Genome-wide identification of SNPs and copy number variation in common bean (Phaseolus vulgaris L.) using genotyping-by-sequencing (GBS)
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Next-generation sequencing technologies have increased markedly the throughput of genetic studies, allowing the identification of several thousands of SNPs within a single experiment. Even though sequencing cost is rapidly decreasing, the price for whole-genome re-sequencing of a large number of individuals is still costly, especially in plants with a large and highly redundant genome. In recent years, several reduced representation library approaches have been developed for reducing the sequencing cost per individual. Among them, genotyping-by-sequencing (GBS) represents a simple, cost-effective, and highly multiplexed alternative for species with or without an available reference genome. However, this technology requires specific optimization for each species, especially for the restriction enzyme (RE) used. Here we report on the application of GBS in a test experiment with 18 genotypes of wild and domesticated Phaseolus vulgaris. After an in silico digestion with different RE of the P. vulgaris genome reference sequence, we selected CviAII as the most suitable RE for GBS in common bean based on the high frequency and even distribution of restriction sites. A total of 44,875 SNPs, 1940 deletions, and 1693 insertions were identified, with 50 % of the variants located in genic sequences and tagging 11,027 genes. SNP and InDel distributions were positively correlated with gene density across the genome. In addition, we were able to also identify putative copy number variations of genomic segments between different genotypes. In conclusion, GBS with the CviAII enzyme results in thousands of evenly spaced markers and provides a reliable, high-throughput, and cost-effective approach for genotyping both wild and domesticated common beans.
KeywordsCommon bean Copy number variation (CNV) Genome-wide SNPs calling Genotyping-by-sequencing (GBS) Next-generation sequencing
This work used the Vincent J. Coates Genomics Sequencing Laboratory at UC Berkeley, supported by NIH S10 Instrumentation Grants S10RR029668 and S10RR027303. This project was supported by Agriculture and Food Research Initiative (AFRI) Competitive Grant No. 2013-67013-21224 from the USDA National Institute of Food and Agriculture.
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