A First Generation Hapmap of Chickpea for Mining Superior Alleles for Crop Improvement

Chickpea (Cicer arietinumL., 2n=16) is a self-pollinated and second most important food legume crop. It is primarily grown in developing countries and contributes to a larger part of human food and animal feed in these areas. Due to exposure of the crop to range of biotic and abiotic stresses, crop productivity is <1 ton per hectare. Because of a very narrow genetic diversity in the elite genepool, molecular breeding approaches have been quite challenging for crop improvement in chickpea. With an objective to understand genome architecture and genome dynamics as well as to mine the superior alleles for breeding traits in the elite cultivars of chickpea, a non-redundant set of 140 cultivars that includes 82 varieties released in India were subjected to whole genome re-sequencing (WGRS) on Illumina HiSeq 2000 platform. 5X-12X (with an average 7.3X) coverage WGRS data were generated for 129 lines and RAD sequence data (0.80X) were generated on 11 lines. Alignment of sequence data to the draft genome sequence of chickpea (Varshney et al. 2013, Nature Biotechnology 31:240-246) has provided >1.3 million SNPs in genome, >108 K in mRNA and >42 K in CDS regions. By using these structural variations (SNPs, Indels, PAVs, CNVs), a comprehensive analysis has been undertaken on LD decay and temporal diversity in terms of released varieties in different decades, as well as market type (desi and kabuli). HapMap analysis has provided large-scale variations in the gene sequences. These data will be useful to tag the genomic regions for traits of interest to breeders that may be applied for facilitating chickpea breeding.