Genome-wide single nucleotide polymorphism and Insertion-Deletion discovery through next-generation sequencing of reduced representation libraries in common bean

Citation

Zou, X., Shi, C., Austin, R.S., Merico, D., Munholland, S., Marsolais, F., Navabi, A., Crosby, W.L., Pauls, K.P., Yu, K., Cui, Y. (2014). Genome-wide single nucleotide polymorphism and Insertion-Deletion discovery through next-generation sequencing of reduced representation libraries in common bean. Molecular Breeding, [online] 33(4), 769-778. http://dx.doi.org/10.1007/s11032-013-9997-7

Abstract

Single nucleotide polymorphisms (SNPs) and insertions-deletions (InDels) are valuable molecular markers for genomics and genetics studies and molecular breeding. The advent of next-generation sequencing techniques has enabled researchers to approach high-throughput and cost-effective SNP and InDel discovery on a genomic scale. In this report, 36 common bean genotypes grown in Canada were used to construct reduced representation libraries for next-generation sequencing. Using 76 million sequence reads generated by the Illumina HiSeq 2000 Sequencing System, we identified a total of 43,698 putative SNPs and 1,267 putative InDels. Of the SNPs, 43,504 were bi-allelic and 194 were tri-allelic, and the InDels comprised 574 insertions and 693 deletions. The putative bi-allelic SNPs were distributed across all 11 chromosomes with the highest number of SNPs observed in chromosome 2 (4,788), and the lowest in chromosome 10 (2,941). With the aid of the recent release of the first chromosome-scale version of Phaseolus vulgaris, 24,907 bi-allelic SNPs, 79 tri-allelic SNPs, 315 insertions, and 377 deletions were located in 8,758, 77, 273, and 364 genes, respectively. Among these 24,907 bi-allelic SNPs, 7,168 nonsynonymous bi-allelic SNPs were identified within 36 common bean genotypes that were located in 4,303 genes. A total of 113 putative SNPs were randomly chosen for validation using high-resolution melt analysis. Of the 113 candidate SNPs, 105 (92.9 %) contained the predicted SNPs. © 2013 Springer Science+Business Media Dordrecht.