SNP discovery in common bean by restriction-associated DNA (RAD) sequencing for genetic diversity and population structure analysis.

Abstract

Researchers have made great advances into the development and application of genomic approaches for common beans, creating opportunities to driving more real and applicable strategies for sustainable management of the genetic resource towards plant breeding. This work provides useful polymorphic single-nucleotide polymorphisms (SNPs) for high-throughput common bean genotyping developed by RAD (restriction site-associated DNA) sequencing. The RAD tags were generated from DNA pooled from 12 common bean genotypes, including breeding lines of different gene pools and market classes. The aligned sequences identified 23,748 putative RAD-SNPs, of which 3357 were adequate for genotyping; 1032 RAD-SNPs with the highest ADT (assay design tool) score are presented in this article. The RAD-SNPs were structurally annotated in different coding (47.00%) and non-coding (53.00%) sequence components of genes. A subset of 384 RAD-SNPs with broad genome distribution was used to genotype a diverse panel of 95 common bean germplasms and revealed a successful amplification rate of 96.6%, showing 73% of polymorphic SNPs within the Andean group and 83% in the Mesoamerican group. A slightly increased He (0.161, n=21) value was estimated for the Andean gene pool, compared to the Mesoamerican group (0.156, n=74). For the linkage disequilibrium (LD) analysis, from a group of 580 SNPs (289 RAD-SNPs and 291 BARC-SNPs) genotyped for the same set of genotypes, 70.2% were in LD, decreasing to 0.10%in the Andean group and 0.77% in the Mesoamerican group. Haplotype patterns spanning 310Mb of the genome (60%) were characterized in samples from different origins. However, the haplotype frameworks were under-represented for the Andean (7.85%) and Mesoamerican (5.55%) gene pools separately. In conclusion, RAD sequencing allowed the discovery of hundreds of useful SNPs for broad genetic analysis of common bean germplasm. From now, this approach provides an excellent panel of molecular tools for whole genome analysis, allowing integrating and better exploring the common bean breeding practices.