Combining SNP discovery from next-generation sequencing data with bulked segregant analysis (BSA) to fine-map genes...

Next generation sequencing (NGS) technologies are providing new ways to accelerate fine-mapping and gene isolation in many species. To date, the majority of these efforts have focused on diploid organisms with readily available whole genome sequence information. In this study, as a proof of concept, we tested the use of NGS for SNP discovery in tetraploid wheat lines differing for the previously cloned grain protein content (GPC) gene GPC-B1. Bulked segregant analysis (BSA) was used to define a subset of putative SNPs within the candidate gene region, which were then used to fine-map GPC-B1.

We used Illumina paired end technology to sequence mRNA (RNAseq) from near isogenic lines differing across a ~30-cM interval including the GPC-B1 locus. After discriminating for SNPs between the two homoeologous wheat genomes and additional quality filtering, we identified inter-varietal SNPs in wheat unigenes between the parental lines. The relative frequency of these SNPs was examined by RNAseq in two bulked samples made up of homozygous recombinant lines differing for their GPC phenotype. SNPs that were enriched at least 3-fold in the corresponding pool (6.5% of all SNPs) were further evaluated. Marker assays were designed for a subset of the enriched SNPs and mapped using DNA from individuals of each bulk. Thirty nine new SNP markers, corresponding to 67% of the validated SNPs, mapped across a 12.2-cM interval including GPC-B1. This translated to 1 SNP marker per 0.31 cM defining the GPC-B1 gene to within 13-18 genes in syntenic cereal genomes and to a 0.4 cM interval in wheat.

This study exemplifies the use of RNAseq for SNP discovery in polyploid species and supports the use of BSA as an effective way to target SNPs to specific genetic intervals to fine-map genes in unsequenced genomes.