable 2. Chromosome wise percentage of primers showing polymorphism between parents, Tetep and Mahsuri \nMutant. \n \n\n\n\n \nTable 3. List of polymorphic primers with their linked gene/QTLs. \n \n\n\n\nPrimer Chromosome Gene/QTLs \n\n\n\nRM562 1 Saltol (Adak et al., 2020; Roshni et al., 2019; Ganie et al 2016) \n\n\n\nRM6324 1 Qdse1 (Rahman et al., 2016) \n\n\n\nRM317 4 - \n\n\n\nRM17708 4 - \n\n\n\nRM136 6 Pi9 (Haque et al., 2021) \n\n\n\nRM314 6 Grain yield/Aromatic \n\n\n\nRM336 7 Linked to ShB resistance qSBR7-1 (Vidya et al 2018; Yadav et al., 2015) \n\n\n\nRM224 11 Pi-l(1), Pi, Pik-h, Pi-ks ( Miah et al., 2013) \n\n\n\nRM7102 12 Pita, Pita-2, Pi20(t), Pi-ks, Pi4, agronomic traits (1000-grain weight)  \n\n\n\n \nThere are nine SSR markers found to be \npolymorphic between those two varieties; RM224, \nRM6324, RM317, RM136, RM314, RM336, RM562, \nRM7102, RM17708. Three out of nine polymorphic \nprimers are categorized as linked gene to blast \nresistance (Miah et al., 2013); RM224, RM136 and \n\n\n\nRM7102. The foreground has 20% percentage of \npolymorphism while background marker has 12% \npercentage of polymorphism. The total percentage \nof polymorphism for this survey is 15.5% out of 60 \nmarkers. \n\n\n\n\n\n\n\n\n\n\n\nChromosome \nnumber \n\n\n\nTotal number \nmarkers screened \n\n\n\nfor each \nchromosome \n\n\n\nNumber of \npolymorphic \n\n\n\nmarkers on each \nchromosome \n\n\n\nNumber of \nmonomorphic \n\n\n\nprimers on each \nchromosome \n\n\n\nPercentage of \npolymorphism on each \n\n\n\nchromosome \n\n\n\n1 13 4 9 30.76 \n\n\n\n2 3 0 3 0 \n\n\n\n3 5 0 5 0 \n\n\n\n4 10 2 8 20.00 \n\n\n\n5 9 0 9 0 \n\n\n\n6 7 1 6 14.29 \n\n\n\n7 3 0 3 0 \n\n\n\n8 3 0 3 0 \n\n\n\n9 1 0 1 0 \n\n\n\n10 2 0 2 0 \n\n\n\n11 2 1 1 50.0 \n\n\n\n12 2 1 1 50.0 \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2021, e-ISSN: 2811-3594 \n\n\n\n\n\n\n\n \nPage 6 of 7 Page 21 of 22 \n\n\n\nFigure 1. Gel view for PCR products for Tetep and Mahsuri Mutant with few SSR markers (M = 50-bp) \n \n \nMinor and major gene associated with blast \nresistance in rice is based from the R gene. \nAccording to Fukuoka et al. (2014) and Ashkani et al. \n(2016), more than 100 gene and loci have been \nidentified for blast. Ning (2020) stated that about \n98% of 792 M.oryzae isolated in China were resisted \nby LAC23 from West Africa that has Pi-1 and the \ngene is a resistance gene in broad spectrum towards \nleaf blast while Khan (2018) stated that Pi-1 is not a \nstrong gene yet once combined with other gene, \nthey increase in performance. This is well proven \nsince Tetep is resistant to blast in every growth \nstage.  The performance of resistance in blast is \ndifferent in both leaf blast and panicle blast. The \nbroad-spectrum gene that covered leaf blast \nresistance might give different result when tested in \nheading stage due to R genes controlled are \ndifferent depending on growth stage (Ning et al., \n2020). Currently, there is no finding on Pi-1 gene in \npanicle blast. Mahsuri Mutant has showed no \nsusceptibility towards blast (Faruq et al., 2004). \nTherefore, Mahsuri Mutant might have more blast \nresistance gene present which is yet identified and \nmight be discovered due to genetic mutation \ninvolvement. Marker RM224 is located in \nchromosome 11 with leaf blast resistance gene Pi-\nl(1) Turaidar et al., (2017), Pi, Pik-s, Pi-ks. Another \nmarker found to be polymorphic is RM136 which \nlinked to Pi9 located in chromosome 6 and marker \nRM7102 with resistance gene Pita, Pita-2, Pi20(t)(t) \nin chromosome 12. Chromosomes 6 and 12 are \noften reported to have blast resistance gene. Pik-h \nitself is identified from Tetep which found in marker \nRM224 (Miah et al., 2013) Total variation in \nagronomic trait (1000-grain weight) detected in \nmarker RM7102 (Yang et al., 2021) which means the \nmarker is associated with yield and at the same time \nthe marker itself linked to blast resistance gene. \nTherefore there is correlation between blast \nresistance gene and yield. Over the past two eras, \nseveral ShB resistant QTLs have been mapped. \nAmong these, three QTLs (qSBR 11-1, qSBR 11-2 and \nqSBR 7-1) mapped in Tetep were found consistently \nassociated with ShB resistance across location and \nyears (Vidya et al., 2018) and the marker amplified \nat the target size product and showed \npolymorphism to Mahsuri Mutant. As for RM317 \nand RM17708 there is no gene or QTLs identified yet \nbut, they showed polymorphism between those \ntwo varieties. According to Supari et al. (2019), the \nSSR marker RM317 is the potential marker to be \nused for further identification in Malaysian varieties \nlike Mahsuri, the parent of Mahsuri Mutant. As it is \nshowed polymorphic to Tetep might be due to no \ncompatibility of the information available in the \nmarker to Tetep but available Mahsuri Mutant. \n\n\n\nBecause the fundemantal to the polymorphism \nsurvey, the more unique alleles one accession has, \nthe more genetic diversity/distance it has. \n \nConclusion \nFrom the polymorphism result on all markers \nabove, Mahsuri Mutant indeed has blast resistance \ngene Pi-l (1), Pi-K, Pik-s, Pi-ks however, further \ninvestigation and analysis shall be done to find more \nblast resistance gene present in Mahsuri Mutant. \nThis will be the first study on difference in genetic \ninformation related to blast between Mahsuri \nMutant and Mahsuri. Hence, more information on \nMahsuri Mutant will be available for future research \non blast and mutation of rice. The identification of \nblast gene in Mahsuri Mutant will help in future \nbreeding program as well as creation of new blast \nresistance variety.  \n\n\n\n \nAcknowledgement \nExtension of gratitude is given to International \nAtomic Energy Agency (IAEA) for providing grant for \nthis project under CRP:RC23039. Thanks to \nMalaysian Nuclear Agency (MNA) and Universiti \nKebangsaan Malaysia (UKM) for all the research \nfacilities provided. \n \nReferences \nAdak, S., Datta, S., Bhattacharya, S., Ghose, T. K., & \nMajumder, A. L. (2020). Diversity analysis of \nselected rice landraces from West Bengal and their \nlinked molecular markers for salinity \ntolerance. Physiology and Molecular Biology of \nPlants, 26(4), 669. \n \nAishah Hassan (2017) Magnaphorthe oryzae: \nFungus Pencetus Penyakit Karah Padi. Majalah \nSains. \nhttp://www.majalahsains.com/magnaphorthe-\noryzae-fungus-pencetus-penyakit-karah padi.html. \n[18 November 2021]. \n \nAshkani, S., Rafii, M. Y., Shabanimofrad, M., \nGhasemzadeh, A., Ravanfar, S. A., & Latif M. A. \n(2016). Molecular progress on the mapping and \ncloning of functional genes for blast disease in rice \n(Oryza sativa L.): current status and future \nconsiderations. Critical reviews in \nbiotechnology, 36(2), 353-367. \nhttps://doi.org/10.3109/07388551.2014.961403 \n \nFukuoka, S., Yamamoto, S. I., Mizobuchi, R., \nYamanouchi, U., Ono, K., Kitazawa, N., & Sugimoto, \nK. (2014). Multiple functional polymorphisms in a \nsingle disease resistance gene in rice enhance \n\n\n\n\nhttp://www.majalahsains.com/magnaphorthe-oryzae-fungus-pencetus-penyakit-karah\n\n\nhttp://www.majalahsains.com/magnaphorthe-oryzae-fungus-pencetus-penyakit-karah\n\n\nhttps://doi.org/10.3109/07388551.2014.961403\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2021, e-ISSN: 2811-3594 \n\n\n\n\n\n\n\n \nPage 22 of 22 \n\n\n\ndurable resistance to blast. Scientific Reports,4, \n4550. https://doi.org/10.1038/srep04550 \n \nGanie, S. A., Borgohain, M. J., Kritika, K., Talukdar, \nA., Pani, D. R., & Mondal, T. K. (2016). Assessment \nof genetic diversity of Saltol QTL among the rice \n(Oryza sativa L.) genotypes. Physiology and \nMolecular Biology of Plants, 22(1), 107-114. \n \nHaque, M. A., Rafii, M. Y., Yusoff, M. M., Ali, N. S., \nYusuff, O., Datta, D. R. & Ikbal, M. F. (2021). Recent \nAdvances in Rice Varietal Development for Durable \nResistance to Biotic and Abiotic Stresses through \nMarker-Assisted Gene \nPyramiding. Sustainability, 13(19), 10806. \n \nMiah, G., Rafii, M.Y., Ismail M.R., Puteh, A.B., Rahim, \nH.A., Asfaliza, R. & Latif, M.A. (2013) Blast resistance \nin rice: A review of conventional breeding to \nmolecular approaches. Molecular Biology Reports \n40: 2369\u20132388. \n \nMisman, S. N., & Zakaria, L. (2019). Pathotype \nIdentification of Rice Blast Pathogen, Pyricularia \noryzae Using Differential Varieties in Peninsular \nMalaysia. Tropical Life Sciences Research, 30(2). \n \nNing, X. I. A. O., Yunyu, W., & Aihong, L. (2020). \nStrategy for Use of Rice Blast Resistance Genes in \nRice Molecular Breeding. Rice Science, 27(4), 263-\n277. https://doi.org/10.1016/j.rsci.2020.05.003 \n \nNurulNahar, E., Adam, P., Mazidah, M., Roslan, I., & \nRafii, M. Y. (2020). Rice blast disease in Malaysia:\n Options for its control. Journal of \nTropical Agriculture and Food Science, 48(1), 11 23. \n\n\n\n \nRahman M.H.Yu P.Zhang Y.X. Sun L.P. Wu W.X. Shen \nX.H. Zhan X.D. Chen D.B. Cao L.Y. Cheng S.H. (2016). \nQuantitative trait loci mapping of the stigma \nexertion rate and spikelet number per panicle in rice \n(Oryza sativa L.). Genetic Molecular Research 15(4): \ngmr15048432. \nhttps://doi.org/10.4238/gmr15048432 \n \nRoshni, A. M., Saravanan, K. R., Prakash, M., & \nHarikrishnan, M. (2019). Molecular breeding for \nsalinity tolerance through SSR markers in rice (Oryza \nsativa L.). Plant Archives, 19(2), 3777 3781. \n \nSupari, N., Kaya, Y., Biroudian, M., & Javed, M. A. \n(2019). Molecular characterization of Malaysian rice \ncultivars using SSR markers. In AIP Conference \nProceedings (Vol. 2155, No. 1, p. 020016). AIP \nPublishing LLC. \n \nTuraidar, V., Reddy, M., Anantapur, R., Dalawai, N., \n& Kumar, H. K. M. (2018). Screening of traditional \nrice varieties (TRVs) for blast resistance. J. \nPharmacogn. Phytochem, 7(1), 1384-1388. \n \nVasudevan, K., Gruissem, W. & Navreet K.B. (2015) \nIdentification of novel alleles of the rice blast \nresistance gene Pi54. Scientific Reports 5: 1-11. \n \nYang, G., Yang, Y., Guan, Y., Xu, Z., Wang, J., Yun, Y., \n& Tang, Q. (2021). Genetic Diversity of Shanlan \nUpland Rice (Oryza sativa L.) and Association \nAnalysis of SSR Markers Linked to Agronomic \nTraits. BioMed Research International, 2021. \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n \n\n\n\n\nhttps://doi.org/10.1038/srep04550\n\n\nhttps://doi.org/10.1016/j.rsci.2020.05.003\n\n\nhttps://doi.org/10.4238/gmr15048432\n\n\n\n"
"\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 29 of 36 \n\n\n\n\n\n\n\n\n\n\n\nOFFICIAL JOURNAL \n\n\n\nRESEARCH ARTICLE \n\n\n\n\n\n\n\nGenome Size Determination of Garcinia opaca and Garcinia \npenangiana Using Flow Cytometry (FCM) \n\n\n\n  \nMohamad Azimi Shaharudin, Aiesyaa Majdiena Emlee, Mohd Razik Midin \n\n\n\n\n\n\n\n1Department of Plant Science, Kulliyyah of Science, International Islamic University Malaysia,  \n25200 Kuantan, Pahang, Malaysia \n\n\n\n \n*Correspondence: mohdrazik@iium.edu.my \n\n\n\n\n\n\n\n\n\n\n\nIntroduction\nG. mangostana var. mangostana (Nazre et al., 2018) \nor mangosteen is a well-known tropical fruit, and it is \nhighly preferred by the locals due to its pleasant taste \nand market value. Malaysia, Indonesia, Thailand, and \nPhilippines are the major cultivating countries of \nmangosteen, and it has been scattered in other \ntropical regions, namely Northern Australia, South \nAmerica, and Tropical Africa (Cruz, 2001). \nMangosteen is categorised under obligate apomixis as \nconfirmed by Lim (1984) and Richard (1990a). Thus, \nthe progenies of apomictic mangosteen should be \ngenetically identical to the mother plant (Koltunow et \nal., 1995).  \n\n\n\n discover regarding the origin of mangosteen is \ncontinuously being covered through different \ntechniques using morphological and molecular \napproaches. According to Richard (1990b), \nmangosteen is originated from the hybridization of G. \npenangiana (mistreated as G. mangostana var. \nmalaccensis) and G. celebica Linn (syn. hombroniana \nPierre) by referring to the morphological traits. \nMeanwhile, Abdullah et al. (2012) expected that G. \npenangiana (mistreated as G. mangostana var. \nmalaccensis) and G. opaca King to be the progenitor \nof mangosteen instead of G. celebica due to similar \nallele size and these two Garcinia species were closely \ngrouped in the phylogenetic tree Internal Transcribed \nSpacer (ITS). It is important to note that Nazre (2014) \nemphasized that the samples of G. mangostana var. \nmalaccensis collected from Pasoh Reserved Forest in \nNegeri Sembilan, Malaysia should be treat as G. \npenangiana. Thus, the samples of G. mangostana var. \n\n\n\n \nAbstract \n\n\n\nMangosteen (Garcinia mangostana var. mangostana) is one of the common tropical fruits in South \nEast Asia. The value and economic potential of mangosteen have been recognised by local and \ninternational markets due to its fleshy part of the pulp that can be eaten fresh as well as medicinal \nproperties including anti-inflammatory and anti-oxidative characteristics. Mangosteen grows best in \nfertile soil with slightly acidic conditions and can only be found in cultivated farms especially in few \ncountries including Thailand, Malaysia, Philippines, and Indonesia. In order to improve both quality \nand quantity of mangosteen cultivation, several Garcinia species have been identified as possible \nancestors of mangosteen which can be used in breeding program. Currently, the genome size on \nthese possible ancestors are still unavailable. This study aims to determine the genome size of two \nGarcinia species of possible mangosteen ancestors; G. opaca and G. penangiana using flow \ncytometry (FCM) analysis. By using soybean or Glycine max cv. Polanka (2C=2.5pg) as an external \nreference standard, it was found that the genome size of G. opaca and G. penangiana to be \n3.34\u00b10.05 pg and 4.77\u00b10.31* pg respectively. Recent study proved that the genome size of \nmangosteen to be 6.00\u00b10.17 pg which was higher than the genome size of both G. opaca and G.  \npenangiana. The findings indicate that interspecific variation which resulted from hybridization \nprocess between G. opaca and G. penangiana may occur in the genome of mangosteen. In \nconclusion, cytological data such as genome size for Garcinia species can be utilised for further study \nto determine the origin of mangosteen. \n\n\n\nKeywords: Mangosteen, Garcinia opaca, Garcinia penangiana, Genome size \n\n\n\nReceived: 14 04 2022; Accepted revised manuscript:  01 12 2022; \nPublished online: 01 04 2023 \n*Corresponding author: Dr Mohd Razik Midin, Department \nof Plant Science, Kulliyyah of Science, International Islamic \nUniversity Malaysia \nEmail: mohdrazik@iium.edu.my \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 30 of 36 \n\n\n\n\n\n\n\n\n\n\n\nmalaccensis used by Ha et al. (1988), Richards \n(1990b) and Abdullah et al. (2012) were actually G. \npenangiana.  The problem occurred due to the fact \nthat little is known about G. mangostana var. \nmalaccensis apart from information on herbarium \nspecimens, and the identity of G. mangostana var. \nmalaccensis had not been adequately examined by \nearlier authors, resulting in a typical case of species \nmisidentification (Nazre, 2014). \n \nFurthermore, Sinaga et al. (2010) also suggested that \nG. mangostana var. malaccensis (collected from East \nJava, Indonesia) and G. celebica are the possible \nparent plant as the proportion of isoenzymes bands \nthat were obtained by mangosteen (42.3%), G. \nmangostana var. malaccensis (44.2%) and G. celebica \n(13.5%). Besides, the close genetic connection in \ncluster group between mangosteen, G. mangostana \nvar. malaccensis (collected from Mekarsari Tourism \nPark Bogor, Indonesia) and G. porrecta Laness. by \nemploying of both markers in isoenzymes and \nAmplified Fragment Length Polymorphism (AFLP) \nassumed that both species can be the potential \nparent (Sobir et al., 2009). Other studies found that G. \nmangostana var. malaccensis is the only possible \nancestor of mangosteen by forming a monophyletic \ngroup with the clade of mangosteen in parsimony \nanalysis (Nazre, 2014). The close genetical \nrelationship of mangosteen and G. mangostana var. \nmalaccensis (collected from Bogor, Indonesia) by \nusing ITS sequence is supported by the previous \nfinding done by Yapwattanaphun et al. (2004). \n \nThe origin theory of mangosteen is a continuous \nsubject to be explored. The variation among Garcinia \nspecies in terms of genome size will provide new \ninsight towards the possible parent of mangosteen. \nGenome size (C-value) is defined by the quantity of \nDNA in under one complete haploid genome that \noften corresponds with the cellular size and \nmechanism as well as the ecological traits (Beaulieu \net al., 2008; Wang et al.,2015). Genome size offers a \nbasic biotic significance relating to cellular and \nmolecular biology, ecology, systematics and evolution \ntheory (Bennett and Leitch, 2005, 2011; Vesel\u00fd et al., \n2012; Huang et al., 2013; Wang et al.,2015). \nAccording to Huang et al. (2013), the change of \ngenome size is influenced by the hybridization, \npolyploidization and also the aggregation of a \ntransposable element such as retrotransposons \n(Barakat et al., 1997; Grover & Wendel, 2010; Smarda \n& Bures, 2010; Huang et al., 2013).  \n \nFlow cytometry (FCM) refers to a fast and powerful \nmethod for determining the genome size of an \norganism through the isolation of nuclei in lysis buffer \nby implying a chopping method on plant tissue which \nwas developed by Galbraith et al. (1983) (Wang et al., \n2015). FCM also is a potent and broadly utilized to \n\n\n\nevaluate cell cycle phase arrangement and regulation \nin various cell types (Nunez, 2001; Delobel & \nTesni\u00e8re, 2014). As mentioned by Montante and \nBrinkman (2019), FCM involved several crucial steps \nwhich are 1-data processing, 2-cell population \nspotting, 3-cross-sample differentiation that involves \npopulation mapping, 4-features extrication, 5-\nelucidation and 6-imaging. The accuracy of genome \nsize estimation is sometimes debatable due to \npossible variables in terms of methodology such as \nbuffer selection and staining techniques (Bainard et \nal., 2010). Despite all possible inaccurate genome size \ndetermination, few previous studies (Nath et al., \n2014; Sandhu et al., 2016; Deng et al., 2019) have \nprovided the optimized methods for better yields. \nAccording to Wang et al. (2015), FCM has been \ninvolved in attentive findings regarding interspecific \nand intraspecific variation in genome size. \nInterspecific variation occurs between two or more \nthan one species based on the previous research \ninvolved four different species of bryophytes which \nwas done by Bainard et al. (2010). On the other hand, \nintraspecific variation involves individuals within the \nsame population as documented by Cires et al. \n(2011).  \n \nThe genome size estimation can be an important \nfactor for the potential progenitor of mangosteen. \nthis can contribute to breeding strategies for \nenhancing the quality and quality of mangosteen as a \nvaluable and economically beneficial fruit. Two \nrelated species of mangosteen namely G. opaca and \nG. penangiana Pierre are selected in this study as \nboth species, G. opaca and G. penangiana \n(mistreated as G. mangostana var. malaccensis), \nbeing grouped together with mangosteen in \nphylogenetic tree and have allele size that similar to \nmangosteen (Abdullah et al., 2012). This study aims \nto estimate the genome size of G. opaca and G. \npenangiana for evaluating the variation that could \nestablish more justification on the origin theory of \nmangosteen. \n \nMaterials and Method \n \nPlant Material \nLeaf samples of G. opaca and G. penangiana were \ntaken from Pasoh Forest Reserve in Negeri Sembilan. \nYoung leaves from both species were chosen due to \nits soft leaf structure and having less content of \nsecondary metabolite (Jedrzejczyk & Sliwinska, 2010) \nas compared to older and matured leaves. Thus, it is \neasier to prepare nuclei suspension for FCM analysis \nusing younger leaves. \n \nNuclei Extraction and Staining \nBoth leaf samples of G. opaca and G. penangiana \nwere cut manually into tiny pieces in a petri dish \nusing sharp scalpel to enable nuclei release from the \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 31 of 36 \n\n\n\n\n\n\n\n\n\n\n\ncells. LBO1 (Dole\u017eel et al., 1989) was used as lysis \nbuffer together with RNaseA (Sigma-Aldrich), \npropidium iodide (PI) (Sigma-Aldrich), \nmercaptoethanol (Merck, Darmstadt, Germany) and \npolyvinylpyrrolidone-40 (PVP-40) (Sigma-Alrich) as \nreducing agents (Yokoya et al., 2000). The nuclei \nsuspension was then transferred into 10 mL falcon \ntube (Becton Dickinson, USA) through a 50 \u00b5m nylon \nmesh filter. The nuclei suspension was incubated at 4 \n\u00b0C for a duration of 15 minutes. The incubation period \nwill allow PI to intercalate optimally with the DNA \nstrands. PI fluorochrome was proven to be more \naccurate fluorescent intensity histogram peak \nwithout causing the coefficient of variation (CV) value \nto increase (Dole\u017eel & Barto\u0161, 2005) and capable to \nintercalate the DNA region entirely (Dole\u017eel et al., \n2007). \n \nData Collection \nThe genome size of G. opaca and G. penangiana was \nanalysed using FACSCalibur FCM (BD Biosciences, San \nJose, CA) equipped with 15 mW argon ion laser at 488 \nnm. The FCM machine is integrated with CellQuest \nsoftware (Beckton Dickinson) to quantify the DNA \nfluorescence intensity as well as CV value. All \nhistogram data were derived from more than 1,024 \nchannels and 5,000 nuclei for each sample. \n \nData Analysis \nGlycine max cv. Polanka (soybean) was used as an \n\n\n\nexternal reference standard for genome size \nestimation (Dole\u017eel et al., 1994; Madon et al., 2008; \nMidin et al., 2018) of both G. opaca and G. \npenangiana. The fluorescence intensity of soybean \nwas used to be compared with fluorescence intensity \nof all replicates of both G. opaca and G. penangiana. \nThe ratio was then multiplied with the genome size of \nGlycine max cv. Polanka (2C = 2.5pg) to obtain the \ngenome size estimation of G. opaca and G. \npenangiana. \n \nResults and Discussion \nThe FCM machine detected the fluorescence intensity \nproduced by stained nuclei samples and \ndemonstrated as histogram peaks. The vertical axis \nrepresents the number of measured nuclei while the \nhorizontal axis represents the fluorescence intensity \nemission. Based on the histogram peaks of (Figure 1), \nGlycine max cv. Polanka produced no background  \ndebris as compared to G. opaca and G. penangiana. \nBoth species produced a visible amount of \nbackground debris in the histogram. The background \ndebris may be caused by an excessive amount of \nchopping or the suitability of different species \ntowards the usage of LBO1 buffer. The fluorescence \nintensity histogram with a low CV value were \nmeasured by CellQuest software. Low CV value \nindicate that the histogram peaks produced were \naccurate (Ulrich et al., 1988). \n \n\n\n\n\n\n\n\n \n \nFigure 1. Fluorescence intensity histogram peaks of (A) reference standard, Glycine max cv. Polanka, (B) G. opaca \n\n\n\nand (C) G. penangiana by using LBO1 as isolation buffer (arrows indicated debris background).\n \n\n\n\nSymmetrical histogram DNA peaks with CV less than \n3% were used to determine the genome size of \nG.opaca and G. penangiana. Glycine max cv. Polanka \nwas selected as reference standard due to its \nestablished genome size (Dole\u017eel & Barto\u0161, 2005) and \nthe soft leaf structure which make the sample \npreparation easier (Midin et al., 2013). It is important \nto  use a reference standard that is not too close or \ntoo distant from the selected species to reduce the \noffset errors and overlapping peaks (Johnston et al., \n1999; Bennett et al., 2003; Pra\u00e7a-Fontes et al., 2011). \nIf the species  are too close on a histogram of relative \nfluorescence intensity, the overlapping DNA peaks \ncan interrupt with each other and resulting in an \n\n\n\nartificial approach of the two peak means (Temsch et \nal., 2021). This is because the signals within the \nshared area contribute mutually to the area of each \nother's peak. More signals will be added to channels \non the peripheral of the other peak as the \nsurrounding peaks gets closer (Temsch et al., 2021). \nThe nuclear genome size of both G. opaca and G. \npenangiana is shown in Table 1.  \n \nTable 1. Flow cytometric estimation of genome size of \nG. opaca and G. penagiana. \n\n\n\nSpecies Replicate Genome \nsize (pg) \n\n\n\nMean \u00b1 SD \n(pg) \n\n\n\nB A C \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 32 of 36 \n\n\n\n\n\n\n\n\n\n\n\nG. opaca \n\n\n\n1 3.39 \n\n\n\n3.34\u00b10.05 \n\n\n\n2 3.40 \n\n\n\n3 3.32 \n\n\n\n4 3.34 \n\n\n\n5 3.27 \n\n\n\nG. \npenangiana \n\n\n\n1 4.47 \n\n\n\n4.77\u00b10.31* \n\n\n\n2 5.0 \n\n\n\n3 5.0 \n\n\n\n4 5.0 \n\n\n\n5 4.4 \n*indicates significant difference in the genome size \nbetween G. opaca and G. penangiana at P-value < \n0.05. \n \nThe genome size of G. opaca and G. penangiana were \nto be 3.34\u00b10.05 pg and 4.77\u00b10.31* pg respectively. T-\ntest statistical analysis indicated there were \nsignificant difference in the genome size between G. \nopaca and G. penangiana at P-value < 0.05. The \ngenome size of both species revealed to be lower \nthan mangosteen. Initially, Matra et al. (2014) \nreported that the genome size of mangosteen was \n7.42 pg but recent study by Midin et al. (2018) found \nout that the genome size of mangosteen was 6.00 \u00b1 \n0.17 pg. The value of genome size in mangosteen \ndiffered due to the type of fluorochrome used; DAPI \nby Matra et al. (2014) and PI was used by Midin et al. \n(2018). The inconsistent results may be due to the \nfact that DAPI effectively binds to A and T rich regions \nin the DNA sequence while PI binds to the whole DNA \nsequence (Schwarzacher, 2016; Wallberg et al., \n2016). Apart from that, the inconsistency may be due \nto the fact that DAPI shows blue fluorescence in both \nliving and dead cells, whereas PI only shows an \norange-red signal in dead cells (Zhu et al., 2020). \n \nSince, the genome size of mangosteen was \nsignificantly higher than G. opaca and G. penangiana \nwhich could suggest the hybridization between these \ntwo species. One of the indicators of hybridization \nhad occurred was the changes in phenotypic \ncharacteristics due to the alteration of DNA content \n(Madon et al., 2008; Renny-Byfield et al., 2014) as the \nvariation in phenotypic characteristics within the \nsame species already being observed in other species. \nHybridization can lead to the infusion of new genetic \ninformation, which is either immediately removed or \npartially removed by selection, leaving behind a \nmodified genome. When compared to its progenitors, \nthe particular identity and relationships involving \nintrogressed material and adaptive phenotypes \nremains unclear or at least incompletely described \n(Nieto Feliner et al., 2020). The variation in the \ngenome may originated from endopolyploidy, \nendoreduplication, obstruction of DNA synthesis, \naneuploidy or modulation of repetitive sequences, \n\n\n\ntranslocations and inversions, homoeologous \nexchanges and presence-absence variation (Madon et \nal., 2008; Nieto Feliner et al., 2020). In addition, the \namount of transposable elements may also affects \nDNA content since transposable elements able to \nchange its location and as well as its number of copies \nin the genome (Sabot et al., 2004). \n \nThe information regarding the interspecific genome \nsize between closely related species may provide an \ninsight on the evolution mechanism that occurred as \nwell as taxonomic heterogenity (Bennett & Leitch, \n2005). Interspecific hybridization has been observed \nin other plant species including soybean (Rayburn et \nal., 1997), sunflower (Michaelson et al., 1991), pea \n(Arumuganathan & Earle, 1991) and corn (Rayburn et \nal., 1989). Establishing a good understanding of \ninterspecific variation may help in contributing to \nevolutionary theory in plants as proposed by \u0160marda \n& Bure\u0161 (2010) that latest taxa may have relatively \nlarger interspecific genome size variation compared \nto its previous taxa as Madon et al. (2008) \ndemonstrated interspecific hybrids between two \nElaeis species can produce new individuals with larger \ngenome size as compared to its parents. As \ninterspecific variation naturally occurring \nphenomena, it's reasonable to assume that \nwidespread genetic recombination in nature would \nresult in a plethora of recombinant individuals with a \nvast array of genetic potentials from which selection \nfor positive (adaptive) or negative (deleterious) \nbiochemical and/or physiological attributes and their \ninteractions could take place. Transgressive \nsegregation is more common in plant breeding for \nfeatures that provide an adaptive advantage in less-\nthan-ideal conditions (Benildo, 2019). Besides, \nMurray (2005) emphasised that the information on \ngenome size variation can be used in taxonomical \nclassification as there could be one than one entity \nwithin a species. \n \nConclusion \nIdentifying the origin of mangosteen would require a \nthorough investigation as mostly previous studies \nfocusing more on molecular and morphological \naspects. Multiple theories on the origin of \nmangosteen have been proposed and the data of this \nstudy can help to fill the gap. This study revealed that \nthe genome size of G. opaca and G. penangiana \n(3.34\u00b10.05 pg and 4.77\u00b10.31* pg respectively) were \nsignificantly lower than mangosteen which supports \nthe idea of both species have the potential to be the \nparents of mangosteen as proposed in previous \nstudies. The genome size determination of two \nclosely related species, G. opaca and G. penangiana, \nto mangosteen can boost the understanding on the \ncomplex relationships between plant species in the \nsame genus. \n \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 33 of 36 \n\n\n\n\n\n\n\n\n\n\n\nAcknowledgements \nThis work was funded by Fundamental Research \nGrant Scheme (FRGS) from the Ministry of Higher \nEducation, Malaysia \n(FRGS/1/2019/STG03/UIAM/02/2). 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"\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2021, e-ISSN: 2811-3594 Page 7 of 15 \n\n\n\n\n\n\n\n\n\n\n\nOFFICIAL JOURNAL \n\n\n\nRESEARCH ARTICLE \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nEffect of Ion Beam Irradiation on Agro-Morphophysiological Traits \nof MA03 Rice Genotype \n\n\n\n \nJames Mackester Simoli1, Faiz Ahmad1*, Sobri Hussein1, Shakinah Salleh1, \n\n\n\nMohd Rafii Yusop2 and Abdul Rahim Harun1 \n\n\n\n\n\n\n\n1Agrotechnology and Biosciences Division, Malaysian Nuclear Agency, \n\n\n\nBangi, 43000 Kajang, Malaysia \n2Department of Crop Science, Faculty of Agriculture, Universiti Putra Malaysia, \n\n\n\n43400, Serdang, Malaysia \n\n\n\n \n*Corresponding author: faiz@nm.gov.my  \n\n\n\n\n\n\n\n\n\n\n\nIntroduction \nRice (Oryza sativa) is an essential food grain in Asia \nand contributes 90% of global rice consumption. \nAdditionally, rice is well known as the staple food \nfor local consumers and a small farmer's primary \nincome source. Currently, Malaysia possesses \naround 72% of the rice required for self-sufficiency \nlevel (SSL). Malaysia's government has set a target \nof producing 100% SSL rice to meet the country's \nexpanding population's needs (Rahim et al., 2017). \nThus, under the 10th Malaysia Plan, the \ngovernment kept improving the rice sector with \nvarious initiatives and strategies. The main focus \nwas on enhancing research and development and \ndeveloping existing infrastructures to increase the \nSSL level in Malaysia (Firdaus et al., 2020).\n\n\n\n \nClimate change, which affects precipitation, farm \n\n\n\nseasons, severe drought, flooding, and economic \n\n\n\nstagnation, causes hunger to increase (WHO, 2018). \n\n\n\nTherefore, climate change would affect the rice \n\n\n\nindustry in Malaysia based on the current climate \n\n\n\nchange issue. Different abiotic stresses restrict rice \n\n\n\nproduction in rainfed environments that make up \n\n\n\nabout 45% of the world's rice region (Lafitte et al., \n\n\n\n2004). Two of the most common abiotic factors that \n\n\n\naffect rice production across the globe are drought \n\n\n\nand floods (Dixit et al., 2017).  \n\n\n\n\n\n\n\nFlooding in Kedah and Pulau Pinang caused a \n\n\n\nsignificant drop in rice production in 2017. These \n\n\n\nhave harmed farmers' livelihoods and income and \n\n\n\nthe country's food security (Firdaus et al., 2020).  \n\n\n\n\n\n\n\nAlong with abiotic factors, biotic factors cause rice \n\n\n\nyield reduction significantly in the main granary \n\n\n\n \nAbstract \n\n\n\nIon Beam irradiation is one of the valuable breeding methods to create genetic variation. This method \n\n\n\nis widely used in many countries like Japan, China and Vietnam. MA03 is a rice mutant genotype \n\n\n\nderived from gamma irradiation of Manik variety in the year 1984. Unfortunately, this mutant has \n\n\n\nproduced round grains and is considered a late-maturing variety. Therefore, improvement of MA03 \n\n\n\nmutant type using ion beam irradiation is crucial. This study aims to identify the effects of ion beam \n\n\n\nradiation on agro-morphological traits of MA03. Seeds of MA03 genotype were irradiated at Quantum \n\n\n\nand Radiological Science and Technology (QST), Takasaki, Japan, at doses 0, 10, 20, 40, 60, 80 and 100 \n\n\n\nGy, respectively. The seedlings were planted in a glasshouse, and 10 agro-morphophysiological traits \n\n\n\nwere measured. All agro-morphophysiological traits measured except panicle length and panicle \n\n\n\nnumbers showed significant differences at (p\u22640.05) or (p\u22640.01). Based on reduction dose (RD50) on \n\n\n\nspikelet fertility, the optimum dose for ion beam irradiation is 59.11 Gy. The output from this study will \n\n\n\ngive valuable information for MA03 rice genotypes improvement program via ion beam irradiation, \n\n\n\nrespectively. \n\n\n\nKeywords: Ion beam irradiation; optimum dose; mutant genotype; MA03 \n\n\n\n\n\n\n\n*Corresponding author: Faiz Ahmad, Agrotechnology and \nBiosciences Division, Malaysian Nuclear Agency, \nBangi, 43000 Kajang, Malaysia \n\n\n\nEmail: faiz@nm.gov.my \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2021, e-ISSN: 2811-3594 Page 7 of 15 \n\n\n\n\n\n\n\n \nPage 8 of 15 \n\n\n\narea. Among the biotic factors limiting rice \n\n\n\nproduction in Malaysia includes diseases triggered \n\n\n\nby fungus, bacteria and viruses. Fungus such as \n\n\n\nPyricularia oryzae (Blast) causes a panicle to rot and \n\n\n\ndecrease the crop yield (DOA, 2020). Besides, \n\n\n\npathogenic bacteria, Xanthomonas oryzae causes \n\n\n\nwilting, yellowing and plant death (Lai & Chan, \n\n\n\n2016). \n\n\n\n\n\n\n\nPlant breeding is the best solution to overcome \n\n\n\nthese problems, consisting of various methods to \n\n\n\nselect and produce a variety with the preferable \n\n\n\npotentials on high yield, early maturity, flexible \n\n\n\nharsh environment, resistance to pests and \n\n\n\ndiseases. Additionally, ion beam irradiation is the \n\n\n\nmost effective, current, and reliable method to \n\n\n\ncreate variation in early generation populations. \n\n\n\nMany crops such as rice, barley and sorghum have \n\n\n\nbeen developed via ion beam irradiation.  \n\n\n\n\n\n\n\nThus, the objectives of this study are i) to \n\n\n\ndetermine the effect of ion beam irradiation on \n\n\n\nagro-morphophysiological traits of MA03 genotype \n\n\n\nand ii) to determine the optimum dose based on \n\n\n\nreduction dose (RD50) of spikelet fertility for MA03 \n\n\n\ngenotype.  \n\n\n\n\n\n\n\n\n\n\n\nMethod \n\n\n\nPlant Material  \n\n\n\nRice mutant variety MA03 was used in this study. \n\n\n\nThe seeds were obtained from the Malaysian \n\n\n\nNuclear Agency.  \n\n\n\n\n\n\n\nIrradiation Process \n\n\n\nIrradiation of carbon-ion beams on hulled rice \n\n\n\nseeds MA03 rice variety was done at Quantum and \n\n\n\nRadiological Science and Technology (QST), \n\n\n\nTakasaki, Japan. Takasaki Ion Accelerators for \n\n\n\nAdvanced Radiation Application (TIARA) was used \n\n\n\nas electron cyclotron resonance heavy-ion source \n\n\n\nto produce vertical ion-beam of carbon ion (12C+6; \n\n\n\n320 MeV) and accelerated by an Azimuthally \n\n\n\nVarying Field (AVF) cyclotron (Hidema et al., 2003). \n\n\n\nOnce the ray is produced, it undergoes scanning on \n\n\n\nan irradiation field more excellent than 60 x 60 mm2 \n\n\n\nto get homogenous irradiation.  \n\n\n\n\n\n\n\nThis process took place under vacuum conditions. \n\n\n\nThe beam was an exit to atmospheric condition \n\n\n\nthrough a titanium foil with 30 \u00b5m thickness as a \n\n\n\nfilter in the beam window. The physical properties of \n\n\n\nthe carbon ion-beam produced are as follows: the \n\n\n\nincident energy at the target surface is 311 MeV \n\n\n\n(25.9MeV/u). Seeds were sent back and developed \n\n\n\nto acquire survival curves and offspring. Unirradiated \n\n\n\nseeds (0 Gy) were used as control. \n\n\n\n\n\n\n\nExperimental Design  \n\n\n\nThe experimental design consists of 7 treatments \n\n\n\nconsisting of 0, 10, 20, 40, 60 and 80 Gy, with 5 \n\n\n\nreplications. The total of 175 planting pots required \n\n\n\nfor this experiment was filled with the prepared soil \n\n\n\nand arrangement on the rack, with one seedling per \n\n\n\npot. The experiment was arranged in a randomized \n\n\n\ncomplete block design (RCBD) where each \n\n\n\nreplication consists of 35 seedlings \n\n\n\n\n\n\n\nPlant Agronomy Management \n\n\n\nThe experiment was conducted in the glasshouse \n\n\n\nlocated in the Malaysian Nuclear Agency at Dengkil \n\n\n\nComplex. The soil was air-dried for one week and \n\n\n\ncrushed; then, the soil was mixed with urea, triple \n\n\n\nsuperphosphate (TSP), and muriate of potash (MOP) \n\n\n\nfertilizers. Urea was applied three times at 15, 30, \n\n\n\nand 45 days after transplanting. The rates applied \n\n\n\nwere 160 kg/ha of N as urea, 80 kg/ha of triple super \n\n\n\nphosphate (TSP) and 60 kg/ha of muriate of potash \n\n\n\n(MOP). The fertilizer calculation needed for each pot \n\n\n\nwas determined based on the surface area of the pot \n\n\n\nused (26 cm \u00d7 21 cm).  \n\n\n\n\n\n\n\nData Collection \n\n\n\nThe data collection regarding the agro-\n\n\n\nmorphological traits included i) Leaf Area, ii.) Leaf \n\n\n\nChlorophyll Content (mg/g FW), iii.) Plant Height \n\n\n\n(cm), iv.) Panicle Length (cm), v.) The Number of \n\n\n\nTillers, vi.) The Number of Panicles, vii.) Days to \n\n\n\nFlowering, viii.) Grain Yield/ Plant (g), ix.) Weight of \n\n\n\n1000 Grain (g) and x.) Spikelet Fertility. \n\n\n\n\n\n\n\nData Analysis  \n\n\n\nAnalysis of variance (ANOVA) and means \n\n\n\ncomparison of Tukey's HSD was performed to \n\n\n\nmeasure significant differences (p\u22640.05) or (p\u22640.01) \n\n\n\namong treatment on 10 Agro-morphological \n\n\n\ncharacteristics using Statistical Tool for Agricultural \n\n\n\nResearch (STAR) version 2.0.1. Curve Expert version \n\n\n\n1.4 was used to indicate the optimum dose based on \n\n\n\nreduction (RD50) of spikelet fertility. \n\n\n\n\n\n\n\n\n\n\n\n \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2021, e-ISSN: 2811-3594 Page 7 of 15 \n\n\n\n\n\n\n\n \nPage 9 of 15 \n\n\n\nResults and Discussion \n\n\n\nLeaf Area & Total Chlorophyll Contents for the \nPhysiological Data \n\n\n\nLeaf area shows significant differences from control \n\n\n\nat the dose of 20 Gy, 60 Gy and 80 Gy (Figure 1). \n\n\n\nANOVA showed significant differences among \n\n\n\ntreatments at (p\u22640.01). Hence the graph line for all \n\n\n\nthese parameters fluctuates, but the dose influences \n\n\n\nshow the line graph decreases after 0 Gy. This is \n\n\n\nbecause ion beams irradiation can generate a high \n\n\n\ndegree of mutagenic effects (Wang et al., 2008). \n\n\n\nMoreover, Ion beams can induce more significant \n\n\n\nalterations to live cells than other radiation sources, \n\n\n\nwhich lead to high biological efficiency (Blakely, \n\n\n\n1992; Lett, 1992). \n\n\n\n\n\n\n\n \nFigure 1: Graph showing the leaf area of MA03 in different doses of carbon ion-beams. \nNote: Means with the same letter are not significantly different among treatments using Tukey's Honest Significant \nDifference (HSD) Test at (p\u22640.05) or (p\u22640.01). \n\n\n\n\n\n\n\nThe line graph of total chlorophyll content reveals \n\n\n\nincreases at dose 10 Gy, and at dose 20 Gy, the total \n\n\n\nis drastically decreasing and declines at 40 Gy, 60 Gy \n\n\n\nand 80 Gy, respectively (Figure 2). An increase in dose \n\n\n\n10 Gy and 20 Gy affects the plant's chlorophyll level \n\n\n\ndue to the mutation caused by radiation. These \n\n\n\nresults relate to the study conducted by Borzouei et \n\n\n\nal. (2010). It reports an increase in chlorophyll \n\n\n\ncontent in wheat seedlings irradiated by low-dose \n\n\n\ngamma-rays, which might be due to growth \n\n\n\nstimulated by gamma-ray irradiation. The total \n\n\n\nchlorophyll shows significantly different among \n\n\n\ntreatments at (p\u22640.01) from ANOVA and no \n\n\n\nsignificant difference from control at 20 Gy, 40 Gy, 60 \n\n\n\nGy and 80 Gy except 10 Gy. \n\n\n\n\n\n\n\n \nFigure 2: Graph showing the total chlorophyll content of MA03 in different doses of carbon ion-beams. \n\n\n\nNote: Means with the same letter are not significantly different among treatments using Tukey's Honest Significant \n\n\n\nDifference (HSD) Test at (p\u22640.05) or (p\u22640.01). \n\n\n\n78.68a\n\n\n\n70.34ab\n\n\n\n61.79b\n\n\n\n69.13ab\n\n\n\n58.18b\n\n\n\n63.11b\n\n\n\n40.00\n\n\n\n50.00\n\n\n\n60.00\n\n\n\n70.00\n\n\n\n80.00\n\n\n\n90.00\n\n\n\n0 10 20 40 60 80\n\n\n\nL\nE\n\n\n\nA\nF\n\n\n\n A\nR\n\n\n\nE\nA\n\n\n\n (\ncm\n\n\n\n2\n)\n\n\n\nDOSE (Gy)\n\n\n\nLeaf Area (cm2) \n\n\n\n15.39bc\n\n\n\n21.88a\n\n\n\n20.83ab\n\n\n\n14.38c\n\n\n\n13.75c\n13.77c\n\n\n\n0.00\n\n\n\n5.00\n\n\n\n10.00\n\n\n\n15.00\n\n\n\n20.00\n\n\n\n25.00\n\n\n\n0 Gy 10 Gy 20 Gy 40 Gy 60 Gy 80 Gy\n\n\n\nC\nH\n\n\n\nL\nO\n\n\n\nR\nO\n\n\n\nP\nH\n\n\n\nY\nL\n\n\n\nL\n C\n\n\n\nO\nN\n\n\n\nT\nE\n\n\n\nN\nT\n\n\n\n\n\n\n\n(m\ng\n/g\n\n\n\n)\n\n\n\nDOSE (Gy)\n\n\n\nTotal Chlorophyll Content\n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2021, e-ISSN: 2811-3594 Page 7 of 15 \n\n\n\n\n\n\n\n \nPage 10 of 15 \n\n\n\nPlant Height, Panicle Length, Number of Tiller, \n\n\n\nNumber of Panicles and Days of Flowering for the \n\n\n\nMorphology Data \n\n\n\nPlant height showed decreasing trend as ion beam \n\n\n\ndose increased (Figure 3). There are significant \n\n\n\ndifferences at (p\u22640.01) among treatments from \n\n\n\nANOVA. The reduced plant height may be due to \n\n\n\ndamage during cell division and elongation \n\n\n\n(Gowthami et al., 2017). Besides that, plant height \n\n\n\nwas used as an index for various physical mutagens' \n\n\n\nbiological effects (Gowthami et al., 2017).Panicle \n\n\n\nlength indicates the graph fluctuates at a specific \n\n\n\ndose and shows no significant difference from the \n\n\n\ncontrol (Figure 4).  \n\n\n\n\n\n\n\n\n\n\n\n \nFigure 3: Graph showing the plant height of MA03 in different doses of carbon ion-beams. \n\n\n\nNote: Means with the same letter are not significantly different among treatments using Tukey's Honest Significant \n\n\n\nDifference (HSD) Test at (p\u22640.05) or (p\u22640.01). \n\n\n\n\n\n\n\n\n\n\n\n \nFigure 4: Graph showing the panicle length of MA03 in different doses of carbon ion-beams. \n\n\n\nNote: Means with the same letter are not significantly different among treatments using Tukey's Honest Significant \n\n\n\nDifference (HSD) Test at (p\u22640.05) or (p\u22640.01). (line graf) \n\n\n\n\n\n\n\n108.58a\n\n\n\n104.06a\n102.38ab\n\n\n\n99.22ab\n\n\n\n92.72bc\n\n\n\n87.75c\n\n\n\n80.00\n\n\n\n85.00\n\n\n\n90.00\n\n\n\n95.00\n\n\n\n100.00\n\n\n\n105.00\n\n\n\n110.00\n\n\n\n115.00\n\n\n\n0 10 20 40 60 80\n\n\n\nP\nL\n\n\n\nA\nN\n\n\n\nT\n H\n\n\n\nE\nIG\n\n\n\nH\nT\n\n\n\n (\ncm\n\n\n\n)\n\n\n\nDOSE (Gy)\n\n\n\nPlant Height\n\n\n\n18.75ns\n\n\n\n19.83ns\n\n\n\n19.17ns\n\n\n\n19.48ns\n\n\n\n18.21ns\n\n\n\n18.83ns\n\n\n\n17.00\n\n\n\n17.50\n\n\n\n18.00\n\n\n\n18.50\n\n\n\n19.00\n\n\n\n19.50\n\n\n\n20.00\n\n\n\n0 10 20 40 60 80\n\n\n\nP\nA\n\n\n\nN\nIC\n\n\n\nL\nE\n\n\n\n L\nE\n\n\n\nN\nG\n\n\n\nT\nH\n\n\n\n (\ncm\n\n\n\n)\n\n\n\nDOSE (Gy)\n\n\n\nPanicle Length\n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2021, e-ISSN: 2811-3594 Page 7 of 15 \n\n\n\n\n\n\n\n \nPage 11 of 15 \n\n\n\nThe number of tillers increased when the dose of 10 \n\n\n\nand 20 Gy were applied but decreased at 40 to 60 Gy, \n\n\n\nrespectively (Figure 5). Besides that, it was apparent \n\n\n\nthat when the dose increased to 80 Gy, the number \n\n\n\nof tillers also increased, and there was a significant \n\n\n\ndifference at (p\u22640.01) at dose 60 Gy from control. \n\n\n\nAdditionally, the panicle number increased in a \n\n\n\ncertain amount of dose at 20 Gy and 80 Gy, but there \n\n\n\nwas no significant difference from control. However, \n\n\n\nit is better to have many tillers because many \n\n\n\npanicles can emerge from paddy, which has a lot of \n\n\n\ntillers. The more of the tiller number will increase \n\n\n\nplant yield in terms of quantity. Unfortunately, \n\n\n\nsometimes the tiller fails in producing a panicle, and \n\n\n\nthe only productive tiller will have a panicle. \n\n\n\nTherefore, any tool used as mutagens in mutagenesis, \n\n\n\nespecially when using physical mutagens such as \n\n\n\nionizing radiation, needs critical monitoring to \n\n\n\nidentify a dose range applied to get a maximum \n\n\n\nmutation (Tanaka et al., 1997). Furthermore, \n\n\n\noptimum dose determination is essential for our \n\n\n\nusers to get the highest mutation and desirable traits. \n\n\n\n\n\n\n\n \nFigure 5: Graph showing the number of tiller and number of panicles in MA03 on different doses of carbon ion-\n\n\n\nbeams. \n\n\n\nNote: Means with the same letter are not significantly different among treatments using Tukey's Honest Significant \n\n\n\nDifference (HSD) Test at (p\u22640.05) or (p\u22640.01). \n\n\n\n\n\n\n\nThe days to first Flowering in reveal significant \n\n\n\ndifferences among treatments at (p\u22640.01) for ANOVA \n\n\n\nand significant difference at 20 Gy, 40 Gy, and 80 Gy \n\n\n\nfrom control (Figure 6 ). The graph shows a decrease \n\n\n\nin days to first Flowering indicates a positive effect of \n\n\n\nion beam irradiation where we need these traits for \n\n\n\nearly maturity in rice plants. This result relates to \n\n\n\nHayashi et al. (2007) that early maturing mutants \n\n\n\nwere identified based on physiological and genetic \n\n\n\ncharacteristics examined. Early maturity benefits \n\n\n\nfarmers by reducing cost management and \n\n\n\naccelerating harvesting time to yield. \n\n\n\n\n\n\n\n \nFigure 6: Graph showing the days to first Flowering of MA03 in different doses of Carbon Ion-Beams. \n\n\n\nNote: Means with the same letter are not significantly different among treatments using Tukey's Honest Significant \n\n\n\nDifference (HSD) Test at (p\u22640.05) or (p\u22640.01).( letak determination dose tu bawah graf ini \n\n\n\n\n\n\n\n\n\n\n\n8.20ab 9.40a\n10.20a\n\n\n\n7.20ab\n\n\n\n4.80b 7.40ab\n\n\n\n6.28ns 6.52ns\n\n\n\n7.48ns\n\n\n\n5.49ns\n\n\n\n3.97ns\n5.47ns\n\n\n\n0.00\n\n\n\n2.00\n\n\n\n4.00\n\n\n\n6.00\n\n\n\n8.00\n\n\n\n10.00\n\n\n\n12.00\n\n\n\n0 10 20 40 60 80\n\n\n\nT\nO\n\n\n\nT\nA\n\n\n\nL\n N\n\n\n\nU\nM\n\n\n\nB\nE\n\n\n\nR\n\n\n\nDOSE (Gy)\n\n\n\nNo. of Tiller and Panicle\n\n\n\nNo.of Tiller No. of Panicle\n\n\n\n116.20a\n\n\n\n112.00ab\n111.00b\n\n\n\n110.80b 111.40ab\n\n\n\n110.00b\n\n\n\n106.00\n\n\n\n108.00\n\n\n\n110.00\n\n\n\n112.00\n\n\n\n114.00\n\n\n\n116.00\n\n\n\n118.00\n\n\n\n0 10 20 40 60 80\n\n\n\nD\nA\n\n\n\nY\nS\n\n\n\n T\nO\n\n\n\n F\nIR\n\n\n\nS\nT\n\n\n\n\n\n\n\nF\nL\n\n\n\nO\nW\n\n\n\nE\nR\n\n\n\nIN\nG\n\n\n\n (\nD\n\n\n\nay\n)\n\n\n\nDOSE (Gy)\n\n\n\nDays To First Flowering on Seedlings Stage\n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2021, e-ISSN: 2811-3594 Page 7 of 15 \n\n\n\n\n\n\n\n \nPage 12 of 15 \n\n\n\nGrain Yield/Plant, 1000 Grain Weight and Spikelet \n\n\n\nFertility for Agronomy Data \n\n\n\nThe grain yield per plant in Figure 7 shows decreasing \n\n\n\nweight as the dose of irradiation increases. There was \n\n\n\na significant difference among treatments at (p\u22640.01) \n\n\n\nfor ANOVA. Meanwhile, irradiated treatments at 10 \n\n\n\nGy, 20 Gy and 40 Gy show no significant difference \n\n\n\nfrom control. There is nothing change between the \n\n\n\ngrain yield and control, but it reveals the higher dose \n\n\n\nlowers the grain yield. This result coincides with \n\n\n\nYasmine et al. (2019) where the increase in the dose \n\n\n\nreceived lower the grain fertility. \n\n\n\n\n\n\n\nThe 1000 grain weight shows that the decreasing \n\n\n\nweight in the graph line from 0 Gy to 10 Gy and \n\n\n\nslightly increase then rapidly decrease started from \n\n\n\n40 Gy (Figure 8). Although the 1000 grain weight \n\n\n\ndecrease started from 0 Gy, there is no significant \n\n\n\ndifference from control at 10 Gy, 20 Gy, and 40 Gy. It \n\n\n\nindicates the optimum dose range between these \n\n\n\nranges from 10 Gy to 40 Gy. This situation needs to \n\n\n\nbe considered because there would be not enough \n\n\n\nmutation generated if too low, and the most \n\n\n\noptimum doses likely produce desirable traits. In fact, \n\n\n\nGowthami et al. (2017) study that the optimum dose \n\n\n\nis the most mutable dose with minimum plant \n\n\n\ndamage. \n\n\n\n\n\n\n\nSpikelet fertility shows that it was significantly \n\n\n\ndifferent at 60 Gy and 80 Gy from control besides, it \n\n\n\nreveals that a higher dose can cause infertile plants \n\n\n\n(Figure 9). There was a significant difference among \n\n\n\ntreatments at (p\u22640.01) for ANOVA. The study on the \n\n\n\neffect of a higher linear energy transfer (LET) of heavy \n\n\n\nion beam irradiation in rice shows the spikelet \n\n\n\nfertility percentage in the main panicle of the M1 \n\n\n\nplant decreased with the increases of dose. (Hayashi \n\n\n\net al., 2018). We can also determine the optimum \n\n\n\ndose through these results and basically below this \n\n\n\ndose range if we want to have the desirable trait in \n\n\n\nfuture studies. \n\n\n\n\n\n\n\n \nFigure 7: Graph showing the grain yield per plant of MA03 in different doses of carbon ion-beams. \n\n\n\nNote: Means with the same letter are not significantly different among treatments using Tukey's Honest Significant \n\n\n\nDifference (HSD) Test at (p\u22640.05) or (p\u22640.01). \n\n\n\n\n\n\n\n \nFigure 8: Graph showing the 1000 grain weight of MA03 in different doses of carbon ion-beams. \n\n\n\nNote: Means with the same letter are not significantly different among treatments using Tukey's Honest Significant \n\n\n\nDifference (HSD) Test at (p\u22640.05) or (p\u22640.01).  \n\n\n\n10.08a\n\n\n\n8.73a 8.62a\n\n\n\n6.62a\n\n\n\n2.06b 1.98b\n\n\n\n0.00\n\n\n\n2.00\n\n\n\n4.00\n\n\n\n6.00\n\n\n\n8.00\n\n\n\n10.00\n\n\n\n12.00\n\n\n\n0 10 20 40 60 80\n\n\n\nG\nR\n\n\n\nA\nIN\n\n\n\n Y\nIE\n\n\n\nL\nD\n\n\n\n/P\nL\n\n\n\nA\nN\n\n\n\nT\n (\n\n\n\ng\n)\n\n\n\nDOSE(Gy)\n\n\n\nGrain Yield/Plant at Seedlings Stage\n\n\n\n17.50a\n\n\n\n16.48ab 16.68ab 16.58ab\n\n\n\n14.91b\n\n\n\n14.25b\n\n\n\n12.00\n\n\n\n13.00\n\n\n\n14.00\n\n\n\n15.00\n\n\n\n16.00\n\n\n\n17.00\n\n\n\n18.00\n\n\n\n0 10 20 40 60 80\n\n\n\n1\n0\n\n\n\n0\n0\n\n\n\n G\nR\n\n\n\nA\nIN\n\n\n\n W\nE\n\n\n\nIG\nH\n\n\n\nT\n (\n\n\n\ng\n)\n\n\n\nDOSE (Gy)\n\n\n\n1000 Grain Weight at Seedlings Stage (g)\n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2021, e-ISSN: 2811-3594 Page 7 of 15 \n\n\n\n\n\n\n\n \nPage 13 of 15 \n\n\n\n \nFigure 9: Graph showing the spikelet fertility of MA03 in different doses of carbon ion-beams.  \n\n\n\n Note: Means with the same letter are not significantly different among treatments using Tukey's Honest Significant \n\n\n\nDifference (HSD) Test at (p\u22640.05) or (p\u22640.01). \n\n\n\n\n\n\n\nDetermination of Optimum Dose on MA03 Rice  \n\n\n\nVariety \n\n\n\nBased 10 agro-morphophysiological traits were \n\n\n\nmeasured, spikelet fertility was used to determine \n\n\n\nthe optimum dose of MA03 rice variety. The spikelet \n\n\n\nfertility of rice variety MA03 decreases when the \n\n\n\ntreatment dose increases (Figure 10). The 50-60 Gy \n\n\n\nrange dose is considered the optimum dose of the \n\n\n\nion beam irradiation for rice mutant variety MA03 \n\n\n\nbased on the 'Reduction Dose Curve Response'. The \n\n\n\nshoulder dose is suitable to compare the 'lethal dose' \n\n\n\nto determine the optimum dose in inducing mutation \n\n\n\nto generate new mutant varieties with the desirable \n\n\n\ntraits (Van Harten, 1998). We found that the plant \n\n\n\nagronomy based on spikelet fertility of the MA03 \n\n\n\nvariety significantly reduces after 60 Gy. This relates \n\n\n\nto study on biological of Carbon Ion on Rice indicates \n\n\n\ngrowth and ripening rates dropped significantly \n\n\n\nwhen the carbon \u2013 ion dose was increased (Hidema \n\n\n\net al, 2003) \n\n\n\n\n\n\n\nRD50 (y-axis) = 40.1578 \n\n\n\nRD50 (x-axis) = 59.1104 \n\n\n\n\n\n\n\n \nFigure 10: Effect of ion beam irradiation on growth rate of MA03 mutant rice variety at the 90th day after sowing. \n\n\n\nThere was polynomial fit Y=a + bx +cx2 +dx3 with a= 8.0759, b = - 1.905136, c = -2.4780, and d = - 3.5836 \n\n\n\n*Note: The highlighted curve is the range of the optimum dose (Gy) and the marked line show intersection \n\n\n\npoint of RD50. \n\n\n\n\n\n\n\n80.32a\n74.85a 75.58a\n\n\n\n75.44a\n\n\n\n37.95b\n\n\n\n26.41b\n\n\n\n0.00\n\n\n\n10.00\n\n\n\n20.00\n\n\n\n30.00\n\n\n\n40.00\n\n\n\n50.00\n\n\n\n60.00\n\n\n\n70.00\n\n\n\n80.00\n\n\n\n90.00\n\n\n\n0 10 20 40 60 80\n\n\n\nS\nP\n\n\n\nIK\nE\n\n\n\nL\nE\n\n\n\nT\n F\n\n\n\nE\nR\n\n\n\nT\nIL\n\n\n\nIT\nY\n\n\n\n (\n%\n\n\n\n)\n\n\n\nDOSE (Gy)\n\n\n\nSpikelet Fertility at Seedlings Stage\n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, YYYY, e-ISSN: 2811-3594 \n \n\n\n\nPage 10 of 17 \n\n\n\n\n\n\n\n \nPage 14 of 15 \n\n\n\nConclusion \n\n\n\nIn conclusion, ion beam irradiation affects the agro-\n\n\n\nmorphophysiological traits of MA03 variety. All the \n\n\n\nagro-morphophysiological traits show significant \n\n\n\ndifferences among treatments evaluated except \n\n\n\npanicle length and panicle number.The spikelet \n\n\n\nfertility was used to measure the optimum dose \n\n\n\nbased on reduction (RD50) is around 50 Gy-60 Gy.  \n\n\n\n\n\n\n\n\n\n\n\nAcknowledgement \n\n\n\nThe author would like thank to the Malaysian \n\n\n\nNuclear Agency (MNA) and Universiti Putra \n\n\n\nMalaysia (UPM) for all the research facilities. The \n\n\n\ngratitude also extended to the Forum for Nuclear \n\n\n\nCooperation in Asia (FNCA) for the seed irradiation \n\n\n\nprogram.  \n\n\n\n\n\n\n\n\n\n\n\nReferences \n\n\n\nArnon, D. I. (1949). Copper enzymes in isolated \n\n\n\nchloroplasts. Polyphenoloxidase in Beta \n\n\n\nvulgaris. Plant physiology, 24(1), 1. \n\n\n\n\n\n\n\nAshraf, M., and M. 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Comparison of \n\n\n\nLET effect of heavy-ion beam irradiation in \n\n\n\n\nhttp://www.doa.gov.my/index/resources/aktiviti-sumber/sumber-awam/maklumat-biosekuriti/perosak-tanaman-padi.pdf\n\n\nhttp://www.doa.gov.my/index/resources/aktiviti-sumber/sumber-awam/maklumat-biosekuriti/perosak-tanaman-padi.pdf\n\n\nhttp://www.doa.gov.my/index/resources/aktiviti-sumber/sumber-awam/maklumat-biosekuriti/perosak-tanaman-padi.pdf\n\n\nhttps://www.thestar.com.my/news/nation/2016/12/06/farmers-suffer-losses-after-blight-destroys-crops/\n\n\nhttps://www.thestar.com.my/news/nation/2016/12/06/farmers-suffer-losses-after-blight-destroys-crops/\n\n\nhttps://www.thestar.com.my/news/nation/2016/12/06/farmers-suffer-losses-after-blight-destroys-crops/\n\n\nhttps://www.who.int/news-room/detail/11-09-2018-global-hunger-continues-to-rise---new-un-report-says.%20Retreived%2019%20December%202020\n\n\nhttps://www.who.int/news-room/detail/11-09-2018-global-hunger-continues-to-rise---new-un-report-says.%20Retreived%2019%20December%202020\n\n\nhttps://www.who.int/news-room/detail/11-09-2018-global-hunger-continues-to-rise---new-un-report-says.%20Retreived%2019%20December%202020\n\n\nhttps://www.who.int/news-room/detail/11-09-2018-global-hunger-continues-to-rise---new-un-report-says.%20Retreived%2019%20December%202020\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, YYYY, e-ISSN: 2811-3594 \n \n\n\n\nPage 10 of 17 \n\n\n\n\n\n\n\n\n\n\n\nPage 15 of 15 \n\n\n\nrice. RIKEN Accel Prog Rep, 51, 238. \n\n\n\n\n\n\n\nHidema, J., Yamoto, M., Kumagai, T., Hase, Y., \n\n\n\nSakamoto, A., & Tanaka, A. (2003). Biological effects \n\n\n\nof carbon ion on rice (Oryza sativa L.). JAERI-\n\n\n\nreview, 33, 85-87. \n\n\n\n \n\n\n\n\n\n"
"\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 1 of 10 \n\n\n\n\n\n\n\n\n\n\n\nOFFICIAL JOURNAL \n\n\n\nRESEARCH ARTICLE \n\n\n\n\n\n\n\nFull-Term Amniotic Fluid Stem Cell Line Maintains Its Genome \nStability upon Prolonged Culture and Cryopreservation \n\n\n\n \nMuhammad Muhtadee Amran1, Mathandaver Devasharmini1, Khairul Akmal \n\n\n\nAbdul Rahman1, Siti Sarah Mustaffa Al Bakri1, Nurfarhana Ferdaos3, \nNorshariza Nordin1,2* \n\n\n\n\n\n\n\n1Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, 2Genetics and Regenerative Medicine (ReGEN) \nResearch Group, Universiti Putra Malaysia, Serdang, Malaysia, 43400 UPM Serdang, Selangor, Malaysia \n\n\n\n3Department of Pharmacology and Chemistry, Faculty of Pharmacy Kampus Puncak Alam, 42300 UiTM Cawangan Selangor, \nMalaysia \n\n\n\n \n*Correspondence: shariza@upm.edu.my \n\n\n\n\n\n\n\n\n\n\n\nIntroduction   \nOver the past few decades, life expectancy has \nsignificantly escalated, increasing the prevalence and \nburden of ageing-related disorders globally, known as \ndegenerative diseases (Mateo et al., 2020). \nUnfortunately, treatment for most degenerative \ndiseases, particularly neurodegenerative diseases, \n\n\n\nonly alleviates the symptoms. Presently, there is no \ndefinitive cure for these diseases. One prospective \ntreatment is to use stem cells for regenerative therapy. \nConsequently, exploring suitable stem cell sources with \nhigh therapeutic potential has become indispensable \n(Loukogeorgakis & De Coppi, 2017). Stem cells hold \ntremendous therapeutic potential in regenerative \ntherapy by healing and regenerating cells, tissues, or \norgans to replace those whose functions have been \ncompromised by disease, tissue loss, ageing, or severe \ninjuries. Therefore, extensive \n\n\n\n \nAbstract \n\n\n\nAmniotic fluid stem cells (AFSCs) from full-term gestation pregnancy are broadly multipotent immune-\nprivileged cells. They have fewer ethical issues with promising therapeutic potential, making them an \nideal prospective stem cell type for therapy. Obtaining them in high quantity and quality in-vitro is \nessential for their use in bedside applications. One aspect of high-quality cells is maintaining their \ngenome stability upon prolonged culture and cryopreservation. Genome instability may cause \nmalignant transformation which may affect their effectiveness in therapy. Here, we aim to evaluate \nthe genome stability of our in-house established rat full-term AFSC line (R3) based on the chromosomal \nnumber and RNA expression of selected markers upon prolonged culture in-vitro and \ncryopreservation. The cryopreserved R3 at passages (P) 36 to 38 were revived and cultured. \nMorphological features of newly revived P36 and P37 cells were compared before subjecting P37 cells \nto karyotyping. A semi-q RT-PCR analysis using Image J was performed to evaluate the relative \nexpression level of markers for stemness (Nanog), tumour suppressor (p53), and senescence (p16) \ngenes against the housekeeping gene, GAPDH, using RNA extracted from P36 and P38 cells. RNA \nextracted from differentiated R3-derived neural stem cells (NSCs) was included as a positive control \nfor the non-transformational baseline. There was no significant difference in cell morphology between \nP36 and P37 cells. Karyotyping analysis revealed that the P37 cells retained the rat diploid chromosome \nnumber (2n=42). Only p53 was expressed in P36, P38 and NSCs, while Nanog and p16 remained \nsuppressed. Freshly thawed R3 from prolonged cryopreservation may induce stress factor on R3, \ncausing p53 pathway activation, thus inhibiting Nanog expression. However, the stress is still tolerable \nas the p16 gene remained suppressed, indicating R3 has not entered malignant transformation. This \nfinding marks R3 as a sensitive yet stable stem cell line that can be applied safely in downstream \napplications. \n\n\n\nKeywords: amniotic fluid stem cell; full-term rat amniotic fluid stem cell; genome stability; transformation and \nkaryotyping \n\n\n\nReceived: 15 04 2022; Accepted revised manuscript:  01 12 2022; \nPublished online: 01 04 2023 \n*Corresponding author: Dr Norshariza Nordin, Faculty of \nMedicine and Health Sciences, Universiti Putra Malaysia, \nSerdang, Selangor, Malaysia \nEmail: shariza@upm.edu.my \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 2 of 10 \n\n\n\n\n\n\n\n\n\n\n\nresearch on cell-based therapy is necessary to \nestablish and verify a robust downstream \nregenerative medicine application. The utilisation of  \nstem cell-based therapy is a promising alternative to \ntreat a variety of hereditary and degenerative \nillnesses due to the stem cells\u2019 unique properties, \nespecially their ability to self-renew and their high \ndifferentiation potential into various cell types. \nHence, obtaining these stem cells in a significantly \nlarge and adequate amount is necessary for cell-\nbased therapy and transplantation (Ramasamy et al., \n2018). \n \nEfforts have been made to investigate a different \nsource of pluripotent or broadly multipotent stem \ncells free of tumorigenesis and ethical ambiguity. As \nsuch, the amniotic fluid stem cells (AFSCs) line, which \nis derived from amniotic fluid (AF) from either mid-\nterm or full-term gestation, could be such a robust \nstem cell line that fulfils the criteria of an alternative \nsource for stem cells and has become a recent study \nfocus (Ramasamy et al., 2018). Previous research has \nsuggested that AFSCs have a promising therapeutic \napplication in regenerative medicine due to their \nbroad multipotency status and less ethical concerns \n(Antonucci et al., 2012). Indeed, several groups have \nisolated AFSCs from various species, including \nhumans (You et al., 2017) and animals such as mice \n(De Coppi et al., 2007), rats (Bollini et al., 2011; \nFerdaos et al., 2008; Mun-Fun et al., 2015), canines \n(Choi et al., 2013), bovines (Rossi et al., 2014) and \nequines (Iacono et al., 2012). \n \nMammalian pregnancy, such as human, is divided into \nthree trimester periods of gestation. The first \ntrimester begins from the first to the thirteenth \nweeks of gestation. The second trimester is from \nweek-14 to 27, the third trimester begins from week-\n28 and the full-term gestation is from week-37 to 40 \n(Guerrero & Florez, 1969; reviewed in Hamid et al., \n2017). Human AFSCs (hAFSCs) can be harvested from \nAF of various gestation periods, including from the \nsecond trimester AF collected via amniocentesis, \nwhere these stem cells are commonly used for a \nprenatal diagnosis for screening any abnormalities in \nthe foetal development such as Down\u2019s syndrome or \nfor identifying the gender of the foetus using \nkaryotyping (De Coppi et al., 2007; Delo et al., 2006; \nKlemmt et al., 2011; reviewed in Aziz et al., 2019). \n \nHuman AFSCs hold great prospects as competent cells \nto be used in regenerative medicine and stem cell-\nbased therapy (Guo et al., 2002; Yu et al., 2016) as \nthese stem cells exhibit characteristics of highly \nproliferative cells that express pluripotent markers \n(i.e., Nanog, and Oct4) (Aziz et al., 2016), hence the \ncells are observed to have wide differentiation \npotential (Bossolasco et al., 2006; De Coppi et al., \n2007; reviewed in Rodrigues et al., 2018). The cells \n\n\n\nalso have low tumorigenicity (Bossolasco et al., 2006; \nThirumala et al., 2013), thus preventing teratoma \nformation when injected into an immunocompromised \nanimal model (Perin et al., 2007; Davydova et al., 2009). \nThese characteristics of hAFSCs are similar to the mouse \n(De Coppi et al., 2007) and rat AFSCs (Mun-Fun et al., \n2015). Therefore, obtaining sufficient quantity and \ngood quality of AFSCs when culturing them in-vitro is \nessential (Rosner et al., 2012). However, stem cell \ngenome instability due to prolonged culture has \nbecome a concern. This can affect its therapeutic \neffectiveness in regenerative medicine applications and \nmay present a significant biosafety threat (Kuniakova et \nal., 2015). Assessing the stem cell\u2019s genome stability \nupon prolonged culture and cryopreservation hence \nbecomes crucial. \n \nOur in-house established rat-full-term AFSC line (R3) \n(Mun-Fun et al., 2015) from AF of pregnant Sprague \nDawley (SD) rats on the 20th day of gestation has been \ncultivated up to 100 passages without losing its \ndifferentiation ability. However, the genome stability \nstatus of the R3 upon prolonged cultures has yet to be \nassessed at chromosomal and RNA expression levels. \nThis raises some concerns about the high likelihood that \nthe ex-vivo expansion may result in genetic instability (a \ncell\u2019s genetic condition that consists of mutations \nacquisition, DNA repair deficiency and chromosomal \nabnormality) and malignant transformation (cells \ndisplay malignant-like phenotypes such are \nimmortalization, cell contact inhibition suppression and \nmalignancy) (Borgonovo et al., 2014). These conditions \nmay impact the R3 therapeutic efficacy in downstream \napplications. \n \nIn this study, we aim to investigate the genome stability \nbased on the chromosome number and the RNA \nexpression levels of relevant markers (Nanog, p53, and \np16) that indicate the transformation state of rat full-\nterm AFSC line upon prolonged cultures [R3 passage 36 \n(P36) to P38]. The study's findings may contribute to the \noptimisation and utilisation of genetic quality checking \nfor downstream applications and merits either in \nresearch or in clinical applications that are applicable to \nhuman regenerative medicine and veterinary \nregenerative medicine. \n \nMethods \nStem Cell Line Culture \nThe stem cell line used was the full-term rat amniotic \nfluid stem cell line (R3) established in-house by Mun-\nFun et al. (2015). P36 R3 cells were revived from the \nliquid nitrogen tank and cultured in the culture media \nthat contained; Glasgow Minimum Essential Medium \n(GMEM), supplements, 10% foetal bovine serum (FBS) \n(Gibco) and 15 ng/mL leukaemia inhibitory factor (LIF). \nThe culture flask was pre-coated with 0.1% porcine \ngelatine (Sigma). When the R3 reached confluency at \n70-80%, the cells were harvested using 0.25% trypsin-\n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 3 of 10 \n\n\n\n\n\n\n\n\n\n\n\nEDTA (Gibco) for three minutes of incubation. The R3 \ncells were then passaged to P37 and P38. The P36 R3 \ncells were also transdifferentiated into the neural \nstem cells (NSCs) for the non-transformational \nbaseline control. \n \nKaryotyping \nP37 R3 were subjected to karyotyping. The cells\u2019 \nmetaphase was blocked using a freshly prepared 100 \nng/mL of colcemid (Gibco) in ethanol for 2 hours and \n30 minutes. The hypotonic solution for cell bursting \nwas carried out using a freshly prepared 0.75 M \nhypotonic potassium chloride solution (Scharlau). The \ncells were fixed using a 1:3 ratio of Carnoy\u2019s fixative \nof methanol (J.T. Baker) and glacial acetic acid \n(Friedemann-Schmidt). Two different drying methods \nwere applied for optimisation: air-drying and hot \nplate drying at 55\u2103. Once dried, the karyotype \nsamples were observed under a light microscope \n(Olympus), and the metaphase spread of \nchromosomes was counted manually. \n \nPrimer Designing Tools \nThe primer pairs sequences were designed by using \nthe PrimerBlast software from the National Center of \nBiotechnology Information (NCBI). The website was \nretrieved at: https://www.ncbi.nlm.nih.gov/tools/ \nprimer-blast/index.cgi. The primer pairs that were \ndesigned by PrimerBlast (NCBI) software were Nanog \n(NM_001100781.1), p16 (NM_031550.2), and GAPDH \n(NM_017008.4); meanwhile, only p53 \n(NM_030989.3) primer was taken from Bars-Cortina \net al., (2019) published paper. The primer sets were \nfurther analysed and verified its integrity and quality \nusing bioinformatic software: the Sequence \nManipulation Suite (retrieved from: \nhttps://www.bioinformatics.org/sms2/pcr_ primer_s \ntats.html) and the Beacon Designer (Primer Biosoft \nInternational, retrieved from: https://www.premier \nbiosoft.com/qOligo/Oligo.jsp?PID=1). The primers \nwere purchased from Integrated DNA Technologies \nco. (IDT). All primer pairs were optimised for their \nannealing temperatures by performing the gradient \nPCR analysis for each primer set. \n \nSemi-Quantitative Reverse Transcription PCR (Semi-\nq RT-PCR) Test \nR3 cell lines at P36 and P38, and NSCs were subjected \nto RT-qPCR for Nanog, p53, p16 and GAPDH (as \n\n\n\nhousekeeping gene). Total RNA was extracted from the \ncells (RNeasy\u00ae Mini Kit, Qiagen) and they were \nsubjected to cDNA synthesis (QuantiTect\u00ae Reverse \nTranscription Kit, Qiagen). Polymerase Chain Reaction \n(PCR) was performed using the PCR reagents (Promega \nPCR kits) according to the manufacturer\u2019s protocol. The \nPCR mix consisted of 1.5 mM MgCl2, 0.2 mM dNTPs mix, \n10 pmol/\u03bcL of each forward and reverse primer, 1U Taq \nDNA polymerase, 1X PCR buffer and nuclease-free \nwater. The conventional PCR was done using the \nPeqLab thermal cycler (PeqStar, Germany) and ran the \nPCR product on agarose gel electrophoresis analysis. \nThe gel image was further analysed for the semi-\nquantification using Image J. The normalisation of gene \nexpression was done against the housekeeping gene \nexpression. \n \nStatistical Analysis \nSPSS Statistics Version 27.0 (IBM SPSS Inc., Chicago, IL) \nwas used as the statistical analysis tool. Results were \npresented as in mean \u00b1 standard error (SEM) to \nmeasure the relative RNA expression levels (i.e., Nanog, \np53 and p16) between different passages of R3 (early: \nP36, and late: P38). A bar graph was plotted using \nMicrosoft Excel (Office 365). \n \nResult and Discussion \nIn this study, we assessed the effect of long-term \nculture (passages 36-38) and cryopreservation on the \ngenome stability of the amniotic fluid stem cell line (R3) \nestablished from AF of full-term gestation pregnant rats \n(Mun-Fun et al., 2015).  The genome stability was \nexamined based on the chromosome number and the \nexpression of Nanog, p53 and p16. A newly thawed R3 \nof P36 was cultured and propagated into P37 and P38 \nbefore being subjected to further analyses.  We began \nby analysing the morphology of the cells at P36 and P37 \nbefore subjecting P37 cells to karyotyping.  P36 and P38 \ncells were used for assessing the gene expression to \ndetermine the stem cells' sensitivity upon reviving. \n \nMorphology Comparison Assessment \nThe first assessment was on the morphological features \nof R3 at P36 and P37 upon reviving the cells from \ncryopreservation. We found that both passaged cells \nretained similar features exhibiting good quality AFSCs \nwith multiple nucleoli, high cytoplasmic-nucleolus ratio, \nand presented a cuboidal-like morphology (Figure 1). \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 4 of 10 \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n \nFigure 1. Morphology of R3 cell line at two different passages (P36 and P37) observed under objective lens 4x (A, \n\n\n\nB) and 20x (C, D) magnifications. The R3 cell line at (A) passage 36 exhibits a homogenous cuboidal-shaped \nmorphology and retains this morphological feature in (B) passage 37. Both passages had similar features of cells \n\n\n\nwith multiple nucleoli (red arrows) (C, D).  The scale bar is 100 \u00b5m and 500\u00b5m. \n \nThese morphological features, as shown and \ndescribed in Figure 1, perfectly match the \nmorphologies described by Mun-Fun et al. (2015) that \nthe c-kit positive cells isolated from rat full-term AF \nbeing more homogeneous, with most of the cells \nhaving a cuboidal morphology. In addition, according \nto Stepinski (2018), the ribosomes, which regulate \nprotein biosynthesis, are produced by nucleoli at a \nrate that is directly correlated with the rate of cell \ngrowth and proliferation. \n \nThis observation led us to conclude that the R3 has a \nhigh proliferation rate, as indicated by the presence \nof multiple nucleoli. This suggests that the R3 cells are \nproliferative and could propagate good-quality AFSCs \nfeatures upon prolonged culture. The newly thawed \ncells (P36) also could transdifferentiate into NSCs \n\n\n\nindicating the differentiation potential is not lost \nupon prolonged culture and cryopreservation. Based \non the morphological assessment, the P36 R3-derived \nNSCs exhibit the expected morphology of NSCs \nsuggesting the success of the transdifferentiation \nprocess. There is a morphological difference between \nthe two groups as shown in Figure 2. \n \nThe P36 R3 cell line representing the undifferentiated \ngroup showed a homogenous cuboidal-like \nmorphology. Meanwhile, the NSCs represented the \ntransdifferentiated group showed elongated \npyramidal-shaped cells. Therefore, we may conclude \nthat the R3 cells at passage 36 to 37 have retained its \nundifferentiated state of AFSCs features and can \ntransdifferentiate into NSC-like cells. \n\n\n\n \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 5 of 10 \n\n\n\n\n\n\n\n\n\n\n\nFigure 2. Morphology of P36 R3 and P36 R3-derived NSCs observed under 4x objective lens magnification. (A) R3 \ncell line at P36 exhibits a homogenous cuboidal-like morphology. (B) The R3-derived NSCs showed elongated \n\n\n\npyramidal-shaped morphology. This group was used as the control group for the non-transformational baseline.  \nThe scale bar is 500\u00b5m. \n\n\n\nChromosomal Number Assessment \nThe second assessment was done on the karyotyping \nanalysis of R3 at P37, where the cells retained the \nstandard diploid chromosome number of rats, 2n=42 \n(Figure 3). The karyotypes presented a normal diploid \nchromosomal number of 42 for rats, suggesting \ngenomic stability with the maintenance of the \nchromosome number. \n \nRNA Expression Assessment \nOur final assessment was conducted on the RNA \nexpression levels of Nanog (stemness), p53 (tumour-\nsuppressor), and p16 (senescence and \ntransformation) on three groups of cells: \nundifferentiated R3 at P36 and P38, and R3-derived \nNSCs as baseline control and GAPDH as the \nhousekeeping gene. Nanog (Figure 4) and p16 (Figure \n5) genes were suppressed, but the p53 (Figure 6) gene \nwas activated in all groups. The expression of the p53 \ngene was then semi-quantified for its relative \nexpression normalised against GAPDH using the \nImage J analysis on the gel band \n\n\n\nintensities. A bar graph was plotted based on the \nmean value \u00b1 SEM measured from the normalisation \nof relative expression of the p53 gene against the \nGAPDH, as shown in Table 1 and Figure 7. \n \n\n\n\n \nFigure 3. The karyotyping analysis exhibits that P37 \nR3 retains its diploid chromosome numbers (2n=42) \nafter prolonged culture. The image is representative \nof three karyotypes, n=3.  The scale bar is 200\u00b5m \n\n\n\n\n\n\n\nFirst Gel Reading Second Gel Reading \n\n\n\n\n\n\n\n\n\n\n\nFigure 4. Both results showed that Nanog gel bands were absent in P36 and P38 R3 cell line and NSCs. This may \nindicate that Nanog was not expressed in these three samples. Meanwhile, GAPDH gel bands were observed in all \n\n\n\nsamples showing the expression of GAPDH. \n \n\n\n\nFirst Gel Reading Second Gel Reading \n\n\n\n\n\n\n\n \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 6 of 10 \n\n\n\n\n\n\n\n\n\n\n\nFigure 5. Both results showed that p16 gel bands were absent in P36 and P38 R3 cell line and NSCs. This may \nindicate that these three samples did not express the p16. Meanwhile, GAPDH gel bands remained present in all \n\n\n\nsamples showing that the GAPDH was expressed. \n \n\n\n\nFirst Gel Reading Second Gel Reading \n\n\n\n\n\n\n\n\n\n\n\nFigure 6. Both results showed the presence of p53 gel bands in P36 R3 cells and NSCs. This may indicate that all \nsamples expressed p53. In addition, GAPDH gel bands were observed in all samples showing the expression of \n\n\n\nGAPDH. \n \n\n\n\nTable 1. Band intensities semi-quantification of p53 and GAPDH genes using ImageJ analysis tool. \nMarker p53 GAPDH \nSample P36 P38 NSC NTC P36 P38 NSC NTC \n\n\n\nGel Reading 1 5453 5628 8782 0 5933 7367 17032 0 \nGel Reading 2 6506 7601 8466 0 8519 4105 12248 0 \nMean Value 5979 6615 8624 0 7226 5736 14640 0 \n\n\n\n\n\n\n\n \nFigure 7. The R3 cell line at P38 has the highest normalised p53 expression level (1.15 unit), followed by the R3 cell \nline at P36 (0.83 unit), while the NSCs had the lowest normalised expression level of the p53 gene (0.59 unit).  The \n\n\n\nerror bars are the mean value \u00b1 SEM.\n \nIt was found that the Nanog was not expressed by \nP36 and P38 R3 and NSCs (Figure 4). However, the \np53 was expressed by all cell types (Figures 6 and 7). \nThis may indicate that R3 cells were possibly \nexperiencing stress factors during reviving and \nculturing. According to Fu et al. (2019), under normal \nconditions, stem cells will express an average Nanog \nlevel, allowing them to have self-renewal ability and \nimmortality. However, when there is an oncogenic \ninsult or genotoxic stress, p53 is activated at high \n\n\n\nexpression. It inhibits Nanog from being expressed, \ncausing the stem cells to lose their stemness integrity \nand either enter spontaneous differentiation, \nsenescence, or apoptosis. This event simultaneously \nactivates p16 pathways (Ruzankina & Brown, 2007) to \ninhibit cell cycles which may lead to spontaneous \ndifferentiation, cell senescence, apoptosis, DNA \nrepairs or, in the worse case, may differentiate to \nmalignancy (malignant transformation) (Figure 8). \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 7 of 10 \n\n\n\n\n\n\n\n\n\n\n\n \nFigure 8. Summary of concept for stem cell survival in maintaining its genome stability. The diagram shows the \nrelationship between the p53 and p16 pathways and their outcomes. Nanog is important for stemness integrity; \np53s is the whole genome guardian, and p16 functions in cell cycle checkpoint and arresting when there is mutation \nor damage in the DNA sequence. \n\n\n\n \nAfter a prolonged period of cryopreservation and \nearly stage of reviving, R3 may experience stress \nwhich activates the p53 pathway and inhibits the \nexpression of Nanog transiently. The p16 gene \nremained suppressed, indicating that R3 has not \nundergone a malignant transformation; hence the \nstress is still tolerable. The behaviour of R3 cells in \nculture and the state of their genome stability may be \ndetermined by environmental factors. \n \nDuring R3 cell culture works, we also found the \nbehaviours of R3 cells were abnormal such as they \ntook about two months to attach and propagate \nbefore they reached high confluency (70-80%) upon \nfreshly thawed from cryopreservation. Usually, the \nR3 cells have a high proliferative rate at about 36 \nhours of population doubling (Mun-Fun et al., 2015). \nIt was also found that the R3 cells, within two months, \npresented high apoptotic bodies. These behaviours of \nR3 cells may validify our conclusion that the R3 cells \nexperienced stress during the cell culture and caused \nthe inhibition of Nanog expression due to the \nactivation of the p53 expression. \n \nWe suspected the R3 was misbehaving due to the \nprolonged cryopreservation, and freshly thawed \nculturing may induce cellular stress. Previous studies \nreported that culturing cells from freshly thawed and \ncryopreservation triggers the stress on the cells in \ncultures (Kenny et al., 2001; Van Casteren et al., \n\n\n\n2009). During cryopreservation and thawing, there \nwas a dynamic change in osmotic pressure between \nthe cell and its surrounding environment (Attaran et \nal., 1966; Das et al., 2010), which might influence the \nintracellular and cell membrane structures of the cells \n(Gittes et al., 1972). Due to that, the prolonged \nfreezing and thawing processes increase the cellular \nreactive oxygen species (ROS) formation (Bilodeau et \nal., 2000), cause oxidative stress to the cells, and \npromote cellular apoptosis and reduction in cellular \nfunctions. Upon freshly thawed and culturing, these \nactivities might have affected cell viability (Baumber \net al. 2000). \n \nWe found that the stress experienced by the R3 cells \nmay be tolerable as the p16 gene was not expressed \nin P36 and P38 R3 and NSCs (Figure 5). The p16 gene \nis a specialised tumour suppressor factor that plays a \nrole in cell cycle arrest that results in cellular \nsenescence (Serrano et al., 1993). Normal \nproliferative cells express p16 at a low level; however, \nDNA damage, oncogenic stress, and physiological \nageing will result in high levels of p16 expression \n(Bartkova et al., 2006; Collado et al., 2005; De Jonge \net al; 2009; Ressler et al., 2006; Serrano et al., 1997; \ncited in Witkiewicz et al., 2011). This phenomenon is \nessential in aged cells to control their cell \nproliferation rate and limit the growth of tumours \ntriggered by oncogenes (Bartkova et al., 2006). \n \nBased on the results, we can conclude that the stress \nfactors induced the R3 cells to activate p53 pathways \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 8 of 10 \n\n\n\n\n\n\n\n\n\n\n\nand led the R3 cells to undergo the DNA repairs and \ncellular apoptosis. But we could assure that the R3 \ncells had not entering the malignant transformation. \nThese findings indicate that the R3 cell line at \nprolonged cultures (P36 to P38) had a stable genome \nand indirectly showed that the R3 cells are sensitive \nto environmental stress like other highly proliferative \nstem cells. Mandal et al. (2011) stated that the cells' \nproliferative state determines the stem cells' \nsensitivity degree toward DNA damage. The higher \nthe proliferation state of the stem cells, the higher \nthe sensitivity of the stem cells towards the endo- and \nexogenous stress factors. \n \nConclusion \nOur findings revealed that the R3 genome is stable \nupon prolonged culture and cryopreservation. We \nalso discovered that R3, like other stem cell types, is \nsensitive to environmental stress. Future cell culture \nand application should consider both cellular ageing \nand environmental variables for stable cells for their \nsafe use in downstream applications in research and \nclinical fields. For future recommendations, we highly \nsuggest that the culture condition must be optimum \nwhen reviving cryopreserved cells. The newly thawed \ncells must be stabilised for few passages before using \nthem in downstream applications. \n \nAcknowledgement \nWe thank the Department of Biomedical Sciences for \nthe FYP fund and MOHE for FRGS \n(FRGS/1/2020/SKK06/UPM/02/2) and SCND \nResearch Group members: Chong Yoong Yi, Carmen \nDing & Wan Nur Tihani, family & friends. We declare \nno conflict of interest in this project. \n \nReferences \nAntonucci, I. et al. (2012). Amniotic Fluid Stem Cells: \nA Promising Therapeutic Resource for Cell-Based \nRegenerative Therapy. 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High risk of infertility and long-term gonadal \ndamage in males treated with high dose \ncyclophosphamide for sarcoma during childhood. \nCancer. 91:613\u2013621. \n \nKlemmt PA, Vafaizadeh V, & Groner B. (2011). The \npotential of amniotic fluid stem cells for cellular \ntherapy and tissue engineering. Expert Opin Biol Ther; \n11(10): 1297-314. \nhttps://doi.org/10.1517/14712598. 2011.587800. \n \nKuniakova M., Oravcova L., Varchulova-Novakova Z., \nViglaska D. & Danisovic L. (2015). Somatic stem cell \naging and malignant transformation \u2013 impact on \ntherapeutic application. Cellular and Molecular \nBiology Letters, 20 (5); 743- 756. \nhttps://doi.org/10.1515/cmble-2015-0045 \n \nLoukogeorgakis, S. P., & De Coppi, P. (2017). Concise \nReview: Amniotic Fluid Stem Cells: The Known, the \nUnknown, and Potential Regenerative Medicine \nApplications. Stem Cells, 35(7), 1663\u20131673. \nhttps://doi.org/10.1002/stem.2553 \n \nMandal, P.K., Blanpain, C., & Rossi, D.J. (2011). 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DOI: \nhttp://dx.doi.org/10.1016/j.rvsc.2015.07.010 \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 10 of 10 \n\n\n\n\n\n\n\n\n\n\n\nPerin, L., Giuliani S., Jin D., Sedrakyan S., Carraro G., \nHabibian R., Warburton D., Atala A., & De Filippo R., \nE. (2007). Renal differentiation of amniotic fluid stem \ncells. Cell Prolif, 40: 936\u2013948 \n \nRamasamy, T. S., Velaithan, V., Yeow, Y., & Sarkar, F. \nH. (2018). Stem Cells Derived from Amniotic Fluid: A \nPotential Pluripotent-Like Cell Source for Cellular \nTherapy? Current Stem Cell Research & Therapy, \n13(4), 252\u2013264. \nhttps://doi.org/10.2174/1574888x13666180115093\n800 \n \nRessler S, Bartkova J, Niederegger H, Bartek J, \nScharffetter-Kochanek K, & Jansen-D\u00fcrr P, et al. \n(2006). p16INK4A is a robust in vivo biomarker of \ncellular aging in human skin. Aging Cell; 5: 379\u201389. \ndoi: 10.1111/j.1474-9726.2006.00231.x. \n \nRodrigues, M., Antonucci, I., Elabd, S., Kancherla, S., \nMarchisio, M., Blattner, C., & Stuppia, L. (2018). p53 \nIs Active in Human Amniotic Fluid Stem Cells. Stem \nCells and Development, 27(21), 1507\u20131517. \nhttps://doi.org/10.1089/scd.2017.0254 \n \nRossi B, Merlo B, Colleoni S, Iacono E, Tazzari PL, & \nRicci F, et al. (2014) Isolation and in vitro \ncharacterization of bovine amniotic fluid derived \nstem cells at different trimesters of pregnancy. Stem \nCell Rev Rep, doi:http://dx.doi.org/ 10.1007/s12015-\n014-9525-0. \n \nRuzankina Y., & Brown E. J. (2007). Relationships \nbetween stem cell exhaustion, tumour suppression \nand ageing. British Journal of Cancer, 97; 192 \n \nSerrano, M., Hannon, G. J., & Beach, D. (1993). A new \nregulatory motif in cell-cycle control causing specific \ninhibition of cyclin D/CDK4. Nature; 366, 704\u2013707. \n \nSt\u0119pi\u0144ski, D. (2018). The nucleolus, an ally, and an \nenemy of cancer cells. Histochemistry and Cell \nBiology, 150(6), 607\u2013629. \nhttps://doi.org/10.1007/s00418-018-1706-5 \n \nThirumala S, Goebel WS, & Woods EJ. (2013). \nManufacturing and banking of mesenchymal stem \ncells. Expert Opin Biol Ther; 13(5): 673-91. \nhttps://doi.org/10.1517/14712598.2013.763925. \n \nVan Casteren N., J., van der Linden G., H., Hakvoort-\nCammel F., G., H\u00e4\u0650hlen K, Dohle G., R., & van den \nHeuvel-Eibrink M., M. (2009). Effect of childhood \ncancer treatment on fertility markers in adult male \nlong-term survivors. Pediatr Blood Cancer. 52:108\u2013\n112. \n \nWitkiewicz, A., K., Knudsen, K., E., Dicker, A., P., & \nKnudsen, E., S. (2011). The meaning of p16ink4a \n\n\n\nexpression in tumors: functional significance, clinical \nassociations, and future developments. Cell \nCycle;10(15):2497-503. doi: 10.4161/cc.10.15.16776. \nEpub 2011 Aug 1. PMID: 21775818; PMCID: \nPMC3685613. \n \nYou Q, Cai L, Zheng J, Tong X, Zhang D, & Zhang Y. \n(2017). Isolation of human mesenchymal stem cells \nfrom third-trimester amniotic fluid. Int J Gynecol \nObst, \ndoi:http://dx.doi.org/10.1016/j.ijgo.2008.06.012n.d. \n \nYu B, Cai H, Xu Z, Xu T, Zou Q, & Gu M. (2016). \nExpressions of stem cell transcription factors Nanog \nand Oct4 in renal cell carcinoma tis- sues and clinical \nsignificance. Artif Cells Nanomed Biotechnol; 44(8): \n1818-23. \nhttps://doi.org/10.3109/21691401.2015.1105238. \n \n\n\n\n\n\n\n \n*Correspondence: shariza@upm.edu.my\n\n\n\n"
"\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2021, e-ISSN: 2811-3594 \n \n\n\n\nPage 23 of 35 \n\n\n\n\n\n\n\n\n\n\n\nOFFICIAL JOURNAL \n\n\n\nREVIEW ARTICLE \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nDevelopment of Salinity Tolerant Rice through Induced Mutation \n \n\n\n\nMohamad Amirul Mohamad Zhahir1, Farah Habibah Md Zin1, Nor\u2019Aishah \nHasan2,3, Sobri Hussein4, and Shamsiah Abdullah1,2 \n\n\n\n\n\n\n\n1Faculty of Plantation and Agrotechnology, Universiti Teknologi MARA  \n\n\n\nCawangan Melaka, Kampus Jasin, 77300 Merlimau, Melaka \n2Agriculture Biotechnology Research Group, Universiti Teknologi MARA, Malaysia \n\n\n\n3Faculty of Applied Sciences, Universiti Teknologi MARA Cawangan Negeri Sembilan, \n\n\n\nKampus Kuala Pilah, 72000 Negeri Sembilan \n4Research Agrotechnology and Biosciences Division, Malaysian Nuclear Agency, \n\n\n\n 43000 Kajang, Selangor, Malaysia. \n \n\n\n\n*Correspondence: shamsiah3938@uitm.edu.my \n\n\n\n\n\n\n\n\n\n\n\nIntroduction \nRice (Oryza sativa) is an important staple crop in \nseveral countries including Malaysia that feeds \nalmost half of the world\u2019s population. Rice is the \nmonocotyledonous plant\u2019s model system (Thi et al., \n2016) and this diploid species having a tiny genome \ncompared to other farmed cereals (Moin et al., \n2017). Rice is an excellent food and source of \ncarbohydrates and energy (Fukagaw et al., 2019). \nTherefore, Rice has been the subject of research on \nfood security and sustainability. Furthermore, \ndespite the problem of economic growth effect and \nclimate change, with an increasing world population, \nhuman demands necessitate a rise in rice output \nresulting in food shortage (Tran et al., 2019; Qin et \nal., 2020). All of these problems are \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nexpected to boost the rice yields and attaining food \nsecurity much more difficult in future. Drought, \ntemperature, flood and salinity are all common abiotic \nstresses that rice face as they grow in dynamic settings \n(Qin et al., 2020).  \n\n\n\nIn vast rice-growing regions, all of these stressors \nresult in considerable yield losses. One of the most \nserious environmental stressors faced by Oryza sativa \nis salt stress because rice is the most salt-sensitive \namong other grains with salinity threshold of 3 dSm-1 \nfor most cultivated varieties (Hoang et al., 2016). One-\nfifth of the world's arable land and one-third of \nirrigated agricultural land are salt-affected, and the \nproblem is expected to be increasing at a very rapid \npace (Machado et al., 2017). It is assumed that the \nsalinity problem would affect 100,000\u2009ha of rice area \nby by 2056 (Hakim et al, 2014). Continuous intrusion \nof saline water would result in dwindling of rice area \nleading to food shortages in domestic and global \nmarkets. Many studies have been carried out to \ncomprehend the influences of saline habitats on seed \n\n\n\n \nAbstract \n\n\n\nSalinity has a range of impacts on rice including inhibition of germination, decrease in dry matter \n\n\n\nproduction, difficulties in crop area establishment and even sterility. As the world's population grows, so \n\n\n\ndoes the amount of land available for agricultural pursuits, hence improving salt tolerance of rice needed \n\n\n\nto increase the potential of saline land and ensure food security. Induced mutagenesis is one of the \n\n\n\npromising breeding strategies for trait improvement and ways to increase genetic variety in crops. In this \n\n\n\nreview, several rice mutant lines that were developed through mutagenesis using chemical (N-Methyl-N-\n\n\n\nNitrosourea and sodium azide) or physical (gamma ray & ion beam) mutagens have been discussed \n\n\n\nconcerning their effect for the rice crop improvement. The past and present progress in induced mutation \n\n\n\nfor rice tolerant is significant for future breeding program of this important crop. This article provides an \n\n\n\noverview of some potential approaches in rice and discusses the progress involved in enhancing salinity \n\n\n\nresistant in rice. \n\n\n\nKeywords: Induced mutation; Oryza sativa, rice; mutant line; mutagenesis; salinity; salt stress \n\n\n\n\n\n\n\n*Corresponding author: Dr shamsiah Abdullah, Faculty of \nPlantation and Agrotechnology, Universiti Teknologi MARA  \nCawangan Melaka, Kampus Jasin, 77300 Merlimau, Melaka \nEmail: shamsiah3938@uitm.edu.my \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, YYYY, e-ISSN: 2811-3594 \n \n\n\n\nPage 35 of 35 \n\n\n\n\n\n\n\n4 \n\n\n\ngermination, growth, reproduction, and population \ndynamics of crop plants.  \n \nHence, it is very important to create and produce \nOryza sativa that is tolerant to salt stress. \nFurthermore, a better understanding of the processes \nbehind salinity tolerance rice will aid in development \nof salinity tolerant cultivars (Qin et al., 2020). \nAccording to Hase et al. (2020), there were three \nimportant factors to the success of mutation breeding: \nthe efficiency of mutagenesis, the starting plant \nmaterial and mutant screening. Therefore, this review \nis to address the challenges and opportunities in \ndeveloping salt-tolerant rice through induced \nmutation. Furthermore, describes the potential \nmutagens and provides reference for efforts aimed at \nrapidly and precisely cultivating salt tolerance rice. \n \n \n \n \n\n\n\nRice (Oryza sativa) \nOryza sativa L. is the most important staple food crop \nfor more than 3.5 billion people worldwide and \nprovides a large fraction of the dietary protein and \ntotal food supply (Haque et al., 2021). Rice is one of the \nmajor cereals grains in the world and is one of the main \nsources of carbohydrate and protein (Arnarson et al., \n2020). Rice is Malaysia's third most important crop, \nfarmed mostly in eight granaries in Peninsular \nMalaysia, covering a total area of 681 559 acres in the \nyear 2015 and meeting around 70% of local demand \n(Department of Agriculture Peninsular Malaysia, 2016; \nFAMA, 2008). Malaysia needs to expand its rice land to \nmeet present and future domestic demands. Oryza \ngenus consists of 23 species, of which only two are \ncultivated (Menguer et al., 2017). Cultivated rice \n(Oryza sativa) is part of the Oryza genus including the \ncultivated African rice (Oryza glaberrima) (Manful et \nal., 2016). Figure 1 illustrates schematic \nrepresentation of evolutionary pathway of Asian and \nAfrican cultivated rice (Nadir et al., 2018).\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nFigure 1: Simplified schematic representation of the evolutionary pathways of Asian and African cultivated rice and the \nevolutionary dynamics of reproductive barriers in rice. \n\n\n\n (Adapted from Nadir et al., 2018) \n\n\n\n\n\n\n\nAdaptive divergence \n\n\n\nGenetic \ndifferentiation \n\n\n\nIntrogression \n\n\n\nSelection \n\n\n\nEcological \ndiversification \n\n\n\nCommon \nancestor \n\n\n\nOryza rufipogon \n\n\n\nWild perennial \n\n\n\nOryza nivara \n\n\n\nWild annual \n\n\n\nOryza sativa \n\n\n\nAnnual/perennial \n\n\n\nIndica Japonica \n\n\n\nTemperate \njaponica \n\n\n\nTropical \njaponica \n\n\n\nOryza longistaminata \n\n\n\nWild perennial \n\n\n\nOryza barthii \nWild annual \n\n\n\nOryza glaberrima \n\n\n\nAnnual \n\n\n\nAdaptive divergence \n\n\n\nGenetic differentiation \n\n\n\nIntrogression \n\n\n\nSelection \n\n\n\nEco-geographic \ndiversification \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, YYYY, e-ISSN: 2811-3594 \n \n\n\n\nPage 35 of 35 \n\n\n\n\n\n\n\n4 \n\n\n\nSalt Stress Study in Rice \n \nEffects of Salinity in Rice \nSalinity adversely affects seed germination, plant \ngrowth, and development, causing significant crop \nyield losses worldwide (Abdgawad et al., 2016). A \nplant\u2019s capacity, potential to develop and finish its life \ncycle on a field with high level of sodium chloride \nconcentration is referred to as salinity tolerance \n(Motos et al., 2017). It affects rice in two ways which \nfirst, increase salinity level within the rice can be \npoisonous and excessive salt concentrations make it \nmore difficult for roots to extract water in the soil \n\n\n\n(Shrivastava et al., 2015). Rice response to salt \ntolerance varies depending on its stage of \ndevelopment (Kordrostami et al., 2017). Unravelling \nthe mechanisms underlying these physiological and \nbiochemical responses to salt stress could provide \nvaluable strategies to improve agricultural crop yields \n(Zhao et al., 2021). Table 2 below demonstrates the \nphysiological, morphological and biochemical \n\n\n\nresponse of rice under salt stress. \n\n\n\n \n \nTable 2: Schematic table shows the physiological, morphological and biochemical responses of rice under salt stress. \n\n\n\nPhysiological responses Morphological responses Biochemical responses \n\n\n\n\u2022 Reduced cell membrane \nstability.  \n\n\n\n\u2022 Reduced photosynthesis and \nactivity of photosynthetic \nenzymes. \n\n\n\n\u2022 Reduced cell inflammation. \n\n\n\n\u2022 Rapid closure of stomata. \n\n\n\n\u2022 Disorder in ion absorption. \n(Ma et al., 2020) \n\n\n\n\u2022 Low tiller numbers. \n\n\n\n\u2022 Leaf tip burning reduced \nnumber of florets per panicle. \n\n\n\n\u2022 Low pollen viability. \n\n\n\n\u2022 Less panicle numbers. \n\n\n\n\u2022 Low harvest index and yield. \n\n\n\n\u2022 Less grain weight. \n\n\n\n\u2022 Stunted shoots and roots. \n(Celymar et al., 2020; Haq et al., \n2010, Akram et al. 2019) \n \n\n\n\n\u2022 Reduction in total chlorophyll \ncontent. \n\n\n\n\u2022 Changes in activity of \nantioxidant enzymes. \n\n\n\n\u2022 Accumulation of proline. \n\n\n\n\u2022 Changes in metabolism \n\n\n\n\u2022 Changes in antioxidant \nactivities \n\n\n\n(Mohammad et al., 2019; \nRahman et al., 2017). \n\n\n\n \n \nIn terms of salinity stress reactions at different life \nstages, rice has been reported to be resistant to salt \nthroughout maturation, appears to have less of an \nimpact on ripening and germination (Reddy et al., \n2017). However, it becomes responsive to salt stress \nduring seedling (2-3 leaf stages) (Hoang et al., 2016). \nApart from the seedling stage, reproductive phase \n(pollination and fertilization) is another highly \nresponsive to salt stress (Singh et al, 2015). As a result, \nthe seedling stage is the best time to divide rice \ngenotypes into groups depending on their salt tolerant \n(Das et al., 2015). \n \n \n \n\n\n\nSalt tolerance Mechanism in Rice \nUnderstanding the salt stress tolerance mechanism of \nrice is crucial for identifying the responsible genetic \nmaterial. The relationship between the physiological \nand molecular responses of plants causes the effect of \nsalt stress (Zhang et al., 2018). Rice plants may adapt \nto salt through complex mechanisms, making it critical \nand necessary to identify particular salinity tolerance \ncharacteristics. Rice adaptations to salinity divided into \nthree categories: tissue tolerance, osmotic tolerance \nand ion exclusion (Prusty et al., 2018; Assaha et al., \n2017; Samiullah et al., 2016; Hussain et al., 2017; Li et \nal., 2011; Mohammad et al., 2015; Reddy et al., 2017) \nas illustrated in Figure 2 below.\n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, YYYY, e-ISSN: 2811-3594 \n \n\n\n\nPage 35 of 35 \n\n\n\n\n\n\n\n4 \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nFigure 2: Adaptive mechanisms of rice under salt stress \n \n\n\n\n \n \nDevelopment of Salt Tolerant Through Induced \nMutation \nMany advanced strategies have been developed to \nimprove tolerant rice varieties that can respond to \nenvironmental challenges such as submersion and \ndrought (Singh et al., 2015). Nevertheless, because of \nits complex nature, overcoming the obstacles of rice \nsalt-tolerant enhancement is difficult. Salt tolerant is a \nquantitative trait controlled by several genes and can \nbe transmitted across subsequent generations, hence, \ncan be improved via identifying and isolating key genes \naccountable for salt stress with aid of modern \nmolecular techniques (Rahneshan et al., 2018). \nDespite the fact that phenotype is the ultimate \nexpression of molecular compositions, it is negatively \nimpacted by environmental factors via a variety of \nphysiological and biological processes (Huong et al., \n2020).  \n \nPlant breeding requires genetic variation of useful \ntraits for crop improvement. Often, however, desired \nvariation is either lacking or dwindling (Anders et al., \n2021). Moreover, the rate of spontaneous mutations \nis very low (Xu et al., 2019). Therefore, mutation \ninvestigation was a prior technique for the selection of \n\n\n\nthe most promising rice (Chaudhary et al, 2019). \nMutation occurs through the application of biological, \nchemical, or physical mutagens (Yusuf et al., 2016).The \nmost commonly used physical mutagens are gamma \nray, ion beam and chemical mutagens used are N-\nmethyl-N-nitrosourea (MNU), ethylmethane sulfonate \n(EMS) and sodium azides. \n \nChemical Mutagens used in rice tolerant \ndevelopment \nThe effects of chemical mutagent are silent or \nmissense mutations (50%) while only 5% of nonsense \nmutations are observed (Nawaz et al., 2014). The \nchemical mutagens were found to be highly effective \nin inducing true gene mutations and the specificity of \naction could be investigated through analysis of their \nreaction with different DNA base. As compared with \nphysical mutagens, chemicals may give rise to \nrelatively more gene mutations rather than to \nchromosomal changes. The assessment of optimum \ndose of mutagen for chemicals is determined by \nvarying the concentration and duration of treatment, \nthe solvent used or the pH of the solution (Kunzang et \nal., 2017). Table 3 shows several applications of \ninduced mutation in rice using chemical agents.\n\n\n\n\n\n\n\nSalt in soil \n\n\n\nIon exclusion mainly \n\n\n\ninvolves Na\n+\n and Cl\n\n\n\n-\n\n\n\nprevents their excess in \nleaves by absorbing a lot of \n\n\n\nwater and keeping salt \nlevels unchanged (Assaha \net al., 2017; Samiullah et \n\n\n\nal., 2016) \n\n\n\nInvolves Na\n+\n \n\n\n\ncompartmentalization in \nvacuoles, synthesis of \n\n\n\ncompatible solutes and \nproduction of enzymes \n\n\n\ncatalysing detoxification \nof reactive oxygen \n\n\n\nspecies (Reddy et al., \n2017). \n\n\n\nEndure the drought \ncomponent of salinity \n\n\n\nstress by increasing \ntrehalose and proline \n\n\n\ncontents while \nmaintaining stomatal \nconductance and leaf \nexpansion (Hussain \net al., 2017; Li et al., \n\n\n\n2011). \n\n\n\n \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, YYYY, e-ISSN: 2811-3594 \n \n\n\n\nPage 35 of 35 \n\n\n\n\n\n\n\n4 \n\n\n\nTable 3: Examples of mutant lines produced through chemical mutagens application for salt tolerant of rice. \n \n\n\n\n \nType of mutagen \n\n\n\n \nMechanism of mutation \n\n\n\n \nMutants produced \n\n\n\n \nReferences \n\n\n\nN-Methyl-N-\nNitrosourea (MNU). \n \n\n\n\nGuanine and cytosine \nalkylation, G/C to T/A \ntransitions. \n \n\n\n\nSKLo/BC15TB \nTBR1 X KD18 \nDT84 and Q5 \n\n\n\nHuong et al., 2020. \nXuan et al., 2019. \nKakar et al., 2019. \n \n\n\n\nEthyl \nmethanesulfonate \n(EMS) \n \n\n\n\nInduce G/C to A/T \ntransitions randomly. \n \n\n\n\nNagina 22 Mohapatra et al., \n2014. \n\n\n\nSodium azide (NaN3) \n \n\n\n\nG/C to A/T transition, \ninsertion, inversion, \nduplication and deletion. \n \n\n\n\nSalt hypersensitive (shs1). \nFARO-44, FARO-52, FARO-57, \nNERICA L-34, and NERICA L47. \n\n\n\nLin et al., 2016. \n \nBeckley et al., 2020. \n\n\n\n\n\n\n\nN-Methyl-N-Nitrosourea (MNU) \nAccording to Xuan et al. (2018), rice lines developed by \nMNU mutation exhibited high yield, good quality, and \nwere a potential source for breeding new rice cultivars. \nIn rice, MNU-activated mutant populations were \ndiscovered to have high-frequency mutations, which \nwere valuable for genetic approaches (Suzuki et al., \n2008). In other study conducted by Huong et al. (2020), \nthe rice seeds of origin cultivars that were soaked in \n150 mM MNU for 3 h before drying, showed that the \nmutant line SKLo/BC15TB and cultivar BC15TB were \nfound to be promising candidates for diversity analysis \nof salt-tolerant rice. In this study, the mutant lines \nwere classified into three groups of salinity tolerance, \nincluding tolerant, moderately tolerant, and \nsusceptible groups. While Xuan et al. (2019) \ndiscovered the M2 (self\u2010pollinated from M1) and M3 \n(self\u2010pollinated from M2) individuals obtain salinity \ntolerant levels as the recurrent TBR1 (Huong et al., \n2020). In this study, the F1 generations of the TBR1 \n(female cultivar, salinity tolerant) x KD18 (male \ncultivar, salinity susceptible) were preliminarily \ntreated with N\u2010methyl\u2010N\u2010nitrosourea (MNU) to induce \nthe mutants M1. The M1 generation was self\u2010\npollinated to obtain M2, and M3 was induced by the \nM2 self\u2010pollination.  \n \nEthyl methanesulfonate (EMS) \nSeveral reports have demonstrated that the \napplication of EMS improves agronomically important \ntraits including abiotic stress tolerance. It has become \na primary resource for development of improved \nvarieties. Among these, traits for drought tolerance \nsuch as root length, the volume of roots, and root \nweight were increased and a heat tolerant mutant \nwith higher photosystem II efficiency was identified \n(Mohapatra et al., 2014; Poli et al., 2013). In the \nsalinized hydroponic culture experiment, treatment \nfrom 0.6 to 1.0 % EMS was found to be effective at \n\n\n\nwhich 72-92% germination of EMS induced Nagina22 \nmutants was observed (Shankar et al., 2021). The N22-\nL-1013, N22-L-806 and N22-L-1010 276 were identified \nas typical Na excluders while rest of the tolerant \nmutants showed tissue tolerance mechanism. \n(Mohapatra et al., 2014). to screen salt tolerant \nmutants of aerobic rice cultivar Nagina 22 and to study \nthe nature of salt tolerance from a total of 432 EMS \ninduced M4 mutants. \n \nHowever, in several studies showed difficulty in \nobtaining the correct EMS dosage is a major obstacle \nin the production of high-salt-tolerance rice where the \ngradual increase in EMS resulted in large reductions in \nnumber of stems, growth and survival (Serrat et al., \n2014; Badawi et al., 2015). Study by Marcelina et al., \n(2017) on calli of petunia (Petunia \u00d7 atkinsiana D. Don \n\u2018Prism Red\u2019), found that the cells were damaged after \nimmersion in the 5.0 mM EMS solution which \nindicated by the changes in callus colour into brown. \nThe increase in concentration of applied EMS, also \ncaused decrease in germination, seedling height, root \nlength and emergence under field conditions in rice \nvariety MR219 treated with EMS Ali et al. (2012). \n \nSodium Azide (NaN3) \nThe mutagenic effect of sodium azide (NaN3) greatly \ndepends on the pH of the treatment solution and \nsimilarly to the MNU (N-methyl-N-nitrosourea), can be \nincreased further by pre-germination of seeds prior to \nNaN3 treatment (Damian et al., 2012). The mutagenic \neffects of sodium azide appear soon after sowing the \nseeds and can be observed by naked eyes (Dubey et \nal., 2017). It has been used to improve their yield, \nquality traits and create resistance against biotic and \nabiotic stresses in various crops (Weldemichael et al., \n2021). Observation on the effects of NaN3, as a \nchemical mutagen, on the growth, yield, genetic \nparameters, and RAPD profile of five rice varieties, \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, YYYY, e-ISSN: 2811-3594 \n \n\n\n\nPage 35 of 35 \n\n\n\n\n\n\n\n4 \n\n\n\nFARO-44, FARO-52, FARO-57, NERICA L-34, and \nNERICA L47, showed that the treatment significantly \nreversed the negative effects associated with plant \ndevelopment under saline conditions. In this study, the \nplanting materials were treated with NaN3 with the \nconcentration range of 0 to 0.032% NaN3 at pH 3 for 6 \nh (Beckley et al., 2020).  \n \nIn rice, sodium azide predominantly causes transitions \nfrom G/C to A/T and similar sequences at the mutation \nsite were identified as 5\u2019-GGR-3 \u2018(Tai et al., 2016). High \nheritability values were recorded for number of tillers \nper plant (78.06%), number of panicles per plant \n(78.74%), and 100-grain weight (98.15%) indicating the \npossibility of evolving higher yield variants through \nselection. Chlorophyll mutations observed were \nalbino, viridis, and striata. Increased iron and zinc \namounts in polished grains, starch and amylose \ncontents and production of new aromatic rice were \nalso observed (Lin et al., 2014). Lin et al., (2016) \ndeveloped a salt hypersensitive (shs1) mutant using \nNaN3 which plays avital role in Na+ homeostasis and \nantioxidant metanolism. \n \nPhysical mutagens  \nPhysical agents are the most used mutagens in rice \n(FAO/IAEA, 2019). The treatment of plant materials \nwith physical radiations to induce mutations is called \nirradiation. Electromagnetic waves travelling at a high \nspeed through a space are called radiations or rays. \nRadiation/rays is defined as energy travelling through \na distance in the form of waves or particles. These are \nrelatively high energy levels of electromagnetic (EM) \nspectrum that are capable of dislodging electrons from \nthe nuclear orbits of the atoms that they impact upon. \nThe radiation used in plant breeding is of two types: - \nionizing radiations and non- ionizing radiations. These \nionizing components of the electromagnetic include \ncosmic, gamma and X-rays. Reactive Oxygen Species \n(ROS) are produced by ionizing radiation which caused \noxidative damage when interact with DNA, changes \nthe nucleotide and breaks a single-strand or double \nstrand (Vivian et al., 2019). \n \nGamma Rays  \nPhysical mutagens include electromagnetic radiation, \nsuch as gamma rays, X rays, and UV light, and particle \nradiation, such as fast and thermal neutrons, beta and \nalpha particles (Kodym et al., 2021). Among the \nphysical mutagens, (gamma) rays are the most \ncommonly used mutagens in mutation breeding \n(Beyaz et al., 2017). Gamma-rays (\u03b3-rays) have been \nwidely used to generate mutants in rice, ca. 92% of the \nrice mutants obtained with physical agents, were \ngenerated with \u03b3-rays (FAO/IAEA, 2019). Superior \ntraits in local rice varieties are obtained through plant \nmutation techniques utilizing gamma-ray irradiation. \n\n\n\nThe mutation has the potential to produce a wide \nrange of traits depending on the technique and \nintensity of gamma-ray irradiation used (Hanifah et al., \n2020). \n\n\n\n \nReports have indicated that gamma irradiation at low \ndose induces growth and vigour, while salt stress on \nthe other hand causes a reduction in growth and \nvigour. The interaction between gamma radiations \ninduced salt tolerance response of crop plants may \noperate at various levels through the involvement of \nmultiple attributes (Kumar et al., 2017). As classical \nbreeding studies take too much time, it is obvious that, \nmutation practices should spread among field plants. \nAs an addition, as gamma rays do not pose a threat for \nhumankind and environment and they are easily \nresulted, thus there has been a strong consideration \nthat this application should be preferred (Kamile et al., \n2015). \n\n\n\n \nGamma-rays were able to create genetic variability for \nabiotic stress tolerance, such as salinity in ST-87 and \nST-301 lines (Song et al., 2012). Two salt-tolerant rice \nmutants induced by gamma-irradiation were selected \nfor in vivo and vitro screening techniques, and their \nphysiological characteristics were evaluated. Using a \nsalt stress screening, 2 candidate lines for salt \ntolerance (ST-87 and ST-301) were selected out of \n1,500 M6 mutant lines. To estimate whether a \ntolerance to salinity was improved in the ST-lines \nduring the differential stage, Song et al. planted WT \nand ST-lines in soil trays without salt stress for 3 weeks, \nand then irrigated them with 171 mM NaCl salt \nsolutions. Demonstrated that salt stress significantly \naffected the growth of both the ST-lines and WT \nplants. After a salt level treatment in soil, the WT plant \ngradually wilted and did not show shoot elongation for \n3 days. In contrast, ST-87 and ST-301 continued to \ngrow for 7 days. The symptoms of major damage \ncaused by salt stress, such as the wilting and yellowing \nof old leaves, and the death of older leaves or whole \nplants, were more moderate and delayed in the 2 ST-\nlines as compared with the WT symptoms. \n \nImportant findings were obtained through Gamma \nrays treatment toward rice improvement. Two mutant \nlines, Shua-92 and IR-8, were developed using gamma \nrays for salinity tolerance in rice. Seeds of 3 rice \nvarieties viz., Shua-92, Sarshar and IR-8 were irradiated \nwith gamma rays (150, 200 and 250 Gy of Cobalt-60) \nfor determining the effectiveness of different doses of \nirradiation on growth behaviour. The radiation dose of \n150 Gy was found effective at which mutants of Shua-\n92 and IR-8 were not only alive at the higher level of \nsalinity (75 mM) but also attained comparable height \nat this treatment, where the plants of parent varieties \ncould not establish (Shereen et al., 2009). \n\n\n\nEmbryogenic callus of indica rice (Oryza sativa L.) cv. \nBasmati 370 induced on MS medium containing 9.05 \n\n\n\n\u00b5M2, 4-D was irradiated at 50 Gy of gamma rays of \n60Co for creating genetic variability against salinity \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, YYYY, e-ISSN: 2811-3594 \n \n\n\n\nPage 35 of 35 \n\n\n\n\n\n\n\n4 \n\n\n\n(Saleem et al., 2005). Salinity tolerant lines were also \nobtained in mutant lines, Inpari 34 and Inpari 35. Inpari \n34 and Inpari 35 varieties tolerant to salinity at \nseedling phase and cannot perform well when planted \nin salinity prone area. To increase the resistance of \nInpari 34 and Inpari 35 to salinity in the next phase of \ngrowth can be done with genetic mutations by using \ngamma-ray radiation combined with in vitro selection. \nThe gamma-ray irradiation dose given is 20-30 Gy. The \nmutant callus selected on NaCl media produced a \nsalinity tolerant mutant plantlet. The same method \nhas also been applied to callus varieties inpari 13 and \nCiherang which produce salinity tolerant lines (Yunita \net al., 2020). Previous studies have shown.  \n \nAccording to FAO/IAEA (2020), a new rice variety of a \ngood productive potential and salinity tolerance was \nobtained at the National Institute of Agricultural \nSciences (INCA), starting from in vitro culture of \nJucarito-104 (J-104) rice seeds irradiated with protons. \nSeeds from J-104 rice variety were irradiated with \ndifferent doses of protons (10, 20, 30, 40, 60, 90, 110 \nand 210 Gy) at the Phasotron of DUVNA. The irradiated \nseeds were cultured in vitro for callus induction and \nplant regeneration. It was possible to release the \nmutant GINES that showing difference with the donor \nJ-104 in cycle, yielding, grain quality, salinity tolerance \nas well as disease tolerance. The AFLP analysis showed \ndifferences between the mutant and the donor J-104. \nThe rice variety GINES is the first mutant release from \nin vitro mutagenesis using protons (Gonzalez et al., \n2008). \n\n\n\n \nMutation techniques in combination with anther \nculture were also reported. In order to produce new \nrice genotypes with better adaptation to salinity of the \nCosta Rican commercial rice cultivars, seeds of the \nseven commercial varieties of Costa Rica ('CR 1821', \n'CR 1113', 'CR 5272', 'SETESA 9, 'CR 750', 'WS', 'CR \n9027' and 'CAMAGO 8') were irradiated with gamma \nrays from a Cobalt-60 source, using a dose of 250 Gy. \nSixty four mutants from treated populations were \nselected as resistant to salinity (Maluszynski et al., \n2011). Studies of gamma radiation to induce mutation \nin indica rice \u2018CR-5272\u2019 are well documented, it is also \nwell acknowledged that six promising salt-tolerant \nlines and four drought-tolerant lines were selected \nfrom plants grown from irradiated seeds (M2). A \nhormetic response to irradiation was observed in \nseeds which irradiated at 50 Gy showed increased \ncallus induction and callus weight (Abdelnour et al., \n2020). \n\n\n\n \nFinding by In-Sok et al., (2003), salt tolerant mutants \nwere obtained in rice variety, \u2018Hawsungbayeo\u2019, \nthrough in vitro mutagenesis of in vitro cultured \nanther-derived calli. Various doses of gamma ray were \napplied to investigate the effect of radiation on callus \nformation on medium containing 1% NaCl, green plant \n\n\n\nregeneration, frequency of selected doubled haploid \nmutants and of the salt tolerant screen. It was \ndemonstrated that the dose of 30 and 50 Gy gamma \nrays had significant effects on callus formation, \nregulation and selection of salt tolerance. The \nfrequency of salt tolerant mutants indicates that \nanther culture applied in connection with gamma rays \nis an effective way to improve salt tolerance. \n\n\n\n \nThe use of gamma irradiation to induce mutation helps \nfarmers and seed manufacturing companies in \naccessing and monitoring characteristics of crops that \nare targeted for improvement (Jankowicz et al., 2017). \nThis technique creates variation within the crop \nvariety, plus offers the possibility of inducing desired \nattribute to select improved cultivars and also for \ngenerating novel mutant traits. \n\n\n\n \nIon Beam  \nAccording to Satoh et al., (2019), ion beams were \nalready explored as novel mutagens by researchers in \nTakasaki Ion Accelerators for Advanced Radiation \nApplication (TIARA), National Institutes for Quantum \nand Radiological Science and Technology, Japan. It is \ndiffers from \u03b3-rays concerning the linear energy \ntransfer, and produces important deletions, greater \nthan 1Kbp (Zarqa et al., 2014). Ion beam radiation \ninduces mutations with high frequency at a relatively \nlow dose and also induces a broad spectrum of \nphenotypes without affecting other plant traits being \nthese an advantage in applying ion beam for rice \nmutation (Ishikawa et al., 2012). Recently, the \nmutations induced by ion beams have also been \ninvestigated in rice by comparing the efficiency, \nspectrum, mutation rate and optimum dose to that of \ngamma rays. Based on the analysis by Yamaguchi et al. \n(2009), the mutation rate of ion beams was higher \nthan that of gamma rays and appeared to efficiently \ninduce mutants with little radiation damage.  \n \nRecent years, several plant species has been induced \nwith heavy ion irradiation which is carbon ion.  Mega-\nelectronvolts (MeV) usually used to measure the total \nparticle energy and the linear energy transfer (LET) in \nkeV/\u03bcm, are used to describe the amount of energy \nthat the ions ultimately deposits in the plant tissues \n(Melsen et al., 2021). Ichida et al. (2019) used an \nexome-sequencing procedure to examine the \ncharacteristics and distribution of mutations caused by \nC ion beams in the absence of bias introduced by visual \nmutant selections. The ion beam irradiation \n \nsuch as carbon and neon ions are used to allow the \nselection of mutant rice in plant development and \nmetabolism, in industrial and nutritional quality, the \nbiotic and abiotic stress tolerance, and in herbicide \ntolerance with a low dose at range 20-50Gy, and fast \nneutron bombardment at 20Gy as compared to \ngamma rays at range 50-350Gy (Viana et al., 2019). \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, YYYY, e-ISSN: 2811-3594 \n \n\n\n\nPage 35 of 35 \n\n\n\n\n\n\n\n4 \n\n\n\n \nThe morphological mutants among ion-beam \nirradiated seeds of Oryza sativa cv. MR219 under salt \nstress was identified (Hasan et al., 2021). 14 distinct \nmutations were involved in a significant number of \nmutants\u2019 tolerance to drought and salinity. Under \nambient pressure, carbon-ion irradiation at doses of \n70 Gy was achieved in 3 minutes. In the M2 generation, \na total of 22 salt-tolerant plants were found.  \n\n\n\n \nUsing heavy ion beam irradiation, Hayashi et al., (2007) \nirradiated rice seed by C or Ne ions accelerated to \n135MeV/u within a dose range of 10 to 400 Gy. Among \nall mutant lines, line 6-99L was taller than wild type in \nnormal paddy field and showed salt-tolerance in a \nsaline paddy field was observed in 40 Gy at C or Ne ion \nirradiation with 22.6 keV/\u03bcm.  \n\n\n\n \nIn other study, M0 seeds of local aromatic rice varieties \n(Oryza sativa L. var \u2018Pare Bau\u2019) from Sulawesi, \nIndonesia were irradiated with Argon-ion beam at \ndose 10Gy and Carbon-ion beam at dose 150Gy (Okasa \net al., 2021), and grown in paddy field. The average LET \nof Argon-ion beam and Carbon-ion beam were \naccelerated at 300keV/\u03bcm and 30keV/\u03bcm \nrespectively. 19 M3 mutant lines (18 PB-A and 1PB-C) \nwere selected due to early heading and high yield \nperformance as compared to control rice lines. \n\n\n\n \nsdbc1 mutant lines was obtained from japonica \ncultivar Wuyungjing7 that treated with carbon-ion \nbeam at 80MeV/nucleon of energy and 120Gy dose \n(Ye et al., 2021).  As the results, the semi-dominant \nbrittle culm (sdbc) mutant Sdbc1 rice has produced low \ncellulose content and secondary wall thickness, as well \nas enhanced the biomass enzymatic saccharification as \ncompared to wild type (WT). \n\n\n\n \nRecently, low-energy ion beam was targeted to Thai \njasmine rice variety, KDML 105 (Oryza sativa L. cv. \nKDML 105) to improve the yield and seed quality. This \nrice variety were irradiated by N-ion beam that \naccelerated at high energy (60keV) to fluences of 1-2 \u00d7 \n1016ions/cm2 and were grown at the controlled field. \nResulting, the HyKOS21 mutant rices were produced \ncharacteristics such as semi-dwarfness, high yield \npotential and photoperiod insensitivity (Semsang et \nal., 2018). \n\n\n\n \nThis shows that ion beam was able to induce potential \nmutant lines suitable for high salinity with improved \nyield. In terms of improvement of quality of rice with \nrespect to amylose, ion beam is more effective than \ngamma rays in producing lower amylose content \n(Ibrahim et al., 2014). However, the dose and the \nfrequency of the ion beam type play an important role. \nThe study by Pick et al. (2013), demonstrated that low \ndoses (10 Gy) of ion beam have a stimulating effect on \nthe height, root length, and fresh weight of the \nplantlets but not on the number of leaves. Meanwhile, \ndoses higher than 10 Gy caused reductions in all the \nmorphological parameters (Pick et al., 2013). The \ntarget area of the bombardment by ion beam is too \nsmall and the deposition rate is generally low. Study by \nPhanchaisri et al. (2007), nitrogen bombardment \ncauses variations in some important traits, such as \nplant height, leaf, tegument and pericarp colour. Plus, \nPKOS1, HyKOS1 (dwarf) and TKOS4 (tall) mutants were \nobtained through bombardment with the low energy \nNitrogen ion. Zheng et al. (2020) reported that, all \nthree ion beam (Ar, C and Ne) have found effective for \nmutation induction when suitable dose were applied \nto 2 indica (LH15 and T23) and 2 japonica (DS551 and \nGS48) rices. These study has found out that 50% of \nrelative seedling survival rate and seed set were \nachieved for most rice genotypes when using this \nrecommendation dose for Ar (100Gy), C (200Gy) and \nNe (200Gy) radiation. \n \nConclusion  \nThe growing population needs greater research and \ntechnical progress in order to boost rice production for \ndomestic consumption. Malaysia needs to develop and \nexpand its rice acreage to meet present and future \ndomestic demand. Modern biotechnology techniques \nwill make a substantial contribution to the \ndevelopment of high-yielding salinity tolerance rice. \nThere is a requirement for field-testing of laboratory-\ndevelopment varieties, particularly in varied sodium \nchloride concentrations because varieties function \ndifferently under controlled setting than in fields. The \nexperimental findings by several author of this review \nconfirmed that mutant rice may assist in more \neffective development in various traits. 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"\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2021, e-ISSN: 2811-3594 Page 1 of 6 \n\n\n\n\n\n\n\n\n\n\n\nOFFICIAL JOURNAL \n\n\n\nREVIEW ARTICLE \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nMesenchymal Stem Cells (MSCs) Acellular Therapy as A Prospective \nTreatment for Covid-19: A Brief Review \n\n\n\n \nNorshariza Nordin1,2, Khadijat Abubakar Bobbo3,4 and Khairul Akmal Abdul Rahman1,2 \n\n\n\n\n\n\n\n1Genetics & Regenerative Medicine Research Group, Faculty of Medicine and Health Sciences, \nUniversiti Putra Malaysia, Serdang, Selangor, Malaysia \n\n\n\n2Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, \nUniversiti Putra Malaysia, Serdang, Selangor, Malaysia \n\n\n\n3UPM-MAKNA Cancer Research Laboratory, Institute of Bioscience, \n\n\n\nUniversiti Putra Malaysia, 43400 UPM, Selangor \n4Department of Human Anatomy College of Medical Sciences, Faculty of Medicine, \n\n\n\nGombe State University, Gombe State-Nigeria \n \n\n\n\n*Correspondence: shariza@upm.edu.my \n\n\n\n\n\n\n\n\n\n\n\nIntroduction \nCovid-19 has become one of the major health \nconcerns globally since December 2019.  The \ndisease is caused by a novel respiratory-related \nvirus \u201ccoronavirus\u201d, a member of the class of severe \nacute respiratory syndrome (SARS)-like \ncoronavirus-2, Sars-CoV-2, (Atluri et al., 2020; \nHoffmann et al., 2020; Rajarshi et al., 2020). \nCoronavirus in a very short time became the most \nstudied virus and researchers are developing drugs  \n\n\n\n\n\n\n\nbased on COVID-19 symptoms and the virus behaviour \n(Chrzanowski et al., 2020). The SARS-CoV-2 infection \nhas already resulted in over 2 million deaths and more \nthan 200 million confirmed cases globally \n(https://www.worldometers.info/coronavirus/), thus \nthe urgent need for treatment. \n \nThe virus has infected majority of people in the global \ncommunity and the symptom varies depending on the \nage group and individual health condition. The majority \nof the population that have contacted the virus are said \nto be asymptomatic while a percentage of the infected \npopulation are presented with a spectrum of \nsymptoms, from mild-to-severe conditions to more \n\n\n\n \nAbstract \n\n\n\nThe global pandemic due to COVID-19 has reached a very alarming phase.  There is an urgent need of \n\n\n\nfinding treatment for this disease, particularly for the severe condition. The severity of the disease \n\n\n\ncondition is complicated as it involves an individual\u2019s immune system status.  Fortunately, this \n\n\n\ncondition provides a promising avenue for stem cells, specifically mesenchymal stem cells (MSCs), to \n\n\n\nplay a role as the prospective treatment modalities for this disease for its immunomodulatory and \n\n\n\nregenerative properties. MSCs could be used to treat patients suffering from COVID-19 as it is able to \n\n\n\nself-renew and differentiate into specialized cells. Apart from that, it also can modulate immune \n\n\n\nresponse via the paracrine effect of cytokine and cell-to-cell contact with the immune cells.  Up until \n\n\n\nnow, multiple research and clinical trials involving stem cells as a treatment for Covid-19 patients have \n\n\n\nbeen registered globally to unravel the prospect of MSCs for cellular as well as acellular therapy for \n\n\n\nCOVID-19.  Here we aim to briefly review the possibility of utilising MSC for these therapeutic \n\n\n\napproaches and weigh if acellular (cell-free) therapy could be a better alternative treatment for this \n\n\n\ndisease compared to the cellular approach.  We found MSC acellular therapy (MSC-exosome) may \n\n\n\nprovide more advantages and could overcome limitations posed by cellular-based MSC therapy.  \n\n\n\nHowever, the safety and efficacy of MSC-exosomes require further investigation before serving as a \n\n\n\npotential alternative for COVID-19 treatment. \n\n\n\nKeywords: Stem Cell; Acellular Therapy; Cellular Therapy; Mesenchymal Stem Cell; Exosome; Secretome \n\n\n\n\n\n\n\n*Corresponding author: Dr Norshariza Nordin, Faculty of \nMedicine and Health Sciences, Universiti Putra Malaysia, \nSerdang, Selangor, Malaysia \n\n\n\nEmail: shariza@upm.edu.my \n\n\n\n\nhttps://www.worldometers.info/coronavirus/\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2021, e-ISSN: 2811-3594 Page 2 of 17 \n\n\n\n\n\n\n\n\n\n\n\nPage 2 of 6 \n\n\n\nserious or critical conditions, with about 2% of \nreported cases being fatal (Atluri et al., 2020; Wang et \nal., 2020; Rajarshi et al., 2020). Serious conditions are \nconfirmed to sudden progression deterioration with \nrespiratory difficulty (Rajarshi et al., 2020) requiring \nmechanical ventilators and intensive care unit (ICU) \nsupport due to lung and multiple organ failure (Atluri \net al., 2020; Golchin et al., 2020; Moll et al., 2020).   \n \nUp until now, the therapeutic strategy was only to \nalleviate the symptoms. Clinicians and researchers \nhave come up with various treatment strategies and \ntreatments using stem cells are one of them. \nMesenchymal stem cell (MSC) is one of the \nprospective stem cell types that can be used for the \ntreatment of COVID-19 critical patients, these critical \npatients are ventilator bound due to difficulties in \nbreathing which is a result of damage/injuries at their \nalveolar-capillaries barrier/epithelial cells. This \ndamage is reported to be as a result of hyperimmune \ncytokine response to the virus causing \ninjuries/damages to the cells in the process of \nprotecting the body from the infected cells leading to \ninjured site inflammatory response and more \ncytokine production (Wang et al., 2020). This \ngradually over warms the residual stem cells from \nrecruiting and repairing the injured alveolar cells \n(Rajarshi et al., 2020), gradually forming pneumonia \nfibrosis which later becomes fibrous stripes in the \nlungs (Ulrich and Pillat, 2020), which then ultimately \nresulting in dysfunction in the body blood \noxygenation (Chrzanowski et al., 2020).  \n \nStem cell therapy has promised experimental and \nclinical results for a long time. Most of the researchers \nhave conducted many research on various disease \nmodels whether it is in vitro, in vivo or clinical studies \n(Lee et al., 2020). As stem cell therapy involves a non-\nsurgical procedure, it helps patients to avoid high risk, \ncomplex surgery, therefore, reducing the risks of \ncomplications. However, it also comes with a \ndrawback such as tumour formation upon \ntransplantation. Apart from that, there are also the \nrisks of graft failure as host\u2019s immune system may \nnegatively respond toward the transplanted stem \ncell. The activity of transplanted stem cells such as \ntheir endurance, and inappropriate integration and \ndifferentiation could be a problem. In such, it is hard \nto determine whether the stem cell could be \ndifferentiated into the desired cells (Raik et al., 2018).  \n \nDue to the limitation of stem cell cellular therapy, \nresearchers have come up with the idea of stem cell \nfree therapy or acellular therapy, in which, treatment \nis done without using the cells, instead, it utilizes the \nvaluable secreted molecules, such as nucleic acids, \nmicroRNA, lipids, protein, growth factors and many \nmore (Rezakhani et al., 2021), released by the stem \ncells into the cultured medium known as secretome.  \n\n\n\nThe questions remain whether treatment utilising MSC \nacellular therapy would provide a better approach for \nCOVID-19 compared to MSC cellular therapy. In this \nshort review, a brief overview on both approaches is \ndiscussed in addition to short introduction to COVID-19 \npathogenesis in the lung and SARS-CoV-2 entry gain.  \n \n \nThe Virus and Its Pathogenesis in the Lung \nCovid-19 viruses or SARS-CoV-2 could be transmitted \nvia respiratory droplet or contact with contaminated \nsurfaces (Rezakhani et al., 2021). The viruses will reside \nand proliferate in the alveolar type-II cells of the \nrespiratory system. Upon releasing the viral particle, it \nwill cause the cells to undergo apoptosis and eventually \ndie. Then, the released viral particle will infect the \nadjacent cells resulting in propagation of more virus. \nSubsequently, the function of the alveolar as gaseous \nexchange area is disrupted and causing pneumonia in \nthe patient. Apart from that SARS-CoV-2 could also \ninduce cytokine storm, an excessive activation of \nimmune cells (CD8+ T cells & T helper 17 cells) and \nactivation cascade of auto-amplifying cytokine \nproduction (IL-6, IL-1\u03b2, IFN, and CXCL10). This \nphenomenon could be grave to the patients as it may \ncause multiorgan failure such as lung, kidney and heart \n(Jayaramayya et al., 2020). \n \nThe virus entry is by binding to angiotensin-converting \nenzyme 2 (ACE2) and CD147 (Basigin or EMMPRIN) \nreceptors (Hoffmann et al., 2020; Rajarshi et al., 2020; \nRoger et al., 2020; Ulrich and Pillat, 2020).  These \nreceptors are, unfortunately, widely distributed in the \nlungs and other organs of the body including the heart, \nliver, digestive organs as well as the kidneys (Atluri et \nal., 2020; Golchin et al., 2020; Roger et al., 2020).  These \ncells are invaded by the viral RNA resulting in not only \nlosing the airway epithelial cells but also a potential \nloses of the cellular regeneration across the body (Atluri \net al., 2020; Ulrich and Pillat, 2020). The body \nautomatically launches into a concurrent release and \naccumulation of cytokine and inflammatory responses \nagainst the virus and that of tissue/organ restoration \nresulting to a cloud of cytokines around host tissues \nknown as cytokine release syndrome or cytokine storm \n(Wang et al., 2020). This gradually forms pneumonia \nfibrosis and later becoming fibrous stripes in the lungs \nin response to early-phase and later-phase of COVID-19 \nrespectively (Ulrich and Pillat, 2020), and ultimately \nresulting in dysfunction in the body blood oxygenation \n(Chrzanowski et al., 2020).  \n \n \nPotential Treatment  \nAs the global races towards finding a cure for the \nCOVID-19, patients have been treated or experimented \nwith some known agent to target the entry of the virus, \nmultiplication of the viral genetic materials and the \nimmune response using established anti-viral, anti-\n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2021, e-ISSN: 2811-3594 Page 3 of 17 \n\n\n\n\n\n\n\n\n\n\n\nPage 3 of 6 \n\n\n\nmalarial and anti-inflammatory drugs alongside with \nmany more new drugs (Chrzanowski et al., 2020). \nAlthough vaccines have been developed and being \nadministered worldwide, finding for effective \ntreatment for COVID-19 is still critically needed. An \nincreasing number of researchers are reportingly \nfocused on the potentials of the robust Mesenchymal \nstem cells (MSCs) therapies in treatment of lung \ndamaged in COVID-19 patients due to its \nimmunomodulatory and regenerative properties \n(Chrzanowski et al., 2020; Ferreira et al., 2018; \nForsberg et al., 2020). MSCs have been reported to \nnot only completely block and suppress the cytokines \nstorm, but also most importantly, regenerate alveolar \ncells, restoring the damaged lungs thus improving the \nfunction of the alveolar-capillary barrier (Chrzanowski \net al., 2020).  \n \n \nMesenchymal Stem Cells (MSCs) Therapy  \nBased on the well-established knowledge of MSCs \nwhich have been used to treat many human diseases \n(Forsberg et al., 2020), it have been shown to have a \nset of unique characteristic of clinical context ranging \nfrom its homing ability, cell-to cell and paracrine \nimmunosuppressive and immune-stimulating as well \nas regenerative properties which could provide key \nroles in the treatment of COVID-19 patients \n(Chrzanowski et al., 2020; Ferreira et al., 2018; \nForsberg et al., 2020). Mesenchymal stem cells have \nmany established sources in the body, such as bone \nmarrow, dental pulp, umbilical cord blood etc, and \ncan lineage differentiate into a wide range of cell \ntypes giving them the ability to differentiate at injured \nsites to repair and regenerate (Forsberg et al., 2020). \nThe remarkable recovery of critical ill aged COVID-19 \npatients after receiving an intravenous (IV) \nadministration of MSCs treatment in a novel clinical \nstudy in China, paved the way for exploring MSCs as \nthe potential treatment for this disease (Rajarshi et \nal., 2020). \n \n \nLimitations of Mesenchymal Stem Cell (MSCs) \nCellular Therapy  \nAlthough many studies have reported the novel \npotentiality of using MSCs in the treatment of critical \nCOVID-19 patients, there are reservations towards \nthe use of MSCs as a cellular therapy. These include \ncompliance with good MSCs manufacturing practice \n(GMP) for stem cell viability and upscaling; the quality \nof the cells based on the source and preparation \n(Chrzanowski et al., 2020); and the identification of \nthe most effective MSC type suited for the treatment \n(Chrzanowski et al., 2020; Moll et al., 2020), which \ncompromising the cost-effectiveness of the therapy \n(Pinky et al., 2020). The route of administration which \naffects the homing and timing to site target (Pinky et \nal., 2020), and ultimately determination of the right \n\n\n\ndosage also provides another limitation of MSC cellular \ntherapy. In addition, there is a concern of disturbed \ndifferential capacities of MSCs or tumorgenicity \npotential as well as the storage difficulties as the cells \nneed to be kept in liquid nitrogen (Pinky et al., 2020; \nChrzanowski et al., 2020).  Some studies have reported \ninjected MSCs undergo autophagy and apoptosis \nreleasing more cytokines at the target injured site \n(Pinky et al., 2020).  \n \nTreatment with MSCs also should be done with caution \nas procoagulant tissue factor (TF/CD142) of MSCs could \ncompromise hemocompatibility which could aggravate \nthe pro-thrombotic state of the patient increasing the \nrisk of death due to thrombotic multi-organ failure \n(Moll et al., 2020).  Allergic reaction leading to multi-\norgan failure could also be presented in patients \ntreated with MSCs (Atluri et al., 2020; Moll et al., 2020). \nAn alternative administration route is intramuscular \n(IM) injection evading the hemocompatibility issues \nand has longer cell life due to the immediate highly \nvascularized environment promoting an immediate \nmediation of the MSCs beneficial paracrine properties \n(Moll et al., 2020). MSC has been known to mediate its \neffect through paracrine factors as part of its mode of \naction. \n \n \nMSCs-Driven Extracellular Vehicles (EVs) \nBased on the limitations posed by the MSC cellular \ntherapy, the MSCs-driven cell-free therapy or acellular \ntherapy have recently been explored as alternative \ntreatment for COVID-19 critical condition patients \n(Chrzanowski et al., 2020). It has been well established \nthat MSCs exert its actions through the means of \nparacrine action of its environment dependent \nsecreted bioactive molecules released into the cultured \nmedium known as the secretome (Ferreira et al., 2018).  \nStudies have shown that MSCs-derived cell-free \nsecretome have several free- and cell-secreted-vesicles \nencapsulated factors including cytokines, chemokines, \nimmunomodulatory molecules, and growth factors \n(Ferreira et al., 2018). The secretome contains largely \nthe extracellular vesicles (EVs). EVs are of different \nsizes, the largest of which are known as apoptotic \nbodies with a diameter of 500-4,000nm (Cheng et al., \n2017), microvesicles with size of 100-1,000nm in \ndiameter and the smallest, exosomes, of 30-120nm \ndiameter (Ferreira et al., 2018; Forsberg et al., 2020). \nThese EVs could be isolated based on their size \nseparated using ultracentrifugation (UC) technique \n(Allan et al., 2019).  \n \nThese MSCs-derived secretome especially the EVs have \nbeen investigated to mimic the cellular MSCs \ntherapeutic potentials such as immunomodulation, \nstimulating vascularization, inhibiting fibrosis and \nrecruiting other cells (Allan et al., 2019; Ferreira et al., \n2018). Mesenchymal stem cells-derived secretomes \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2021, e-ISSN: 2811-3594 Page 4 of 17 \n\n\n\n\n\n\n\n\n\n\n\nPage 4 of 6 \n\n\n\ncontains a large amount of exosomes, which \nencapsulate and imbed cytokines, with a similar \ntherapeutic efficacy as with MSCs (Forsberg et al., \n2020). They have been identified in their tissue repair \ncapacity, therapeutic potential in cardiovascular \ndisease, immune related diseases, tumour inhibition \nand neurological diseases (Cheng et al., 2017).  Bases \non this knowledge, MSCs-EVs have been recently \nexplored in the treatment of COVID-19 patients.  \nResults have shown it to also exhibit similar \ntherapeutic properties as the stem cells in \nattenuating the inflammatory response as well as \nrestoring the functions of the lungs by the means of \nregeneration (Chrzanowski et al., 2020).  \n \nThe use of EVs has some advantages over MSCs, one \nof these is its feasible administration route which \nexplores a respiratory disease tailored inhalation \nroute to critical patient, hence, EVs avoids \naggregating with host injured microenvironment \n(Chrzanowski et al., 2020; Pinky et al., 2020). \nExosomes have also been explored for the treatment \nof COVID-19 for their small size and high stability \n(Pinky et al., 2020) with the ability to deposit \ncytokines directly to target site and induce \nimmunomodulatory function, with no risk so far in \ndeveloping pulmonary embolisms (Forsberg et al., \n2020)  These have put MSC-exosomes as the \npromising acellular therapy for COVID-19.  \n \n \nMSCs -Exosome as Prospective Treatment for Covid-\n19 \nUp until September 2020, there are 7 clinical trials \ninvolving the use of exosome to treat Covid-19 \npatients. Two therapeutic strategies have been \napproached in utilising MSC-exosomes in this \ntherapy; 1) direct injection of the exosome for \ntreatment and 2) the use of the exosomes as drug \ncarrier (Rezakhani et al., 2021). Clinical study shown \nthat, exosomes from MSCs could protect and induce \nthe proliferation of lung epithelial cells as it expresses \nAlpha-1-antitrypsin (AAT), hence, protecting the cells \nfrom enzyme released by neutrophils. Moreover, it \nalso able to modulate immune response as it \nexpresses anti-inflammatory factors on it surfaces \n(Pinky et al., 2020). In a recent COVID-19 open-lab \ncohort studies, the use of allogenic bone marrow \n(BM)-derived MSCs-exosome was observed to \ndemonstrate a significant decrease in cytokines \nstorm, an enhanced immunity and oxygenation, and \nit was said to reverse lung fluid accumulation, with no \nadverse effect, demonstrating its multi-mechanism in \nrestoring damaged lungs in COVID-19 patients (Pinky \net al., 2020; Sengupta et al., 2020). \nIn addition, stem-cell free therapy also provides \ntherapy that is immune-compatibility and non-\ncytotoxic (Lee et al., 2020) as it does not involve cells. \nApart from that, it is relatively free against any ethical \n\n\n\nissues. The small size of exosomes allows it to pass \nmany barriers especially the blood-brain-barriers, thus, \nproviding easy access to reach any targeted sites. \nAcellular therapy also reduces the time and cost \nassociated with the expansion and maintenance of \nstem cell. Being non-living cells in nature, exosome is \nmore stable throughout prolonged freezing and \nthawing as compared to stem cells. Even with extensive \nand promising potential of stem cell free-therapy via \nexosomes, it comes with disadvantages as it lack of \nstandard manufacturing methods and recommended \nisolation protocol as each of researchers\u2019 team used \ndifferent isolation protocol (Pinky et al., 2020).  \n \n \nConcluding Remarks \nWith the wide application of MSCs in the treatment, \nMSCs could be injected intravenously or \nintramuscularly and will be homing to the site of the \ninjury in the lung and repair the damage tissue via \ndifferentiation into the alveolar type-II cells (Li et al., \n2020). Besides, it will also release factors that will \nactivate resident stem cells in the lungs to differentiate \ninto alveolar type-II cells and compensate the loss cells. \nOn the other hand, the MSCs secreted factors, such as \nepidermal growth factor, keratinocyte growth factor, \nhepatocyte growth factor and many more, have been \nable to promote repair of the epithelial and endothelial \ncells. Besides, it is also effective in reducing lung fibrosis \nand matrix metalloproteinases. Therefore, the alveolar \ntype-II cells will be able to regenerate and able to \nconduct its normal function. Therefore, stem cell-free \ntherapy via exosomes, could be a promising treatment \nfor Covid-19 patients as it provides more benefits as \ncompared to direct stem cell therapy. This include \nhaving a lower risk of tumour formation, no effect on \nresidence stem cells stability, lower tendency of it been \nblocked by the hostile microenvironment and has a \nlonger shelf life allowing for cheap global accessibility. \nHowever, there is a need for further studies to establish \nits efficacy and safety in more patients. Extensive study \nat clinical trial level should be done to further explore \nthe capabilities of exosomes in treating Covid-19 \npatients. Based on the outcomes of the study, \nexosomes could be mass produced in the industry and \nbe formulated for the patient to consume it. The \ntreatment responses of COVID-19 patients with MSCs \nare definitely positive, however the results from the use \nof MSC-exosomes is gradually showing it could be \nbetter than cellular MSCs as it has properties that could \novercome limitations of MSC cellular therapy.  \n \n \nReference: \nAllan, D., Tieu, A., Lalu, M., & Burger, D. (2019). \nMesenchymal stromal cell\u2010derived extracellular vesicles \nfor regenerative therapy and immune modulation: \nProgress and challenges toward clinical application. \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2021, e-ISSN: 2811-3594 Page 5 of 17 \n\n\n\n\n\n\n\n\n\n\n\nPage 5 of 6 \n\n\n\nSTEM CELLS Translational Medicine, 9(1), 39\u201346. \nhttps://doi.org/10.1002/sctm.19-0114 \n \nCheng, L., Zhang, K., Wu, S., Cui, M., & Xu, T. (2017). \nFocus on Mesenchymal Stem Cell-Derived Exosomes: \nOpportunities and Challenges in Cell-Free Therapy. \nStem Cells International, 2017, 1\u201310. \nhttps://doi.org/10.1155/2017/6305295 \n \nChrzanowski, W., Kim, S. Y., & McClements, L. (2020). \nCan Stem Cells Beat COVID-19: Advancing Stem Cells \nand Extracellular Vesicles Toward Mainstream \nMedicine for Lung Injuries Associated With SARS-CoV-\n2 Infections. Frontiers in Bioengineering and \nBiotechnology, 8. \nhttps://doi.org/10.3389/fbioe.2020.00554 \n \nFerreira, J. R., Teixeira, G. Q., Santos, S. G., Barbosa, \nM. A., Almeida-Porada, G., & Gon\u00e7alves, R. M. (2018). \nMesenchymal Stromal Cell Secretome: Influencing \nTherapeutic Potential by Cellular Pre-conditioning. \nFrontiers in Immunology, 9. \nhttps://doi.org/10.3389/fimmu.2018.02837 \n \nForsberg, M. H., Kink, J. A., Hematti, P., & Capitini, C. \nM. (2020). Mesenchymal Stromal Cells and Exosomes: \nProgress and Challenges. Frontiers in Cell and \nDevelopmental Biology, 8. \nhttps://doi.org/10.3389/fcell.2020.00665 \n \nGolchin, A. (2020). Cell-Based Therapy for Severe \nCOVID-19 Patients: Clinical Trials and Cost-Utility. \nStem Cell Reviews and Reports, 17(1), 56\u201362. \nhttps://doi.org/10.1007/s12015-020-10046-1 \n \nGolchin, A., Seyedjafari, E., & Ardeshirylajimi, A. \n(2020). Mesenchymal Stem Cell Therapy for COVID-\n19: Present or Future. Stem Cell Reviews and Reports, \n16(3), 427\u2013433. https://doi.org/10.1007/s12015-\n020-09973-w \n \nHoffmann, M., Kleine-Weber, H., Schroeder, S., \nKr\u00fcger, N., Herrler, T., Erichsen, S., Schiergens, T. S., \nHerrler, G., Wu, N. H., Nitsche, A., M\u00fcller, M. A., \nDrosten, C., & P\u00f6hlmann, S. (2020). SARS-CoV-2 Cell \nEntry Depends on ACE2 and TMPRSS2 and Is Blocked \nby a Clinically Proven Protease Inhibitor. Cell, 181(2), \n271\u2013280.e8. \nhttps://doi.org/10.1016/j.cell.2020.02.052 \n \nIrmak, D. K., Dar\u0131c\u0131, H., & Kara\u00f6z, E. (2020). Stem Cell \nBased Therapy Option in COVID-19: Is It Really \nPromising? Aging and Disease, 11(5), 1174. \nhttps://doi.org/10.14336/ad.2020.0608  \n \nJayaramayya, K., Mahalaxmi, I., Subramaniam, M. D., \nRaj, N., Dayem, A. A., Lim, K. M., Kim, S. J., An, J. Y., \nLee, Y., Choi, Y., Kirubhakaran, A., Cho, S. G., & \nVellingiri, B. (2020). Immunomodulatory effect of \n\n\n\nmesenchymal stem cells and mesenchymal stem-cell-\nderived exosomes for COVID-19 treatment. BMB \nReports, 53(8), 400\u2013412. \nhttps://doi.org/10.5483/bmbrep.2020.53.8.121  \n \nLee, Y. H., Park, H. K., Auh, Q. S., Nah, H., Lee, J. S., \nMoon, H. J., Heo, D. N., Kim, I. S., & Kwon, I. K. (2020). \nEmerging Potential of Exosomes in Regenerative \nMedicine for Temporomandibular Joint Osteoarthritis. \nInternational Journal of Molecular Sciences, 21(4), \n1541. https://doi.org/10.3390/ijms21041541  \n \nLi, Z., Niu, S., Guo, B., Gao, T., Wang, L., Wang, Y., Wang, \nL., Tan, Y., Wu, J., & Hao, J. (2020). Stem cell therapy for \nCOVID\u201019, ARDS and pulmonary fibrosis. Cell \nProliferation, 53(12). \nhttps://doi.org/10.1111/cpr.12939  \n \nManchikanti, L. (2020). Expanded Umbilical Cord \nMesenchymal StemCells (UC-MSCs) as a Therapeutic \nStrategy InManaging Critically Ill COVID-19 Patients: \nTheCase for Compassionate Use. Pain Physician, \n2;23(4;2), E71\u2013E83. \nhttps://doi.org/10.36076/ppj.2020/23/e71 \n \nMoll, G., Drzeniek, N., Kamhieh-Milz, J., Geissler, S., \nVolk, H. D., & Reinke, P. (2020). MSC Therapies for \nCOVID-19: Importance of Patient Coagulopathy, \nThromboprophylaxis, Cell Product Quality and Mode of \nDelivery for Treatment Safety and Efficacy. Frontiers in \nImmunology, 11. \nhttps://doi.org/10.3389/fimmu.2020.01091 \n \nPinky, Gupta, S., Krishnakumar, V., Sharma, Y., Dinda, A. \nK., & Mohanty, S. (2020). Mesenchymal Stem Cell \nDerived Exosomes: a Nano Platform for Therapeutics \nand Drug Delivery in Combating COVID-19. Stem Cell \nReviews and Reports, 17(1), 33\u201343. \nhttps://doi.org/10.1007/s12015-020-10002-z \n \nRaik, S., Kumar, A., & Bhattacharyya, S. (2017). Insights \ninto cell-free therapeutic approach: Role of stem cell \n\u201csoup-ernatant.\u201d Biotechnology and Applied \nBiochemistry, 65(2), 104\u2013118. \nhttps://doi.org/10.1002/bab.1561  \n \nRajarshi, K., Chatterjee, A., & Ray, S. (2020). Combating \nCOVID-19 with mesenchymal stem cell therapy. \nBiotechnology Reports, 26, e00467. \nhttps://doi.org/10.1016/j.btre.2020.e00467 \n \nRezakhani, L., Kelishadrokhi, A. F., Soleimanizadeh, A., \n& Rahmati, S. (2021). Mesenchymal stem cell (MSC)-\nderived exosomes as a cell-free therapy for patients \nInfected with COVID-19: Real opportunities and range \nof promises. Chemistry and Physics of Lipids, 234, \n105009.  \nhttps://doi.org/10.1016/j.chemphyslip.2020.105009  \n \n\n\n\n\nhttps://doi.org/10.1002/sctm.19-0114\n\n\nhttps://doi.org/10.1155/2017/6305295\n\n\nhttps://doi.org/10.3389/fbioe.2020.00554\n\n\nhttps://doi.org/10.3389/fimmu.2018.02837\n\n\nhttps://doi.org/10.3389/fcell.2020.00665\n\n\nhttps://doi.org/10.1007/s12015-020-09973-w\n\n\nhttps://doi.org/10.1007/s12015-020-09973-w\n\n\nhttps://doi.org/10.1016/j.cell.2020.02.052\n\n\nhttps://doi.org/10.14336/ad.2020.0608\n\n\nhttps://doi.org/10.5483/bmbrep.2020.53.8.121\n\n\nhttps://doi.org/10.3390/ijms21041541\n\n\nhttps://doi.org/10.1111/cpr.12939\n\n\nhttps://doi.org/10.36076/ppj.2020/23/e71\n\n\nhttps://doi.org/10.3389/fimmu.2020.01091\n\n\nhttps://doi.org/10.1007/s12015-020-10002-z\n\n\nhttps://doi.org/10.1002/bab.1561\n\n\nhttps://doi.org/10.1016/j.btre.2020.e00467\n\n\nhttps://doi.org/10.1016/j.chemphyslip.2020.105009\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2021, e-ISSN: 2811-3594 Page 6 of 17 \n\n\n\n\n\n\n\n\n\n\n\nPage 9 of 9 Page 6 of 6 \n\n\n\nRogers, C. J., Harman, R. J., Bunnell, B. A., Schreiber, \nM. A., Xiang, C., Wang, F. S., Santidrian, A. F., & Minev, \nB. R. (2020). Rationale for the clinical use of adipose-\nderived mesenchymal stem cells for COVID-19 \npatients. Journal of Translational Medicine, 18(1). \nhttps://doi.org/10.1186/s12967-020-02380-2 \n \nSengupta, V., Sengupta, S., Lazo, A., Woods, P., Nolan, \nA., & Bremer, N. (2020). Exosomes Derived from Bone \nMarrow Mesenchymal Stem Cells as Treatment for \nSevere COVID-19. Stem Cells and Development, \n29(12), 747\u2013754. \nhttps://doi.org/10.1089/scd.2020.0080 \n \nUlrich, H., & Pillat, M. M. (2020). CD147 as a Target \nfor COVID-19 Treatment: Suggested Effects of \nAzithromycin and Stem Cell Engagement. Stem Cell \nReviews and Reports, 16(3), 434\u2013440. \nhttps://doi.org/10.1007/s12015-020-09976-7 \n \nWang, J., Jiang, M., Chen, X., & Montaner, L. J. (2020). \nCytokine storm and leukocyte changes in mild versus \nsevere SARS\u2010CoV\u20102 infection: Review of 3939 COVID\u2010\n19 patients in China and emerging pathogenesis and \ntherapy concepts. Journal of Leukocyte Biology, \n108(1), 17\u201341. \nhttps://doi.org/10.1002/jlb.3covr0520-272r \n \nWorldometer \nhttps://www.worldometers.info/coronavirus/  \n \n\n\n\n\nhttps://doi.org/10.1186/s12967-020-02380-2\n\n\nhttps://doi.org/10.1089/scd.2020.0080\n\n\nhttps://doi.org/10.1007/s12015-020-09976-7\n\n\nhttps://doi.org/10.1002/jlb.3covr0520-272r\n\n\nhttps://www.worldometers.info/coronavirus/\n\n\n\n"
"\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 11 of 28 \n\n\n\n\n\n\n\n\n\n\n\nOFFICIAL JOURNAL \n\n\n\nREVIEW ARTICLE \n\n\n\n\n\n\n\nGenetic Consequences of Induced Mutagenesis in development of \nnew plant varieties: A Review \n\n\n\n \nMd Al-Mamun 1,2, Mohd Y. Rafii 1,3*, Yusuff Oladosu1 and Zaiton Ahmad4 \n\n\n\n\n\n\n\n1Laboratory of Climate-Smart Food Crop Production, Institute of Tropical Agriculture and Food Security (ITAFoS), \nUniversiti Putra Malaysia (UPM), 43400, UPM Serdang, Selangor, Malaysia \n\n\n\n2Bangladesh Jute Research Institute (BJRI), Dhaka-1207, Bangladesh  \n\n\n\n3 Department of Crop Science, Faculty of Agriculture, Universiti Putra Malaysia (UPM), \n43400, UPM Serdang, Selangor, Malaysia  \n\n\n\n44Agrotechnology and Biosciences Division, Malaysian Nuclear Agency, \nBangi, 43000 Kajang, Selangor Malaysia \n\n\n\n \n*Correspondence: mrafii@upm.edu.my \n\n\n\n\n\n\n\n\n\n\n\n1. Mutation Breeding \nSince Stadler, (1928) demonstrated the first creation \nof artificial mutations in plants, these techniques have \nresulted in the development of numerous plant \ngenetic resources. The main benefit of mutation \nbreeding is its capacity to enhance one or a few \nspecific characteristics of the desired variety. In \naddition, mutant breeding is a universally and \n\n\n\nstraightforward applicable technique, and its \ncontinuous usage in and plant breeding demonstrates \nits utility. Generally, mutation is a change or alteration \nin DNA, genes, or chromosomes caused by internal or \nexternal factors, such as a replication error or UV light \nexposure. It is a normal biological process that can be \nbeneficial or harmful. It promotes evolution by \nintroducing new alleles into nature (Mba et al., 2010). \nMutations cause heritable changes in an organism's \ngenetic material that occurs without recombination or \nsegregation (Forster and Shu, 2012). Mutation has been \nthe most important component in evolution because \nchanges are passed down through generations, \nresulting in the emergence of unique\n\n\n\n \nAbstract \n\n\n\nThe genetic impacts of induced mutations have led to irreversible changes in genetic material, which \nare then transferred on to the exposed individual's offspring. This technology has contributed \nsignificantly to agricultural development through development and release of thousands improved \ncrop varieties. Plant breeders could not rely on spontaneous mutations because it scarcely and \ninfrequently. To induce artificial mutation, agents capable of causing new and heritable mutations in \nplant genomes have been introduced. Induced mutagenesis using various physical and chemical \nmutagens allows plant breeders to quickly generate desirable features, beginning crop improvement \nprogrammes and developing new crop types. Mutagens such as gamma irradiation, has been useful \nfor producing genetic variants and developing new plant varieties from which desirable mutants could \nbe successfully identified. Acute gamma irradiation of plant materials is done in minutes or hours at \nrelatively high dose rates. In contrast, chronic gamma irradiation is done for weeks or months at \nrelatively low dose rates. Chronic gamma irradiation may produce more genetic variations than acute \ngamma irradiation with minimal adverse effects. The primary goal of the plant mutation breeding \nprogramme is to develop mutants with less unfavorable morphological and physiological \nconsequences and have more powerful genetic effects to produce new varieties with desirable traits. \nThe quantity of genetic variation within a particular population is primarily responsible for crop genetic \ntrait improvement. As a result, the goal of this review was to assess the mutagenic efficiency and \neffectiveness for the selection of promising mutants based on agromorphological traits, which may \nthen be utilized to improve plant genetic improvement. \n\n\n\nKeywords: Crop improvement, Gamma irradiation, Induced mutations, Mutagens, Plant mutation breeding \n\n\n\n \n*Corresponding author: Prof Dr Mohd Rafii Yusop, Institute \nof Tropical Agriculture and Food Security \nUniversiti Putra Malaysia \nEmail: mrafii@upm.edu.my \n \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 12 of 28 \n\n\n\n\n\n\n\n\n\n\n\nindividuals, species, and genera (Mba et al., 2010). As \na result, mutation breeding is an important tool in \nmodern plant breeding, which includes treating the \nplanting materials with appropriate chemical or \nphysical mutagens (Shu et al., 2012; Chang et al., \n2020). Furthermore, compared to conventional \nbreeding, mutation induction is the best way to \ndevelop new varieties with desirable traits within a \nshort period (Oladosu et al., 2016).  \n \nNumerous physical and chemical mutagens have \nbeen used as effective agents in inducing desirable \nmutations. The achievement of successful mutant \nlines generally depends on the mutagens' \neffectiveness (Roy Chowdhury and Tah, 2013). \nPhysical mutagensis accounted for most of the \nreleased of mutant varieties due to its random \nvariations in the entire crop genomes and creating a \nwide array of mutations among genes of \ninterest (Aisha et al., 2017). Ionizing radiation has \nbeen used to induce a wide range of DNA mutations \ninvolving, chromosomal aberrations, point mutation, \nDNA rearrangement and large gene insertion and \ndeletions (Shirasawa et al., 2016). Exposure of \nionizing radiation such as X-rays and gamma rays to \nplant materials causes biological and photochemical \ndamage in the DNA sequence, causing the purine or \npyrimidine bases to be generated (Esnault et al., \n2010; Pathirana, 2011; Lagoda, 2012). Chemical \nmutagens alkylate the phosphate groups and purine \npyrimidine bases in DNA (Raina et al., 2018). \n \nGamma rays are the most widely used energetic \nelectromagnetic radiations that are considered best \npenetrating physical mutagen than other physical \nmutagens due to their convenience, ease of use, high \npenetrating ability, and a low disposal \nproblem (Abaza et al., 2020).  Radiation exposure at a \nhigh dosage rate for a short period is known as acute \ngamma irradiation while chronic exposure occurs \nover a lengthy period (weeks to months) at a low dose \nrate (Hase et al., 2020). Both acute or chronic ionizing \nirradiation can impact plants depending on their age, \nspecies, morphology, physiology, and genome \ninitiation (Hong et al., 2018). In several studies, acute \nirradiation at high doses showed harmful effects on \nvarious plant species and increased chromosome \naberrations in Allium cepa (Paradiz et al., 1992).  It \nalso caused univalent, stickiness, fragments, laggards, \nbridges, micronuclei, and early maturity in wheat \n(Verma and Khah, 2016). On the other hand, chronic \nirradiation is done in gamma rooms, gamma \ngreenhouses, or gamma fields equipped with gamma \nirradiators (Forster and Shu, 2012). Chronic gamma \nirradiation is best for developing novel mutant \ncultivars with superior genotypes in ornamentals like \nhibiscus, orchids, roses, and chrysanthemums \n\n\n\nbecause it can yield a broad spectrum of mutations with \nless irradiation damage (Azhar and Ahsanulkhaliqin, \n2014). \n \n2. History of plant mutagenesis \nDe Vries (1901 - 1903) was the first scientist to coin the \nterm \"mutation\". The first study on mutation induction \nfor crop improvement was carried out by John Stadler \nin 1928 on barley and maize using X-Ray irradiation \n(Stadler, 1928; Kharkwal, 2012). Subsequently, this \nmethod was adopted as one of the most valuable tools \nfor tracing genes on individual chromosomes, studying \nDNA structure, gene regulation, and expression to \nexplore genomes (Shu et al., 2012). Following the \ndiscovery of X-Ray irradiation, mustard gas has been \ncited as the first chemical agent utilized in mutation \ninduction (Auerbach and Robson, 1944). In 1934, the \nfirst commercial mutant cultivar of tobacco was \ndeveloped. Acquaah (2006) reported 77 cultivars that \nwere released as commercial varieties using \nmutagenesis before to 1995, and this number increased \nto 484 in 1995. Since then, new mutant types have been \ncontinually reported across different countries, \ndramatically increasing commercial mutant varieties. \nSome of the mutants plants include food crops (such as \npea, maize, rice, wheat, and barley), fruit trees (such as \npeach, citrus, and apple), and ornamentals (such as \nchrysanthemum, poinsettia, and dahlia). Due to \nmutation breeding, agronomic characteristics such as \nearly maturation, product quality, lodging resistance, \nwinter hardiness, and pest and disease resistance have \nbeen developed.  \n \n3. Mutation's causes and effects \nThe mutation causes are diverse, but can be divided \ninto natural (spontaneous) and artificial (induced) \nmutations. Spontaneous mutation happens without the \nneed of human intervention. This type of mutation has \nlow occurrence frequency. There is a considerable \nrange of diversity in wildlife around the world due to \nheritable spontaneous mutation. Muller (1930) and \nStadler (1928) proposed solutions of these limitations \nby inducing mutation artificially and with high \nfrequency, contrary to the naturally occurring \nmutation. Significant variations of a broad range of \ncharacters can be obtained through induced mutations. \nA mutagen can effectively lead to mutations, however, \nthe resulting unwanted effects such as lethality or \nsterility, can reduce its efficiency. Studies have proven \nthat treatments with mutagens can substantially \naugment mutation frequency 100 times more than \nspontaneous mutations (van Harten, 1998). \n \nSpontaneous mutation occurs naturally in crop plants \nduring evolutionary adaptations at low frequency, i.e., \n10\u22125\u201310\u22128. The background level of mutation, which is \nthought to be a key contributor to the natural genetic \n\n\n\nvariability in populations, consists of this kind of \nmutation. Spontaneous mutations happen due to \n\n\n\nDNA replication errors, natural lesions, and substitution \nof transposable compounds during regular cell growth \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 13 of 28 \n\n\n\n\n\n\n\n\n\n\n\nand are primarily recessive (Raina et al., 2018). \nHowever, this nature's frequency is insufficient for \ncreating variability in an individual crop's genetic \nmakeup to improve desirable characteristics \n(Gulfishan et al., 2015). Among the notable mutants \nidentified through spontaneous permanent, heritable \nvariations include barley, wheat, and peas, \neliminating head/pod shattering and decreasing seed \ndormancy due to domestication (Roy Chowdhury and \nTah, 2013).  \n \nThe most significant discovery was the novelty in \nexperimental plant mutagenesis during the early 20th \ncentury, which flourished into mutation breeding to \ninduce genetic variation (Sevanthi et al., 2018). These \nare caused by treating a plant or plant parts such as \nseed, rhizomes, tubers, pollen, bulbs, ovules, and \nstolon with the mutagens. Induced mutations can \nproduce desired traits either not found in nature or \nlost during evolution and have considerably improved \nglobal food security (Roy Chowdhury and Tah, 2011). \nThe goal of induced mutation is to increase the \nmutation frequency rate to choose suitable plant \nbreeding variants (Jain, 2010). Systematically, \nmutations in the plant genome revealed similar plant \nmorphology effects due to spontaneous or induced \nprocedures. In either case, DNA activities can be \nchanged through substituting the nucleotides, \ndeletion/insertion of DNA sequences, and regulating \nits modification. Certain characters of crops were \nacquired from spontaneous or purposefully induced \nmutagenesis within the same gene segments. For \ninstance, semi-dwarf rice varieties that were \nsupported by the Green Revolution process were \nfreely derived from spontaneous and directed \nmutations in the gene to have gibberellin 20-oxidase \n(Sevanthi et al., 2018). In growing science fields, \ninduced mutagenesis with physical and chemical \nmutagens has been widely used to create genetic \nvariations within crop varieties (Jain, 2010). Plant \nmaterials are treated with physical (gamma rays, ion \nbeams, fast neutrons) or chemical (EMS, DES, sodium \nazide) mutagens to induce mutation. Creating new \ngenetic variability through induced mutagenesis has \nbeen significantly exploited for crop improvement. \n  \n3.1. Plant Materials \nThe plant tissue used for mutagenesis is primarily \ndetermined by crop propagation and the available \nfacilities. The materials used in mutation induction \ninclude seeds, seedlings, tubers, stems, buds, bulbs, \npollen, in vitro plantlets, embryos, microspores, \ncalluses, and other propagules (Spencer-Lopes et al., \n2018). Generally, seeds are preferred plant materials \nfor breeding because they are simple to handle, easy \nto transport, and can be kept and utilized whenever \n\n\n\nneeded. In addition, the inducing mutation in seed-prop \npropagated plants is relatively straightforward with \navailable facilities. \n \nFor any plant mutation breeding to be successful, three \nessential factors must be fulfilled: healthy starting plant \nmaterial (original seeds), effectiveness and efficiency of \nthe mutagens, and finally, screening and identification \nof induced mutants. Plant mutation breeding systems \nshould be appropriately planned and adequate for \nselecting desirable mutants because there is a \nlikelihood of having low mutation frequencies. It is \nbasically a chance event; therefore, a higher \nexperimental sample population (seeds, seedlings, \nrhizomes, etc.) is highly recommended for early \ngenerations. Genotypes give various responses to \nmutagen treatments; thus, two or more varieties can be \nused for mutagenesis studies. Since the chance of a \nmutation occurring is about one in a thousand plants, a \nminimum of 500 to 1,000 M2 generation plants should \nbe screened to achieve the statistical probabilities of \nbeing sourced from at least 20 M1 populations. \nHowever, it depends on the crop's nature and viability \nin M1 generation (Kumar et al., 2019). \n \n3. 2. Mutagens \nA wide range of mutagens has been utilized in induced \nmutation breeding programs which can be categorized \ninto physical, chemical and biological (Janick, 2015). \nMutagens have the potential to enhance maturity \n(Aslam et al., 2012; Albokari, 2014), yield (Al-Mamun et \nal., 2022a; Horn et al., 2016), adaptability (Suprasanna \net al., 2014) and improvement of several other traits \n(Ilyani, et al., 2019). Different chemical and physical \nmutagens have varied abilities and efficiency in \ngenerating mutation. Meanwhile, transposons, viruses \nand bacteria are known agents for biological mutagens \nthat can be integrated into an organism's genome and \nchange its genetic composition during cell division (Dixit \nand Kumar, 2018). \n \n3.2.1. Physical mutagens \nThere are two types of physical mutagens: (i) Ionizing \nradiation and (ii) non-ionizing radiation. Ionizing \nradiation in the forms of electromagnetic radiations \nsuch as X- rays, gamma (\u03b3) rays, \u03b1-rays, UV rays, \u03b2-rays, \nhigh-energy ion beams, fast neutrons, and particles \nfrom accelerations are highly penetrating. On the other \nhand, UV rays which are non-ionizing radiation have low \npenetrating powers that normally induce the formation \nof dimer and DNA bases deamination (Bado et al., \n2015). These mutagens interact with atoms and \nmolecules in plant cells, releasing free radicals. These \nradicals can induce mutation in plants because they \ncreate severe cell \n\n\n\ndamage in plant cell components, modifying only a \nfew essential traits without disturbing the genotype \nand showing significant yield (Pramanik et al., 2018). \n\n\n\nIn mutation breeding research, a dose of irradiation is \ngenerally expressed in kR or Gray (Gy), where 1 Gy=100 \nrad and 1 kR=10 Gy. The absorbed unit of a dose \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 14 of 28 \n\n\n\n\n\n\n\n\n\n\n\n(radiation absorbed dose) is the rad, which equals 100 \nerg/g=10-2 joule/kg and is measured in rad per \nsecond, minute, or hour. Gamma-ray irradiation and \ndeletions of small segments 2\u201316 bp can induce \nnucleotide changes, resulting in a mutation frequency \nof one mutation/6.2 Mb (Udhaya et al., 2019). \nIonizing radiation, as well as alpha (\u03b1) and beta (\u03b2) \nparticles and neutrons, are the most employed \nmutagens (Mba et al., 2012). \n \nGamma radiation is the most efficient physical \nmutagen widely employed in plant breeding. When \nionizing radiation, such as gamma rays and X-rays \ncontact with genetic components in plants that \nproduce purine or pyrimidine bases, they cause \nbiological and photochemical damage that results in \nDNA sequence changes (Esnault et al., 2010; \nPathirana, 2011; Lagoda, 2012). Minor to massive \ndeletions, point mutations, single- and double-\nstranded brakes, and even chromosome losses could \nall be caused (Maghuly et al., 2017). Ionizing \nradiation's effects on causing changes are generally \nproportional to the energy absorbed by the treated \ntissue and the treatment dose, therefore, high doses \nof radiation can cause more biological damage. \nVarious types of plant materials have been treated \nwith physical mutagens. Plant tissues having high \nwater content (soft tissues) are treated with low dose \nof irradiation in comparison with seeds. Ultra-violet \n(UV) light, as non-ionizing radiation, can be applied to \ncreate mutation, but it has limited ability to penetrate \nplant tissues since it has low energy compared to \ngamma radiation (Mba et al., 2012). Thus, the \napplication of UV to generate variations in plants has \nbeen limited because of the limited penetration \nability. Mustard gas is also the first chemical agent \nused in mutation induction while comparing its effect \nwith ionizing radiation (Auerbach and Robson, 1944). \n \n3.2.1.1 Gamma Irradiation \nGamma irradiation is high-energy radiation from \ngamma-ray originating from radioisotopes, such as \nCobalt-60 (60C) or Caesium-137 (137Cs) from \nirradiators or open gamma fields (Table 1). Gamma-\nrays are high-energy electromagnetic radiation \nconsisting of photons with short wavelengths of 0.001 \nto 0.1 A\u00ba and high penetration capabilities into \nmaterials such as animal or plant tissues. Gamma \nirradiation affects genetic materials in different \nforms, such as breaking DNA strands, disrupting DNA \ncross-linking, DNA proteins, eliminating a base, and \nalternate chemicals of a base (\u00c7elik and Atak, 2017). \nIn addition, the effect of irradiation in inducing \nmutation on different crops was presented in table 1.  \n \nTable 1. Gamma irradiation induces genetic variation \nin a wide range of plants species \n\n\n\nSl. \nno. \n\n\n\nCrop Original \nVariety \n\n\n\nReference \n\n\n\n1 Bambara \ngroundnut \n\n\n\nZaria, Kano Adebola & \nEsson, \n2017 \n\n\n\n2 Black Cumin NRCSSAN-\n1, BHUVN-\n1 \n\n\n\nTantray et \nal., 2017 \nAmin et \nal., 2019 \n\n\n\n3 Capsicum Pusa jwala, \nG4 \n\n\n\nGulfishan \net al., \n2011 \n\n\n\n4 Chickpea  Raina et \nal., 2017 \n\n\n\n5 Chrysanthemum  Momin et \nal., 2012 \n\n\n\n6 Coriander  Jafri et al., \n2013 \n\n\n\n7 Cowpea Nakare, \nShindimba, \nBira  \n\n\n\nHorn et \nal., 2016 \n\n\n\n8 Common Bean Kashmir \ncultivars  \n(SR-1) \n\n\n\nWani et \nal., 2017 \n\n\n\n9 Faba Bean  Khursheed \net al., \n2018 \n\n\n\n10 Fenugreek  Hassan et \nal., 2018 \n\n\n\n11 Lentil DPL 62, L \n406, Masur \n95 \n\n\n\nLaskar et \nal., 2018 \nHanif et \nal., 2013 \n\n\n\n12 Mung bean Albizia, \nBauhinia, \nRobinia \n\n\n\nRawat et \nal., 2017 \n\n\n\n13 Mustard Agati \nSarhein \n\n\n\nJaved et \nal., 2000 \n\n\n\n14 Pigeon pea AL 201 Gaur et \nal., 2018 \n\n\n\n15 Soybean Grobogan Wahyudi \net al., \n2020 \n\n\n\n16 Trigonella CO 1, RMt-\n1 \n\n\n\nParveen et \nal., 2006 \n\n\n\n \n3.2.1.2 Chronic Gamma Irradiation \nChronic gamma irradiation exposes the biological \nsample to a range of ionizing radiation-induced either \ncontinuously or alternatingly over an extended period \n(hours, days, weeks, or months) based on the sample \nsensitivity and research specifications. The dose may be \nhigh enough for a sensitive shoot or root system and \ncan cause damage to their cells. Similarly, \n\n\n\ncontinuous gamma irradiation exposure to low doses \ncan result in a higher significant frequency of \n\n\n\nsomaclonal variations with no adverse effects on \nnatural reactions (Azhar and Ahsanulkhaliqin, 2014). \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 15 of 28 \n\n\n\n\n\n\n\n\n\n\n\nTherefore, most plant mutation breeding studies \nusing gamma irradiation have centred on assessing \nthe biological response of acute gamma irradiation on \nthe studied populations. However, few researchers \nevaluated the biological response of the technique to \nchronic gamma irradiation even though it was stated \nthat exposure to chronic gamma irradiation produced \na low quantity of free radicals compared to acute \ngamma irradiation exposure in plants (Vandenhove et \nal., 2010). \n \n3.2.2. Chemical Mutagens \nChemical mutagens are also significantly effective in \ninducing gene mutations, and their precise actions \nmay be studied by analyzing their reactions with \nvarious DNA bases. Many chemical mutagens have \nbeen used to produce elite mutants in crops \n(Khursheed et al., 2015). Chemical mutagens are \neasier to utilize, more commonly available, cheaper, \nmore cost-effective, and more efficient than physical \nmutagens (Khursheed et al., 2018). Chemical \nmutagens include Antibiotics, Base analogs, \nAcridines, Intercalating agents, Deaminating agents, \nAlkylating agents, Nitrous acid, Azide, Hydroxylamine, \nand Metal ions that possess high mutation \nfrequencies and mostly induce point mutations. \nThese chemicals can react with DNA by alkylating \ntheir phosphate groups with purine and pyrimidine \nbases. They can also add an ethyl group to guanine or \nthymine, causing a DNA replication mechanism to \nrecognize the changed base as cytosine or adenine. \nThe chemical mutagenesis process has become a \nwidely accepted method as it does not require \nsophisticated facilities, and the outcome of mutations \nis single nucleotide polymorphisms (SNPs). A study by \nShu et al., 2012 showed that most of the changes \nfound (70\u201399 %) in EMS, selectively alkylate guanine \nbases, leading to GC to AT base pair transitions. All \nthese chemical mutagens are highly carcinogenic; \nthus, serious caution must be taken in handling and \ndisposing of them. Various chemical mutagens such \nas alkylating agents, base analogues and intercalating \nagents have been used in inducing crop mutation (van \nHarten, 1991). Among these categories, alkylating \nagents are the most effective mutagens for inducing \nmutation (Rapoport et al., 1966). Alkylating agents \ncan induce gene or point mutation, resulting in \ndeletion and duplication of DNA nitrogen bases. \n \n4. Types of Induced Mutation \nMost studies on mutation induction in plant species \ndepend on noticeable traits and subsequently, plants \nwere categorized based on their phenotypic \nscreening. According to Lundqvist et al. (2012), the \ninduced mutation is divided into three main types: \ngenome, chromosome, and gene mutation. \n\n\n\n \nVariations in this sort of mutation can arise in the \ngenome's number of chromosomes (ploidy) and the \nachievement or waste of chromosomes (aneuploidy). \nHaploid embryos are achieved by decreasing the \ngenome number of irradiated material (Murovec and \nBohanec, 2012). Tilling (targeting induced local lesions \nin genomes) is an induced mutant in Arabidopsis that \naids haploid formation by failing to join the \nchromosome spindle in mitosis (Ravi and Chan, 2010). \nThe nucleus can be enlarged through induced \npolyploidy, and thus plant cells and tissue, crop yield, \nand enhancement of gene diversities. Genome \nreorganizations may include exchanges, relations, and \ncombinations in and among genomes. Mutations such \nas chromosome translocations, duplications, and \ndeletions can occur naturally and play a role in species \ndevelopment, but they can also be generated. \n \nAneuploidy is when one or more chromosomes are \nmissing, additional chromosomes are present, and \ncurrent chromosome replacements and relocations. \nThey can occur naturally or through crossbreeding, \nprimarily when parents contribute unequal quantities \nof chromosomes or genomes. Irradiation can result in \naneuploidy if chromosomes are accidentally deleted. \nChromosomal disruptions and subsequent \nrearrangement cause chromosome reorganization. \nBoth physical and chemical mutagens can cause such \nchanges, although ionizing irradiation is the more \ntypical cause. Ionizing radiation-induced deletion \nmutations may kill most organisms, but a few, such as \nthe waxy rice mutant, may be feasible and \nadvantageous (Jeng et al., 2009). \n \nSingle nucleotide alterations or tiny indels are common \nmutations in genes. Such changes could be effective \nand result in a new allele. Plant breeding depends on \nsuch mutations because they provide valuable novel \nvarieties. Nucleotide changes in crop plants such as rice, \nwheat, barley, and soybean have enhanced disease and \ninsect resistance, abiotic stress acclimation, \nbiochemical quality, and plant height (Jehan and \nLakhanpaul, 2006; Viana et al., 2019). Non-genic \nmutations can occur and not affect gene function. \nThese mutations are usually neutral and referred to as \nsilent mutations. Point mutations (single base \nalterations) that do not change transcription are \nprevalent (Lee et al., 2012). \n \n4.1. Practical considerations in induced crop mutations \nInduced mutagenesis has been used extensively in plant \nbreeding to create superior varieties with little changes \nin genotype genetic makeup (Raina and Khan, 2020). \nAccording to Lundqvist et al. (2012), induced \n\n\n\nmutation is divided into three main classes: genome, \nchromosome, and gene mutation. Chromosome \nreorganizations result from chromosome breakdown \n\n\n\nand subsequent rearrangement, which physical or \nchemical mutagens can induce. In any plant mutation \nbreeding research, the degree of the rate of mutations \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 16 of 28 \n\n\n\n\n\n\n\n\n\n\n\nbrought about by a unit of mutagen dose is regarded \nas mutagenic effectiveness. In contrast, mutagenic \nefficiency indicates mutations based on biological \ndamage such as lethality, sterility, and injury (Oladosu \net al., 2016). To obtain desirable mutants in plant \nmutation breeding programmes, it is imperative to \ndetermine the effectiveness and efficiency of the \nmutagens as this information is necessary to recover \nsignificant mutations at high rate with lesser lethality \n(Massey and Nautiyal, 2020). Therefore, for induced \nmutagenesis to be exploited in mutation breeding for \ncrop improvement, there is a need for basic studies \non the effectiveness and efficiency of the selected \nmutagen (Chakravarti et al., 2017). Living cells \nrespond to mutagen-induced DNA damage by killing \nor reforming DNA lesions. New variations can be \nformed because of these processes directly related to \nmutation breeding (Shu et al., 2012). According to \nOmar et al. (2008), the seeds could grow at an early \nstage but died after a certain period of growth due to \nDNA damage and the inability to repair it. DNA lesion \nrepair is initiated by viable biological systems, which \ninfluence the formation and frequency of beneficial \nmutant plants (Curtis, 2012). \n \nDetermining and selecting adequate and effective \nmutagen doses are crucial in successful mutation \nbreeding programs. An optimum dose for induced \nmutation is defined as a mutagen dose that produces \noptimal mutation frequency while causing the least \namount of unintended harm. It can be calculated \nusing a radio-sensitivity test (Mba et al., 2010). Radio-\nsensitivity test is the necessary step that must be \ncarried out to determine lethal dose before \ninvestigating mutagenic treatment to avoid excessive \nspoilage of experimental materials. The sensitivity of \nplants to irradiation differs according to plant species, \nvariety, and physiological and biological conditions of \nthe plan. Radiosensitivity is the number of radioactive \nradiations that can produce significant visible \ninfluences in the specified material (Oladosu et al., \n2016). It is usually determined by exposing the \nsubject material to different radiation levels in \ndifferent tests and giving the best result. The dose \nadequate to block 50% germination (LD50) is usually \nused to achieve good seed treatment results. To \nestablish the lethal dose for 50% of treated materials \n(LD50) or 50% growth reduction (GR50), a wide range \nof doses must be tested (Zheng et al., 2013). \n \nMutagenic effectiveness is the mutagen dose with \nmutational actions. In contrast, mutagenic efficiency \nis the variations devoid of relations with unwanted \ngenetic modifications; it is usually quantified from the \n\n\n\namount of mutation frequency and damages linked to \nmutagenic doses such as a decline in plant height, \nbreakages in the chromosomes, lethality, and sterility, \namong others (Usharani et al., 2015). The type and \nextent of damages caused due to mutagens treatments \nwere determined by mutagenic efficiency values \n(Gupta, 2019). Generally, chlorophyll mutants are \nregarded as markers to evaluate the effectiveness of \nvarious mutagens treatments. Chlorophyll mutations \nare grouped into albina, xantha, viridis, chlorina, \nstriata, tigrina, and maculata (Girija et al., 2014). \n \nThe practical aspect of using mutagenic agents in \nmutation breeding depends on the effectiveness or \nefficiency of the agents. The period of mutagen \ntreatment, mutagen dose, pH, temperature, and the \nplant material to be treated are all aspects that can \naffect a mutagen's effectiveness and efficiency \n(Gulfishan et al., 2010; Laskar et al., 2015). The \nefficiency of mutagenic agents is calculated as the ratio \nof mutants with desirable to undesirable traits as \naffected by the agents. Such traits include plant \ndamage, chromosomal aberrations, and sterility or \nlethality of mutant plants (Dhulgande et al., 2011). \nNumerous investigations have been conducted to \ndetermine the effectiveness and efficiency of physical \nmutagens, such as gamma-rays on several crop species \n(Oladosu et al., 2016; Koli and Ramakrishna 2002). The \nlow dose of gamma-rays recorded high efficiency and \neffectiveness for inducing variations on yield \nparameters in soybean, which decreased with the \nincrease in dose of gamma-rays (Pavadai et al., 2010). \nMutation frequencies have been observed with low \nlevels of mutagen. Moreover, the efficiency and \neffectiveness of mutagen are reduced with the \nincreased mutagenic doses or concentration (Satpute \nand Fultambkar, 2012). Mutagen efficacy is determined \nby the amount of biological damage generated (Raina \net al., 2018). The degree of effectiveness and efficiency \ndiffered across mutagenic dosages and two green gram \nvarieties (Mishra and Singh, 2013). They discovered that \nboth had higher levels of effectiveness and efficiency at \nlower and intermediate mutagen dosages, possibly due \nto less biological harm (lethality and sterility). \n \n4.2. Biological Basis of Mutation Breeding \nMutation breeding is based on various biological \nsystems, including DNA damage and repair biology, \nontology and reproductive biology, gene and genome \nbiology, genetics, and functional genomics. DNA lesions \nare formed naturally in living cells during metabolism \nand DNA replication. However, chemical or physical \nmutagens can significantly increase the \n\n\n\nquantity of DNA damaging events and change their \nprofile. Living cells respond to mutagen-induced DNA \ndamage by dying or reforming DNA lesions. New \nvariations can be formed because of these processes \ndirectly related to mutant breeding (Shu et al., 2012). \n\n\n\nThe higher the mutagen dose, the more DNA damage \noccurs. Because each cell can only take a specific \namount of DNA damage, any quantity above that \ncauses the cell to die through apoptosis. This is \nrepresented at the plant level, or in vitro tissue culture, \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 17 of 28 \n\n\n\n\n\n\n\n\n\n\n\nby a reduction or complete stoppage of growth \nfollowing mutagen treatment over specific critical \ndose levels (Osakabe et al., 2012). In general, \nmutagen therapy damages nuclear DNA, and during \nthe DNA repair mechanism, new mutations occur at \nrandom and are heritable (Mba, 2013). These \nalterations can also occur in the cytoplasmic \norganelles, resulting in chromosomal or genomic \nmutations that plant breeders can use to identify \ndesirable mutants (Jain, 2010). After a non-lethal \nmutagen therapy, viable biological processes kick in \nto repair the DNA damages. Because the effects of \nthis process are directly tied to the type and \nfrequency of mutations created, it is crucial and has \nsignificant implications for mutant breeding. The \nmethod influences the number of desirable mutant \nplants produced and their frequency (Curtis, 2012). \n \n5. Mutation breeding approach for developing \nmutants \nAny mutation breeding approach involves successive \nsteps (Figure 1); it should be well-designed and big \nenough with adequate facilities to screen a relatively \nbulky population (Raina et al., 2018). In any plant \nmutation breeding, the initial step is to decrease the \nnumber of latent variations from the mutagen-\ntreated planting materials in the plant's first-\ngeneration (M1) to a reasonable amount to have a \ncomparative assessment and analysis. It's worth \nnoting that the target gene's heritability determines \npopulation size; hence, selecting mutagens with high \nmutation-producing potential will limit the M1 \n\n\n\ngeneration's population size (Goyal et al., 2020).  \n \nGenetically, mutants at Ml generation are in a \nheterozygous state because the mutagen affects one \nallele only when subjected to the dose treatment. \nHowever, the possibility of mutation occurring on \nindividual alleles at one time remains a product of an \nindividual chance of having mutation. In Ml \ngeneration, only dominant mutations can be \nscreened; however, the expression of a recessive \nmutation cannot be identified at that stage. \nTherefore, plant breeders are advised to start \nscreening for possible mutations at subsequent \ngenerations (M2) where segregation is possible (Raina \net al., 2017). In addition, care must be taken to avoid \ncross-pollination at the M1 generation. It will bring \nabout a new set of variables that will be extremely \nhard to distinguish the effects of mutagens among the \npopulation and those from the cross-pollination \n(Khursheed et al., 2018). \n \nScreening and selection usually commence at M2 and \nM3 generations, and three forms of screening and \n\n\n\nselection techniques can be employed. The first one is \nmechanical; the second is morphological, and the third \nis molecular. Mechanical screening can efficiently \ndetect the size, weight, and shape using a suitable \nsieving device. Visual screening remains the most \neffective and competent approach to identify \nphenotypic mutants. It is frequently employed to select \nfor traits such as plant height, number of leaves, \nnumber of branches, adaptation to environments, \ngrowing seasons, resistance to disease, variation in \ncolors, and maturity periods, among others (Aslam et \nal., 2019). If a promising trait is identified with a \nparticular mutant line, the next thing is multiplying \nseeds of such lines for broad field trials. Here, the \nidentified mutant line, control parents, and the rest of \nthe lines should be evaluated. Finally, before its release \nas a new commercial variety, the chosen mutant plant \nneeds to be evaluated for mixtures of various traits such \nas growth habit, plant architecture, and yield across \nvarious environments with diverse water regimes, \nsowing time, and plant density (Mullainathan and \nAruldoss, 2015). \n \n5.1 Impact of Mutant Cultivars \nGenetic variation caused by induced mutagenesis using \nseveral mutagens has tremendously impacted \ncontemporary plant breeding (Beyaz and Yildiz, 2017). \nFor the past seven decades, mutant cultivars have \nsignificantly developed superior global varieties on \nnumerous improved traits such as high yield, drought \ntolerance, reduced pesticides, and fungicide \nrequirements. Numerous successes in crop \nenhancement through mutation breeding have \nresulted in two primary outcomes: established varieties \nthat may be used immediately for commercial \ncultivation and new genetic stocks with improved \nfeatures or greater character combining ability (Roy \nChowdhury and Tah, 2013). These features are \nimproved yield, improved nutritional quality, pest and \ndisease resistance, early maturity, drought and salt \ntolerance, and so on. \n \nThough the primary goal of mutation breeding has been \nthe generation of new varieties, the genetic stocks \ncreated may have a variety of applications in plant \nbreeding and can be utilized as a donor parent or a \nparent in hybrid breeding programmes in traditional \nbreeding programs. Induced mutagenesis and related \nbreeding procedures could improve quantitative and \nqualitative traits in crops in a fraction of traditional \nbreeding time. The global influence of mutation \nbreeding-derived agricultural types demonstrates \nmutation breeding's flexibility and applicability to any \n\n\n\ncrop when proper goals and selection procedures are \nfollowed. Resistance to lodging; improved land usage \nthrough early maturing types to simplify crop \nrotation; cropping systems intensification with \n\n\n\nmodified photoperiod response; qualities for consumer \npreference; improved nutritional values, decline level \nof toxins; new features with fashionable crops; \nsimplicity in harvesting/threshing; improved export \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 18 of 28 \n\n\n\n\n\n\n\n\n\n\n\nvalues and minimized imports (Shu et al., 2012). \nInduced mutation has created 3,364 mutant types in \nover 235 different crops and plant species in over 77 \ncountries (Figure 2) (FAO/IAEA-MVD, 2020). China has \ndeveloped the most number of mutant varieties (810) \n\n\n\nfollowed by Japan (481) and India (330). Most released \nmutant varieties comprises cereals, legumes, flowers, \nberries, edible oils, food vegetables, fodder, forage, \ngrasses, fiber, and nuts (Figure 3) \n \n\n\n\n\n\n\n\n \nFigure 1. Mutation breeding procedure for obtaining new superior varieties adopted with modification from \n\n\n\nOladosu et al. (2016). \n \n\n\n\n \nFigure 2. Distribution of officially released mutant crop varieties based on the continents \n\n\n\n(Adopted from Mutant Varieties Database 2020) \n \n \n\n\n\n\n\n\n\nMutagen \nInduction \n\n\n\nOriginal \nVarietal seeds \n\n\n\nDose optimization  \nLethal dose (LD50) determination \n\n\n\nM1  \nGeneration \n\n\n\nM2 Generation \nsegregating population \n\n\n\n(Mutants screening) \n\n\n\nM3 Generation segregating \npopulation mutant line selection \n\n\n\npreliminary yield evaluation \n\n\n\nM4 Generation \nhomozygosity test \n\n\n\nand yield evaluation \n\n\n\n\uf0a7 Seed Multiplication \n\n\n\n\uf0a7 Multi-location yield trail \n\n\n\nNew superior \nvarieties \n\n\n\nFurther evaluation M5-8 Hybridization \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2021, e-ISSN: 2811-3594 Page 9 of 6 \n\n\n\n\n\n\n\n\n\n\n\n \nFigure 3. Distribution of officially released mutant crop varieties based on crop types \n\n\n\n(Adopted from Mutant Varieties Database 2020) \n \nBreeding programs generally focus on selfing and \ninbreeding to carry forward the same genetic stock to \nthe next generation. This has increased homozygosity \nwith the materials and reduced variability, limiting the \ngenetic potential of the germplasm for future \ndevelopment. To achieve successful plant breeding \nprograms among sexually or vegetatively propagated \ncrop species, it is imperative therefore to achieve \nsubstantial genetic variability (Agbolade et al., 2019). \nMutation breeding is a form of conventional plant \nbreeding that comprises physical or chemical \nmutagenesis to determine the genetic variability that \nwill improve varieties with superior traits (Oladosu et \nal., 2016). Induced plant mutagenesis has immensely \ncontributed to the genetic variability in numerous crop \nspecies by increasing DNA polymorphism \n(Dhakshinamoorthy et al., 2013). \n \nIn several crops, mutation induction is a cost-effective \nand efficient way to produce new cultivars (Oladosu et \nal., 2016). Knowledge and identification of differences \namong available germplasm is a prerequisite for \nselecting appropriate genetic resources adapted to \nenvironments before the commencement of a \nbreeding program (Oladosu et al., 2014). Similarly, \nselection and recommendation for commercial \ncultivation are only proper after comprehensive \ninformation and research. This information can only be \nobtained through the evaluation of available crop \nvarieties. However, in the absence of diverse traits in \nthe gene pool, mutagenesis is often used in crops to \ncreate valuable traits such as plant height, days to \nflowering, color variation, and pathogen tolerance \n(Kang et al., 2016; Oladosu et al., 2016). \n6. Screening Mutant populations for desired traits \n\n\n\nIn general, selection in M1 is not advised since \nmutations may be undetectable due to chimerism, \nphysiological problems, and recessive mutations that \ncan only be manifested in genetically homozygous \nform. However, some dominant mutants can be \nobtained and selected in M1 generation in some \nsituations, such as in barley mildew race D1  (Lundqvist \nand Lundqvist, 1992). Several agronomic \ncharacteristics, such as abiotic and biotic stress \nresistance, are not fully manifested in single cells or \nimmature plants (Maluszynski et al., 1995; van Harten, \n1998). Donini and Sonnino (1998) characterized the \nselection of mutants based on phenotypic screening \ninto: \n \ni. Detection of mutation on qualitative traits (based \n\n\n\non a single plant) by visual screening combined \nwith suitable selection methods for disease \nresistance, resistance, or tolerance to abiotic or \nbiotic stresses. This type of screening can be \napplied to M2 generation. \n\n\n\n \nii. Detection of mutation of quantitative traits \n\n\n\n(based on plant progeny). These can be screened \nthrough physical, biochemical, mechanical, and \nbiometric procedures based on the whole mutant \npopulation. Traits such as yield, biochemical \nparameters, minerals content, size and weight of \nseed and fruit can be assessed in M2 and other \nadvanced generations. \n\n\n\n \nRoy Chowdhury et al. (2012) describe three main \nmutation breeding screening and selection procedures \nto develop a new mutant variety. The\n\n\n\nvisual selection procedures can be effective for the \nphenotypic identification of mutants. Through this \n\n\n\nmethod, plant breeders can reduce mutations to their \nprimary targets. This approach can select traits like \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2021, e-ISSN: 2811-3594 Page 20 of 28 \n\n\n\n\n\n\n\n\n\n\n\nmorphological qualities, yield, disease resistance, and \nabiotic and biotic stress tolerance. In this method, \nprogeny selection and evaluation of progenies \ndepend on their phenotypic performances. The effect \nof genotype and environmental factors on \nphenotypes of selected mutants can be determined \nthrough progeny selection. In the mass selection \nmethod, a great number of plants can be selected \nbased on the similarity of their phenotypic \nperformance and mixed their seeds to develop new \nvarieties. It is commonly applied in mutation \nbreeding. Bulk method of selection can be used for \nmanaging segregation generation in mutation \nbreeding. The selection and evaluation in this method \nare based on the performances of individual plants. \n \nMost mutant variants result from forward-genetic \nphenotypic screens (Pathirana, 2011). Mutants are \nliving organisms with permanent hereditary \nalterations that can be detected using molecular \nmethods or identified utilizing phenotypic \ninstruments (Forster and Shu, 2012). Mutation \ninduction can help generate mutant lines and identify \ntrait-specific genes to create a molecular gene \ndatabase to facilitate molecular functional genomics \nresearch and improve bioinformatics for future plant \nvariety development (Chiew et al., 2016). However, \nthe genetic evaluation of mutant and non-mutant \npopulations through molecular markers has been in \nexistence since the 1970s, when molecular DNA \ntechnology was established (Jehan and Lakhanpaul, \n2006).  \n  \n6.1. Mutation Effects on Plant Morphology and Yield \nIdentifying essential traits using morphological \nclassification is the significant step in exploring plant \ngenetic resources. This system is inexpensive, direct, \nand requires less equipment, in addition, considered \nas the standard method of genetic variability \nassessment (Molosiwa et al., 2013). Girija et al. (2014) \nreported that qualitative traits can easily be detected \namong individual plants and are inheritable. \nQuantitative traits mutations are more relevant in \nplant breeding programs than qualitative mutants. \nHowever, qualitative mutants serve as key indicators \nand can pave the way for further investigation on \nquantitative traits (Horn et al., 2016). As reported by \nTalebi et al. (2012), particularly among the self-\npollinated crop species, it is reasonably clear that \npolygenic mutation has brought about significant \nvariation in mutagen treated populations. Mutations \nwere produced to increase plant productivity in seed- \nand vegetatively propagated crops by subjecting \n\n\n\nbotanical seeds and vegetative parts such as stem \ncuttings, twigs buds, and tubers to mutagenic agents to \nincrease genetic diversity (Jain, 2010; Ulukapi and \nNasircilar, 2015). Furthermore, this system is employed \nto select morphological qualities that can positively \ncorrelate to grain yield and thus facilitate the selection \nof genotypes with desirable traits. Morphological \ncharacters are classified into qualitative and \nquantitative, and the ideal time to identify plant \nmutants is at M2 generation, during this generation, the \npossible mutations that happened at M1 generation \nsegregate to form either homozygous dominant or \nrecessive alleles (Javorka et al., 2019). \n \nVariability is one of the basic prerequisites before \nstarting any judicious plant breeding program. \nMutagenesis has been widely used for inducing \nvariations for plant improvement. Various \nmorphological mutations have resulted in variations in \ngrowth habit, stem pattern, leaf shape, internodes \nmorphology, flower morphology, pod indehiscence, \nseed shape and seed size have been obtained through \nmutation induction in various crop plants. Several \nphysical and chemical mutagens have been employed \nto induce beneficial mutations in a variety of crops. For \nexample, Shah et al. (2001) studied the effect of various \ndoses of gamma-ray (1.0, 1.2 and 1.4 KGy) on \nqualitative and quantitative traits of Brassica napus L. \nDesirable mutations were induced, and new varieties \nwere developed, such as Brassica napus L. cv ABASIN-\n95 with good quality of oilseed and other variety with \nhigh yielding and resistant to Alternaria blight and white \nrust. \n \nAnother study irradiated seeds of two okra varieties at \n300, 400, and 500 Gy of gamma-ray. The growth \nparameters recorded were plant height, number of \nbranches/ plants, leaf area/ plant, fresh and dry \nweight/plant and dry weight/ plant. Photosynthetic \npigments, chlorophylls a, b, \"a + b\" and carotenoids in \nleaves of treated plants were also determined \ncalorimetrically. The results revealed enhancement \nfrom treatments with 300 and 500 Gy, while 400 Gy is \nthe best dose for all study parameters (Hegazi and \nHamideldin, 2010). \n \nRahimi and Bahrani (2011) studied agronomic \ncharacters and fatty acids of mutants of Brassica napus \nL., derived from seeds irradiated with 100, 200, 300, \n400, and 500 Gy. The results demonstrated that various \ndoses of gamma-ray affected all studied traits (plant \nheight, harvest index, 1000-seed weight, seed oil \npercent, linolenic, linoleic and oleic fatty acids).\n\n\n\n They decreased with increasing dose of irradiation up \nto 300 Gy. The lower mean values of investigated \ntraits were recorded at 500 Gy. Malek (2012) induced \nmutant mustard variety (MM-10-4 and MM-08-04) \nwith high seed yielding and a higher number of \n\n\n\nsiliques per plant through seed exposure to 600, 700, \n800, and 900 Gy of gamma-irradiation. \n \nTshilenge-Lukanda et al. (2013) reported that a lower \ndose represented in 100 Gy improved grain yield, \nmorphological and agronomic traits, particularly JL24 \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2021, e-ISSN: 2811-3594 Page 21 of 28 \n\n\n\n\n\n\n\n\n\n\n\nvariety, while higher doses of 400 and 600 Gy \nsignificantly inhibited plant growth and grain yield of \ngroundnut (Arachis hypogaea L.). Aney (2013) \nreported significant induction of variations and \nenhancement on yield and its components such as \npodsize, number of pods per plant, number of seeds \nper plant in two varieties of Pisum sativum when \nexposed to various gamma-ray doses (50, 100, 200 \nand 250 Gy). Sikder et al. (2013) studied the efficiency \nof different gamma-ray doses in inducing mutation of \nthree tomato genotypes by irradiating seeds with 50, \n100, 150, 200 and 250 Gy gamma-rays. Low doses of \ngamma-ray showed higher efficiency than high doses \nin developing desirable mutants. Dosages of 67.3, \n290.9 and 303.8 Gy were recorded as LD50 for \nEC620176, EC620177 and Patharkutchi respectively. \n \nIlyas and Naz, (2014) applied ten doses (0, 10, 20, 30, \n40, 50, 60, 70, 80, 90 and 100 Gy) of gamma-rays from \nthe Cobalt-60 as the source of gamma radiation to \nrhizomes of Curcuma longa collected from different \nareas. The results indicated that the germination \npercentage, curcuminoids, yield of essential oil and \nmorphological characteristics responded differently \nto various gamma-ray doses. Maximum shoot length, \nleaf width and number of leaves were obtained at 60, \n70, and 70 Gy for the samples from Kasur, \nrespectively, while plants collected from Faisalabad \ngave maximum leaf width at 50 Gy. Compared to non-\nirradiated Rhizomes of Kasur plants, 50 Gy yielded \n0.73 percent essential oil output (0.31 percent). \nCurcuminoids output rose (12.4 percent) in plants \nobtained from Kasur at 60 Gy. Taheri et al. (2016) \ninvestigated the impact of different dosages of \nchronic gamma irradiation on three Curcuma \nalismatifolia cultivars. The researchers discovered \nthat higher doses caused phenotypic changes and \nconsiderably impacted plant growth indices and \nflowering ability. \n \n6.2. Variability studies for induced qualitative traits \nGenetic variation is fundamental for successful plant \nbreeding to be accomplished (Horn et al., 2016). Most \ntraditional crop improvement programs depend on \nnatural genetic variation in a gene pool (Rawat et al., \n2017). Unlike spontaneous mutation or controlled \nhybridization between distant parents, induced plant \nmutagenesis can produce genetic variations for \ngenetic enhancements and breeding in a \ncomparatively shorter time (Balkan, 2018). The \napproach of crop improvement through induced \nmutation has been a well-known plant breeding \ntechnique. However, plant mutagenesis techniques \n\n\n\nhave been remodeled to have the ability to generate a \nmuch greater desirable genetic variation as compared \nto those produced by the conventional breeding \napproach (Oladosu et al., 2016). According to the \npooled study of qualitative data, different \ncharacteristics distinguish the genotypes from the \nparental variety (Al-Mamun et al., 2020). These will \nserve as a foundation for selecting mutant cultivars with \nhigh yielding potentials. \n \n6.3. Induced variability for quantitative traits \nQuantitative traits such as plant height, yield, yield \ncomponents, and drought tolerance are the most \ninteresting traits in plant breeding studies and are \ncontrol by many genes and affected by environmental \nfactors. The main aims of any plant breeding program \nare generating variations, selecting desirable variations, \nevaluation, and multiplication. Baur (1924) confirmed \nsubstantial micro-mutation in evaluation, and several \nresearchers in many crops have investigated it. Micro-\nmutations are important in mutation breeding because \nall morphological and physiological traits are influenced \nby micro-mutation and may have a higher mutation \nrate than macro-mutations (Gaul, 1965). Several \nstudies have reported increased genetic variability of \nvarious agronomic traits in mutant populations through \nsignificant changes in coefficient of variation and mean \nvalue compared to control. In addition, several studies \nobtained significant variability in quantitative \ncharacters in various crops such as Bambara groundnut \n(Muhammad et al., 2021), rice (Oladosu et al., 2015), \nKenaf (Al-Mamun et al., 2022b). \n \nWani and Anis (2004) treated seeds of two chickpea \nvarieties (Pusa-212 and Pusa-372) with physical \n(gamma-ray) and chemical (EMS) mutagens to induce \nquantitative variations. From the data collected on \nquantitative traits (plant height, days to flowering and \nmaturity, number of primary and secondary branches, \nnumber of pods per plant and total seed yield), lower \ndoses of mutagens showed stimulatory effects on \nquantitative traits. In comparison, higher doses \nrecorded negative effects of all studied characters. \nSimilarly, Arefrad et al. (2012) irradiated seeds of soya \nbean, Glycine max (L.) with different doses of gamma-\nrays (80, 160 and 240 Gy) to improve qualitative and \nquantitative traits. Based on the evaluation of M2, M3 \nand M4, there were significant improvements among \ntreated and untreated plants in plant height, number of \nbranches per plant, grain yield, and oil content. \nTherefore, doses ranging from 80 to 160 Gy were \nproposed to induce high grain yield and oil content.\n\n\n\nOn a similar note, El-Degwy (2013) studied the \nperformance of M1 and M2 generations derived from \nrice seeds irradiated with 15, 20, and 25 kR gamma \nray doses. The dose 15 kR obtained the greatest mean \nof number of panicles per plant in M1 generations and \nplant height and heading date in M1 and M2 \n\n\n\ngeneration. The dose 25 kR was observed to cause a \nhigher number of spikelets per panicle and the number \nof panicles per plant in M2 compared to the control. This \ndose induced the highest variations among all the \nmutagenic doses. \n \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 23 of 28 \n\n\n\n\n\n\n\n\n\n\n\n7. Conclusion \nMutation breeding is a method of obtaining desired \ntraits or characteristics that do not occur naturally or \nwere lost during the evolutionary process. An \nadequate mutagen must be employed to obtain the \nnecessary frequency and range of beneficial \nmutations in crop development programs. Using \nmutagens has resulted in thousands of mutant \nvarieties, which have improved features in over 250 \nplant species worldwide. Physical mutagens have \nproduced the most mutant types, followed by \nchemical and biological agents. Induced mutagenesis \nand its breeding strategies could be used to improve \ncrops' quantitative and qualitative traits in a lot less \ntime than traditional breeding. Mutagenic treatment \nof seeds and other parts of the plant is still a useful \nmethod for isolating the desired variants and making \ncrops resistant to abiotic and biotic stresses due to its \nrapid and relatively low-cost. Hence, the released \nmutant cultivars are already a part of the Joint \nFAO/IAEA Division's overall commitment and \nstrategies to improve food security around the world. \nThe effects of crop varieties that came from mutation \nbreeding around the world show that mutation \nbreeding has the potential to be a flexible and useful \nmethod that can be used on any crop as long as the \nright goals and selection methods are used. \n \n \n \nAcknowledgements \nThe authors would like to express their gratitude to \nthe Universiti Putra Malaysia and Bangladesh \nAgriculture Research Council for allowing them \npermission to conduct this research. 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Screening of genotypes for identification \nof resistant genotypes for BCMV. Research Journal of \nAgricultural Sciences, 8(2): 320-323. doi: 3818-0611-\n2016-070 \n \n\n\n\n\n\n\n \n*Correspondence: mrafii@upm.edu.my\n\n\n \n1. Mutation Breeding\n\n\n\n\n\n"
"\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 37 of 47 \n\n\n\n\n\n\n\n\n\n\n\nOFFICIAL JOURNAL \n\n\n\nREVIEW ARTICLE \n\n\n\n\n\n\n\nThe Improvement of Drought Stress Tolerance in Rice (Oryza Sativa \nL.) For Nigeria\u2019s Consumption: A Review \n\n\n\n  \n1Awosan Elizabeth Adetutu*, 2Olubiyi Mayowa, 3Rohayu Ma`Arup \n\n\n\n\n\n\n\n1Forestry Research Institute of Nigeria, P.M.B. 5054, Jericho Hill, Ibadan, Oyo State, Nigeria \n2National Center for Genetic Resources and Biotechnology, Moor Plantation, Ibadan,   Nigeria \n\n\n\n3Program of Crop Science, Faculty of Fisheries and Food Science, Universiti Malaysia Terengganu, \n21030, Kuala Nerus, Malaysia \n\n\n\n \n*Correspondence: funmitutu1@gmail.com  \n\n\n\n\n\n\n\n\n\n\n\n1. Introduction\nRice (Oryza sativa), the ultimate and significant food \nsource for the majority of the world's dwellers, and \nit's also becoming a crucial commodity crops in Africa \n(Rasheed et al., 2020). Rice consumption is expanding \nfaster than most staples in Africa and around the \nworld due to the fact that it has become a convenient \nfood for the world's growing population. After maize \nand wheat, it ranks third on the list in terms of \nproduction (Guimara, 2009; Ajah and Ajah, 2014). \nMoreover, Asia processes and utilizes over 90% of \nrice in the globe, with Egypt and Nigeria being the \nleading African producers (USDA, 2017). To keep up \nwith the world's growing population, the World Food \nOrganization estimates that agriculture will \nnecessitate increasing substantially by 2050, \nspecifically for high-end staples like rice (FAO, 2017). \n\n\n\nRice is consumed in Nigeria in large quantities, with \naround 7 million tonnes consumed each year (Umego \net al., 2020). Regardless of this fact Nigeria is one of \nthe most important rice producers in Sub-Saharan \nAfrica and has the resources to address the country\u2019s \npresent food problem. Therefore, in order to address \nthe food security challenge and achieve self-\nsufficiency in rice production, agricultural production \ntechnologies must be developed and continuously \nimproved in order to address the problem of drought \non rice production. \n \n2. Rice in Nigeria \nRice demand has expanded dramatically since the \nprevious years as a result of numerous factors, \nincluding increased population growth, fast \nurbanization, and so on, and has become the deciding \nelement to consider in the change of consumers \ndemands for rice. Rice has been a favoured staple \nover all other staples as men and women become \nincreasingly involved in the work force, and domestic \nproduction has not been able to proffer solutions to \nthese demands, leading to an increased importation \n\n\n\n \nAbstract \n\n\n\nRice is a major food crop for most of the population and is now a key commodity crop in Nigeria. One \nof the major aims of rice breeding efforts around the globe is to generate rice with excellent grain \nquality and yield, although drought stress is frequently a hindrance. Drought stress is predominantly \nan abiotic stress that has a significant impact on rice production while also putting food stability at \nstake. Rice breeders in Nigeria have been able to develop the crop for a variety of traits, including \ndrought tolerance, but output is hampered by periodic droughts brought on by climate change. \nTherefore, there is a pressing need to develop better drought-tolerant rice variety in order to \nincrease output in the face of environmental stresses. A variety of breeding approaches, like \nmolecular breeding and variety introductions from other nations, could be used to improve rice \ndiversity and so enhance it, but these tools have yet to be fully incorporated into the country's rice \nbreeding programs. This review aimed to contribute insights on the current state of progress on rice \nin order to reduce losses caused by water deficits. Rice breeders and researchers may find this \ninformation valuable. \n\n\n\nKeywords: Rice, Drought Tolerance, Production, Molecular Marker Technologies \n\n\n\n \n*Corresponding author: Awosan Elizabeth Adetutu \nForestry Research Institute of Nigeria, P.M.B. 5054, \nJericho Hill, Ibadan, Oyo State, Nigeria \nEmail: funmitutu1@gmail.com \n\n\n\n\nmailto:funmitutu1@gmail.com\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 38 of47 \n\n\n\n\n\n\n\n\n\n\n\nof rice into the country in recent years. Nigeria has a \nrice-growing potential of 4.6 to 4.9 million ha, but \nonly 1.7 million ha are currently cultivated (Ojehomon \net al., 2019). This is as a result that rice production \nhas been entrusted to peasant farmers with lower \nnumber of hectares under tillage without improved \n\n\n\nagricultural production techniques (Oluwaseyi et al., \n2016). Hence, to attain self-sufficiency in rice \nproduction there is the necessity for improvement of \ntechnical efficiency and output production at current \nproduction levels in the country\u2019s rice farms (Figure \n1).\n\n\n\n\n\n\n\n\n\n\n\nFigure 1. Flow concept of drought tolerant improvement strategies in Nigeria's rice\n \nEnhancing yield for consumers without also ensuring \nefficiency may be counterproductive because rice \nmust be palatable to customers, which indicate that \ngrain quality must be improved. With this scenario, it \nis critical to alter or improve existing cultivars with \nfarmers in order to maximise productivity and quality \nwhile avoiding the drought stress component. Rice \nenhancement demands the imaginative employment \nof latest and current plant breeding knowledge to \ngenerate more economic benefits. Rice production, in \ncontrast, has been impeded by a range of factors, \nparticularly abiotic stress for example drought. \n \nDrought is the deficiency or dearth of water severe \nenough to hamper the growth of any plant. It is a \nserious abiotic stress that affect global productivity \nthereby reducing fodder production and grain quality \nby approximately 56% and 62%, respectively \n(Olubumni, 2015). \n \nClimate change will increase the frequency of drought \nand flooding, especially in many African countries. \nThe global trend of water scarcity as a result of \nclimate change, and the increasing water \nconsumption of rice variety have made it a major \nconcern for rice breeding efforts. \n \nDrought can affect crops at any phase of \ndevelopment, but way earlier it hinders \nestablishment of crops along with reduction in yields \nin case it happens during the flowering or pod filling \nphases (Tumwesigye and Musitwa, 2002). Hence, \n\n\n\ndrought-tolerant rice cultivars are an excellent \napproach to preserve rice from drought damage. \nDrought-tolerant varieties must be developed in \norder to grow acreage in locations with low \nprecipitation and inadequate irrigation infrastructure, \nsuch as many regions of Nigeria. Consequently, \nirrigation is also not a feasible drought management \noption in most rainfall zones, due to increasing \nshortage and competitiveness for water supplies. On \nthis account in offering solution to drought stress as \nmuch accessible soil moisture must be emphasized in \nutilizing it for crop growth, biomass, and grain output \nthrough a more drought tolerant variety. \n \nConsequently, some traditionally cultivated endemic \nand some wild rice cultivars such as IKPS, IKFS IJS02, \nIJS09 and Lad-f and their genetic potential allow \ngreater opportunity to enhance drought tolerance in \nmega cultivars (Celestine et al., 2016). Drought \ntolerance (DT), on the other hand, is a complicated \nfeature regulated by a number of genes (Bernado, \n2008), and the difficulties in building simple and \neffective screening procedures makes generating \nresistant varieties a huge issue. Hence, to overcome \nthis huge issue, biotechnology techniques can be \nadopted to play this important role in discovering \ngenes and incorporating them into new breeds. \nHowever, progress has not been accomplished at the \nrequired level to have a major impact on rice output \nin Nigeria due to the trait's genetic complexities. In \nthe development of drought tolerance, genetic \nvariation between rice cultivars is a significant \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 39 of47 \n\n\n\n\n\n\n\n\n\n\n\ncomponent and most drought-tolerant genotypes are \nfrequently used in investigation and are the main \nresource of resistance genes for establishing resistant \ncrop varieties. Rice drought tolerance processes have \nbeen extensively investigated, which may aid in \nunderstanding drought stresses strategies together \nwith it enhancement (Pandey and Shukla, 2015; \nSahebi et al., 2018). Mechanism in drought situations, \nrice yields can be boosted by producing DT varieties. \nOur present assessment focuses on the impacts of \ndrought stress on rice plants, methods for breeding \ndrought-tolerant cultivars, evidence of candidate \ngenes, and outputs in rice for demand in the country. \nThe flow concept of this review can be found in the \nFig 1 above.  \n \n \n\n\n\n3. Drought's Impact on Rice \nDrought in rice is a complicated process influenced by \nseveral of genetic elements as well as complex \nmorphophysiological systems (Li and Xu, 2007). \nDrought stress causes the stomata to contract and \nslowing down gas exchange while phytohormones \nlike cytokinins and abscisic acid regulate stomata \nclosure (Li and Xu, 2007). Drought stress inhibits rice \nplant water content through reduction in cell size, \nleaf area, leaf curling, reducing meristematic activity, \nroot growth disruption, root system destruction \n(Singh et al., 2012a), and water permeability from the \nsoil, eventually resulting in leaf mortality (Singh et al., \n2012a: Zain et al., 2014). List of the factors and \nfeatures to consider when breeding for drought \ntolerance in rice and its function can be found in table \n1 below. \n\n\n\n \nTable 1. Important factors to facilitate induce drought tolerance in rice \n\n\n\n \nFeatures Function  Reference \nLeaf rolling score  Decrease transpiration    Courtois et. al., 2000 \nLeaf starch regulation  Improved osmotic stress tolerance  Thalmann et. al., 2016 \nDeeper and thicker roots  To explore a larger soil volume Yadav et. al. , 1997 \n \nSpikelets fertility  \n \n\n\n\n \nImproved under drought stress \n\n\n\n \nMoonmoon and Islam, \n2017 \n\n\n\n \nMembrane stability \n \nStarch contents \n \nLeaf starch regulation \n \nDeeper and thicker roots \n \nOsmotic adjustment \n\n\n\n \nEffective plants leaves at high temperature \n \nIncreases and protect the plant \n \nImproved osmotic stress tolerance \n \nTo explore a larger soil volume \n \nTo allow turgor conservation at a low plant \nwater potential \n\n\n\n \nTripathy et. al. , 2000 \n \nDien et. al., 2019 \n \nThalmann et. al., 2016 \n \n(Yadav et. al., 1997 \n \nLilley et. al., 1996)    \n\n\n\n4. Drought\u2019s Consequences on Rice \nDrought-induced pressure damages photosynthetic \nenzymes, slows rate of photosynthesis and interferes \nwith multiple steps in the photosynthesis process, \nresulting in a reduction in terms of output and \nbiomass (Ashraf and Harris, 2013; Khan et al., 2018). \nIt also decreases the proportions of many key \nnutrients including nitrogen (N) and phosphorus (P), \nreducing the absorption of nutrients from the soil \n(Cramer et al., 2009). This is related to soil \nmineralization, diffusion, and the breakdown of \nnutrient supply networks in the soil due to mass flow \n(Chapin III, 1991). Drought stress alters rice growth \nand biomass, as well as the grain filling phase, \nresulting in lower yields (Nahar et al., 2016). It has \ndifferent effects on flowering, and panicle formation \nstages (Kim et al., 2020). It also causes genetic \ninfertility and embryo abortion during the \n\n\n\nreproductive stages (Ozga et al., 2017). Furthermore, \nit reduces rate of photosynthesis by damaging \nphotosynthetic pigments, limiting foliage elongation, \ngaseous exchange rate, and enzymatic activity, \nresulting in a reduction in plant production and \nbiomass (Ashraf and Harris, 2013; Fahad et al., 2017; \nHassan et al., 2020). \n \n5. Rice Genetic Diversity in Nigeria \nThe germplasm of O. sativa consists of enhanced \ngenotypes and land races that are currently \nunderutilized in breeding for upland and rain-fed \ndeep water ecological systems. Drought-tolerant \nmaterials can be developed using the deep-rooted \ncharacter and heavy panicle mixed with huge, strong \nculms that characterize upland ecological systems, \nespecially in locations with considerable rainfall, such \nas tropical rainforests. O. glaberrima is endemic to a \n\n\n\nWest African sub-region that is well suited to \nunfavorable African rice growing soil, severe climatic \n\n\n\nconditions, and abiotic stressors including drought \n(Maji and Singh 1993; Paul and Ladeinde, 1995). \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 40 of 47 \n\n\n\n\n\n\n\n\n\n\n\nNevertheless, they have a limited harvest capability, \ngrain spilled before full maturity, and a variety of \nother negative features that make them unappealing \nto both agronomists and consumers. Despite its \nnegative characteristics, it has a lot of room for \ngenetic development because it's adaptable to a wide \nrange of rice-growing ecological environments, from \nhigh upland to deep water. Consequently, O. \nglaberrima has many important traits such as weed \ncompetitiveness, and ability to respond to low input \nconditions. The weed competitive ability of O. \nglaberrima is due to the early vigour, high light use \nefficiency, and high specific leaf area leading to high \ncanopy growth for given amount of assimilates. It has \ndroopy leaves which prevent sunshine from reaching \nthe soil surface. Further, its high root biomass \naccumulation and thin roots with better soil \npenetration ability help compete effectively with \nweeds for nutrients. O. glaberrima has the ability to \nproduce extra tillers (up to 8 tillers/hill) between 40 \nand 80 days after germination, and thus can \ncompensate for any early loss in tillering suffered due \nto weeds (Sarla and Swamy 2005) . The short basic \nvegetative phase and the ability to produce more \nbiomass within a short time allow O. glaberrima to \nsuccessfully compete with the weeds.  \n \nIn the year 1991, the African Center for rice began \nresearch combining two cultivars of rice. O. sativa and \nO. glabberima making use of their genetic differences \nto necessitate a separate breeding strategy. To create \nviable segregating populations, embryo rescue \nprocedures were used (Jones et al., 1997). The newly \ndeveloped material is known as \"Africa's new rice,\" \nand it was this variety that was the first to \nsuccessfully crossbreed the two cultivars on a large \nscale. The key differences between this novel variety \nand conventional farmer-grown O. glaberrima are its \nenhanced capacity to compete against weeds, longer \npanicles carrying roughly 400 grains, and higher \nproduction potential. It also has stronger stems that \ncan survive lodging, less breaking, matures 30 days \nsooner than other traditional kinds, is more resistant \nto biotic and abiotic stresses, and has enhanced \nadaptation to poor African rice cultivation soil \n(AfricaRice, 2010). \n \nDrought-tolerant rice has progressed substantially in \nNigeria over the last few decades, resulting into \nintroduction of fast maturing variety with increased \ngrain outputs, superior grain qualities, higher mill \nrecoveries, and significantly higher nutritive value \nthan those available locally. FARO 44 (Sipi 692033), a \nhybrid of Sipi 661044 and Sipi 651020, is an example \nof enhanced drought tolerant rice types (Abiwon et \nal., 2016). It has an optimum yield of 4-8 tonnes per \nha as well as becoming the predominant cultivar \n\n\n\nacross most ecological lowlands of northern central \nNigeria owing to its high productivity, early maturing, \nlong grain features, and capacity to achieve optimal \nyield with minimal maintenance. FARO 52 (WITA 4) is \na renowned modified rice variety in Nigeria, with a \nyield of 3-7 tonnes per ha (Catalogue of released \nvarieties in Nigeria, 2014). Table 2 list the rest of the \nenhanced drought-tolerant rice varieties in Nigeria. \n \nHowever, some constraints have limited the rapid \nadvancement of rice varieties in Nigeria. The impact \nof climate change may be evident in the country, as \nproven by the annual floods. As a result of this, rice \nproducing farms are damaged while farmers still \nsuffers from severe drought on the same grounds \nwhere the flood happened thus nutrients present in \nthe soil  in these areas are also severely leached \n(Oluwaseyi et al., 2016). However, it's important to \nkeep in mind that in the coming years, there's a high \nlikelihood that water will be scarce due to the impact \nof climate change resulting into low crop yields (Sen \net al., 2017). Similarly, there's the problem of weed \ncompetition, which, if unchecked, can result in a \ncomplete loss. As a result, effective techniques for \nincreasing crop productivity in water-stressed areas \nmust be developed. This ambition is embodied in the \ncreation and application of molecular genetics to the \nproduction of drought-tolerant rice.  Below are some \nother listed drought tolerant rice varieties which can \nbe found in table 2. \n \n6. Strategies for Enhancing Drought Tolerance \nDue to the increasing trend in water scarcity, which is \nleading to a gradual deterioration of water scarcity \naround the world as a result of climate change, and \nthe excessive water requirement for rice cultivar, this \nis a very significant objective for rice breeding \ninitiatives. It is also a major severe constraint in \nproduction of rice in Nigeria and Sub-Saharan Africa, \nwhere nearly 80% of farmers rely on rainfall \n(Oluwaseyi et al., 2016). Moreover, there is this \nlimitation in farmer\u2019s resources to be able to finance \nirrigation equipment. Nonetheless, the complexities \nof the trait, as well as the difficulties in developing a \nreliable and easy selection mechanism make \ngenerating drought-tolerant cultivars a critical task. \n \nThe application of molecular techniques is making a \nsubstantial contribution to the understanding of \ngenes as well as ways for incorporating these into \nnew cultivars. Nevertheless, due to the genetic \ncomplexity of the characteristic, the development \nremains below the desired stage to have a significant \nimpact on rice output. Grain yield and quality \nimprovement is one of the significant goals of \npractically all rice breeding efforts. The majority of \nthe knowledge is focused on the use of crop \n\n\n\nimprovement technologies to improve grain yields \nand qualities of present cultivars. Among these \n\n\n\nstrategies centered on those breeding procedures are \nthe following below. \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 42 of 47 \n\n\n\n\n\n\n\n\n\n\n\n \nTable 2. Released and registered improved drought tolerant rice varieties in Nigeria \n\n\n\n \nS/N  \n \n\n\n\nCrop \nName \n\n\n\nVariety \nName \n\n\n\nOriginal \nName \n\n\n\nNational \nCode \n\n\n\nOrigin/ \nSource \n\n\n\nDeveloping \nInstitute \n\n\n\nOutstanding \nCharacteristics/ \nPotential Yields \n\n\n\nYear of \nrelease \n\n\n\nYear of \nregistry \n\n\n\n1 Rice FARO-\n46  \n\n\n\nITA-150  NGOS-\n91-46 \nIITA \n\n\n\nIbadan IITA, \nIbadan \n\n\n\nIITA, Ibadan Higher yields, \nfast maturing, \nblast resistant \nand drought \ntolerant \n\n\n\n1990 1991 \n\n\n\n2 Rice FARO52 WITA 4  NGOS-\n01-52  \n\n\n\nWARDA/IITA WARDA/IITA Higher yields, \ntolerant to \ndrought and iron \ntoxicity \n\n\n\n2001 2001 \n\n\n\n3 Rice FARO54 WAB \n189-B-B-\nB-8- \nHB \n\n\n\nNGOS-\n03-54 \n\n\n\nWARDA, \nBouake \n\n\n\nNCRI, Baadeggi Higher \nyields,fast \nmaturing \ngood weed \ncompetiveness \nand \ndrought tolerant \n\n\n\n2003 2003 \n\n\n\n4 Rice FARO56 NERICA 2 \nWAB \n450-11-1-\nP31-HB \n\n\n\nNGOS-\n03-56 \n\n\n\nWARDA, \nBouake \n\n\n\nWARDA,NCRI,Ba \nDeggi \n\n\n\nEarly maturity, \nhigh \nyielding, \ntolerant to \ndrought, weed \ncompetitiveness, \nmore \ngrain/panicles. \n\n\n\n2005 2005 \n\n\n\n5 Rice FARO57 TOX4004-\n43-1-2-1 \n\n\n\nNGOS-\n05-57 \n\n\n\nWARDA/IITA NCRI,Badeggi \nIbadan \n\n\n\nHigher yields, \nmedium \nmaturing long \nslender \ngrains, resistant \nto blast,drought, \niron toxicity and \nrice yellow \nmottle virus \ndisease. \n\n\n\n2005 2005 \n\n\n\n6 Rice FARO62 NCRO 49 \nFAROX \n501-B-10-\n2-1-2 \n\n\n\nNGOS-\n11-62 \n\n\n\nNCRI, \nBadeggi \n\n\n\nNCRI, Badeggi Higher yields \nand tolerant \nto drought. \n(4t/ha) \n\n\n\n2011 2011 \n\n\n\n7 Rice FARO64 ART15-7-\n16-38-1- \nB-B-2 \n\n\n\nNGOS-\n15-69 \n\n\n\nAfrica Rice \nCentre \n \n\n\n\nAfrica Rice \nCentre \nand NCRI \n\n\n\nFast maturing \nHigher yields \nand drought \ntolerance. \n(5.2t/ha) \n\n\n\n2015 2015 \n\n\n\n8 Rice FARO65 ART16-5-\n9-22-\n3BB-2 \n\n\n\nNGOS-\n15-70 \n\n\n\nAfrica Rice \nCentre \n \n\n\n\nAfrica Rice \nCentre \nand NCRI \n\n\n\nFast maturing, \nhigh yielding and \ndrought \ntolerance. \n(6.4t/ha) \n\n\n\n2015 2015 \n\n\n\n\n\n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 42 of 47 \n\n\n\n\n\n\n\n\n\n\n\n6.1. Application of Marker Breeding for Drought \nResistance of Rice \nThe regions within a genome containing genes \nassociated with a particular quantitative trait are \nknown as quantitative trait loci (QTLs). Hence, a QTL \ncan be a single gene, or it may be a cluster of linked \ngenes that affect the traits. QTL mapping studies have \nreported in most of the crop plants for diverse traits \nlike yield, quality disease and insect pest resistance, \nabiotic stress tolerance and environmental \nadaptation (Collard et al., 2005). When too many QTL \nregions are involved, a combination of phenotypic \nevaluation and marker-assisted selection is effective \nin optimizing recovery of genetic gains over \nphenotypic evaluation or marker selection alone. This \nstrategy is more effective than phenotypic screening \nalone, according to modeling studies (Moreau et al., \n1997), especially when dealing with populated or low-\nheritable characteristics. Once a gene of interest has \nbeen discovered and connected with several of these \nmarkers, Marker-Assisted Selection can be utilized to \nhelp with these selections. For example knowing the \nlocation of genes and appropriate markers is critical \nfor linkage stability and strengths in rice. Therefore, \nfundamental information is necessary, and molecular \nconnectivity mappings can play a significant role. \nSubsequently, tagging that gene, which entails \nestablishing a strong link between target genes and \nmolecular markers, can help speed up the process. By \nso doing breeders indirectly identify the trait of \ninterests. Rice breeders employ marker genes to \npromote qualitative and quantitative qualities against \nabiotic challenges like drought via marker-assisted \nbreeding (Dormatey et al., 2020). This approach is \nused in transferring genes for the following three \npurposes; (i) identifying helpful alleles, either \nrecessive or dominant, to combine favorable alleles; \n(ii) segregation of favorable plants of a breeding line \naccording to the full genome of the allele location; (iii) \nintrogressing favorable alleles by breaking the \nunwanted linkage (Shamsudin et al., 2016). As a \nresult, a MAS application minimizes the cost and time \nrequired to reach the inheritability character's \ndestination. As a consequence, MAS is the most \nreliable, environmentally friendly, quick, and cost-\neffective method for producing the optimum \ndrought-tolerant rice genotypes. Therefore, as a \nresult, breeding against drought using traditional \nways is challenging. To identify genomic areas \nharboring genes that improve drought tolerance, \nmolecular marker approaches are applied (Timko and \nSingh, 2008). Most important genes may be reliably \nintrogressed into highly desirable drought-sensitive \ntypes if they can be marked with molecular markers, \nhence boosting drought tolerance. \nThe availability of high throughput genotyping \ntechnology opens up new possibilities for Marker \nAssisted Breeding to improve complicated traits like \ndrought tolerance (Mofokeng et al., 2019). \n\n\n\nHowever, the most commonly used molecular marker \nin rice breeding is ISSR markers (Inter Sequence \nSimple Repeats). These ISSR markers are been \nadopted in rice breeding on the account that they are \nmore practicable, repeatable, and widely available. \nThey're also very polymorphic, and they're \ninexpensive to utilize because they don't require any \nprior sequence knowledge. ISSR markers have also \nbeen employed to investigate genetic diversity \nstudies and phylogenetic linkages, as well as for gene \ntagging in molecular assisted selection gene mapping \nand DNA finger printing (Dejen, 2019). Because \ncritical QTLs affecting grain output under drought \nconditions recently been identified, MAS could be \nused to improve drought tolerance. The status of QTL \nmapping for secondary traits linked to drought \ntolerance was examined in depth. However, in \ndrought-stressed situations, MAS for such QTLs has \nnot been beneficial in increasing rice yields \n(Venuprasad et al., 2009). For instance, using this \nstrategy, two important QTLs on chromosomes 2 and \n3 for grain production in lowland drought conditions, \nas well as one QTL on chromosome 6 for prospective \nyield and tolerance to aerobic soil conditions, were \nrecently identified, enhancing Swarna's drought \nresistance (Dejen, 2019). Nevertheless, as genes are \nbeen introgressed into rice plant material also, \nintroduction of varieties from other countries can also \nbe adopted to enhance rice drought performance. \nAnother technique to generate novel variety in a brief \nspan of time is to introduce varieties from other \ncountry and test them in multiple areas. (Oluwaseyi \net. al., 2016). Each year, hundreds of drought-tolerant \nrice varieties and lines are evaluated and tested for a \nvariety of agronomic traits, including grain and yield \nqualities, as well as for different production systems \nfor enhanced consumption. This can be achieved \nby close and strong collaboration between research \ninstitutions, rice breeders at universities across the \ncountry, and research institutions in other countries. \nTo boost phenology and grain yields, breeders \nfrequently utilized parents of exotic materials.  \n \n6.2. Proteomics \nPlant responses to drought stress are followed by \nchanges in protein expression (Wang et al., 2016). As \na result, a proteomics method is an additional \neffective tool for identifying and characterizing the \nproteins that are modified in response to stresses and \nits function to drought tolerance (Khan et al., 2020). \nAdditionally, the proteomics approach can be utilized \nto explore rice response to drought stress and its \ncomplexities of biochemical process (Ghosh and Xu, \n2014; Gong et al., 2015). Over the last decade, \ndevelopments in proteomics have allowed us to \nidentify multiple drought-sensitive proteins in rice \n(Kim et al., 2014). Proteomics can help find potential \ncandidate genes for improving rice's drought \nresistance genetically (Rodziewicz et al., 2014; Barkla \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 43 of 47 \n\n\n\n\n\n\n\n\n\n\n\net al., 2016). High-throughput proteomics has been \nshown to be a powerful technique for the complete \nidentification of drought-sensitive proteins in many \ncrops (Mohammadi et.al., 2012). However, in studies \non cowpea drought tolerance, this has been widely \nobserved (Mohammadi et al., 2012). In the next \nyears, however, genetic technology will be the \nprimary technique of producing new features with \nproteomics in particular, which will help to hasten the \ndiscovering of genes that bestow important \ncharacteristics, allowing for quick progress (Njoku and \nAno, 2018). \n \nProteomics and plant breeding applications are \nadvancing at incredible speeds. Hence, combining \ntraditional breeding methods with genomic tools and \nprocedures allows for proteomic plant breeding \n(Njoku and Ano 2018). Proteomics is critical for \ndeveloping more efficient plant varieties in \nthe context of plant breeding, according to the FAO, \nand it is necessary for the new \"green revolution\" \nrequired to feed an increasing population as well as \nconserving natural resources. That can also be \nintegrated into current breeding techniques (Tester \nand Langridge, 2010; Lorenz et al., 2011; Varshney \nand Tuberosa, 2007). Recently, breakthroughs in \nproteomics have led into the development of new \nplant breeding approaches, which have greatly \nenhanced and accelerated the breeding process \n(Peleman and Van der Voort, 2003; Collard and \nMarkill, 2008; Lorenz et al., 2011). \n \n6.3. Mutation breeding \nAssisted mutant breeding is extensively utilized to \ndevelop varieties with higher grain yield (Oladosu et \nal., 2014), seed quality, insect and/or pest control \n(Oladosu et al., 2015). Many variants have been \ngenerated utilizing mutagenic breeding techniques, \nand are widely explored (Oladosu et al., 2016). For \ninstance, the Iranian rice variety 'Tarom Mahalli' was \nsubjected to gamma radiation (230 Gy), and 11 \ndrought tolerant rice varieties was created from the \nMRQ74 generation (Hallajian et al., 2014). Similarly, \nfrom the common rice cultivar \"MR219\" in Malaysia, \ntwo dominant lines with DT characteristics and large \nyields (\"MR219-9\" and \"MR219-4\") were created \n(Rahim et al., 2012). Drought tolerance is required for \nthe growth of this particular variety; therefore it was \nsubjected to gamma radiation. However, the study \nwas successful in establishing an enhanced drought \ntolerant version (Zain et al., 2016). This method is \nused by breeders to introduce new traits to rice \nvarieties. Rice in Nigeria can be used in the same way \nto promote drought tolerance and food security. \n \n6.4. Gene Pyramiding \nMark assisted selection (MAS) is a selection approach \nwhich relies on markers rather than traits. The close \nrelationship between the marker and the main gene \n\n\n\nor QTL responsible for the phenotypes is critical for \nthe successful implementation of MAS. For example, \nin order to develop lines that are more superior with \ngreatest recovery in Basmati rice, bacterial blight \nresistance (xa13 and Xa21 genes), amylose content \nand fertility restorer gene were introgressed into \nbasmati rice (Gopalakrishnan et al., 2008). \nFurthermore, Shamsudin et al., 2016 employed \nmarker assisted breeding (MAB) to pyramid three \ndrought yield QTLs, namely qDTY2.2, qDTY3.1, and \nqDTY12.1, into the high Malaysia quality rice cultivar \nMRQ74 under reproductive with the goal of \nincreasing yield components. Pyramiding is the \ntechnique of introducing multiple gene or QTL that \ncontrols a trait into a single genetic background. The \nmost practical MAS application in pyramiding \nprocedure is connected to the introgression of many \ngenes with similar phenotypic effects. One example, \nand one of the most common uses of the gene \npyramid, is accumulating genes from several \nbackgrounds imparting resistance to the same disease \n(Huang et al., 1997). As a result, scaling these large-\nscale multi-initiatives for prioritized crops as well as \nspecialized crop species, including wild relatives, is \nthe first challenge now and in the future. \n \n6.5. Traditional or Conventional Breeding \nTraditional breeding has made slight success in \nproducing higher-yielding, drought-tolerant rice \nvarieties, owing to difficulties in accurately targeting \nthe environment, complex drought-resistance-\nenvironment interactions, and a lack acceptable \nbreeding genes and an effective screening technique \n(Wade et al., 1999). For many years, traditional \nbreeding has been employed to determine and \nintegrate many genes into cultivars of interest in \norder to create strong biotic and abiotic stress \nresistance (Ragimekula. et al., 2013). Plus, phenotypic \ninvestigation at the individual level in which the \ntarget gene is present can mostly validate this. \nHowever, traditional crop modification methods have \nbeen criticized for being slow, rigid, labor-intensive, \nand costly (Wieczorek, 2003; Choudhary et al., 2008). \nBreeders' capacity to track the presence or absence \nof target genes using traditional breeding methods is \ncumbersome and limited. This reduces the number of \ngenes that can be stacked into exceptional cultivars \n(Malav, 2016). Therefore, it is necessary to design an \nintervention that can reduce the time and expenses \ninvolved in releasing new cultivars with long-term \nresistance. \n \n7. Conclusion \nIn the future, climate change, erratic rainfall patterns, \nand global warming will put an increasing amount of \nstress on agricultural ecosystems. Nonetheless, \nkeeping crop output steady in the face of present \nglobal climate change is a major challenge, thus, one \nmajor abiotic element that reduces crop output is \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 44 of 47 \n\n\n\n\n\n\n\n\n\n\n\ndrought stress. Meanwhile, grains are the most \nimportant food crops for the global population's \nexistence because as humans rely on animals they \nalso on crops. In Nigeria, sustainable strategy for \nensuring food security is to breed novel rice varieties \nwith high grain production and improved resistance \nto a variety of abiotic stresses in rice-growing region \nthat is prone to drought. In light of the growing \ndemand for high-quality rice in the nation, the \npossibilities for improving rice quality and output \nthrough breeding technology are quite encouraging. \nHowever, traditional breeding techniques have been \nquite successful in the development of new varieties \nin the past. Meanwhile utilizing these methods in \nscreening and selecting favorable plant features is \ntime consuming and costly. Hence, Molecular genetic \ninformation can be use to improve breeding tactics \nfor drought tolerance enhancement.  \n \nReferences  \nAbiwon Babatunde Oluwaseyi, Dambaba Nehemmiah \nand Salihu Bolaji Zuluqurineen (2016). Genetic \nImprovement of Rice in Nigeria for Enhanced Yeild \nand Grain Quality - A Review ARJA, 1(3): 1-18, 2016; \nArticle no.ARJA.2867. DOI:10.9734/ARJA/2016/28675 \n \nAfrica Rice Center (2010). New breeding directions at \nAfricaRice: Beyond NERICA. Cotonou, Benin. \n2010b;11. \n \nAjah, J., and Ajah, F.C. (2014). 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"\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n\n\n\n\u00a9 2020 Malaysian Node of the Human Variome Project | ISSN (Online): 2716-649X Page 36 of 44 \n\n\n\n\n\n\n\n\n\n\n\nOFFICIAL JOURNAL \n\n\n\nRESEARCH ARTICLE \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nAnalysis of Recurrent Parent Genome Recovery in MR264 X \nPongsu Seribu 2 using Marker-Assisted Backcrossing \n\n\n\n \nNor\u2019Aishah Hasan1,2*, Mohd Y.Rafii1,4, Harun A.Rah\u0131m3, Nusa\u0131bah Syed Ali5, \n\n\n\nNorida Mazlan6 and Shamsiah Abdullah7 \n\n\n\n\n\n\n\n1 Institute of Tropical Agriculture and Food Security, Universiti Putra Malaysia, Serdang, Selangor, Malaysia \n2 Faculty of Applied Sciences, Universiti Teknologi MARA, Negeri Sembilan, Malaysia \n\n\n\n3Agrotechnology & Bioscience Division, Malaysian Nuclear Agency, Kajang, Selangor, Malaysia \n4Department of Crop Science, Universiti Putra Malaysia, Serdang, Selangor, Malaysia \n\n\n\n5Department of Plant Protection, Universiti Putra Malaysia, Serdang, Selangor, Malaysia \n6Department of Agriculture Technology, Universiti Putra Malaysia, Serdang, Selangor, Malaysia \n\n\n\n7Faculty of Plantation and Agrotechnology, Universiti Teknologi MARA, Shah Alam, Selangor, Malaysia \n\n\n\n \n*Corresponding author\u2019s e-mail: aishahnh@uitm.edu.my  \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nIntroduction \nRice (Oryza sativa L) is staple foods and one of the \nmost significant sources of nutrients in both \nvitamins and minerals, which contributes source \nof energy for the world population (Xiao et al., \n2019). However, Magnaporthe oryzae, fungal \npathogen for rice blast disease caused \ntremendous losses of yield production and plant \ngrowth due to the extensive range of biochemical, \nmolecular and physiological modification of the \nplants (Ashraff et al., 2014). New improved blast \nresistant variety is the most significant method to \nfulfil the increasing feed- \n \n \n \n \n \n\n\n\n \ndemand and challenge to food security. Generally, \nbackcross breeding had been adopted to transfer a \nfavourable gene from a poor agronomy donor \ngenotype into an attractive recipient elite genotype \n(Lewis and Kernodle, 2009). This conventional \nbreeding technique is aimed to modify the existing \nvariety with introgression of valued gene such as \ndisease resistance. Phenotypic selection conducted \nat certain growth stage which require large samples \nand affected by environmental factors makes this \nbreeding technique have multiple barriers. \nNumerous backcrosses required to be performed \nbut generally between six to eight with \napproximately 3 to 4 years of breeding work. \nDespite that, numerous modern genotypes have \nbeen developing which were still used in this \n\n\n\n \nAbstract \n\n\n\nMarker\u2013assisted backcross (MABC) is a commonly breeding technique used for introgression a blast \nresistance gene into a rice cultivar. It is considered as an advanced method to overcome the drawbacks of \nconventional backcross technique and fasten the recovery of recurrent parent genome (RPG). The MABC \ntechnique was implemented to produce improve blast resistant rice variety by introgress a blast resistant \ngene(s) from a traditional variety possess resistant genes (donor), Pongsu Seribu 2 into a local susceptible \nvariety, MR264. The estimation of recurrent parent genome recovery in earlier generation of backcrossing \nwas analysed using simple sequence repeat (SSR) markers. Parental polymorphism analysis with 375 SSR \nmarkers showed that only 70 of them were found to be polymorphic. In BC1F1 and BC2F1 generation, \nbackground analysis revealed 76.1 to 87.9% and 86.5 to 95.2% of recurrent parent genome recovery, \nrespectively. In selected BC2F2 lines, the average proportion of recurrent genome recovery was 94.4% \nwhich showed a phenotypic similarity to MR264. In this study, seven improved lines associated with blast \nresistance genes and maximum genetic backgrounds of MR264 were identified as improved blast resistant \nvariety. Findings in this study proved the efficiency of MABC technique for rapid recovery of a parental \ngenome in a 2-3 generation of backcrossing population. \n\n\n\nKeywords: Blast; Background selection; Marker-assisted backcrossing breeding; SSR marker; Pongsu \nSeribu 2 \n\n\n\n\n\n\n\n*Corresponding author: Dr Nor\u2019Aishah Hasan, Faculty of \nApplied Sciences, Universiti Teknologi MARA, Negeri \nSembilan, Malaysia \nEmail: aishahnh@uitm.edu.my \n\n\n\n\nmailto:aishahnh@uitm.edu.my\n\n\nmailto:aishahnh@uitm.edu.my\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2021, e-ISSN: 2811-3594 \n \n\n\n\nPage 37 of 44 \n\n\n\n\n\n\n\n\n\n\n\npresent day. The advancement technology of \nmolecular marker has revolutionized the varietal \ndevelopment by using genotyping tools for \nselection process (Ahsraff and Foolad, 2014).  \n \nMarker-assisted backcrossing breeding (MABC) is \na breeding approach that applies a selection \ntechnique through the advantage of molecular \nmarker associated with the desirable gene. \nScreening based on genotype could be done in \nearlier generation, thus shorten the breeding \ntime required for development of ideal genotypes \nand reconstitute the original variety as rapidly as \npossible (Septiningsih et al., 2009). It has been \nconsidered as highly powerful breeding technique \nthat require only a short period of time to develop \nnew varieties and reduces the breeding cycle \nlength by two important selection steps; (1) \nforeground selection, including screening of the \ndonor parent at the desirable locus with marker \nallele and (2) background screening in which \nbreeders screening in entire genomic region \nexcluding the target locus for recurrent parent \nmarker alleles (Hospital, 2005). Currently, \nstringent phenotypic selection generally been \ncouple with MABC in each backcrossed \ngeneration ensures screening of plant with \ntargeted alleles with highest RPG (Basavaraj et al., \n2010). The efficiency of MABC influence by \nseveral factors including the availability of \nforeground markers, number of background \nmarkers and size of the backcross population \n(Singh et al., 2013). According to Servin et al. \n(2003), well placed markers (2 to 4 per \nchromosome of 100cM) could provide sufficient \nanalysis of the genome in backcross programs and \nmay contribute to the successful of recovery RPG \nin the backcross generations. The first successful \n \n\n\n\n \nexperiment reported by Chen et al. (2010) who \nsuccessfully introgress bacterial blight resistance \ngene into Chinese hybrid rice. To date, marker \nassisted-backcrossing method has been widely used \nto incorporate resistance genes by using molecular \nmarker for development of new improved variety \nfrom wild type (Chukwu et al., 2019); Sabar et al., \n2019). \n \nMR264 is a local rice variety with high-yielding \npotential (7245 kg/ha), short maturation period \n(113 days) and semi-dwarf plant stature (Hasan et \nal., 2015). However, MR264 had not been released \nto cultivate by farmer due to high susceptibility to \nfungus, M. oryzae. With consideration that MABC is \na powerful breeding method, the purpose for this \nstudy was to convert the MR264 into an improved \nblast resistant variety with MR264 genetic \nbackground through MABC using Malaysian \ntraditional variety, Pongsu Seribu 2. In addition, the \nacceleration of recurrent parent genome was \ncalculated in backcross populations derived from \nMR264 and Pongsu Seribu 2. \n \nMaterials and Methods \n \nPlanting materials and breeding strategy  \nBC1F1 seeds were produce from a backcross method \nbetween MR264 and four F1 plants carrying Pi-\ngene(s). BC1F1 plants were screened with \nforeground selection using tightly linked markers \nfor blast resistance genes. Plants linked with \nresistance genes and maximum background \nrecovery of MR264 were backcrossed with MR264 \nto produce BC2F1 seeds (Figure 1). Foreground, \nbackground and phenotypic screening were \nperformed in all backcrossed generation to select \nelite plants. \n\n\n\n\n\n\n\n\n\n\n\n \nFig (1). Development of improved blast resistant lines using marker-assisted backcrossing scheme\n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2021, e-ISSN: 2811-3594 \n \n\n\n\n\n\n\n\n8 \n\n\n\nPage 38 of 44 \n\n\n\n \nAnalysis of molecular marker  \nGramene website (http://www.gramene.org) and \nprimers which were already identified by Temynkh \net al. (2012), Ashkani et al. (2013) were applied to \nextract the information on the SSR primer linked \nwith blast resistance. F1 and the backcrossed \ngeneration were identified by using twelve markers \nassociated with blast resistance. Polymorphism \nsurveys between MR264 and PS2, recurrent and \ndonor parent, respectively were screened with 375 \nSSR markers across 12-rice chromosome. A \nminimum of four markers per chromosome were \nconsidered to perform background screening to \nrecover the recurrent genome. \n \nDNA Extraction and PCR Amplification  \nTissue Lyser machine (Qiagen, Germany) were used \nto extract the genomic DNA at 30Hz for 4 minutes. \nNano-drop spectrophotometry (ND1000 \nSpectrophotometer) was used to quantify DNA. \nPCR amplification was performed following a \nprogram of  30 cycles of  94\u00b0C for 1 min at \ndenaturation, 1 minute at 55\u00b0C for annealing, 72\u00b0C \nfor 2 min for polymerization, 72\u00b0C for 7 min for final \nelongation and allow to fast cooling at 4\u00b0C prior to \nanalysis. Molecular Imager\u00ae (GelDocTM XR, Bio-\nRad) was used to visualize the PCR product.  \n \nPhenotypic screening  \nThe plant linked with blast resistance gene(s) with \nmaximum phenotypic similarity to MR264 were \nscreened at vegetative and flowering stage. \nPhenotypic screening was conducted in BC1F1, and \nBC2F1 and BC2F2 generation after foreground \nscreening. Data were recorded for agronomic \ntraits. Individuals with the maximum phenotypic \nranking with MR264 were used selected to produce \nbackcrossed seeds. Similar procedure was used to \nscreen an individual plant with blast resistance \ngene. \n \nData Analysis \nMarker data were scored manually based on the \nhigh intensity of microsatellite bands. For \nforeground selection, plants were marked as R if \nthe banding patterns were similar to the resistant \nparents\u2019 alleles; those exhibiting a similar pattern \nto susceptible plants were marked as S. For \nbackground analysis, Graphical Genotyper \nsoftware was used to analyse the proportion of \nmarkers by scoring %A for homozygous recipient \nparents and %B for donor alleles and % H for \nheterozygous plant. Independent t-test was used to \ncompare the mean difference of agro-\nmorphological data between the parent MR264 \nand blast resistant improved using SPSS 16.0 \nsoftware. 2.  \n\n\n\nResults and Discussions \n \nForeground and background polymorphic SSR \nmarkers  \nSeventy-two polymorphic markers distribute \nacross 12 rice chromosomes were identified which \n11 of them were polymorphic markers that \nassociated with blast resistance genes. Targeted \ngene together with recovery of the recurrent \nparent in backcrossed generations, BC1F1 and BC2F1 \n\n\n\nwere analysed using all polymorphic markers. \nPolymorphic markers are essential because it can \ndifferentiate between two parental genotypes \n(Kanyange et al., 2019). Monomorphic markers \nwere discarded in the screening process because it \nis not useful. This present study demonstrated that \nthe ratio of polymorphic markers (19.2%) was in \nagreement with the study of Lau et al. (2015) \nscreened 472 SSR markers and found 79 (16.74%) \nmarkers polymorphic throughout 12-rice \nchromosomes. Present results also aligned with the \nfindings reported by Linh et al. (2012), Huyen et al. \n(2012), Khanh et al. (2013) and Basavaraj et al. \n(2010) with average 18.7%, 12.6%, 15.1% and \n17.74% polymorphic microsatellites in their various \nparental combinations. The ability to find many \npolymorphic markers distributed across 12-rice \nchromosome could give a vast potential to restore \nrecurrent parent segments rapidly by reducing the \nnumber of backcross generation required with the \ntargeted genes.  \n \nForeground and background polymorphic SSR \nmarkers \n \nForeground selection of blast resistance gene  \nBy using a foreground marker, selection can be \nmade at the reproductive stage and seedling stage, \nwhich allow only the best plant to proceed to \nbackcrossing. Two DNA markers were used in this \nstudy; RM206 closely associated with Pi-kh and \nRM5961 tightly linked with Pi-7(t)) positioned at \nthe long arm chromosome 11 on 79.90cM and \n102.90cM respectively (Sharma et al., 2010; Gupta \net al., 2012; Singh et al., 2012; Hari et al., 2013; \nKhan et al., 2018; Xiao et al., 2020).  \nFour best F1 plants that carried the targeted blast \nresistance genes were backcrossed with MR264 to \nproduce 136 BC1F1 plants. Based on two \nforeground markers, RM206 and RM5961 which \nwere associated with Pi-kh and Pi-7(t) blast \nresistance gene, 23 heterozygous plants were \nselected (Figure 2). Another ten foreground \nmarkers exhibited negative results indicating that a \nfew blast resistance genes were deleted in the \nbackcrossing program with MR264. \n\n\n\n \n\n\n\n\nhttp://www.gramene.org/\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2021, e-ISSN: 2811-3594 \n \n\n\n\n\n\n\n\n8 \n\n\n\nPage 39 of 44 \n\n\n\n \nFig (2). Banding pattern in the BC1F1 population using foreground markers; RM206 and RM5961. \n\n\n\n(M=100 bp DNA ladder) \n \n\n\n\nRecovery of recurrent parent genome  \nWith advent of genotyping technology, graphical \ngenotyping can be used to helps breeders to \nvisualize the genotype of individuals and \npopulations (Young and Tanksley, 1989). It will \ndisplay the specific chromosome for parental origin \nand allele composition according to the \narrangement and coded allele in map order across \nthe entire genome. It is considered as an available \nsoftware package which assists in the screening \nprocess and assessment of plant material with the \nillustration of genotyping data (Van Berloo, 2002). \nThe number of markers varied from the lowest \nnumber, 4 (chromosomes 2, 7 and 8) to the highest \nnumber of markers per chromosome, 10 \n(chromosome 6). The percentage of recurrent \ngenome segment restores varied from 76.1% to \n87.9% in BC1F1 generation. The recurrent parent \n\n\n\nsegment recoveries of plants in the BC1F1 \ngeneration are shown in Figure 3. %. This result \nsupported by the finding of (Chukwu et al., 2019; \nCuc et al., 2012) who reported the average \nrecovery of the recurrent parent genome in BC1F1 \nin MR219 x PS1 and Swarna x Samba Mahsuri with \n83% and 85% respectively.  Majority of the residual \nsegments were distributed over chromosome 11 \nwhich indicate the introgression of the donor \nsegment associated with blast resistance genes. All \nthe chromosomes in the BC1F1 improved line \nconsisted of heterozygous segments (Figure 4). \nBackground screening demonstrated that the \nresidual segment of the donor parent resembles on \nthe chromosome no. 11. Six selected the BC1F1 \n\n\n\nplants were selected based on foreground and \nbackground analysis to produce BC2F1 generation. \n\n\n\n\n\n\n\n \nFig (3). Recovery of recipient parent segment in the BC1F1 and BC2F1 population derived from MR264 x Pongsu \n\n\n\nSeribu. \n  \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2021, e-ISSN: 2811-3594 \n \n\n\n\n\n\n\n\n8 \n\n\n\nPage 40 of 44 \n\n\n\n \nFig (4). Distribution of recipient genomes of the six best individual in the BC1F1 generation. \n\n\n\n \nGenotyping the BC2F1 generation  \n\n\n\nForeground screening of blast resistance gene  \n\n\n\nIn BC2F1 generation, 103 plants confirmed the \nincorporation of, Pi-kh and Pi7(t), blast resistant \ngenes with two foreground markers, RM206 and \nRM5961 respectively (Figure 5). Six plants were \n\n\n\nselected to develop the BC2F2 population based on \nthe targeted genes and maximum agro-\nmorphological similarity to MR264. \n\n\n\n\n\n\n\n \nFig (5). Banding pattern in the BC2F1 population using foreground markers; RM206 and RM5961. \n\n\n\n(M=100 bp DNA ladder) \n \n\n\n\nRecovery of recurrent parent genome  \nThirty plants were analysed from the result of \nforeground selection. A greater number of RPG was \nobserved in BC2F1 plants ranged from 86.5% to \n95.2%. The average RPG recovery in the BC1F1 \ngeneration was 81.6%. Feng et al. (2019) found a \nsimilar result by using elite japonica rice variety, \nKongyu-131 with 99.92. A great acceleration of RPG \nrecovery was achieved in two backcrossed \ngenerations compared to the conventional \nmethods. Compared to the conventional backcross, \nresult from this study showed the maximum \npercentage of recurrent genome recovery with \nonly 2 generations. The successful of this study is \ninfluence by the number polymorphic markers \nused (at least 4 markers per chromosome) and \nevenly distributed across 12 rice chromosomes. A \nwell-placed marker (2 to 4 per chromosome of \n100cM) could provide sufficient analysis of the \ngenome in backcross programs and may contribute \nto the successful of selection making (Prigge et al., \n2008). If the number of polymorphic markers is \n\n\n\nmore, marker-assisted selection could be very \neffective. However, with 19.20% of polymorphic \nmarkers between PS2 and MR264 used in this \nstudy, the background recovery was still adequate. \nPresent finding proves that estimation of recurrent \nparent genome in each backcross strongly enhance \nthe reduction of linkage drag which distributed \nacross genome carried by donor parent. \n\n\n\n \nIn this study, the six best plants 3-F-3, 3-F-8, 3-F9, \n3-F-10, 3-F24 and 3-F-28 were chose based on \nforeground, background and phenotypic selection. \nThe entire chromosome segments of the recurrent \nalleles\u2019 recoveries of the best six plants are \npresented in Figure 6. Among the six plants, \nchromosome 2, 8 and 9 were fully recurrent types. \nPlant 3-F (BC1F1) and 3-F-10 (BC2F1) was the best \nplant and the recovery of this plant is shown in \nFigure 7(a)(b). \n\n\n\n \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2021, e-ISSN: 2811-3594 \n \n\n\n\n\n\n\n\n8 \n\n\n\nPage 41 of 44 \n\n\n\n \nFig (6). Six best plants recurrent genome restoration in BC2F1 generation. \n\n\n\n\n\n\n\n \nFig (7a). Highest recurrent segment of plant 3-F in BC1F1 generation. \n\n\n\n\n\n\n\n \nFig (7b). Highest recurrent segment of plant 32-F-10 in the BC2F1 generation. (Red color = homozygous segments, \n\n\n\nMR264, blue color= homozygous segments, Pongsu Seribu 2 and light grey color= heterozygous segment) \n \n \n\n\n\n\n\n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2021, e-ISSN: 2811-3594 \n \n\n\n\n\n\n\n\n8 \n\n\n\nPage 42 of 44 \n\n\n\nForeground selection of blast resistance gene in BC2F2  \nPlants appearing phenotypically similar to the MR264 \nbackground with homozygous resistant alleles were \nselected using RM206 and RM5961 markers. Finally, 7 \nlines were selected as BC2F2 improved blast resistant \nlines among 36 plants. \n \nRecipient parent genome (RPG) in improved lines  \nBackground selection of advanced blast resistant lines \ncovering 1357.6 cM was constructed with an average \n\n\n\nof 18.85 cM region per marker of the O. sativa genome. \nDistribution of the donor segment was observed to be \ndominant on chromosome eleven. Complete recovery \nof the recurrent parent chromosome was observed on \nmost rice chromosome except on chromosome three, \nfour, eleven and twelve (Figure 8). The average \nproportion of the recurrent genome in selected \nimproved lines was 94.4%, indicating the maximum \nsimilarity at phenotypic level with recurrent parent, \nMR264. \n\n\n\n\n\n\n\n \nFig (8). Distribution of recurrent genome of the six-best individual in the BC2F2 generation \n\n\n\n \nPerformance of agro-morphological traits between \nimproved lines and parent, MR264  \nTo certify the presence of a targeted gene and \nreducing genotyping error, phenotypic selection \nmust be coupled with marker-assisted selection \n(Hospital et al., 1992). Agronomic characteristics \nnormally play a part in backcross breeding and have \nbeen used to develop a new variety. Agronomic \ncharacteristics were first introduced by Ye et al. \n(2008); Allard et al. (1999) for selection of superior \nyield plants. Agro-morphological trait between \nimproved lines carrying Pi-kh and Pi7(t) blast \nresistance gene was compared and measured with \nrecurrent parent, MR264 (Table 1). The results in this \nstudy demonstrated significant differences between \n\n\n\nagro-morphological traits. Mean values of blast \nresistant lines introgressed with Pikh and Pi7(t) genes \nfor all agronomic traits excluding 50% flowering days \nwere likely identical with the recurrent parent; in \nwhich MR264 revealed that the capability of \nimproved lines is identical to MR264 for tested traits. \nHowever, the 50% flowering day showed a minor \nvariation between improved lines and MR264. \nFurthermore, it would be tremendous achievement \nto decrease yield losses in blast disease endemic \nregion and increase yield productivity with \ncultivation of improved blast resistant lines \ndeveloped in this study.\n\n\n\n \nTable 1. Agro-morphological trait between improved lines and the recipient parent, MR264 \n\n\n\nTraits MR264 (n=7) BC2F2 lines (n=7) \n\n\n\nDays of 50% flowering (day) 85.71 a \u00b10.95 84.42 b \u00b10.78 \nPlant height (cm) 83.57 a \u00b12.64 83.14 a \u00b10.89 \nDays to maturity (day) 111.57 a \u00b11.51 114.0 a \u00b11.0 \nTotal tiller /hill (no) 23.85 a \u00b11.67 24.85 a \u00b12.11 \nEffective tiller/hill (no) 22.71 a \u00b11.11 23.28 a \u00b1.1.25 \nPanicle length (cm) 24.57 a \u00b10.97 24.42 a \u00b10.53 \nTotal grain/panicle (no) 176.42 a \u00b114.78 185.85 a \u00b114.06 \nNo. of filled grains/panicle (no) 158.85 a \u00b113.03 168.14 a \u00b115.86 \nSeed setting rate (%) 90.04 a \u00b10.5 90.4 a \u00b1 0.34 \n1000 grain weight(gm) 23.35 a \u00b10.80 24.0 a \u00b10.76 \nYield/plant (g) 39.71 a \u00b10.26 39.9 a \u00b10.28 \nGrain length (mm) 9.77 a \u00b10.21 9.57 a \u00b10.53 \nGrain width (mm) 1.92 a \u00b10.075 1.97 a \u00b10.04 \nGrain length/width 5.06 a \u00b10.17 4.86 a \u00b10.35 \nFlag leaf length (cm) 44.21 a \u00b11.14 44.5 a \u00b10.64 \nFlag leaf width (cm) 1.35 a \u00b10.09 1.42 a \u00b10.05 \n\n\n\nMean\u00b1 SE with different letter indicates the significant differences and independent t-test with 5% level of \nsignificance: n=7 \n\n\n\n\n\n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 1: 12 2021 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2021, e-ISSN: 2811-3594 \n \n\n\n\n\n\n\n\n8 \n\n\n\nPage 43 of 44 \n\n\n\nConclusions \nThe improved BC2F1 lines carrying blast resistance \ngenes (putative Pi-kh and Pi7(t)) with maximum \ngenetic background of MR264 were demonstrated \nsimilar agronomic performance than a recurrent  \nparent, MR264. Therefore, the MABC is a powerful \nbreeding technique to restore genetic background \nBreeding technique to restore genetic background \nof recurrent parent in a smaller number of backcross \ngeneration and the improved lines could be used by \nfuture breeders and genetics in developing durable \nresistant variety in Malaysia. \n\n\n\n \nAcknowledgement \nThe authors are thankful to Universiti Teknologi \nMARA, Universiti Putra Malaysia and Agency \nNuclear Malaysia for guidance and assistance. The \nauthor also would like to extend appreciation to the \nMinistry of Higher Education (MOHE) for providing \nfinancial aid for this research. \n \nReferences \n \nAllard, R. 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International Journal Plant \nBreeding, 2:1\u201310(2008). \n\n\n\nYoung, N.D., Tanksley, S.D. \u201cRFLP analysis of the size \nof chromosomal segments retained around the \ntm-2 locus of tomato during backcross breeding\u201d \nTheoretical Application Genetic, 77: 353\u2013\n359(1989). \n\n\n\n\n\n\n\n\n\n\n"
"\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 48 of 58 \n\n\n\n\n\n\n\n\n\n\n\nOFFICIAL JOURNAL \n\n\n\nREVIEW ARTICLE \n\n\n\n\n\n\n\nVanilla Mutation Breeding In Genomic Era: A Review \n \n\n\n\nBasit Akolade Adigun and Rohayu Ma\u2019Arup \n\n\n\n\n\n\n\nCrop Science Program, Faculty of Fisheries and Food Science, \nUniversity of Malaysia Terengganu, 21030 Kuala Nerus, Malaysia \n\n\n\n \n*Correspondence: rohayu_maarup@umt.edu.my \n\n\n\n\n\n\n\n\n\n\n\nIntroduction\nVanilla planifolia, a member of the orchidaceae \nfamily, is grown for its nuts which yields the well-\nknown flavor vanilla used in production of foods, \nbeverages, perfumes and cosmetics. Gallage and \nM\u00f8ller (2018) state that vanilla is mostly referred to \nas the world\u2019s favorite flavor and described it as the \nsecond most valuable spice globally after saffron. \nCountries leading in Vanilla beans production include \nMadagascar, Indonesia, Uganda, India, Comores, \nMexico etc. (Divakaran et al., 2010). According to FAO \n(2009), USA is one of the top consumers of Vanilla \nbeans and they import in large quantities which are \nfurther processed to yield its extract. Despite its \nglobal uses and values, the importance of the plant \ndoes not suit the level at which systematic plant \nbreeding has been used for its improvement \n(Chambers, 2019). However, some \n\n\n\nresearchers have reported breeding in Vanilla spp. \n(Divakaran et al., 2006; Bory et al., 2008a; Menchaca et \nal., 2011; Grisoni and Dijoux, 2017).  \n \nChambers (2019) considered Vanilla to be a cultivated, \nwild species with great potential for rapid improvement \nif modern plant breeding techniques are adopted. The \norigin of breeding is as early as the beginning of \nAgriculture because Man will domesticate the desired \nplant and abandon the undesired ones. Regardless of its \nglobal usage, the genetic diversity is minimal and \ngenomic resources are few in V. planifolia (Rao et al., \n2014) and they attributed the deficiency in genetic \ndiversity of the crop to the reluctance of the use of \nGMO by the flavor industry. As a result, \nbiotechnological approaches have not been used to \nmodify the quantity or quality of the flavor of the vanilla \nbean (Rao et al., 2014). Sreedhar et al. (2007b) showed \nthat vegetative propagation of the crop may likely \naccount for the limitation in variability of the species. \nHowever, Havkin-Frenkel and Dorn 1997 reported seed \ngermination in vanilla and the chance of having the \nseed dispersed by bird may give room for variations in \nthe Vanilla planifolia species. Researchers \n\n\n\n \nAbstract \n\n\n\nBreeding techniques are aimed at improving both the quantitative and qualitative yield of plants. Plant \nbreeding has started since the beginning of Agriculture because people will select efficient cultivars \nover inefficient cultivars. Mutation breeding utilizes chemical and physical mutagenesis to create \nvariations in the genetic component of the crop. The induced variations are aimed at improving the \ncrop. Mutagenesis is the process through which new alleles are created. Vanilla production cannot \nmeet up with its global demand and sufficient production for global demand can be achieved through \nmutation breeding of Vanilla planifolia. This review provides an overview of Vanilla planifolia mutation \nbreeding in Genomic era, its advantages and the genetic markers used in the process. Mutation \nbreeding protocols start with the induction of mutation in the planting materials followed by the \nselection of desirable traits from the first generation, which are then studied for stability of characters \nin subsequent generations. Ethyl methanesulfonate and cholchicine induced mutation in Vanilla \nplanifolia seed likewise; genetic variations through somaclonal variants in Vanilla have been reported. \nMolecular Markers are used to verify various genes responsible for the phenotypic traits of interest \nand therefore help in the selection process. Thus, this review will focus on mutation breeding in \nGenomic era, its mechanism and reported molecular markers in Vanilla spp. \n\n\n\nKeywords: Mutation breeding, Molecular marker, Vanilla planifolia and Mutagens \n\n\n\n \n*Corresponding author: Dr Rohayu Ma\u2019Arup, Faculty of \nFisheries and Food Science, Universiti Malaysia Terengganu \nEmail: rohayu_maarup@umt.edu.my \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 49 of 58 \n\n\n\n\n\n\n\n\n\n\n\nbelieved that the lack of genetic variation in Vanilla \nplanifolia makes it vulnerable to various infections \n(Dignum, (2001); Borry et al. (2008b); Lubinsky et al., \n2008). Insufficient production of Vanilla, the limited \ngenetic diversity in the species and the industrial use \nof V. planifolia called for the need to improve the crop \nthrough breeding strategies like mutation breeding.  \n \nAdvancement in the field of genetics and plant \nbreeding has been progressive over the years. \nBreseghello and Coelho (2013) described breeding of \nedible plants has a development that coevolved with \nman starting from the onset of agriculture to the \napplication of biotechnological tools and molecular \ntechniques for precision breeding. Early humans have \nspontaneously transformed plants from being \nindependent, wild progenitors, to dependent (on \nhumans) and domesticated varieties suitable for \ncultivation (Acquaah, 2012). This has been \naccomplished through discrimination among the \nvarieties leading to the selection of the most desirable \ncrop population. Notably, early plant breeders (Pre-\nMendelian era) efforts didn\u2019t create new variants but \nencouraged the selected population. Contrastingly, \nefforts of modern plant breeders are basically to \nintroduce new variants that previously did not occur \nin the populations naturally (Acquaah, 2012). \nScientists referred to genomic era as a period of \ndiscoveries in genetic study that coincide with the \ninitiation of sequencing the entire human genome in \n1990 (Sarkar, 2007; Cabana et al., 2012). Since the \ncommencement of the Human genome project (HGP) \ncompletion of sequencing for new species genomes \nare announced monthly, as of 2007 sequence of over \n150 species have been reported (Sarkar, 2007). \nGenomic era is indicated with the invention of whole \ngenome sequencing technologies (Cabana et al., \n2012). As of 2017, genomic sequencing of 236 \nangiosperm species have been reported (Chen et al., \n2018). Selection of pure lines and elite crosses in most \ncrops is one of the accomplishments of plant breeders \nin the twentieth century (Rao, 2004). \n \nMutation breeding can go a long way in improving \nVanilla planifolia, ensure demands for the plant are \nmet and introduce considerable number of variations \nin the genome. The use mutation breeding technique \ntowards the improvement of Vanilla planifolia is \nfeasible since early report of conventional \nmutagenesis of Vanilla seeds was recorded \n(Dequaire, 1976) and in vitro generated somaclonal \nvariants in Vanilla have been reported by Ramirez-\nMosqueda and Iglesias-Andreu (2015). This review \nwill focus on mutation breeding in the Genomic era, \nits mechanism and reported molecular markers in \nVanilla spp. \n \nMutation breeding \n\n\n\nMutations are variations in the genetic component of a \ncell. Foster and Shu. (2012) stated that mutations are \nhereditary changes that occur naturally and suddenly, \nwhich are not caused by recombination and \nsegregation. Mutation is the main source of variation in \nliving organisms. Evolutionary diversification is the sum \nof phenotypic diversity of the species for a long period \nof time and is as a result of genetic variation. Mutation \nbreeding can improve numerous qualitative and \nquantitative features of plants and has been \nsuccessfully applied in the improvement of several \nplants (Pandit et al., 2021). Mutations that occur in \nbody cells may not be retained in future generations, \nbut such mutations are of great importance in \nvegetative produced species (Ulukapi and Nasircilar, \n2018). Mutations that lead to the transformation of \nnew individuals or species are considered as essential \nfactors of evolution since they can be passed to future \ngenerations (Mba et al., 2010).  \n \nMutation can either be natural (spontaneous) or \nartificial (induced). Spontaneous mutations occur \nnaturally without any manipulation by man and it \nproduce alternative form of genes for the evolution of \nthe species. Natural mutations are part of the \nevolutionary process. Spontaneous mutations produce \nviable mutants which are recombined with existing \nforms and become incorporated under the mechanism \nof natural selection (Acquaah, 2012). Natural mutants \nformed during evolutionary process are of great impact \nin Speciation (Ulukapi and Nasircilar, 2018). Mba, \n(2013) compiled some domesticated crops and the \nspontaneous mutations they have undergone (Table 1). \nSpontaneous mutations rate in higher plants are very \nlow, researchers state that it may be as low as 10-5\u201310-\n\n\n\n8 per locus (Jiang and Ramachandran 2010; Acquaah, \n2012).  \n \nArtificial or induced mutation involves mutagenic \nagents that are used for mutagenesis in the organism. \nMutagenesis can be used to induce variants of genes \nthat can be recombined into existing cultivars followed \nby hybridization through the mechanism of artificial \nselection. According to Acquaah (2012), modern crop \nproduction systems can provide supplemental care to \nensure mutants that wouldn\u2019t have survived under \nnatural selection to become productive. Mutagenesis is \naimed at increasing the rates of mutation that favors \ndesired traits (Acquaah, 2012). \n \nUlukapi and Nasircilar (2018) state that the term \nMutation was first used at the beginning of the 1900s \nby de Vries. Also, the first mutation breeding work was \nobtained in 1927 in Datura stramonium by radium ray \napplication and this research gave a new perspective of \nplant breeding (Lande, 1995). The knowledge of natural \nmutation has led to the development of many new \nvarieties of plants with induced mutation (Ulukapi \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 50 of 58 \n\n\n\n\n\n\n\n\n\n\n\nand Nasircilar, 2018). H. Muller in the 1920s revealed \nthe mutagenic effects of X-rays on the fruit fly \n(Drosophila) and since his discovery researchers have \nbegun to experiment on the mutagenic effects of X-\nrays on various organisms. Jankowicz-Cieslak et al. \n(2017) explained that scientists have shown that the \nrate of natural mutation could be increased by \ntreating Drosophila and cereals with X-rays in the \nearly decades of the twentieth century. One of the \nmilestones then was the release of commercial \nmutant tobacco in the 1930s. These aforementioned \nachievements all came prior to the research that \nproves the DNA to be the heritable material and this \nunderscored the basic advantage of induced \nmutations for crop breeding i.e. prior knowledge of \ngenes or gene function is not a requirement to \nsuccessfully create new varieties of plant (Jankowicz-\nCieslak et al., 2017). \n \nTable 1.  \nNatural mutations and domestication of some crops.  \n(Mba, 2013) \n \n\n\n\nMutation that promoted \nthe domestication of the \ncrop \n\n\n\nExamples of crops \n\n\n\nNullification of bitterness \nand toxicity \n\n\n\nAlmonds, lima beans, \nwatermelons, \npotatoes, egg-plants, \ncabbages nuts \n\n\n\nPrevention of the need for \nsexual reproduction \n(Seedless or \nPathenocarpy) \n\n\n\nBananas, grapes, \noranges, and \npineapples \n\n\n\nRemoval of natural seed \ndispersal mechanism \n(shattering of pods and \nheads) \n\n\n\nPeas, wheat, barley \n\n\n\nLoss of the hard seed coat \nand other germination \ninhibitors (dormancy) \n\n\n\nWheat, barley, peas \n\n\n\nFacility for self-\ncompatibility \n(hermaphroditism) \n\n\n\nGrapes, papaya, etc. \n\n\n\n \nMutation Breeding in the Genomic Era \nMutation breeding has been adopted globally by \nplant breeders since the awareness in the 1920s that \nirradiation and chemical substances could be used to \ninitiate heritable mutations in plants (Stadler, 1928). \nThe scientists then have a high expectation for this \nmethod on improvements of various crops and in fact \na significant number of varieties was released \n(Lundqvist, 2014). Holme et al. (2019) showed that \nthe gene pool used for modern barley breeding today \ncontained the old mutant genes. Mba, (2013) \nexplained that since the 1980s, there is decline in the \ninterest of plant breeders on the use of mutation \n\n\n\nbreeding and suggested that it may be due to excited \ninterest in the new genetic modification technologies or \nthe difficulties in dealing with the load of unwanted \nmutations in selected lines which impedes \ndevelopment of high-yielding varieties. \n \nAccording to Mccallum et al. (2000) the discovery of \nTargeting Induced Local Lesions in Genomes (TILLING) \ntechniques by the end of 20th century was accompanied \nwith a high improvement about the utilization of \nmutants. TILLING is a technique that is based on reverse \ngenetics and it combines the advantage of classical \nmutagenesis and high-throughput methods of mutation \nidentification (Szarejko et al., 2017). TILLING was \ninitially developed as an alternative to insertional \nmutagenesis for Arabidopsis (McCallum et al. 2000). \nKurowska et al. (2011) reported that TILLING has \nsuccessfully been utilized in crops such as barley, wheat \nand maize.  \n \nMutations that convert the wild type to a mutant form \nare referred to as forward mutations, while those that \nchange a mutant phenotype to the wild phenotype are \nreferred to as reverse mutations. Forward mutations \nare of much occurrence compared to reverse mutations \n(George, 2012). According to Holme et al. (2019) in the \npast, mutation breeding was exclusively based on \nforward mutations and it involves screening mutant \npopulations for desirable traits. TILLING allows reverse \ngenetics approaches possible, since this technique is \naimed at the detection of mutations in specific genes. \nSzarejko et al. (2017) showed that the objective of \nTILLING is to probe regions carrying the variations in the \ngene of interest and through subsequent phenotypic \nanalysis of the mutants and their progeny, roles of the \nanalyzed gene could be determined. \n \nTILLING may also be carried out for genes that have a \nknown role in producing a series of alleles that result in \nvariant of modified traits of interest (Szarejko et al., \n2017). The newly identified alleles can serve as a \nvaluable genetic resource in breeding works (Szarejko \net al., 2017). TILLING has been used for the \nimprovement of several crops, which include: \nimprovement of starch quality in Triticum aestivum and \nTriticum turgidum (Slade and Knauf, 2005), increased \nshelf life in Solanum lycopersicum (Okabe et al. 2011), \nenhanced digestibility in Sorghum bicolor (Xin et al. \n2008) and Avena sativa (Chawade et al. 2010). \n \nAccording to Jankowicz-Cieslak et al. (2017) the use of \nTILLING has accompanied the general development of \nmolecular insight into the genetic base for crop traits \nand development of efficient new generation DNA \nsequencing techniques. In principle, this now makes it \npossible to find mutations in any pre-selected gene \nacross the genome of crop plants, if the DNA sequence \nof the gene is known and if a suitable mutant \npopulation is available (Jankowicz-Cieslaket al., 2017). \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 51 of 58 \n\n\n\n\n\n\n\n\n\n\n\nTILLING population resources are present for cereal \ncrops like barley and wheat (Krasileva et al., 2017; \nSzurman-Zubrzycka et al., 2018). According to Hasan \net al. (2015) conveying mutations into new varieties \nwill be more effective than what is obtainable in the \npast because of the possibility of DNA marker-\nassisted backcrossing. Taheri et al. (2017) state that \ngenome size or ploidy level of species doesn\u2019t serve \nas a barrier in TILLING practice. \n \nOther than TILLING there are various techniques used \nby researchers that can target specific sequences in a \ncomplex genome of plant cell. Site-directed \nmutagenesis is a molecular biology technique used to \ngenerate mutation at specific region in a DNA \nmolecule (Osakabe et al., 2011). These techniques \ncan target defined sites in genomes and precisely \nexert mutations which can be as simple as single \nnucleotide mutation (Fichtner et al., 2014). Site-\ndirected mutations are one of the methods which can \nbe used to create new plant varieties with improved \nalleles and traits, more (Gurushidze et al., 2017). Site \nspecific mutagenesis technique in model and crop \nplant species, customizable endonuclease: \nmeganucleases, zinc-finger nucleases (ZFNs), \ntranscription activator-like effector nucleases \n(TALENs), and RNA-guided endonucleases (RGENs); \nthe latter derive from a clustered regularly \ninterspaced short palindromic repeats/CRISPR \nassociated (CRISPR/Cas) microbial defense system are \nreviewed by Fichtner et al. (2014). Gurushidze et al. \n(2017) suggested that these techniques will go a long \nway in contributing to our general science knowledge \nby helping to further analyze the roles and regulation \nof genes. All these techniques and technologies, if \nused appropriately will increase plant breeding \nefficiency and help bridge the gap between \nproduction and demand of most valuable crops. \n \nMechanism of Mutation Breeding \nBreeding protocols can be divided into four stages; \nIdentification of variation if available but if absent it \ncan be created, induction of variation, selection of \norganisms with desired trait and evaluation of the \nnew breed (Mutant). According to Jankowicz-Cieslak \net al. (2017), mutation breeding can be in three \nstages:  introduction of mutations, screening for \nputative mutant candidates, and mutant evaluation \nfor official release. The last stage is standardized in \nsome countries. Mutagens tend to damage the DNA \nof organisms while causing mutation but with time \nthese damages become part of the organism. \nChatterjee and  Walker,   (2017) state that cells have \nintricate and sophisticated systems that can repair \nDNA, damage tolerance, cell cycle checkpoints and \napoptosis pathways all work together to reduce the \nharmful effect of DNA damage. \n \n\n\n\nMutagenic Agents \nMutagenic agents are substances or particles that are \ncapable of inducing mutagenesis in living organisms. \nMutagenesis is the process whereby gradual \ntransmittable changes occur in the genetic information \nof an organism and are not as a result of segregation or \nrecombination of genes, but induced by chemical, \nphysical or biotic agents (Roychowdhury, 2013). There \nare three types of mutagenesis: Physical mutagenesis in \nwhich mutations are initiated through irradiations like \ngamma rays, X-rays, beta particles, neutrons, protons \nand alpha particles or treatment with chemical \ncompounds, site specific mutagenesis and DNA \ninsertion through activation of transposable elements \nin the genetic material (Kharkwal and Shu, 2009; Forster \nand Shu, 2012).  \n \nIrradiation and treatment with chemical mutagens are \nthe two major methods adopted for creating mutations \nin plants (Leitao, 2011; Mba et al., 2011). According to \nHolmeet al. (2019) X-rays and gamma radiation have \nconsequence of causing deletion of chromosome part \nand point mutations. Gamma ray radiation accounted \nfor about 70% of the world\u2019s successful cultivars \n(Acquaah, 2012) also, Mutant varieties produced with \nionising radiation (gamma rays) are prevalent among \nregistered mutant varieties (MVD 2016). One of the \ndisadvantages of irradiation is that special equipment \nor facilities are required to generate them. \n \nChemical mutagens may have mild effect on plant \nmaterials and they can be applied without sophisticated \nequipment or facilities compared to irradiation. \nAccording to Acquaah, (2012) undesirable mutations \nare associated with chemical mutagens and it has less \nachievement compared to physical mutagens. In \nchemical mutagenesis plant material is soaked in \nmutagen solution for the induction of mutations. Most \nmutagenic compounds are carcinogenic in nature \ntherefore appropriate precautions should be observed \nwhile making use of them. Examples of chemical \nmutagens are natriumazide (NaN3) and \nethylmethanesulfonate (EMS) both cause single base \nsubstitutions in genes. Merits of chemical mutagens \ninclude the ability to produce high density mutant \npopulation and screening of the population for \nmutations is very easy (Szarejkoet al., 2017). \n \nFactors to be considered while making choice of \nmutagen for mutation breeding work are previous \nreports on the species, availability of mutagens, costs \nand infrastructure (Bado et al. 2015; Mba 2013; MVD \n2016). Some commonly used chemical mutagens and \ntheir modes of action have been simplified in Table 1. \nHigh concentration of EMS affects the rate of \ngermination of most plants as a result; EMS is used at a \nvery low concentration (1%) for most seeds. \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 52 of 58 \n\n\n\n\n\n\n\n\n\n\n\nChamber (2019) pointed two limitations of the use of \nEMS as mutagen in Vanilla breeding: germinating \nsufficient number of seeds for treatment and the \nspatial and temporal requirement for first generation \nof seedlings in to obtain enough homozygote and \nmutated allelic population for phenotyping. EMS \ncombined with diligent screening for unique genes \ncould be adopted to promote resource efficiency and \ndevelop accessions with improved traits without \nregulatory barriers in Vanilla (Chamber, 2019). \nSiddique et al. (2020) treated large amount of Dwarf \nCapsicum annum L. treated with 1.3% EMS and they \nreported large amount of mutant phenotype of which \n28.6 % of the population show obvious mutations on \ngrowth parameters like plant height, leaf colour, leaf \nmorphology, flower and fruit development.  \n \nPolyploidy is a condition in which a living organism \npossesses more than 2 sets of chromosomes. Viana et \nal. (2019) state that increasing ploidy level of a plant \nincreases the plant yield and possibly organs tend to \nincrease in size. Colchicine is a pretreatment drug \nused in cytogenetics studies of plants. It has been \nproven to induce polyploidy in plants. About 70% of \nflowering plants have exhibited polyploidy many \ntimes during their evolutionary process (Zhang et al., \n2014). Manzoor et al. (2019) described colchicine to \nbe a significant mutagen and its mechanism of action \nprevents the formation of microtubules and enhances \nchromosome doubling. It is used in the development \nof polyploid plants and it serves as a mitotic poison by \ninducing many mutagenic effects on plants (El-Nashar \nand Ammar, 2015). \n \nTable 2. \nSome commonly used chemical mutagens and their \nmodes of action (Mba, 2013). \n\n\n\nChemical \nmutagenic agent \n\n\n\nMode of action \n\n\n\nBase analogues \ne.g.,  \n5-bromouracil \n(BU), 5-\nbromodeoxyuridin\ne, 2-aminopurine \n(2AP) \n\n\n\nIncorporates into DNA in place \nof the normal bases \nduring DNA replication thereby \ncausing transitions \n(purine to purine or pyrimidine \nto pyrimidine); and \ntautomerization (existing in \ntwo forms between which \nthey interconvert e.g., guanine \ncan exist in keto or enol \nforms). \n\n\n\nNitrous acid Acts through deamination, the \nreplacement of cytosine by \nuracil which can pair with \nadenine and thus from \nsubsequent cycles of \nreplication lead to transitions. \n\n\n\nAlkylating agents \nsuch as: sulfonates \n\n\n\nThey react with bases and add \nmethyl or ethyl groups \n\n\n\ne.g., \nethylmethanesulfo\nnate (EMS), diethyl \nsulfonate (DES); \nSulphur mustards \ne.g., ethyl-2-\nchloroethyl \nsulphide; Nitrogen \nmustards e.g., 2-\nchloroethyl-\ndimethyl amine; \nand Epoxides e.g., \nethylene oxide \nOthers are \nethyleneimine, \nhydroxylamine. \n\n\n\nand, depending on the affected \natom, the alkylated base \nmay then degrade to yield a \nbaseless site, which is \nmutagenic and \nrecombinogenic, or mispair to \nresult in \nmutations upon DNA \nreplication. \n\n\n\nIntercalating \nagents such as \nacridine orange, \nproflavin, ethidium \nbromide \n\n\n\nThey insert between bases of \nDNA thereby causing a \n\u201cstretching\u201d of the DNA duplex \nand the DNA polymerase in \nturn recognizes this stretch as \nan additional base and inserts \nan extra base opposite this \nstretched (intercalated) \nmolecule. This results in \nframeshifts i.e., an alteration of \nthe reading frame since codons \nare groups of three \nnucleotides. \n\n\n\nMiscellaneous \ngroup of agents; \nLarge molecules \nreferred to as \n\u201cbulky\u201d lesions \n(e.g., N-acetoxy-N-\n2-acetyl-\naminofluorine\u2014\nNAAAF). \n\n\n\nThey bind to bases in DNA and \ncause them to be \nnoncoding thereby preventing \ntranscription and DNA \nreplication; They cause intra- \nand inter-strand crosslinks (e.g. \nPsoralens); They also cause \nDNA strand breaks (e.g. \nperoxides). \n\n\n\n \nMutation Breeding in Vanilla \nEarly report of conventional mutagenesis in Vanilla \nseeds was in the 1970s (Dequaire, 1976). Regenerated \nplantlets were moved to the field. However, the status \nof those plants is currently unknown as reported by \nChamber (2019). EMS Mutagenesis reduced Vanilla \nseed germination at concentration of 0.1%, although \nthe seeds do not exhibit dose response (Jose, 2005). \nMolecular analysis of Vanilla planifolia plantlets \nregenerated through indirect organogenesis revealed \n71.66 % genetic polymorphism using inter-simple \nsequence repeats (ISSR) marker and morphological \nvariations were also observed in the form of variegated \nindividuals in the regenerated plantlets (Ramirez-\nMosqueda and Iglesias-Andreu. 2015). Researchers \nhave reported the selection of Vanilla planifolia \ngenotypes resistant to soil fungus Fusarium oxysporum \nf. sp. one of the most destructive pathogens of Vanilla \ncausing stem and root rot \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 53 of 58 \n\n\n\n\n\n\n\n\n\n\n\n(Ram\u00edrez-Mosqueda et al., 2019). The researchers \nreported that a quarter of population of 8week old \nplants displayed resistance to Fusarium when \nexposed to the pathogen (Fusarium mycelial) \nsuspension the research awaits field-based \nevaluations (Ram\u00edrez-Mosqueda et al., 2019). \nChamber, 2019 suggested the need to understand the \ninheritance of the resistance mechanism either \nthrough de novo somaclonal variation or through \nsegregation of recessive allele. \n \nKhosravi et al. (2008) treated Dendrobium with \nColchicine and they detected 6 - 26% variations in the \nregenerants compared to the mother plant. Growth \ninhibiting effect of colchicine at high concentrations \nwas also reported. Possibly if V. planifolia is treated \nwith same quantity of colchicines similar result may \nbe obtained since both Vanilla and Dendrobium \nbelong to Orchidaceae. Colchicine treatment 0.2% \nwas reported to be capable of reducing the survival \nrate of Vanilla seeds by half and 0.4% produced the \nhighest rate of chromosome doubling (Jose, 2005). \nChambers (2019) found that resulting polyploids were \nmorphologically different from their diploid controls \nand showed presence of thicker leaves. \n \nMolecular Markers for Detection of Variation in \nMutants \nMolecular markers give chance for the manipulation \nand devising efficient conventional plant breeding \nthrough selection of the molecular markers linked to \nthe trait of interest and not directly on the trait \n(Babujee and Gnanamanickam, 2000). Nadeem et al. \n(2018) stated that molecular markers are sequences \nof nucleotides that can be studied through the \npolymorphism present among the nucleotide \nsequences of different individuals. Markers can be \nused for identification of genes responsible for \nspecific phenotypic characters and therefore help in \nselection processes of the new breed. Scientists have \nreported the role of molecular markers in the \nimprovement of different qualitative and quantitative \ntraits such as flowering time, photoperiodism, plant \nheight, seed length and weight, aroma, amylose \ncontent, oil content and resistance to infections in \nvarious crops. (Lubberstedt et al., 2005; Kage et al., \n2016; Lema, 2018). \n \nAccording to Chambers (2019) Most of the molecular \nmarker research in Vanilla is mostly for genetic \ndiversity evaluation and not for marker-enhanced \nbreeding. However, Amplified Fragment Length \nPolymorphism (AFLP) markers have been used for \ngenotyping a mapping population of hybrid progeny \nfrom crossing of V. tahitensis and V. pompona \n(Lepers-Andrzejewski et al. 2012). Vos et al. (1995) \nstate that AFLPs are fit to evaluate highly clonal \ngermplasm because they can generate rapid, reliable \n\n\n\nand easily detectable numerous polymorphisms that \nare widely distributed throughout the genome. \nBautista-Aguilar et al. (2021) reported minimum level of \ngenetic variation was detected by ISSR and SSR markers \nin germplasms of Vanilla spp. in In vitro conservation \nconditions. Lubinski et al. (2008) utilized AFLP marker \nfor genetic analysis of Vanilla planifolia and they \ndetected somatic mutations which account for the \nobserved differences among genotypes. Ramos-\nCastella\u00b4 et al. (2016) also attributed some of the \nvariations observed in Vanilla with the use of ISSR \nmarker to be as a result of somatic mutation.  Chambers \n(2019) revealed that the first application of marker-\nassisted breeding in Vanilla breeding programs is the \ndevelopment of species-specific markers to confirm \nhybrid progeny. \n \nBoth the PCR based techniques molecular markers, \nRAPD and ISSR have been employed in evaluating \ngenetic variation in V. planifolia. (Verma et al., 2017) \nRAPD and ISSR require only minute quantity of DNA \nsample without radioactive labels and are simpler as \nwell as faster. Martin et al. (1991) have proved the two \nmarkers to be quite efficient in detecting genetic \nvariations, even in closely related organisms like two \nisogenic lines of tomato. Considering various molecular \nmarkers, the RAPD technique is simple, rapid, and \nrequires only a few nanograms of DNA, has no \nrequirement of prior information of the DNA sequence \nand has feasibility of automation with higher frequency \nof polymorphism, which makes it suitable for routine \napplication for the analysis of genetic diversity (Babu et \nal. 2007). The genetic diversity between V. pompona, V. \nplanifolia and V. tahitensis was studied by Besse, et al. \n(2004) using RAPD, the research revealed V. planifolia \nand V. tahitensis specimens shared 14 markers (of \nwhich 12 are constant) which were not encountered in \nthe V. pompona. \n \nAccording to Aklilu (2021), single nucleotide \npolymorphisms (SNPs) are single nucleotide changes \nthat are also detectable by PCR and millions of them \nexist between inbred strains. SSR and SNP markers have \nbeen applied to detect double-haploid and genotypes \nof isogenic lines and hybrids (Wu et al., 2015). The use \nof more than one molecular marker has also been \nsuggested by some researchers to increase the rate of \ndetection of variations. Joshi et al. 2000 stated that \ndetection of additional polymorphism could be done \nusing RAPD in combination with ISSRs. Martins et al. \n(2004) also suggested the use of a combination of two \ntypes of markers that amplify different regions of the \ngenome will enhance genetic analysis of variations. \nSreedhar et al. (2007a) combined both RAPD and ISSR \nfor the evaluation of high quality clonal \nmicropropagated V. Planifolia, although they reported \nlack of variation among the \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 54 of 58 \n\n\n\n\n\n\n\n\n\n\n\nmicropropagated plants. Sreedhar et al. (2007b) \nshowed the need for further efforts such as seed \ngermination, mutation breeding, genetic engineering \nand induction of somaclonal variants in order to \nbroaden the genetic base of vanilla cultivars. Borry et \nal. (2008b) suggested the use of codominant markers \nsuch as microsatellite markers will help resolve \npossible interspecific hybridization events in Vanilla \ngenus. \n \nConclusion \nVanilla planifolia is grown for its fruit, which yields the \nvanilla flavor used in foods, beverages, perfumes and \ncosmetics. Despite the global use of the plant, its \nproduction is insufficient, and the plant is well known \nfor its lack of variation in the genome. Scientists \nbelieve that the reason for the aforementioned \nchallenges is because the plant is mostly propagated \nthrough vegetative methods. This review discussed \nVanilla mutation breeding in Genomic era: Very low \nconcentrations of EMS and Colchicine have been used \nto induce mutation in Vanilla spp and several \nmolecular markers have been used to detect the \nvariations in the mutants. AFLP markers were utilized \nfor the detection of variations in hybrid progenies of \nthe cross between V. x tahitensis and V. pompona. \nLikewise, ISSR, RAPD and SSR markers have been used \nto detect variations in Vanilla spp. One of the \ntechniques discovered recently is TILLING, which has \na lot of potential of being a useful tool in Vanilla \nmutation breeding. \n \nAcknowledgments \nWe acknowledge the Universiti Malaysia Terengganu \nfor providing funding support for this project \n(UMT/TAPE-RG/2020/55278). \n \nReferences \nAcquaah, G.  (2012). Principles of Plant Genetics and \nBreeding. Second Edition. John Wiley & Sons, Ltd. 740 \npp. \n \nAklilu, E. (2021). Review on Forward and Reverse \nGenetics in Plant Breeding. 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BMC Plant Biol., 8, 1\u201314 \n \nZhang, C., Cao, D., Kang, L., Duan, J., Ma, X., Yan, G., & \nWang, Y. (2014). Ploidy Variation and Karyotype \nAnalysis in Hemerocallis spp. (Xanthorrhoeaceae) and \nImplications on Daylily Breeding. N. Z. J. Crop. Hortic. \nSci., 42, 183\u2013193. \n \n\n\n\n\nhttps://www.ncbi.nlm.nih.gov/pubmed/?term=Chen%20Z%5BAuthor%5D&cauthor=true&cauthor_uid=26511913\n\n\nhttps://www.ncbi.nlm.nih.gov/pubmed/?term=Wang%20L%5BAuthor%5D&cauthor=true&cauthor_uid=26511913\n\n\nhttps://www.ncbi.nlm.nih.gov/pubmed/?term=Liu%20X%5BAuthor%5D&cauthor=true&cauthor_uid=26511913\n\n\nhttps://www.ncbi.nlm.nih.gov/pubmed/?term=Lu%20Y%5BAuthor%5D&cauthor=true&cauthor_uid=26511913\n\n\n\n\n \n*Correspondence: rohayu_maarup@umt.edu.my\n\n\n\n"
"\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 59 of 74 \n\n\n\n\n\n\n\n\n\n\n\nOFFICIAL JOURNAL \n\n\n\nREVIEW ARTICLE \n\n\n\n\n\n\n\nBambara Groundnut (Vigna Subterranea L. Verdc): A Model \nUnderutilized Legume, its Resiliency to Drought and Excellency of \n\n\n\nFood & Nutrient values -A Review \n \n\n\n\nMd Mahmudul Hasan Khan1, 3*, Mohd Y. Rafii1, 2*, Shairul Izan Ramlee2, \nMashitah Jusoh2 and Md Al-Mamun1 \n\n\n\n\n\n\n\n1Laboratory of Climate-Smart Food Crop Production, Institute of Tropical Agriculture and Food \nSecurity (ITAFoS), Universiti Putra Malaysia (UPM), 43400, UPM Serdang, Selangor, Malaysia. \n\n\n\n2Department of Crop Science, Faculty of Agriculture, Universiti Putra Malaysia (UPM), 43400, UPM \nSerdang, Selangor, Malaysia \n\n\n\n3Bangladesh Agricultural Research Institute (BARI), Gazipur-1701, Bangladesh. \n \n\n\n\n*Correspondence: mrafii@upm.edu.my \n \n\n\n\n\n\n\n\n1.0 Introduction \nThe Bambara groundnut (Vigna subterranea [L.] \nVerdc.; 2x = 2n = 22) is an underutilized or neglected \nlegume belongs to the kingdom of Plantae, family of \nFabaceae and sub-family of Faboidea, which grown at \nthe low level of agricultural inputs broadly in all over \nAfrica (Azam-Ali et al. 2001; Ntundu et al. 2006; \n\n\n\nOkonkwo and Opera 2010;). Bambara ground is widely \ngrown tropical and humid regions,  recently available in \nmany regions of south America, Southeast Asia \n(Indonesia, Thailand, and Malaysia) and Oceania \n(Baudoin and Mergeai, 2001). Sprent et al. (2010) \nstated that it can fix atmospheric nitrogen to accelerate \nsoil productivity as well as on the agronomic and \nnutritional aspect it becomes a \u201ccomplete food\u201d like \nlucrative cereal species (Halimi et al. 2019). Halimi et al. \n(2019) noted that, presence of geocarpic nature, it is \nnear relative to Vigna unguiculate  (Cowpea), \nphysiologically adaptable to \n\n\n\n \nAbstract \n\n\n\nIn this review, we explore the potency of Bambara groundnut to boost the nutritional sanctuary, its \ndiversity, production, utilization, resiliency with climate changes, socio-economic potential, and its \ngenetic upgrading efforts. The climate change challenges couple with the global agricultural policies \ncurrently emphasizes only a precise crop species, which direct the threat to food security and supply. \nBambara groundnut has the significance to contribute to food and nutritional security in the current \nclimate change situation. It requires particularly low agricultural inputs and can fix atmospheric \nnitrogen, tolerant to biotic and abiotic stress. Bambara groundnut is a storehouse of dynamic nutrients, \nwhich offer carbohydrates, especially essential amino acid, protein, fatty acid, calories, fiber, minerals, \nand vitamins for growth and developed undernourishment people of lower economic nations where \nanimal proteins are very precious. The milk of Bambara seeds can apply to infant feeding as a \nsupplement of mother\u2019s milk due to it high nutrient profiles. To improve a high resilient and \nnutritionally rich upcoming agriculture, underutilized Bambara groundnut can play a vital role as a \ndrought-tolerant, nitrogen-fixing, low risk to disease-insect infestation, and fit to grow in poor soil. \nHowever, like other underutilized crops, there is a substantial lack of information on modern \nproduction technologies also undesirable traits like they need a long time to cook and daylength \nsensitivity  to  pod  formation  which  need  to  improve via improving breeding  approaches and \nprocessing procedures to the welfare of the future increasing population. This review also evaluates \nthese features and reflects what are the succeeding ways of fixing the potentiality of Vigna \nsubterranean L.. Verdc.  \n\n\n\nKeywords: Bambara groundnut, Underutilized legume, Resiliency, Drought, Food & Nutritional, HCT & HTM \nphenomena \n\n\n\nReceived: 01 04 2022; Accepted revised manuscript:  01 12 2022; \nPublished online: 01 04 2023 \n*Corresponding author: Prof Dr Mohd Rafii Yusop, Institute \nof Tropical Agriculture and Food Security \nUniversiti Putra Malaysia \nEmail: mrafii@upm.edu.my \n \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 60 of 74 \n\n\n\n\n\n\n\n\n\n\n\nthe position of Arachis hypogaea (Groundnut), even \nthough physically its grains are like Cicer arietinum \n(Chickpea). Like other major legumes (e.g. Soybean, \nGroundnut) extensive scientific research and financial \nassistance must be implemented to enhance this crop \nimprovement, though till date, Bambara groundnut \nhas taken into less attention from global research \ncommunities and has provided inadequate financial \nsupport through governmental and non- \ngovernmental authorities to its betterment (Oyeyinka \net al. 2015). Due to the presence of a considerable \namount of oil in peanut it can be grown as an oilseed \ncrop and may have replaced theBambara groundnut \nthough, peanut was introduced in West Africa from \nSouth American country Brazil (Karunaratne et al. \n2015). So social awareness must increases with the \ndiet and nutrient potentialities of Bambara \ngroundnut. This crop treats as completely balanced \nfood, and easy to cultivate in poor soil (Oyeyinka et al. \n2015). In the case of low-income countries, animal \nproteins are not readily available; hence, there is an \nextreme requirement to acquire protein from agri-\nbased food sources. Mazahib et al. (2013) referred \nthat bambara ground as \u201ccomplete food\u201d because it \ncontains carbohydrates (63%-65%), protein (18%-\n19%), and fat (6.5%). In terms of essential amino acids \nsuch as valine, threonine, phenylalanine, methionine, \nlysine, and isoleucine content Bambara seeds are \nhigher than Groundnut (Bamshaiye et al. 2011). Due \nto high nutrient profile and a versatile adaptation to \nextreme environmental conditions, Bambara \ngroundnut provides income for marginal growers and \nassists as a primary diet for most low-income \nconsumers to remedy malnutrition. Globally, the \ntrend of population growth increases, a recent \nestimation of 80 million, which is projected to reach \n9.2. billions by 2050 (Kakol 2011). To minimize the \nnutritional gap, solve frequent nutritive challenges \nwith assurance of food safety, underutilize Bambara \ngroundnut can assist as a manner to addressing the \ncurrent challenges also reducing the dependency of \nstaple food crops (such as wheat, corn and rice) \nconsumption in the lower-income countries (Feldman \net al. 2019). However, the best production \ntechnologies and seed processing scheme has not yet \nbeen well recognized and published globally \n(Feldman et al. 2019). Adzawla et al. (2016) and \nOlayide et al. (2018) mentioned that landraces of \nBambara groundnut have still been cultivated by local \nfarmers, one of the main reasons that it exhibits \ndrought resistance with acceptable yield. Global \nclimate change and irregular precipitation pattern in \nseveral regions of the world have created a demand \nfor agriculture and crop rearrangements based on \ntheir resiliency properties (Mayes et al. 2012). Like \nother underutilized crops, the Bambara groundnut \ncan be an important phase of a highly resilient and \nmultifaceted system that delivers supplementary \n\n\n\nfood and nutritional safety. Consequently, the current \nstudy sketches the standards and significant use of \nBambara groundnut, its progress  of current scientific \nstudies and their assessment of both beneficial and \nnon-beneficial attributes with the summarization of \nfuture improvement (breeding) requirements and \nprospects.  \n \n2.0 Domestication and center of Bambara groundnut \ndiversity \nAfrica is the geographic birthplace of Bambara \ngroundnut has been broadly described by (Basu et al. \n2007). According to Vavilov's (1926) idea, the basic \nprinciples of crop domestication are the center of \ndomestication is strongly connected to the place where \nseveral families involving ancestral siblings are found. \nFrom the breeding scene, the midpoint of diversity is \nhigher economically significant than the center of \ndomestication. It has been suggested by (Aliyu et al. \n2016) the past-alleged grounds of Bambara groundnut \nare the region of Sudan. The wild landraces of Bambara \ngroundnut are declared to confine the nearby state of \nNigeria (Yola and Plateau), in Cameroon (Garoua state) \nregion has been allowed as center of domestication of \nBambara groundnut (Basu et al. 2007). A research \nfinding stated that Burkina Faso accessions showed the \nmaximum genetic diversity than Cameroon/Nigeria \naccessions also stated that no wild species of Bambara \ngroundnut was detected anyplace in Burkina Faso \n(Somta et al. 2011). However, the most reliable center \nof Bambara groundnut\u2019s domestication is the nearby \narea of Burkina Faso (Albert et al. 2006). Commonly, the \nlandraces of east Africa are the outgrowth of west \nAfrican landraces was announced by Olukolu et al. \n(2012) and Somta et al. (2011). Another report revealed \nthat the core place of Bambara groundnut \ndomestication was west Africa (Rungnoi et al. 2010). A \nnoticed available from Somta et al. (2011) and \nMolosiwa (2012) that west African genotypes have \nextreme genetic diversity than another region. Azman \n(2016) stated that Vigna subterranea [L.] is known as \ndrought resistant African pulses and its secondary \ncenter of cultivation observed in southeast Asia, mainly \nin south Thailand, West Java and parts of Malaysia, \nwhere this crop is known as \u2018Kacang Poi\u2019 and vastly \ncultivated in Kedah state in the northern part of \nPeninsular Malaysia. \n \n3.0 Socio-economic values of underutilized Bambara \ngroundnut \nBambara groundnut has been graded as the 3rd most \nimperative grain legume afterward groundnut (Arachis \nhypogaea L.) and cowpea (Vigna unguiculata) (Howell \net al., 1994). Bambara groundnut has a significant role \nin nutrient and food safety, income-generating sources \nto resourceless farmers, and consumers in developing \ncountries. GFS (2012) defines food security as refers to \nthe area in which people always have economic, social, \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 61 of 74 \n\n\n\n\n\n\n\n\n\n\n\nand physical entree to adequate food, which \nmitigates the daily dietetic and nutritional demands \nfor a healthy and dynamic life. Bambara groundnut is \nbelonging to pulse legume has been graded as \nunderutilized crop species grown in tropical and \ndeveloping countries. It can assure food and nutrient \nsafety for local areas also globally (Halimi et al. 2019). \nThis crop is commonly grown in a short-range by \nmarginal rural farmers and low earning peoples \n(Feldman et al. 2019). Bambara groundnut \nbotanically matches with peanut (Arachhis hypogaea \nL.) , which migrate from South America (Karunaratne \net al. 2015) and occupied the major cultivated area \nreplacing the Bambara nut also its closest relative \nCowpea (Vigna unguiculata L.). Bambara cultivation is \nstrongly adjusted to low input agricultural elements \non badly drained soils and limited environmental \nresources. Traditionally, this crop gives assurance to \nthe farmers and consumers providing households \nnutrition and food security (Olayide et al. 2018; \nMayes et al. 2019). Due to the scarcity and shortage \nof enough protein accumulation in the least income-\nearning communities who cannot bear expensive \nprotein sources such as animals (Yao et al. 2015), the \nBambara groundnut can be a vital source to meetup \nthis protein demand. Tilman et al. 2011 stated that \nthe global food crisis is increasing swiftly with about \n100% \u2013110% simultaneously increasing crop \ndemands from 2005 to 2050. Usually, there is a huge \ngap within accumulation in population and crop \nproduction. This neglected crop can survive under \ntremendous soil and environmental limitations \nprevailing in the emerging world especially in Africa \nand Asia. Almost all the African underutilized crops \nparticularly Bambara groundnut are notably dryness \ntolerant while some of them resist water stagnant for \na long duration than the main crops of the world. The \ntotal global production of the Bambara groundnut is \nunremarkable due to the use of ordinary plant \nmaterials and weak agronomic practices. \nUnderutilized groundnut is also fit to the agro-ecology \nand socio-economic circumstances in the African and \nAsian continent (McCann 2005). \n \n4.0 Bambara groundnut: features associated with \nfood and nutrient security \nFor marginal farmers, the Bambara groundnut is an \nideal crop due to it becoming high yielding \npotentialities using low input of management \npractices with poor soil (Begemann et al. 2002) and \nninety-eight percent growers in Swaziland considered \nBambara groundnut as lucrative crops. This crop has \nthe efficiency to promote nourishment, boost food \nassurance, foster pastoral improvement, and support \nsustainable land uses. For healthy living, food security \nmay be obtained when the whole human community \nallows social, physical and economical entrance to \nenough, healthful and nutritious food uptake that can \n\n\n\ntake care of their dietary demands and nutritional \npreferences (Massawe et al. 2016; Mustafa et al. 2019). \nTypically, two features associated with food security \nconditions that are availability and stability. Food \navailability involves the permanence of an adequate \nquantity of food with the proper number of quint \nessential components afforded through indigenous \nintroduction or production. Food stability is a policy \nthat supplies enough food throughout the year \nconstantly for households and unique populations. \nFood availability is related to getting entrance to \nenough resources by individuals or groups of individuals \nto meet up with their daily necessities (Mustafa et al. \n2019). Although Bambara groundnut considered as \nneglected underutilized crop, it has the capacity to \naddress the challenges of climate change and world \nfood security (Olayide et al. 2018). This underutilized \ncrop contributes an important function in the field of \nfood safety and the welfare of low earnings producers \nand customers in the progressing countries (Mabhaudhi \net al. 2019). Most of the underutilized crops are \nresilient to severe climatic conditions and have \npossibilities to reduced greenhouse gases and better \nadaptability to poor soil management (Mabhaudhi et al. \n2018). This crop can fix atmospheric nitrogen (28.42-kg \nN ha-1) estimated by Yakubu et al. (2010), the synthesis \nnitrogen, not for its current use, but its leaves can \ndeposit nitrogen for the next crop when incorporated \nwith soil after the harvest. Bambara groundnut typically \na bean though it is known as groundnut, features such \nas dryness tolerance, low input requirement, N2-fixing, \nsoil physio- chemical properties storage ability, and day \nlength control make this crop unique for food and \nnutritional security. For low income earning users, \nunderutilized crops serve as nutrients and better diets \n(Hunter et al. 2019). Considering their various food \nreimbursements and tolerance to severe climatic \nstresses, underutilized Bambara groundnut are \nconsidered as the future-crop or new- millennium crop. \n \n5.0 Market, Food and Nutritional values of Bambara \ngroundnut \nThere is a high potentiality of Bambara groundnut to \npromote nutrient deficiency and heighten food \navailability. The seed offers an entire food, due to the \npresence of an ample amount of protein, carbohydrate, \nand fats. Different researchers discovered the bio-\nchemical constitution of Bambara seeds. The available \nvalues of nutritional composition from the Bambara \ngroundnut are high. The research findings of \nOuedraogo et al. (2008) noted that due to the higher \ncontent of carbohydrates (65%-70%) and protein (18%-\n27%), this legume is predominantly cultivated for \nhuman food as fully balanced diet. Based on the \nfindings of Mazahib et al. (2013) Bambara seeds assume \nas complete diet thus it contains carbohydrates (63 to \n65%), protein (18%-19%) and fat \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 62 of 74 \n\n\n\n\n\n\n\n\n\n\n\n(6.5%) on the other hand according to Oyeyinka et al. \n(2018) it contains 61%-69% carbohydrate, 17%-27% \nprotein, 3.3%- 6.4% fiber, 3.1%-4.4% ash, 3.6%-7.4% \nfat, while Halimi et al. (2019) reputed that its seeds \npossesses protein (18%-24%) with high lysine and \nmethionine, CHO (51%-70%), crude oil (4%-12%), ash \n(3%-5%) and fiber (93%-12%) and considered as \ncompletely balanced diet. A research by KariKari et al. \n(1997) revealed that per 100g of bambara seeds \ncomprised calcium (95.5\u201399.0mg), iron (5.1\u2013 9.0mg), \npotassium (11.45 - 14.36mg) and sodium (2.9 - \n10.6mg). Another report by Amarteifio et al. (2006) \nstated that per 100g dry weight seeds are rich in iron \n4.9-48mg compared to a scale of 2.0\u2013 10.0mg in other \nlegumes, potassium 11.44\u201319.35mg, sodium 2.9\u2013\n12.0mg and calcium 95.8-99mg. However, like other \nlegume beans, the Bambara groundnut is lacking in \nsulfur-containing proteins which can be overcome to \nimprove as a full diet by incorporating rice or corn \nflour. From the study of Ndidi et al. (2014) and \nMazahib et al. (2013), it was observed that the micro-\nnutrient combination was found to be calcium (95.5\u2013\n99.0mg), potassium (5.1\u20139.0mg) and sodium (2.9\u2013\n10.6mg) as well as ample quantity of zinc (20.98 \u00b1 \n1.07mg) in each 100g dry seeds. According to USDA \ndaily recommended value of minerals for an adult is \nabove the 15 mg/100g/person, which enhances the \nstrength of existing prostate health positively in \nmales. Bambara groundnut contains about 7% fat, \nwhich can be used in the formulation of a low-fat diet \nthat can be announced as a better plant source of \nfats. The gross energy contained in Bambara \ngroundnut is more than the other legumes (Feldman \net al. 2019) and estimated energy value is about 367\u2013\n414 kal/100mg recorded by Boateng et al. (2013). Due \nto huge protein content, it gives support in mitigating \nnutritional dysfunction both in human beings and \nanimals (Massawe et al. 2002) and as an entire diet, \nthe nutritional value of the Bambara groundnut \nrepresents the ability to meet the eligibility of both \nrequirements. Masindeni (2006) reported that \nBambara groundnut can be used as regular foods, \nhydrated seeds can be milled and incorporated with \ntraditional samp or use to prepare soup in South \nAfrica and Swaziland. Conventionally, it also has \nmedicinal value counter to nausea particularly during \nwomen pregnancy by chewing and swallowing fresh \nbeans and green leaves can be used as fodder by \nmixing with other grass or direct feeding to livestock. \nResearch from Bamshaiye et al. (2011) and Mazahib \net al. (2013) reported that Bambara groundnut seeds \nare rich in essential amino acids (80%) which are more \nthan cowpea (64%), soybeans (74%) and groundnut \n(65%) in terms of arginine, leucine, valine, \nmethionine, and lysine. A reasonable portion of \nminerals and vitamins such as zinc, iron, thiamin, \nriboflavin, niacin, vitamin AB and carotene but poor \nascorbic acid (Mubaiwa et al. 2017; Mubaiwa et al. \n\n\n\n2018) and a greater amount of fatty acids such as \nlinoleic acid, oleic acid, and palmitic acid has been \nreported. There was no difference in the nutrient \ncomposition in the case of seed, seed coat, and flour so, \npeople can receive nutrients when eating any of them \nhowever Ojimelukwe and Ayernor (1992) mentioned \nthat red seed contains more iron compared to the \ncream colored seeds. Composite flour is prepared using \nBambara nut and mixed into noodles preparation thus \nproteinization of diets can simply be made by Bambara \nnut flour fortification (Effa et al. 2016). Like steamed \npeanut, fresh young Bambara seeds can be steamed \nand eaten moreover, steamed paste is made into \npudding named Moi-Moi or Okpa (Okpuzor et al. 2010) \nin Nigeria. The protein percentage of Ojojo prepared \nfrom water Yam (Dioscorea alata) can be increased by \nthe addition of Bambara flour. Adu-Dapaah et al. (2016) \nnoted that milk made from Bambara groundnut is rich \nin protein (15%-16%) than milk made of soybean (4%) \nand the color and flavor of Bambara milk have \npreferences over other legumes. The young Bambara \ngroundnut seeds are deeply roasted (snacks) and found \nin supermarkets of Indonesia and Malaysia called \n\"Kacang Bogor\" or \"Bogor nut\" with high prices. \nRecently, the center for future crops (http://www. \nCrops for the future.org) and Feldman et al. 2019) \ndevised versatile recipes using the Bambara groundnut. \nBambara groundnut has the efficacy to afford a staple \nfood for people where animal protein is infrequent \nand/or high price also has the potentiality to grow \nwhere the cultivation of other legumes is unsafe due to \nminimum precipitation. \n \n6.0 Bambara groundnut production and factors impact \non production \nBerchie et al. (2013) revealed that the Bambara \ngroundnut can be cultivated in two seasons per year, \nwhere rainfall occurs in the bimodal pattern and \nduration of sowing effects on the yield of this crop. The \nyield of Bambara groundnut recorded higher (up to 4 t \nha\u22121) in low rainy and temperate season than the heavy \nrainy season, additionally the pod yield was affected by \nthe time of sowing (Berchie et al. 2013). The typical \nBambara groundnut growers cultivate it as for food or \nsale for money or both, a survey conducted by the \nBerchie et al. (2010), including 200 Bambara groundnut \ngrowers, 33 salespersons, 68 users in Ghana, it was \ndiscovered that 63% women involve cultivating the \ncrop, while men are 37%; 78% growers cultivate for \nfood, whereas 73% grower cultivate the crop for cash \nand 63%-83% growers use family lands for cultivating \nthe crop. The mean production per grower varied from \n0.6 to 1.0 t ha\u22121 under the cultivated land of average \n1.1 acres, and production trends of Bambara groundnut \nhave not gone up due to factors such as unpredicted \nrainfall pattern, labor and funds shortage, unavailable \nof viable seeds and lack of improving cultivation \npractices (Berchie et al. 2010). A \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 63 of 74 \n\n\n\n\n\n\n\n\n\n\n\ntwo year (2013\u201314) research on Bambara nut by Effa \net al. (2016) recorded that in the first year highest \nunited seed yield is 1.68 tons per hectare from \n111,111plants per hectare, while in the second year \nyield drastically falls due to viral leaf curl diseases. The \nhighest yield (1.95 t ha-1) was estimated by Shiyam et \nal. (2016) incorporating organic fertilizers with the \nusage of 2.5 ton/ha in Calabar. Yields of Bambara nut \nrecorded 432.5 kgha-1 by Toungos et al. (2009) with \nthe usage of 60 kgha-1 P2O5 in yola whereas, in \nIgbariam, southeast Nigeria maximum yield (1.65 t \nha-1) was observed using 110 kgha-1 of P2O5 (Nweke \nand Emeh, 2013). Collinson et al. (2000) noted that \nthe total yield of Bambara groundnut diminished \nfrom 3 t ha-1 to zero in Tanzania due to the delay of \nsowing by 60 days. Khan et al. (2020) recorded \nmaximum average yield of 1635.29 kgha-1 while the \nminimum was 380 kgha-1 when evaluated 150 \ngenotypes in tropical Malaysia. Plant density and \ngrowth habits influence the total yield of Bambara \nnut, supported by Kouassi and Zero (2010), they \nrecorded the highest yield with maximum plant \ndensity (250 thousand/ha) in plain land using semi- \nbunch types in C\u00f4te d'Ivoire. Abejide et al. (2018) \nreported that high nitrogen in soils causes more \nvegetative growth, especially in leaves by producing a \npoor pod and seed set, thus it means the crop gives \nbetter yield in poor resource soil, which is supportive \nto marginal farmers. When the Bambara groundnut is \ngrown in a controlled environment, it gives better \nyield, while the peanut failed to produce more pods if \nit has grown under proper management, thus it is the \nevidence of potentialities of Bambara groundnut. \nOgwu et al. (2018) reported that this crop has a credit \nto tolerating insect- pest and diseases, which majorly \naffects the growth and yield. A parasitic weed Striga \nspecies was seen in sandy soil a be suppressed by \nBambara groundnut (Olayide et al. 2018). Due to \nvarious maturity time about three to six months are a \nnotable characteristic of Bambara groundnut \n(Feldman et al. 2019) which provides chances to \nharvest all year round with reducing yield losses. \nEnough storage life of this crop gives food \nsupplements (Islam et al. 2016) during the whole year \nhelping mitigate the nutrient gap between one \nharvest season to another. \n \n7.0 Research trends on underutilized Bambara \ngroundnut improvement \nThe word \u2018Underutilized\u2019 leads to the neglect of a \nspecies by domestic and worldwide research and \nscientific societies. Underutilized species are \ncommonly classified as crops with little significance at \na wider range. Bambara groundnut research has been \nstarted since 1971 when a group of agronomic \nexperiments was carried in the western and southern \nstates in Africa. An extremely high coefficient of \nvariation in terms of yield within varieties was \n\n\n\nobserved. From 1972 to 1975, most of the research was \non fertilizer use, ridging, and spacing of yield \nimprovement of Bambara. To get a high yield potential \nwith resistance to disease and insect-pest germplasm \nwas collected and evaluated for selection of most \npromising ones. The research projects initiated involve \nlandraces preservation, seed multiplication, \ncharacterization, and evaluation. In the 1989\u201390 \nbreeding plan, which was launched with the first single-\nplant selection simultaneously, duplication and multi-\nlocation adaptive trials have also been carried. Bambara \ngroundnut improvement programs were conducted \nusing pureline selection methods isolating the plants \nwith maximum pod and seed numbers in Botswana \n1993 and 1995. A large variation among the accessions \nin Botswana was recorded for traits such as seed size, \npod number, 100 seed weight, and total seed yield. \nThrough the optimum use of water and maintaining the \nday length at 12hr the yield of Bambara groundnut was \nrecorded equivalent to 3000 kgha\u22121. Research findings \nusing six genotypes by Wigglesworth (1997) observed \nthat no significant variation was found in phenotypic \nperformance but notable variation was found within \ngenotypes, especially for the 100-seed weight trait with \nhigh heritability, considered this features for selecting \ngenotype with large sized seed and high yield. The TCRU \n(tropical crops research unit), Nottingham University, \nUK conducted research on Bambara groundnut from \n1997 to 2000 to set the extent of diversity in vegetative \nand reproductive attitudes between and within \ngenotypes and the findings of these studies were \nobserved a weak association among reproductive and \nvegetative improvement of investigated Bambara \ngenotypes (Massawe, 2000). The University of \nNottingham in the UK and the Technical University of \nMunich in Germany conducted  an  additional  \nexperiment  from  1997  to  2003  in  a  collaborative  \nproject  to  the application of molecular methods, to \nenrich the knowledge of diversity between and within \ngenotypes, and to facilitate the reasonable profiteering \nof these resources in development programs. Massawe \net al. (2005) noted research findings conducted using \nRAPD (Randomly Amplified Polymorphic DNA) and AFLP \n(Amplified Fragment Length Polymorphism) primers \nexplored the higher degree of polymorphism among \nBambara groundnut genotypes. A project building upon \nthe last eight years of research on productivity increase \nin Bambara groundnut was extended from 2000 to \n2003, with the attachment of African associate nations \nsuch as Botswana, Namibia, and Swaziland improved \nseveral \"pure lines\" and combined into buildup \n\"multiline\" to hold the genetic heterogeneity, which \naffords stable yield among genotypes (Massawe et al. \n2005). Recently, EU-funded projects operated from \n2006 to 2009 to develop idealized enriched varieties, to \nuse molecular schemes (AFLP, SSR and DArT markers) \nand to employ marker-assisted selection in \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 66 of 74 \n\n\n\n\n\n\n\n\n\n\n\ncrop advancement. Some research output of \nBambara groundnut genetic analysis using molecular \ntools , which were concise by Aliyu et al. (2016) and \nMuhammad et al. (2020) is summarized in Tables 1 \nand 2. Dakora (2006) suggested that the Bambara \ngroundnut production can be strengthened with the \ninoculation of Bradyrhizobium as effective symbiosis. \nAmong the underutilized crops, the species have \nnecessary commercial values such as high yield, which \nmay draw attention to growers who can provide the \nneeded inputs for better production and bumper \nyield (Barbieri et al. 2014). Landraces of underutilizing \ncrops are cultivated using conventional methods of \nfarming and fundamentally grown by indigenous \npeople, but across centuries, these have undergone \nbiological and cultural evolution (Galluzzi and Noriega \n2014). Many published types of research supported \nthat neglected or minor crops can strengthen and \nadvance the world food security status. However, \ndifferent research associated to underutilize crops, \nwhich provide confidence in this area, particularly \nwhere food safety challenges are unstable (Massawe \net al. 2016; Cullis and Kunert 2017). The \n\n\n\nincorporation of the neglected crop exactly Bambara \ngroundnut in regular diet habits, diverse food chain, \nand has a constructive impression, additionally, act as a \nusual tool for promoting human well-being. The \nunderutilized crop species are not only specified for \nregional significance; but also, can improve on the \ndiversity of human nutrition at a wider range \n(Baldermann et al. 2016). Globally, some research \nprogresses have been noted on underutilized crop \nspecies by several institutions and research platforms, \nwhich include African Orphan Crops Consortium (AOCC) \n(Hendre et al. 2019), the Modern Plant Breeding \nPlatform (MPBP) (Ribaut and Ragot 2019) and Center \nfor Crops for the Future (CCFF) (Gregory et al. 2019). \nEspecially, the African Orphan Crops Consortium \ndevoted their efforts to the sequencing of the genome \nof 101 underutilized/neglected/orphan crops in African. \nBesides this, several forums and organizations are \ncontinuing their awareness campaigns and promotion \nprograms related to the significance of underutilized \ncrop species among local consumers and recently the \nConference of International Food for Future were held \nin Cologne, Germany. \n\n\n\n \nTable 1. Genetic analysis of Bambara groundnut using several molecular tools \n\n\n\n\n\n\n\nCrop \nName of \nprimers Research types Sources \n\n\n\n SSR Genetic study of Ghanaian Bambara groundnut accessions by SSR Siise and \nMassawe (2013)  \n\n\n\nSSR Genetic diversity and population structure of Bambara groundnut \naccessions revealed by microsatellite (SSR) \n\n\n\nMolosiwa et al. \n(2015) \n\n\n\nSSR, \nDArT \n\n\n\nQTL analysis of morphological traits and linkage map construction of \nBambara groundnut \n\n\n\nAhmad et al. \n(2016) \n\n\n\nDAMD, \nSCoT \n\n\n\nGenetic diversity study by Directed Amplified Minisatellite DNA and Start \nCodon targeted marker and their competency valuation Bambara \ngroundnut \n\n\n\nIgwe and \nAfiukwa (2017) \n\n\n\nRAPD Valuation of the genetic relationship of Bambara groundnut based on \nmorphological traits and RAPD markers \n\n\n\nFatimah et al. \n(2018) \n\n\n\nSSR Morphological characterization of Ghanaian Bambara groundnut \naccessions based on SSR markers \n\n\n\nAliyu and \nMassawe (2013) \n\n\n\nDArT Genetic diversity and phenotypic descriptors revealed by DArT markers \nin Bambara groundnut \n\n\n\nOlukolu et al. \n(2012) \n\n\n\nRAPD \nAFLP \n\n\n\nAFLP and RAPD markers based genetic diversity study of Bambara \ngroundnut \n\n\n\nMassawe et al. \n(2003), Massawe et \nal. (2002) \n\n\n\n\n\n\n\nBa\nm\n\n\n\nba\nra\n\n\n\n g\nro\n\n\n\nun\ndn\n\n\n\nut\n \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 65 of 74 \n\n\n\n\n\n\n\n\n\n\n\nTable 2. Summarized research findings on Bambara groundnut (BG) diversity involving molecular markers \n\n\n\n \n8.0 Landraces conservation for future food security \nand breeding program \nA considerable amount of hereditary heterogeneity of \nBambara groundnut germplasm has managed \nfollowing low input agricultural systems (Massawe \n2000). Sesay et al. (2003) reported that participatory \nplant breeding is effective for germplasm conservation \nwhere producers and users preferred their suitable \nideotypes from broadly diverse germplasms planted in \nresearch location and/or in farmer's field. It is a critical \npart of enhancing the grower\u2019s interest in preserving \npure germplasm while choosing new promising lines. \nTo ensure the long period food security use of wild \nraces, germplasm, pure lines, mixtures and cross \nbreeding programs in Bambara groundnut is an \nimpartial and broad approach to its improvement and \nwill be fascinating to producers due to their excellent \nperformance concerning productivity and adaptability. \nThe statement from Sesay et al. (2003), noted that \nmaintaining the genes of germplasms through \nbreeding approaches and through local producers\u2019 \nconservation programs is a burden for researchers or \nscientists. In Benin germplasm of Bambara groundnut \nwas planted assist in leading the germplasm \nenhancement programs (Olukolu et al. 2012) for \ninstances the line \"Sambou-touroukpa\" is early within \n103 days of maturity after showing and this promising \nline released as a commercial cultivar to be served in \nthe ongoing climate change circumstances. However, \nto escape crossing of the same genotypes and to \neradicate the duplication, molecular characterization \nof Bambara groundnut germplasm is highly \nappreciated is applied by Siise and Massawe, (2013) in \nGhanaian and Somta et al. (2011) in African \ngermplasm. To sustain heterogeneity, most effective \napproach is to implement in-situ and ex-situ \nconservation policies of the collected Bambara \ngroundnut germplasms. \n\n\n\n \n9.0 Research on pests and disease outbreak: an \nobstacle for Bambara groundnut improvement \nBambara groundnut assumes to be free from severe \npests and disease infections, especially in xerophytic \nconditions. Due to the hardness of its shell may defend \nupon most of the insects but in the stored pod of \nBambara, especially strike by bruchids (Callosobruchus \nsubinnotatus) in grain and weevils mentioned by Golob \net al. (1999) in Ghana. Bambara seeds are highly \ntolerated to bruchid and weevils when stored in \nunshelled conditions (KariKari et al. 1997). Like other \ncrops, traits enhancement activities to improve the \nyield and palatability shorten the life cycle and cooking \ntimes may also reduce the yield stability of Bambara \ngroundnut. Mostly other legumes (such as in Vigna \nunguiculata; cowpea) growing area may be the causes \nof disseminated viral disease in Bambara groundnut. \nNg et al. (1985) discovered two most usual viral \ndiseases are CAMV (Cowpea Aphid born Mosaic Virus) \nand CMV (Cowpea Mottle Virus) in Bambara \ngroundnut. Thottappilly and Rossel (1997), reported \nthat eight transmissible viral diseases affect the \nBambara groundnut. In humid area diseases caused by \nfungus-like Cercospora sp for leaf spots, Fusarium sp \nfor wilt and Sclerotium rolfsii for stem rot is common \nin Bambara groundnut found by Begemann (1988). \nResearch findings from Goli et al. (1997) during a trial \nconducted in Burkina Faso noted that the Bambara \nplant attacks heavily by virus along with fungus (CLS) \ntoward a certain genotype TVSU 218 resulted in plant \ngrowth fully collapse. Tanimu and Aliyu (1995), \ndescribed due to access dryness and humidity in \nNigeria, the leaves of Bambara groundnut are fit for \nthe attack through \n\n\n\nNo. of \ngenotypes \n\n\n\nTypes and no. of \nmarkers \n\n\n\nMarkers linked \nto BG Polymorphic (%) References \n\n\n\n223 AFLP=10 SSR=10 AFLP (N/A)  \nSSR (No) \n\n\n\nRange from 8.5% to 37.7% with mean of \n22% for AFLP \nFor SSR- five among fourteen showed \npolymorphism \n\n\n\nSingrtn and \nSchenkel, 2003 \n\n\n\n342 DArT=635 Yes - Stadler, 2009 \n240 SSR=22 Fivemarkers  \n\n\n\nwere linked \nAverage PIC 0.58 with the range between \n0.10 and 0.91 \n\n\n\nSomta et al.  \n2011 \n\n\n\n363 RAPD=14 ISSR=3 ISSR (No)  \nRAPD (N/A) \n\n\n\nAverage 70% with a range between 50% \nand 100% for RAPD \nAverage 72.4% with a range between 60% \nand 85.7% for RAPD \n\n\n\nRungnoi et al. 2012 \n\n\n\n40 DArT=554 yes - Olukolu et al. 2012 \n\n\n\n24 DArT= 201 \nSSR= 68 \n\n\n\nYes Average 0.42 with a range between 0.08 \nand 0.89 for SSR. \n\n\n\nMolosiwa et al. \n2015 \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 66 of 74 \n\n\n\n\n\n\n\n\n\n\n\nPuccinia spp. (Rust) and Colletotrichum sp. (Leaf blight) \nand viral diseases by Rosette. Ntundu (1995), reported \nthat the leaf spot due to Cercospora canescens and \npowdery mildew are the widely disseminated diseases \noccurred on Bambara groundnut in Tanzania. \nGwekwerere (1995), documented that Bambara \ngroundnut can be severely attacked by root-knot \nnematode (Meloidogyne javanica) and aphids, which \nrepresent 65% of the insect pest in Zimbabwe. There is \nan observation by Collinson et al. (1997) is under a \ncertain condition the total experiment may be \ndamaged by diseases that were extremely susceptible \nto pests and diseases. Goli et al. (1997) screened 27% \nof the ITTA\u2019s germplasms which showed tolerance to \nCLS (Cercospora leaf spot). \n \n10.0 Hard-to-Milled (HTM) and Hard-to-cook (HTC) \nphenomena \nThough Bambara ground is legume with high food and \nagronomic values still treated as a neglected crop, the \nmain bottlenecks are HTC and HTM phenomena \n(Mubaiwa et al. 2018). The term hard -to-cook refers \nto as the expanse of energy spent to prepare a legume \ngrain consumable. Mubaiwa et al. (2017) reported \nsome factors influencing the cooking time of the \nBambara groundnut. Due to long time storage before \ncooking, it increases the initial water uptake rate as \nwell as cooking time. The major constraint to uptake \nthis crop is long cooking time cause higher fuel costs \n(Adzawla et al. 2016). The cooking time of the Bambara \ngroundnut can be reduced using local salt (Mubaiwa et \nal. 2017) and fermentation before cook (Ademiluyi and \nOboh 2011), it also improves the mineral composition \nand eliminates the anti-nutritional component exists in \nBambara seeds. Pretreatment of bamabra seeds \nexpands the milling proficiency from 65% to 70%, \nadditionally soaking, sprouting, roasting, infrared \nheating and can be used as pretreatment methods \nbefore cooking and milled  into  flour  (Mubaiwa  et  al., \n2018). Using infrared heating treatment of 15min \nbefore cooking reduces the cooking time 162min to \n60min for the whole fresh nut and from 41min to \n30min for dehulled Bambara nut reported by \nOgundele and Emmambux, (2018). The cooking time \n3.6 h recorded by Mubaiwa et al. (2017) for soybean, \nwhich is also identical time for this crop. Mubaiwa et \nal. (2018) stated that as a unique crop for nutritional \nand food security, shortening the cooking time could \nbe a significant benefit for most marginal growers, in \nmajor growing areas. Making flour from hydrated \nBambara seeds and its full or partial uses can be one \nmethod to shorten cooking time, besides various food \nrecipes, derivatives, processed foods, confectionaries \nand accessions (lines) have been discovered also \nevaluated by Feldman et al. (2019) to fix the hard-to-\ncook phenomenon. \n11.0 Important features resiliency to Bambara \ngroundnut \n\n\n\n \n11.1 Drought resilient trait of Bambara groundnut \nNaturally Bambara groundnut is a drought tolerance \nlegume, willingly adjustable to diverse ecological \ncircumstances and can be intercropped with other \nnon-legumes making it an imperative lucrative crop in \nseveral emerging states (Rungnoi et al. 2012). Drought \nincreases several responses of plants in both above \nand below ground soil such as tolerance (Fahad et al. \n2017), avoid (Liu et al. 2005) and escape (Ludlow and \nMuchow, 1990). Mabhaudhi et al. (2013), Muhammad \net al. (2015) and Chai et al. (2016) reported that all \nthree mechanism of drought, such as tolerance, \nescape and avoidance exist in Bambara groundnut. \nMabhaudhi et al. (2013) noted the Bambara \ngroundnut primarily tolerates drought via escape and \navoidance with the crop displaying little water usage. \nAvoidance of drought is most general in the plant, \nwhich happens due to irregular water stresses. It is the \nstrength of crop to sustain necessary physiological \nmanners at the time of minor, moderate, and erratic \ndrought stress. Bambara groundnut minimizes water \nlosses by intensifying soil water retention via deep and \nprolific root arrangements, higher management of gas \nexchange by the stomata, canopy size decrease, and \nimprovement in wax buildup on the surface of the leaf \n(Chai et al. 2016). A report from Chai et al. (2016) \nstates that Bambara groundnut plants can sustain \nspecific levels of physiological motion under severe \ndrought stress conditions by controlling hundreds of \ngenes and their systems. Bambara groundnut has \nbecome ideal crop due to survivable of water deficit \ncondition and presence of three drought tolerance \nmechanisms enhances the strength to provide a \nsignificant quantity of yield under a minor, moderate, \nor even extreme drought stress. Feldman et al. 2019 \nreported that this stress tolerance behavior of \nBambara groundnut becomes an extensive model \nlegume for farming in an arid climate and uniformly \nbecomes a future crop in the area where the incident \nand severity of drought and irregular rainfall patterns \ndue to climate change. Moreover, the crop has \nadjusted to various climatic conditions such as high day \ntemperature and low night temperature (Botswana), \nthe high humid and far milder region (Indonesia). \nMubaiwa et al. (2018) concluded that dry area where \nprecipitation less than 800mm/year has shown a \npreference for the Bambara groundnut over cowpea, \ncorn, or groundnut. Many researchers (Al Shareef et al. \n2014; Chibarabada et al. 2015; Nautiyal et al. 2017) \nfrom the last three decades-initiated attempts at \nexplaining the mechanism of drought tolerance of \nBambara groundnut. Bambara groundnut can hold leaf \nturgor pressure by reducing in leaf area, control of the \nstomatal performance and osmotic \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 67 of 74 \n\n\n\n\n\n\n\n\n\n\n\nregulation (Collinson et al. 1997) and Bennett et al. \n(1981) suggested that the plant can significantly \nsustain turgor at water potential of -2.0 MPa \n(megapascal), which is lower than peanut (Arachis \nhypogaea; -1.2 to -1.6MPa). The presence of tannins \n(polyphenols) in dark-colored seeds of Bambara \ngroundnut performs as anti-oxidizer under drought \nstress that provides better germination percentage \ncompared to light-colored seeds however, in terms of \neating, this habit might be less acceptable (Mwale et \nal. 2007). Alternatively, among the germplasm\u2019s \ndifferences happen in the degree of drought tolerance, \ntheir center of origin, the strength and speediness of \ndrought stress as well as degree of phenological effect \n(Nautiyal et al. 2017). Research conducted by Berchie \net al. (2012) to assess different germplasm of Bambara \ngroundnut for drought tolerance and heat resistance, \nwas revealed that plant can survive when water supply \nwas stopped at 30 days after planting, while some \naccessions were showed resistance to drought up to \n120 days. In drought stress conditions, much research \nhas been conducted and found several physiological \nand growth features tolerance to drought stress in \nBambara groundnut e.g. (a) expansion of canopy, \nduration and size reported by Mwale et al. (2007) (b) \nreported on biomass collection and partitioning by \nMabhaudhi et al. (2013), (c) Phenological flexibility \nreported by Nautiyal et al. (2017), (d) air or gas \nexchange (Chai et al. 2016; Nautiyal et al. 2017) (e) \nphotosynthesis control and osmoregulation (Chai et al. \n2016; Nautiyal et al. 2017) and (f) leaf temperature \nreported by Nautiyal et al. (2017). Mwale et al. (2017) \nreported that drought commonly reduces the \nproduction of different crops including Bambara \ngroundnut, however, a considerable production of 1.7 \nt ha-1 was still recorded, but it was varied from 1.3 to \n2.1 tha-1. , the productivity of the Bambara groundnut \nunder drought stress is linked with the efficiency \nresource conversion into a useful form. Due to drought \nstress, the decline in the coefficient of radiation \nconservation (\u03b5s) from 1.51\u20131.02gMJ\u22121 was observed \nin Bambara groundnut (Mwale et al. 2007), whereas \nthe coefficient of radiation conservation (\u03b5s) in \nBambara groundnut is higher than those found in \nsoybean (Glycine max; 0.52 to 0.92gMJ-1) reported by \nDe-Costa and Shanmugathasan, (2002) and that of \ncowpea (0.07\u00b1 0.03\u20130.50 \u00b1 0.01 gMJ\u22121 m-2) reported \nby Craufurd and Wheeler, (1999) under limited water \nlevel in soil. Potentially for higher yield, it is essential \nto determine water use efficiency (\u03b5w) of the plant to \nconvert to dry matter and Mwale et al. (2007) reported \nthat for Bambara groundnut under drought stress \ncondition water use efficiency (\u03b5w) was at 1.65 g kg\u22121 \n, which is higher than other legumes such as chickpea \n(1.11g kg-1) & Lentil (1.37g kg-1) cultivated in low \nrainfall environments (Zhang et al. 2000). Resilience \ntraits supported plants to cope with abiotic stress such \n\n\n\nas heat, salinity, and drought, as well as biotic stress \nand loss of perfect land for farming increasing \nurbanization and soil erosion (Massawe et al. 2016), \nunder these situations, the solution is to expand the \npractice of agriculture farming with principal food \ncrops that can evenly assist as a manner of risk \ndispersal. According to Olayide et al. (2018), Bambara \ngroundnut is one of the stable legumes, has been \ntreated as typical crops having resilience and verified \ntraits suitable for adverse environmental challenges. \n \n11.2 The root system of Bambara groundnut \nThe emphasis on the trait of shoot over root ratio is \nreasonable and has the technical obstacles in fixing up \nand managing the complex root-soil inter-\ncommunication. Root observation and excavation \nprocedures used to phenotyping root habits, which is \ndiverse from laboratory and (paper or growth media) \nto greenhouses or field (earth media). Due to the \nheterogenic condition of soil physics, phenotyping \napproaches do not provide a true representation of \nthe roots also it is labor-intensive and causes of land \ndamage (Richard et al. 2015). Recently, the good news \nis the invention of advanced technologies of genomics \nis starting to mitigate technological barriers and give \nchances to analyze root characteristics that allow high-\nthroughput phenotyping using computer-based \nmodels and software for tracking the root phenotype \nin response to different adverse conditions. \nImplementing the advanced techniques such as Root \nReader3D (Clark et al. 2011), the Root Scans (Burton et \nal. 2012), the Root Nav (Pound et al. 2013), WinRhizo \n(Joshi et al. 2017), micro-computed X-ray tomography \n(\u00b5CT) (Mairhofer et al. 2011), ImageJ (Ryosuke and \nYoichiro, 2013), and algorithms phenotypic \ninvestigations of Bambara groundnut roots can be \ncreated dynamic additionally, heighten the perception \nhow root growth of Bambara plant varied in relation to \ndrought. \n \n11.3 Bambara groundnut responses to day length \n(photoperiod) \nRound the equator region where day length is \nconstant, is the region of Bamabara groundnut has \noriginated (Pasquet et al. 1999). This crop vastly \ncultivated in different latitudes in Africa where the \nphotoperiod is going to decrease and increase during \nplanting. It was established by Linnemann et al. (1995) \nthat Bambara groundnut needs12h day length for \nhigher pod-set and seed yield, while day length > 12h \ncause to more vegetative growth (leaves) by reducing \nthe pod yield (Oyiga, 2010) but the onset and \ndevelopment of flowering, the development pod \nformation can be disabled by long photoperiod of \nmore than 14 hours. Furthermore, it was observed \nthat some plants did not produce pods when day \nlength raises from 14hr to 16 hr. This day length \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 68 of 74 \n\n\n\n\n\n\n\n\n\n\n\nsensitivity features of Bambara groundnut cause a \nbarrier of this crop expansion further away from the \nequator. Lastly, during the growing season, the \nselection of photoperiod could be a way to get \nmaximum pod-filling as well as pod yield. Kendabie et \nal. (2012) exposed that considerable variation exists \namong the Bambara groundnut landraces regarding \nthe photoperiod effect. Four distinct groups of \naccession have been identified (Bamnetwork 2014) \nregarding day length and these are (1) short-day \n(qualitative) accession e.g. Ankpa 4; (2) short-day \n(quantitative) accession e.g. TN, Gresik, LunT; (3) Long-\nday (quantitative) accession e.g. 686, DodR; (4) Day \nlength-neutral accession e.g. 519\u20133, Uniswa-red, Dip-\nc. \n \nConclusion \nThe underutilized Bambara groundnut has an \nexcellence to contributing the nutritional and food \nsafety. Bambara groundnut enables us to grow under \nsevere climate conditions while major crops are badly \nsuited to the environment. Enlarging underutilized \ncrop plants with plenty of genetic stocks and \npotentially profitable attributes are looking upon as \none of the solutions that could address food and \nnutritional security concerns. Due to the global \nclimatic changes, genetic analysis alongside molecular \nresearch in underutilized crops, particularly for \nBambara groundnut, is holding high importance \nbecause of their genetic tolerance living ability and \nnon-living stresses phenomenon. By exactly \nbroadening up the morphological and molecular \ngenetic improvement of such important features, it \nwill not only enhance the genetics and breeding of \nBambara groundnut crops but rather the whole crop \nbreeding, adaptation to weather alteration mitigation, \nimprove income generation, as well as nutrient and \nfood security. The modern model of uses of \nunderutilized crop species regarding productivity, \nprocessing, consumption, and research, is intended to \nbroaden the uniformity in the prevailing global diet \nthat is a vital preference in the current world \nsituations. So, the significance of underutilized crop \nspecies (NUS) for planetary nutrient and food security \nis currently getting awareness of global scientific \nsociety and food safety policymaking institutes also \nmodern enhancement policies alongside divergent \ngenetic and genomic resources are implemented to \naccelerate its yield potentiality. This critical review \nexplored contributions and intelligences of different \nresearchers in Bambara groundnut along with \nextracted outcomes from original ground of research \nto endure the evidence for future researchers \ninvolving Bambara groundnut improvement. \n \nAcknowledgments \nThe author is grateful to the Ministry of Agriculture \n(MOA), Bangladesh Agricultural Research Council \n(BARC), Bangladesh Agricultural Research Institute \n\n\n\n(BARI), the People\u2019s Republic of Bangladesh for \nadequate funding and other support through the \nProject of NATP Phase-II. The authors are grateful to \nUniversity Putra Malaysia (UPM). \n \nFunding \nBangladesh Agricultural Research Council (BARC), The \nPeople\u2019s Republic of Bangladesh for adequate funding \nand other support through the Project of NATP Phase-\nII; University Putra Malaysia.  \n \nAuthor Contributions \nM.M.H.K wrote the first draft and incorporated the \nreviewed inputs into this manuscript. Later, M. 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Water use \nand water use efficiency of chickpea and lentil in a \nMediterranean environment. Aust J Agric Res, 51, pp. \n295\u2013304. \n \n\n\n\n\n\n\n \n*Correspondence: mrafii@upm.edu.my\n\n\n\n"
"\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 75 of 81 \n\n\n\n\n\n\n\n\n\n\n\nOFFICIAL JOURNAL \n\n\n\nRESEARCH ARTICLE \n\n\n\n\n\n\n\nSelection of Premium Leafy Vegetables for Plant Factory \n \n\n\n\nNorfadzilah A. F., Mohd Abid A., Nur Syafini G. \n\n\n\n\n\n\n\nHorticulture Research Centre, MARDI Headquarters, 43400 Serdang \n \n\n\n\n*Correspondence: fadzilah@mardi.gov.my \n \n\n\n\n\n\n\n\nIntroduction\nA plant factory is a factory that grows plant indoor. \nThe \u2018factory\u2019 could be a space, a house or building \nthat has facilities for growing plant, normally with \ncontrolled environment in terms of lighting, \ntemperature, humidity, CO2 levels, and nutrient \ndistribution (Luna Maldonando et al., 2016, Liu et al. \n2022). Plants grown in plant factories are often grown \nvertically in hydroponic systems (Liu et al., 2022). The \noriginal concept of plant factory dating back to 1949 \nwhich was implemented at the California Institute of \nTechnology. This environmentally controllable crop \nlaboratory is called a phytotron, which refers to the \ncrop (phytos) and the complex machinery that \nregulates the needs of the crop (tron) (Went, 1949).  \nIts ability to regulate and manipulate the \nenvironment makes it dependable for all-year crop \nproduction. Vertical  planting system give advantage \n \n \n \n \n \n \n\n\n\nfor more spacing and increase production thus, \nmaximising the yield per unit area. This system is also \nsoilless hence removing the risk of soil-borne disease \nand making it easy to regulate the use of water and \nnutrient uptakes. Being inside buildings, the plants are \nalso protected from pests and diseases, which can \nreduce the need for pesticides or fungicides (Roberts et \nal., 2020). The plant factory is suitable for small-sized \ncrops such as leafy vegetables, herbs and even small-\nsized fruit plant such as strawberries and tomatoes. For \ndeveloped countries such as Japan, Netherlands, \nGermany and the United State, the cultivation of crop is \nmore widespread covering varieties of vegetables and \nfruits and even cereal crops (Asseng, 2020).  \n \nThe products of plant factory are considered premium \nproduct. This is due to the production cost and the \nquality of the produce. Nowadays, consumers are more \naware on global issues regarding the safety of our \nplanet such as carbon emission, food security, food \nsafety. Therefore, many of them are willing to pay \npremium prices as to show support to environmental \nfriendly, improved and healthy products. (Li and Kallas, \n2021, Casini et al., 2019) \n\n\n\n \nAbstract \n\n\n\nRecently, premium vegetables that are produced in plant factories have started to appear in the \nMalaysian market. Malaysians' dietary trends now tend to value nutritious, quality and ready-to-eat \nfood. Thus, high valued nutritious vegetables have a bright future in Malaysia. The selection of \nvegetables for plant factory is important to ensure the profitability and sustainability of this system. \nMARDI has conducted a study covering aspects of varietal selection and development of cultivation \nsystems for plant factory. Vegetable varieties from the species of Brassica rapa, Lactuca sativa, \nBrassica oleracea and Eruca vesicaria are among those that have been tested in the plant factory. \nThese species are so far in demand in Malaysian market and have good price. Selected varieties of \nthese species will undergo further study to enhance their phytonutrient content by manipulation of \nLED lighting spectrum. There are several criteria that need to be considered in selecting crop for plant \nfactory such as yield, growth and quality. Each of these elements has several other parameters that \nneed to be measured. With various elements to consider, combination of statistical analysis, scoring \nand weightage based on collected data and brainstorming between the researchers were used to assist \nin making the best selection. This paper discusses the selection made for 13 vegetable varieties from \nthe Brassica rapa species. \n\n\n\nKeywords: Food safety, Varietal selection, Vegetables, Weightage-scoring \n\n\n\nReceived: 15 03 2022; Accepted revised manuscript:  01 12 2022; \nPublished online: 30 04 2023 \n*Corresponding author: Norfadzilah Ahmad Fadzil, \nHorticulture Research Centre, MARDI Headquarters, 43400 \nSerdang \nEmail: fadzilah@mardi.gov.my \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 76 of 81 \n\n\n\n\n\n\n\n\n\n\n\nResearch on vegetables in the plant factory is still very \nnew in MARDI. It was started in 2018. Most of the \nvegetables grown are from lettuce types such as \ngreen coral, red coral, romaine and butterhead. In \naddition, other leafy vegetables such as curly kale \n(Brassica oleraceae var. acephala), arugula (Eruca \nvesicaria) and also herbs such as red veined sorrel \n(Rumex sanguineus) and sweet basil (Ocimum \nbasilicum) are also grown in the plant system. At that \nstage, the cultivation was focused on the optimization \nof the plant factory system.  \n \nIntensive evaluation and selection of vegetable types \nfor plant factory started in the 12th Malaysia Plan to \nobtain more accurate and comprehensive \ninformation related to vegetable varieties that are \nsuitable for plant factory. This study is one of a more \ncomprehensive plant vegetable production system \nresearch under the sub-project of Functional LED \nLighting System and Efficient Input Development for \nImproving Crop Performance in Plant Factory and \nControlled Environmental Structures. Selection of \nvegetables is important to ensure sustainable \nproduction. For the evaluation, 13 Pak choy types \n(Brassica rapa var chinensis), 35 lettuce (Lactuca \nsativa), 5 Arugula (Eruca vesicaria) and 2 types of kale \n(Brassica oleracea var acephala) were evaluated. A \nspecific selection index was developed for each \nvegetable types in this experiment. These selection \nindices were developed to give a conclusive idea on \nthe performance of each vegetable based on several \npriorities. The performance of certain traits is \nsometimes not in line with the other, for example \nhigh yielding (heavier) vegetables usually take a \nlonger time to harvest or, there are also highly \nnutritious vegetables but smaller in size and thus \naffect yield and vice versa. Therefore, these selection \ncriteria need to be discussed among researchers from \nvarious fields to determine the appropriate \nweightage and scores for each parameter measured \nbefore a selection index can be developed. Similar \nselection index was also used for rambutan selection \n(Sarip, 2020). This paper presented result on B. rapa \nvar chinensis, also known as pak choy. \n \nPak choy (B. rapa var. chinensis) is a vegetable  type \nfrom the Brassicaceae family, also known as chinese \ncabbage. Compared to another type of chinese \ncabbage which is also known as napa cabbage (B. rapa \nvar. pekinensis) the pak choy type does not produce \noblong crinkly, tightly packed, pale green leaves. \nThere are various varieties of pak choy on the market, \nincluding Siew Pak Choy or Shang Hai pak choy, which \nhas green leaves and stems and soft texture; nai pak \nchoy, which has a white and crunchy stem also known \nas dwarf pak choy and crincle leaf pak choy; white \nstem and a curly dark green top. Types of pak choy \nare also classified based on harvest time, early \n\n\n\nharvested pak choy called baby pak choy. Usually pak \nchoy is only eaten after being cooked, but it can also be \neaten raw in salads or sandwiches. Pak choy is rich in \ncalcium, phosphorus, iron, magnesium, and vitamin K \nand vitamin A. In Malaysia, this vegetable is widely sold \nin wet markets and supermarkets. In the supermarket, \nthis vegetable is usually sold in packs weighing 100 - \n200g at a price ranging from RM1.50 - RM 3.50 / 100g \ndepending on the type and stage of harvest. \n \nMATERIALS AND METHODS \nThe experiment was carried out in MARDI Plant Factory, \nMARDI Headquarters, Serdang. Thirteen pak choy \nvarieties (Table 1) were evaluated in this experiment. \nExperiment were conducted in randomize complete \nblock design with three replications.  \n \n \nTable 1. List of pak choy variety evaluated Plant Factory \n\n\n\nNo. Code Variety Company \n1.  PC1 280 Dwarf type Pak choy Green \n\n\n\nEagle \n2.  PC2 288 F1 Hybrid Shang Hai \n\n\n\nDwarf Pak choy \nGreen \nEagle \n\n\n\n3.  PC3 822 Curly Dwarf Pak \nchoy \n\n\n\nGreen \nEagle \n\n\n\n4. PC4 217 Purple Red Dwarf  Green \nWorld \n\n\n\n5. PC5 Fan Pak choy No.6 Green \nWorld \n\n\n\n6. PC6 Pak choy Nai You No. 15 Green \nWorld \n\n\n\n7. PC7 Pak choy Ong King No. \n24 \n\n\n\nGreen \nWord \n\n\n\n8. PC8 Pak choy F1 Bushido 802 GWG \n9. PC9 Pak choy F1 Big Jade 800 Leckat \n10. PC10 Nai You BBS013 Serbajadi \n11. PC11 Pak choy Ivory BBS020 Serbajadi \n12. PC12 Pak choy Susu Kecil \n\n\n\nBBS061 \nSerbajadi \n\n\n\n14. PC14 Milky Nai Pak choy \nSH186 \n\n\n\nSerbajadi \n\n\n\n \nThe plants were planted in multilayer deep flow \ntechnique (DFT) hydroponic system. Fertilizer solution \nwas given at 0.8-1.0 mS/cm for the first 5-7 days after \ntransplant then, was increase gradually up to 1.8mS/cm \nuntil harvest. Red blue spectrum of LED growth light \nwas used for plant lighting which measured intensity \nranged from 250-380umol.m-2.s-1 at 30-10cm from \nluminaire. Eight hours of light exposure was given from \nday 1-7 after after transplanting or until transplant \nestablished to fulfill 6-8 mol/m2/day of daily light \nintegral (DLI). Plants was exposed for 12 hours (DLI-14-\n16mol/m2/day) of red blue LED grow light for the rest \nof duration until harvesting at day 30.\n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 77 of 81 \n\n\n\n\n\n\n\n\n\n\n\nTo develop selection index for pak choy that is \nsuitable for plant factory, selection criteria were \nfocused on three main components; yield, growth \nand quality. In order to develop the scoring for \npreference, ten measurement that is representing \nthe three components were chosen. \n \nFor yield and yield-related characteristics, selection \ncriteria were made based on fresh weight and \nnumber of leaves. Yield characteristics are indeed the \nselection criteria for any crop. Vegetables from plant \nfactory are sold fresh and high fresh weight thus \nbecomes one of the priorities. The number of leaves \nis also characteristics that contribute to the weight of \nthe plant. In addition, products from plant factory can \nalso be sold by leaf harvest.  \n \nSelection criteria representing the growth \ncharacteristics were based on the germination rate, \nday of the two true leaves initiation and days to \nmature. Days for two true leaves indicate time to \ntransplanting. These characteristics provide \ninformation for the growth rate of the variety. The \nspeed of growth is an important feature of crops in a \nplant factory as it will give impacts on yield and \noperating costs, the faster the plant grow, the more \ncrop cycle, increase yield, increase production thus \ncompensating the production cost. \n\n\n\nAnother important aspect in the selection of varieties \nfor a plant factory is the quality-related characteristics \ncovering colour, appearance, texture and nutritional \nvalue. For this evaluation, the characteristics given \nattention are uniformity, leaf texture, leaf color, \nvitamin C content and antioxidant content. These \nfeatures influence users\u2019 choice through visual and \nsensory assessment. The uniformity factor is important \nto evaluate because the plant factory products are \nlabeled as high-quality products. Uniformity will also \nfacilitate crop management in the plant factory in terms \nof input and packaging. Nutritional value which is a \nhidden characteristic however is becoming increasingly \nvalued by consumers, researchers and the medical \nprofession and laboratory analytical information.   \n \nA ranking was given to the characters measured to \ndetermines its priority. This has been made based on \nanalysed data, observations and discussions among \nresearchers and previous experiance. Scoring for each \ncharacter was developed based on analysis and \nobservation conducted specifically for each character \nand experiment.  \n \nRESULTS AND DISCUSSION \nSelection index for pak choy variety was developed \nbased on ten traits measured and observed (Table 2).  \n\n\n\n \nTable 2. Selection index criteria, measurement, rank and score for 13 pak choy variety evaluated in plant factory \n\n\n\nComponent Measurement Ranking Score Description \nGrowth Germination rate 7  Germination rate (%) \n\n\n\n1 (Poor) <50 \n2 (Satisfactory \u2265 50-70< \n3 (Good) \u2265 70-90< \n4 (Excellent) \u2265 90 \n\n\n\nDays for two true leaves initiation 4  Days to transplant \n1 (Poor) \u2265 20 \n2 (Satisfactory \u2265 18-20 < \n3 (Good) \u2265 15-18< \n4 (Excellent) <15 \n\n\n\nDays to mature 2   \n1 (Poor) \u2265 35 \n2 (Satisfactory) \u2265 30- 35< \n3 (Good) \u2265 25 \u2013 30 < \n4 (Excellent) < 25 \n\n\n\nYield Fresh weight 1  Fresh weight (g) \n1 (Poor) < 100g \n2 (Satisfactory) \u2265 100 - 150< \n3 (Good) \u2265 150-200 < \n4 (Excellent) \u2265 200 g \n\n\n\nLeaves number 3   \n1 (Poor) <10 \n2 (Satisfactory \u226510 - 12< \n3 (Good) \u226512-14< \n4 (Excellent) \u226514 \n\n\n\nQuality Uniformity 8  Uniformity \n1 (Poor) Not uniform \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 78 of 81 \n\n\n\n\n\n\n\n\n\n\n\n \nScoring and weightage calculation are presented in \nTable 3. Based on the calculations, five types of \npakchoy varieties were selected in the top position \nout of 13 pak choy varieties.  \n  \nThe varieties are PC8, PC7, PC10, PC5 and PC3 (Table \n4 and Table 5). Each of these types of vegetables has \nadvantages in several aspects. The combination of \ncharacter values and weights that indicate the priority \nof a character has made the variety selected. Pak choy \nvariety PC8 had a relatively good score for all traits, \nwhere there was no score of 1 for all traits measured. \nThe highest score (4) was obtained from the \ngermination rate characteristic where this variety had \na germination rate exceeding 90%. In addition, the \nvariety has a fast maturation period, high number of \nleaves, nutrient content and antioxidants that are \nrelatively good where all these characteristics get a \nscore of 3. Fresh weight which is a feature in the main \nranking however is not so high for PC 8 which is at a \nscore of 2. PC 8 has a yield of around 101.55 g only. In \naddition, leaves texture for this variety is categorised \nas soft with a score of 2. \n \nFor the second selection, PC7, fresh weight gives a \nhigh score of 4 followed by the number of leaves with \na score of 3. These characteristics have high \nweightages that contribute for the selection. \nHowever, in terms of maturity, PC7 got a score of 1 at \nmaturity and the days for transplant showed a \nrelatively slow maturity. PC 7 has good antioxidant \nand vitamin C content and fast germination rate. \nVariety PC10 is at the third rank. In this evaluation, \nthis variety has a low fresh weight value of below \n\n\n\n100g and a relatively late maturity period. The \nadvantages of this variety is its high germination rate \n(score 4) and score 3 on the number of leaves, day for \ntransplant, vitamin C content, uniformity and leaves \ncrunchiness. \n \nThe fouth variety selected is PC5. This variety have \nmoderate performance. Fresh weight, leaves number, \nantioxidant, vitamin C, uniformity and leaves texture \nare scored as 2. Germination rate of this variety was \nexcellent. Days to transplant score of 3 but it took \nlonger time to mature with score of 1. \n \nThe fifth selection is PC 3. This variety also has a low \naverage fresh weight and a slow maturation period on \na score of 1. However this variety has a score of 4 for \ngermination rate and leaves texture. This variety is also \nuniform, with good antioxidant content. The number of \nleaves and the content of vitamin C are on a score of 2. \n \nThe use of selection index for the selection of vegetable \ntypes provides a different point of view according to the \npriority in the selection. In this study all plants were \ngiven the same treatment in terms of fertilizer input, \nirrigation, temperature and lighting. This may affect the \nactual performance of some varieties that have specific \ngrowth requirements. The type of variety also \ncontibutes to the evaluation. Some of the varieties \nwhich have dwarf characters may be classified into their \nown group to get fairer comparison.  \n \nVarieties that have low selection index are not \nnecessarily bad. Weights and rankings affect the value \nof the selection index. Rankings are selected based on \n\n\n\nBased on cumulative subscore on standard \ndeviation of fresh weight, vegetable length \nand width \n\n\n\n2 (Satisfactory Fairly uniform \n3 (Good) Uniform \n4 (Excellent) Very uniform \n\n\n\nLeaves Texture 9   \n1 (Very soft) <5 \n2 (Soft) \u2265 5-10 < \n3 (Crunchy) \u2265 10-15 < \n4 (Very \ncrunchy) \n\n\n\n\u226515 \n\n\n\nVitamin C 6  Vitamin C (mg/100g \nFW) \n\n\n\n \n1 (Poor) < 5 mg/100g FW \n2 (Satisfactory 6-15 mg/100g FW \n3 (Good) 16-35 mg/100g FW \n4 (Excellent) >35 mg/100g FW \n\n\n\nAntioxidant 5  % Inhibition of DPPH \n(antioxidant activity) \n \n\n\n\n1 (Poor) < 20% \n2 (Satisfactory 21-50% \n3 (Good) 51-70% \n4 (Excellent) >70% \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 79 of 81 \n\n\n\n\n\n\n\n\n\n\n\nresearcher preferences and these rankings can be \nmodified as needed. For example, if priority is given \nto quality value over weight, other varieties such as \n\n\n\nPC6, PC2 and PC 1 will precede the selection. Similarly \nif growth criteria are given priority, they will give \ndifferent results.  \n\n\n\n \nTable 3. Measurement, weight and score for 13 pak choy variety evaluated in plant factory \n\n\n\n    Score \n\n\n\nMeasurement Weight PC1 PC2 PC3 PC4 PC5 PC6  PC 7 PC8 PC9 PC10  PC11 PC12 PC14 \n\n\n\nFresh weight 0.2 2 1 1 1 2 1 4 2 1 1 1 1 1 \n\n\n\nDays to mature 0.18 1 1 1 1 1 1 1 3 1 1 1 1 1 \n\n\n\nLeaves number 0.16 3 3 2 3 2 1 3 3 2 3 2 3 2 \n\n\n\nDays to transplant 0.13 1 1 3 1 3 1 1 3 3 3 1 1 2 \n\n\n\nAntioxidant content 0.11 3 3 3 4 2 4 3 3 3 2 2 3 2 \n\n\n\nVitamin C content 0.09 2 3 2 1 2 4 3 3 2 3 4 1 4 \n\n\n\nGermination rate 0.07 3 3 4 3 4 4 3 4 4 4 4 4 4 \n\n\n\nUniformity 0.04 3 3 3 3 2 3 2 3 3 3 3 3 2 \n\n\n\nLeaves texture 0.02 2 2 4 2 2 4 2 2 3 3 3 4 3 \n \n\n\n\nTable 4. Selection index for 13 pak choy variety evaluated in plant factory \n\n\n\n  Score \n\n\n\nMeasurement PC1 PC2 PC3 PC4 PC5 PC6  PC 7 PC8 PC9 PC10  PC11 PC12 PC14 \n\n\n\nFresh weight 0.4 0.2 0.2 0.2 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 \n\n\n\nDays to mature 0.18 0.18 0.18 0.18 0.18 0.18 0.18 0.18 0.18 0.18 0.18 0.18 0.18 \n\n\n\nLeaves number 0.48 0.48 0.32 0.48 0.32 0.32 0.32 0.32 0.32 0.32 0.32 0.32 0.32 \n\n\n\nDays to transplant 0.13 0.13 0.39 0.13 0.39 0.39 0.39 0.39 0.39 0.39 0.39 0.39 0.39 \n\n\n\nAntioxidant content 0.33 0.33 0.33 0.44 0.22 0.22 0.22 0.22 0.22 0.22 0.22 0.22 0.22 \n\n\n\nVitamin C content 0.18 0.27 0.18 0.09 0.18 0.18 0.18 0.18 0.18 0.18 0.18 0.18 0.18 \n\n\n\nGermination rate 0.21 0.21 0.28 0.21 0.28 0.28 0.28 0.28 0.28 0.28 0.28 0.28 0.28 \n\n\n\nUniformity 0.12 0.12 0.12 0.12 0.08 0.08 0.08 0.08 0.08 0.08 0.08 0.08 0.08 \n\n\n\nLeaves texture 0.04 0.04 0.08 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 \n\n\n\nSelection index 2.07 1.96 2.08 1.89 2.09 2.09 2.09 2.09 2.09 2.09 2.09 2.09 2.09 \n\n\n\n \nTable 5. Top 5 variety of Pak Choy and its characteristiscs \n\n\n\nRank Score Variety Characteristic \n\n\n\n1 2.85 \n\n\n\n\n\n\n\nFresh weight: 101.55 g \nMaturity: 30 days \n\n\n\nVitamin C (mg/100g FW): 23.48 \nAntioxidant content (%): 42.76 \n\n\n\nLeaf texture: Soft \n \n\n\n\n2 2.52 \n\n\n\n\n\n\n\n \nFresh weight: 202.55g \n\n\n\nMaturity: \u2265 35 days \nVitamin C(mg/100g FW): 32.82 \nAntioxidant content (%): 45.99 \n\n\n\nLeaf texture: soft  \n \n\n\n\n3 2.2 \n\n\n\n\n\n\n\nFresh weight: 84.07g \nMaturity\u2265 35 days \n\n\n\nVitamin C(mg/100g FW): 33.97 \nAntioxidant content (%): 38.13 \n\n\n\nPC8 \n \n\n\n\nPC7 \n \n\n\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 80 of 81 \n\n\n\n\n\n\n\n\n\n\n\n \nCONCLUSION \nThe selection of vegetables for plant facotry is crucial \nto ensure sustainability of this system. Vegetables \nfrom the plant factory must have characteristics that \nare appropriate in terms of their quality and the \ninvestment that has been made in them. Production \ncan be increase through yields and its related traits. \nBeside that, additional crop rotation by using fast \nmaturity varieties could also increase yield and save \noperating costs. The produce of the plant facotry must \nalso meet the perception of the consumer in terms of \nquality. These include visual appearance, taste and \nnutrient content. This leafy vegetable screening study \nwill be expanded in the future to involve various other \ntypes of vegetables that have the potential to be \nhighlighted to the Malaysian community. \n \nACKNOWLEDGEMENT \nThis research was funded by 12th Malaysia Plan \nDevelopment Fund through the project PRH 503. The \nauthors gratefully acknowledge all our collegues for \nvaluable scientific discussion. We also thank Mr. Mohd \nRaimi, Mr. Mohd Khairul Anuar and Mr. Muhammad \nAzizi for technical assistant through out the project.  \n \nREFFERENCES \nAres G., Ha B. and Jaeger S. R. 2021. Consumer \nattitudes to vertical farming (indoor plant factory with \nartificial lighting) in China, Singapore, UK, and USA: A \nmulti-method study Food Research International 150 \n(2021) 110811 \n \n\n\n\nAsseng S., Guarin J.R., Raman M. , Monje O., Kiss G., \nDespommiere D.D, Meggers F.M, and Gauthierg P. P. \nG. 2020. Wheat yield potential in controlled-\nenvironment vertical farms. PNAS  August 11, 2020  \nvol. 117  no. 32 \nwww.pnas.org/cgi/doi/10.1073/pnas.2002655117 \n \nLi S. and Kallas Z. 2021. Meta-analysis of consumers' \nwillingness to pay for sustainable food products. \nAppetite. Volume 163, 1 August 2021, 105239 \n \nLiu, Y.; Mousavi, S.; Pang, Z.; Ni, Z.; Karlsson, M.; Gong, \nS. 2022. Plant Factory: A New Playground of Industrial \nCommunication and Computing. Sensors. 22, 147. \nhttps://doi.org/10.3390/s22010147 \n \nLuna-Maldonado A., Vidales-Contreras \nJ.A and Rodr\u00edguez-Fuentes H. 2016. Advances and \nTrends in Development of Plant Factories. Front Plant \nSci 7: 1848 doi: 10.3389/fpls.2016.01848 \n \nRoberts J. M. , Bruce T. J. A. , Monaghan J. M. , Pope T. \nW. , Leather  S. R. , Beacham A. 2020. Vertical farming \nsystems bring new considerations for pest and disease \nmanagement. Annals of Applied Biology \nVolume176, Issue3 Pages 226-232 \nhttps://doi.org/10.1111/aab.12587 \n \nSarip J. 2019. Pembangunan Klon Rambutan Mutiara \nMerah dan Mutiara Wangi Inovasi Masa Hadapan. \nSyarahan Perdana 21 November 2019 Dewan Tan Sri \nYusof Hashim, Ibu Pejabat MARDI \n \n  \n\n\n\n\n\n\n\nLeaf texture: crunchy \n\n\n\n4 2.09 \n\n\n\n\n\n\n\nFresh weight: 149.18g \nMaturity: \u2265 35 days \n\n\n\nVitamin C (mg/100g FW): 14.92 \nAntioxidant content (%): 23.75 \n\n\n\nLeaf texture: soft \n\n\n\n5 2.08 \n\n\n\n\n\n\n\nFresh weight: 82.52g \nMaturity \u2265 35 days \n\n\n\nVitamin C (mg/100g FW): 19.28 \nAntioxidant content (%): 42.13 \n\n\n\nLeaf texture: very crunchy \n\n\n\nPC10 \n \n\n\n\nPC3 \n \n\n\n\nPC 5 \n \n\n\n\n\nhttps://www.ncbi.nlm.nih.gov/pubmed/?term=Vidales-Contreras%20JA%5BAuthor%5D&cauthor=true&cauthor_uid=28018386\n\n\nhttps://onlinelibrary.wiley.com/action/doSearch?ContribAuthorRaw=Roberts%2C+Joe+M\n\n\nhttps://onlinelibrary.wiley.com/action/doSearch?ContribAuthorRaw=Bruce%2C+Toby+J+A\n\n\nhttps://onlinelibrary.wiley.com/action/doSearch?ContribAuthorRaw=Monaghan%2C+James+M\n\n\nhttps://onlinelibrary.wiley.com/action/doSearch?ContribAuthorRaw=Pope%2C+Tom+W\n\n\nhttps://onlinelibrary.wiley.com/action/doSearch?ContribAuthorRaw=Pope%2C+Tom+W\n\n\nhttps://onlinelibrary.wiley.com/action/doSearch?ContribAuthorRaw=Leather%2C+Simon+R\n\n\nhttps://onlinelibrary.wiley.com/action/doSearch?ContribAuthorRaw=Beacham%2C+Andrew+M\n\n\nhttps://onlinelibrary.wiley.com/toc/17447348/2020/176/3\n\n\n\n\n\n\nMalaysian Journal of Genetics (MJG) | Vol. 2: 12 2022 \n\n\n\n\u00a9 by Persatuan Genetik Malaysia, 2022, e-ISSN: 2811-3594 Page 81 of 81 \n\n\n\n\n\n\n\n\n\n\n\nVan Gerrewey, T.; Boon, N.; Geelen, D. 2022. Vertical \nFarming: The Only Way Is Up?. Agronomy 2022, 12, 2. \nhttps://doi.org/10.3390/ agronomy12010002 \n\n\n\nWent W.  1949 THE PHYTOTRON Frits 1949 \nhttp://calteches.library.caltech.edu/1008/1/Phytotro\nn.pdf \n\n\n\n\n\n\n\nAppendix \nMean of several characters measured among 13 pak choy varieties \n\n\n\nVariety Fresh \nweight (g) \n\n\n\nNumber of \nleaves \n\n\n\nAntioxidant \ncontent \n\n\n\nInhibition of \nDPPH \n\n\n\n(%) \n\n\n\nVitamin C content \n(mg/100g FW) \n\n\n\n\n\n\n\nLeaves \ntexture (N) \n\n\n\n\n\n\n\nPC1 102.8c 13.9a 41.8ef 14.4f 8.1e \n\n\n\nPC2 77.3de 13.0a 54.6bc 32.6c 7.2e \n\n\n\nPC3 82.5cde 11.5bcd 42.1ef 19.3e 16.5bc \n\n\n\nPC4 62.5e 12.8ab 76.5a 2.9h 7.8e \n\n\n\nPC5 149.28b 10.2de 23.8h 14.9f 9.8de \n\n\n\nPC6 61.8e 9.6e 61.4b 44.8a 21.9a \n\n\n\nPC7 202.6a 13.1a 46.0de 32.8c 8.5de \n\n\n\nPC8 101.6c 13.4a 42.8ef 23.5d 8.1e \n\n\n\nPC9 90.2cd 10.7de 42.0ef 18.3e 11.3cde \n\n\n\nPC10 84.1cde 12.6 abc 38.1g 34.0c 12.7cde \nPC11 80.9cde 11.25cd 35.5g 46.3a 14.2cd \n\n\n\nPC12 97.0cd 13.1a 50.6cd 3.8g 20.8ab \n\n\n\nPC14 96.6cd 10.1de 37.5g 38.2b 11.1cde \n\n\n\nF-Test \nSignificant \n\n\n\n** ** ** ** ** \n\n\n\n \n\n\n\n\n\n\n \n*Correspondence: fadzilah@mardi.gov.my\n\n\n \nAres G., Ha B. and Jaeger S. R. 2021. Consumer attitudes to vertical farming (indoor plant factory with artificial lighting) in China, Singapore, UK, and USA: A multi-method study Food Research International 150 (2021) 110811\n\n\n\n\nLi S. and Kallas Z. 2021. Meta-analysis of consumers' willingness to pay for sustainable food products. Appetite. Volume 163, 1 August 2021, 105239\n\n\nLuna-Maldonado A., Vidales-Contreras J.A and Rodr\u00edguez-Fuentes H. 2016. Advances and Trends in Development of Plant Factories. Front Plant Sci 7: 1848 doi: 10.3389/fpls.2016.01848\n\n\nRoberts J. M. , Bruce T. J. A. , Monaghan J. M. , Pope T. W. , Leather  S. R. , Beacham A. 2020. Vertical farming systems bring new considerations for pest and disease management. Annals of Applied Biology Volume176, Issue3 Pages 226-232 https://doi.o...\n\n\nSarip J. 2019. Pembangunan Klon Rambutan Mutiara Merah dan Mutiara Wangi Inovasi Masa Hadapan. Syarahan Perdana 21 November 2019 Dewan Tan Sri Yusof Hashim, Ibu Pejabat MARDI\n\n\n\n"