Judul: Molecular Characterization of Resistance Banana Cultivars to Panama Wilt Disease Caused by Fusarium oxysporum f.sp. cubense
Abstrak: Sustainability of banana and plantain in Indonesia encounters the development of banana pests and diseases that dramatically decreased national banana production. Panama wilt disease caused by Fusarium oxysporum f.sp. cubense (FOC) is one of major banana diseases that infected almost all of banana plantation in Indonesia. A series of experiments were carried out to isolate, characterize resistance gene analogues (RGAs) and defense gene analogues (DGAs), and to develop molecular markers for disease resistance against fusarium wilt. The experiment was started by the assessment of resistance banana cultivars against FOC tropical race-4 (TR4), and selected two cultivars showed resistant to FOC i.e. Calcuta-4 and Klutuk Wulung. From those selected cultivars and one resistant cultivar, Rejang, 17 RGAs were isolated and characterized and showed high sequence identity to NBS-LRR. The RGA sequences were designated as MNBS1-MNBS17. Based on phylogenetic analysis, the RGAs were classified into four groups. First group contained 14 RGA sequences (MNBS1-MNBS14), and the other three groups contained one sequence MNBS15, MNBS16, and MNBS17, respectively. The isolation and characterization of DGA (chitinase and β-1,3-glucanase genes) were carried out using local banana cultivars. Eight putative chitinase sequences (586 bp in length) were isolated from Rejang, Klutuk Wulung, Kepok, Ambon Hijau and Barangan. The sequences were showed high identity (90 %) to banana class II chitinase gene and coded by MaChi. Four putative β-1,3- glucanase sequences (788 bp in length) were isolated and characterized from Rejang, Klutuk Wulung, Ambon Hijau and Barangan. The sequences shared 99 % identity to banana β-1,3-glucanase, and designated as MaGlu. Based on SNP identification, it was revealed that RGA sequences from Rejang (MNBS2-MNBS5) and Calcuta-4 (MNBS6-MNBS14) contained 16 and 9 putative SNPs, respectively. Based on SNP analysis, RGA sequences of Rejang and Calcuta-4 generated 4 and 8 haplotypes, respectively. Twenty two SNPs were identified from 8 chitinase fragments and generated 8 haplotypes, while 8 putative SNPs were identified from 4 β-1,3-glucanase fragments and generated 4 haplotypes. SNAP markers were developed based on non synonymous SNPs identified from RGA (MNBS) and DGA (chitinase and β-1,3-glucanase) sequences. Using PCR technique and allel specific primers approaches, 7 loci based on RGA and DGA sequences were selected as SNAP markers for FOC resistance banana cultivars, there were SNP4_MNBS, SNP2_MChi, SNP6_MChi, SNP8_MChi, SNP10_MChi, SNP11_MChi, and SNP1_MGlu. However, the use of SNP1_MGlu locus can be omitted, because without SNP1_MGlu primers, the grouping of banana cultivar base on FOC resistance will be better.
Keyword: DGA, haplotype, RGA, SNP, SNAP marker

Judul: Molecular Based Classification and Phylogenetic Analysis of Indonesian Banana Cultivars
Abstrak: Banana cultivars are complex hybrids and have been further modified by various mutations. The specific ancestor of the cultivars was difficult to be elucidated. Therefore, the taxonomic status and nomenclature have long been a complicated issue. The goals of the study were to characterize banana accessions from various regions in Indonesia based on microsatellite markers to obtain classification which is stable and accurate and to elucidate phylogenetic relationships of banana cultivars inferred from trnL-F intergenic spacer of cpDNA. The study was conducted using 151 accessions that have been morphologically classified and unclassified 116 accessions. Thirty nine accessions which represented various genomic groups and 12 sequences of different taxa of Musa downloaded from GenBank were used for phylogenetic analysis. Banana accessions were characterized using 12 microsatellite primers. Only 8 primers: MaCIR108; MaCIR332a; MaCIR327b; Ma-1-17; Ma-1-27; Ma-1-132; Ma-3-90; and Ma-3-139 produced clear alleles and exhibited polymorphic banding patterns. Total 267 banana accessions were effectively classified into 3 species based only on: 4 alleles of MaCIR108 with the size of more than 270 bp; alleles of MaCIR108 with the size of 270 bp or less; and 1 allele of Ma-3-90 with the size of 152 bp. There are 130 accessions of AA or AAA; and AAA designated under Musa acuminata, 10 accessions of BB designated under M. balbisiana, 64 accessions of AAB and 63 accessions of ABB designated under hybrid species M. x paradisiaca. Eleven accessions of pure the A genome and 9 accessions containing the B genome previously identified based on morphology have been reclassified into M. x paradisiaca and M. acuminata. The study also exhibited that microsatellites are an effective marker for identifying banana cultivars. Analysis of 267 banana accessions using the 8 primers detected only 208 genotypes because 88 accessions formed 29 identical genotypes. In general, the banana accessions clustered according to their genomic groups, except 15 accessions of AAB; accessions of AA or AAA; and AAA. In the phylogeny inferred from the trnL-F region, 40 accessions having the A-type chloroplast consisting of AA wild; AA; AA or AAA; AAA; AAB; and ABB cultivars were clearly differentiated from 11 accessions having the B-type chloroplast consisting of BB, AAB, and ABB cultivars. The A-type chloroplast accessions are most probably derived from female M. acuminata, while those with the B-type chloroplast may be derived from female M. balbisiana. However, the specific acuminata ancestor of each cultivar remains unidentified. Genetic relationships among banana accessions based on the trnL-F region are not in agreement with those based on the microsatellite most probably due to the differences of inheritance mode of both DNA markers.
Keyword: Genetic analysis diversity, Microsatelite, Filogeni, trnL-F Intergenic Spacer

Judul: Hamiltonian formulation for linear waves motion in two layers fluid
Abstrak: The surface wave could be considered as a wave that separates two fluids, namely water and air. Based on this assumption, it is introduced the interfacial wave, a wave between two layers of fluid with different density. The formulation of interfacial waves motion begins with deriving the base equation of irrotational ideal fluid. Furthermore, according to irrotational fluid assumption, the base equation can be stated in velocity potential. In this derivation, the fluids domain is assumed to be restricted by rigid lid boundary conditions, both at the upper and lower limit. Therefore, the interfacial waves motion can be explained in a hamiltonian formulation. In the hamiltonian formulation, total energy is defined as the sum of kinetic and potential energy. The hamiltonian system is obtained from reduction of kinetic energy by using the Dirichlet Neumann Operator. The resulted kinetic energy equation is nonlinear. Therefore, this form is linearized by first part of the Taylor expansion. This linearization gives a dispersion relation of linear wave. Based on this dispersion relation, the phase speed of the linear wave depends on the density ratio of the two layers fluid.
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