DOI: 10.5061/dryad.c59zw3rhk
title: Multi-locus genome-wide association study for grain yield and drought tolerance indices in sorghum accessions

description: Drought is a significant factor that causes yield loss in essential cereal
 crops such as sorghum (Sorghum bicolor (L.) Moench), necessitating the
 development of drought-tolerant varieties adaptable to various water
 conditions. This study aimed to pinpoint drought-tolerant sorghum lines
 and genomic regions for tolerance by utilizing 216 sorghum accessions in
 stressed and non-stressed environments at two locations. Genetic diversity
 was evident among accessions in terms of grain yield under different
 watering regimes. Drought stress indices such as the stress tolerance
 index, mean Productivity, geometric mean productivity, harmonic mean
 productivity, Yield Stability Index and Yield Index were identified as
 effective measures for selecting drought-tolerant sorghum. Cluster
 analysis classified genotypes into four groups based on their association
 with grain yield, highlighting Acc#28546 and Acc#216739 as highly drought
 tolerant across environments. This study identified 32 and 22 Quantitative
 trait nucleotides (QTNs) for drought indices and grain yield under stress
 and non-stress conditions, respectively, at two locations, with five
 common QTNs linked to multiple drought indices. Colocation analysis
 revealed that these QTNs were associated with known stay-green-related
 QTLs, and 47 putative genes near these QTNs potentially influenced drought
 tolerance traits. It is suggested that accession selection considers
 multiple indices for robust evaluation. Understanding the identified genes
 and their functions provides insights into the genetic mechanisms
 governing plant responses to drought stress, offering prospects for
 developing improved drought-resistant sorghum varieties through further
 genetic research.S.
description: The field experiment was conducted at two sites at the Ethiopia
 Institute of Agricultural Research: the Melkassa Agricultural Research
 Center (MARC) and the Werer Agricultural Research Center (WARC). The MARC
 is situated at a latitude of 8<sup>0 </sup>24’ 985” N and a
 longitude of 39<sup>0</sup> 19’ 185” 9E, with an altitude of
 1550 m above sea level. The WARC is located at a latitude of
 9<sup>0</sup> 22’’ N and a longitude of
 40<sup>0</sup> 11’’ E at an altitude of 750 m above sea level.
 Both areas are recognized as semiarid and drought prone regions. These
 sites were selected for the study due to their historical weather data
 indicating low rainfall, in addition to the presence of well-organized
 irrigation facilities. Genomic DNA (gDNA) was then
 extracted from the frozen tissues following the CTAB protocol with some
 modifications (Rogers and Bendich,
 1985). The gDNA samples were subsequently subjected to DNA
 sequencing through genotyping by sequencing technology using DArTseqTM
 technology. This process was carried out via the Integrated Genotype
 Service and Support platform in Nairobi, Kenya, utilizing a combination of
 DArT complexity reduction methods and next-generation sequencing protocols
 described in the works of Elshire et
 al. (2011) and Kilian et
 al. (2012). The complexity reduction method involved digestion
 with the methylation-sensitive restriction enzyme PstI, along with the use
 of frequently cutting enzymes such as AluI, BstNI, TaqI, or MseI. PCR
 adapters were subsequently ligated to the PstI fragment ends, followed by
 PCR amplification using primers complementary to the PstI adapters. Only
 fragments with PstI adapters at both ends were amplified. DNA fragments
 were digested, ligated to adapters, and amplified via PCR (Kilian et al., 2012). Sequencing
 was performed on an Illumina HiSeq 2000 platform using a single-read
 strategy with 77 cycles. The resulting sequence data was analyzed using
 the DArT (Diversity Arrays Technology, Kenya) analytical pipelines (Barilli et al., 2018). The primary
 pipeline employed stringent quality control measures, filtering out
 low-quality sequences based on barcode region characteristics.  Unique
 sequences per sample were then used for marker calling. Subsequently, the
 data was processed through the secondary pipeline, which utilized DArT
 P/L's proprietary SNP calling algorithms (DArTsoftseq). Finally, the
 SNP markers were identified with reference to the genome of Sorghum
 bicolor V3.1.
description: # Multi-locus Genome-wide Association Study for Grain Yield and Drought
 Tolerance Indices in Sorghum Accessions
 [https://doi.org/10.5061/dryad.c59zw3rhk](https://doi.org/10.5061/dryad.c59zw3rhk) The `Hapmap_200_edited.txt` contains 17638 SNP markers generated from 216 sorghum accessions. `Mlk_induces.xlsx` contains grain yield under both well-water and water stress and drought indices estimated from grain yield. Abbreviations * Ys = Yield mean of each accession under water-stress condition (kg/ha) * Yi = Yield mean of each accession under well-water condition (kg/ha) * SSI=Stress Susceptible index * STI=Stress tolerance index * MP=Mean Productivity * TOL=Tolerance index * GMP=Geometric Mean Productivity * HMP=Harmonic Mean Productivity * YR=Yield reduction ratio * YSI=Yield Stability Index * Genotype codes * YL=Yield index | code | Genotype Name | | :--- | :-------------- | | G1 | Acc#220236 | | G2 | Acc#20710 | | G3 | Acc#220244 | | G4 | Acc#220240 | | G5 | Acc#26110 | | G6 | Acc#30318 | | G7 | Acc#31681 | | G8 | Acc#220018 | | G9 | Melkam | | G10 | Malt sorghum#9 | | G11 | Acc#235804 | | G12 | Acc#235794 | | G13 | Acc#220265 | | G14 | Acc#15964 | | G15 | Acc#220246 | | G16 | Acc#19615 | | G17 | Acc#235817 | | G18 | B-35 | | G19 | Acc#30317 | | G20 | Malt sorghum#10 | | G21 | Malt sorghum#2 | | G22 | Malt sorghum#7 | | G23 | Malt sorghum#5 | | G24 | Malt sorghum#4 | | G25 | Malt sorghum#8 | | G26 | Malt sorghum3 | | G27 | Acc#20205 | | G28 | Acc#69212 | | G29 | Acc#235793 | | G30 | Acc#211022 | | G31 | Acc#220253 | | G32 | Acc#5622 | | G33 | Acc#220281 | | G34 | Acc#235808 | | G35 | Acc#220010 | | G36 | Acc#238440 | | G37 | Acc#6928 | | G38 | Acc#235814 | | G39 | Acc#220277 | | G40 | Acc#234089 | | G41 | Acc#235803 | | G42 | Acc#238442 | | G43 | Acc#24083 | | G44 | Acc#231230 | | G45 | Acc#6094 | | G46 | Acc#235792 | | G47 | Acc#234066 | | G48 | Acc#220250 | | G49 | Acc#220279 | | G50 | Acc#220256 | | G51 | Acc#234113 | | G52 | Acc#220243 | | G53 | Acc#9911 | | G54 | Acc#22239 | | G55 | Acc#234070 | | G56 | Acc#220251 | | G57 | Acc#220264 | | G58 | Acc#15443 | | G59 | Acc#7125 | | G60 | Acc#23178 | | G61 | Acc#220237 | | G62 | Acc#27919 | | G63 | Acc#20681 | | G64 | Acc#2814 | | G65 | Acc#29310 | | G66 | Acc#25442 | | G67 | Acc#238431 | | G68 | Acc#235812 | | G69 | Acc#20762 | | G70 | Acc#30503 | | G71 | Acc#25596 | | G72 | Acc#27599 | | G73 | Acc#220012 | | G74 | Acc#15526 | | G75 | Acc#220262 | | G76 | Acc#23644 | | G77 | Acc#11119 | | G78 | Acc#22334 | | G79 | Acc#2416 | | G80 | Acc#29977 | | G81 | Acc#222285 | | G82 | Acc#22040 | | G83 | Acc#28548 | | G84 | Acc#23053 | | G85 | Acc#28547 | | G86 | Acc#220266 | | G87 | Acc#235798 | | G88 | Acc#234110 | | G89 | Acc#19627 | | G90 | Acc#220260 | | G91 | Acc#6723 | | G92 | Acc#30001 | | G93 | Acc#28551 | | G94 | Acc#220270 | | G95 | Acc#227091 | | G96 | Acc#28556 | | G97 | Acc#22074 | | G98 | Acc#16044 | | G99 | Acc#20387 | | G100 | Acc#28550 | | G101 | Acc#20713 | | G102 | Acc#220274 | | G103 | Acc#20700 | | G104 | Acc#69571 | | G105 | Acc#28546 | | G106 | Acc#30469 | | G107 | Acc#220255 | | G108 | Acc#20727 | | G109 | Acc#220249 | | G110 | Acc#216739 | | G111 | Acc#220272 | | G112 | Acc#9713 | | G113 | Acc#220261 | | G114 | Acc#29409 | | G115 | Acc#20665 | | G116 | Acc#20351 | | G117 | Acc#19262 | | G118 | Acc#220242 | | G119 | Acc#216736 | | G120 | Acc#20749 | | G121 | Acc#2848 | | G122 | Acc#238444 | | G123 | Acc#30898 | | G124 | Acc#32087 | | G125 | Acc#10978 | | G126 | Acc#29876 | | G127 | Acc#3583 | | G128 | Acc#10234 | | G129 | Acc#9577 | | G130 | Acc#222888 | | G131 | Acc#19053 | | G132 | Acc#235811 | | G133 | Acc#69573 | | G134 | Acc#220269 | | G135 | Acc#22291 | | G136 | Acc#28545 | | G137 | Acc#220238 | | G138 | Acc#1127 | | G139 | Acc#234102 | | G140 | Kem Kem | | G141 | Acc#3443 | | G142 | Acc#36524 | | G143 | Acc#3675 | | G144 | Acc#234115 | | G145 | Acc#239130 | | G146 | Acc#10876 | | G147 | Acc#235810 | | G148 | Acc#29375 | | G149 | Acc#31852 | | G150 | Acc#220254 | | G151 | Acc#220247 | | G152 | Acc#220267 | | G153 | Acc#23601 | | G154 | Acc#220252 | | G155 | Acc#23635 | | G156 | Acc#26833 | | G157 | Acc#3073 | | G158 | Acc#220227 | | G159 | Acc#2787 | | G160 | Acc#216744 | | G161 | Wedi Aker | | G162 | Acc#15752 | | G163 | Acc#14963 | | G164 | Acc#220278 | | G165 | Acc#28740 | | G166 | Acc#227085 | | G167 | Acc#220248 | | G168 | Acc#235791 | | G169 | Acc#9830 | | G170 | Acc#8218 | | G171 | Acc#220275 | | G172 | Acc#28991 | | G173 | Acc#6193 | | G174 | Acc#7463 | | G175 | Acc#9600 | | G176 | Acc#235813 | | G177 | Acc#220257 | | G178 | Acc#230065 | | G179 | Acc#235807 | | G180 | Acc#220276 | | G181 | Acc#20697 | | G182 | Acc#22330 | | G183 | Girana-1 | | G184 | Acc#220241 | | G185 | Acc#25702 | | G186 | Acc#20842 | | G187 | Acc#234101 | | G188 | Acc#220268 | | G189 | Acc#36633 | | G190 | Acc#220259 | | G191 | Acc#33173 | | G192 | Acc#220013 | | G193 | Acc#28688 | | G194 | Acc#220250 | | G195 | Acc#2398 | | G196 | Acc#220273 | | G197 | Acc#29911 | | G198 | Acc#235790 | | G199 | Acc#15428 | | G200 | Acc#13845 | | G201 | Acc#30175 | | G202 | Acc#238447 | | G203 | Acc#19126 | | G204 | Acc#28557 | | G205 | Acc#2262 | | G206 | Acc#27287 | | G207 | Acc#31693 | | G208 | Acc#30619 | | G209 | Acc#23637 | | G210 | Acc#23650 | | G211 | Acc#22506 | | G212 | Acc#3121 | | G213 | Acc#220001 | | G214 | Acc#19847 | | G215 | Acc#28549 | | G216 | Acc#69568 |