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Characterization of genetic diversity, population structure, and linkage disequilibrium is a prerequisite for proper management of breeding programs and conservation of genetic resources. In this study, 186 chickpea genotypes, including advanced “Kabuli” breeding lines and Iranian landrace “Desi” chickpea genotypes, were genotyped using DArTseq-Based single nucleotide polymorphism (SNP) markers. Out of 3339 SNPs, 1152 markers with known chromosomal position were selected for genome diversity analysis. The number of mapped SNP markers varied from 52 (LG8) to 378 (LG4), with an average of 144 SNPs per linkage group. The chromosome size that was covered by SNPs varied from 16,236.36 kbp (LG8) to 67,923.99 kbp (LG5), while LG4 showed a higher number of SNPs, with an average of 6.56 SNPs per Mbp. Polymorphism information content (PIC) value of SNP markers ranged from 0.05 to 0.50, with an average of 0.32, while the markers on LG4, LG6, and LG8 showed higher mean PIC value than average. Unweighted neighbor joining cluster analysis and Bayesian-based model population structure grouped chickpea genotypes into four distinct clusters. Principal component analysis (PCoA) and discriminant analysis of principal component (DAPC) results were consistent with that of the cluster and population structure analysis. Linkage disequilibrium (LD) was extensive and LD decay in chickpea germplasm was relatively low. A few markers showed r2 ≥ 0.8, while 2961 pairs of markers showed complete LD (r2 = 1), and a huge LD block was observed on LG4. High genetic diversity and low kinship value between pairs of genotypes suggest the presence of a high genetic diversity among the studied chickpea genotypes. This study also demonstrates the efficiency of DArTseq-based SNP genotyping for large-scale genome analysis in chickpea. The genotypic markers provided in this study are useful for various association mapping studies when combined with phenotypic data of different traits, such as seed yield, abiotic, and biotic stresses, and therefore can be efficiently used in breeding programs to improve chickpea.

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Different methods have been developed to estimate of genotype by environment interaction (GEI) in crop plants. In this study, 14 kabuli type chickpea genotypes were assessed for seed yield in four stations over three successive years (2010)(2011)(2012)(2013) at west highlands of Iran. Randomized complete block design was used in all test environments with four replicates. Combined analysis of variance for seed yield revealed significant differences between genotypes, locations, and interaction between these two sources. The mean seed yield of genotypes averaged over environments showed that V4 and V2 had the highest (1163.58 kg ha -1 ) and the lowest seed yield (759.07 kg ha -1 ), respectively. Significant GE interaction implied that chickpea genotypes had various responses to different environments and, the stability analysis could be performed. To investigate GEI and identify the best performing stable genotypes, several stability parameters were employed. According to Wricke's ecovalance, stability variance, Plaisted method, and genotypic stability V5, V8 and V3 were the most stable genotypes. Based on CV, regression coefficient and MS(GE), V1 and V5 found to be stable and adapted to diverse environments, and the other genotypes distributed among stability statistics. Based on the AMMI biplot, 12 test environments divided into two mega environments. These mega environments included very cold districts like Maragheh and similar areas, and relatively softened regions of Kurdistan and similar environments. For these two mega environments, V6 and V4 showed more adaptability, respectively. In conclusion, the two genotypes, V4 (FLIP 00-39C) and V6 (FLIP 99-26C) could be recommended as new cultivars to chickpea farmers for autumn sowing in west areas of Iran.