Abstract
Summary With the advance of next-generation sequencing (NGS) technologies and reductions in the costs of these techniques, bulked segregant analysis (BSA) has become not only a powerful tool for mapping quantitative trait loci (QTL) but also a useful way to identify causal gene mutations underlying phenotypes of interest. However, due to the presence of background mutations and errors in sequencing, genotyping, and reference assembly, it is often difficult to distinguish true causal mutations from background mutations. In this study, we developed the BSAseq workflow, which includes an automated bioinformatics analysis pipeline with a probabilistic model for estimating the segregation region and an interactive Shiny web application for visualizing the results. We deeply sequenced a male sterile parental line (ms8) to capture the majority of background mutations in our bulked F2 data. We applied the workflow to 11 bulked F2 populations and identified the true causal mutation in each population. The workflow is intuitive and straightforward, facilitating its adoption by users without bioinformatics analysis skills. We anticipate that BSAseq will be broadly applicable to the identification of causal mutations for many phenotypes of interest.
Availability BSAseq is freely available on https://www.sciapps.org/page/bsa
Contact liya.wang{at}cshl.edu, ware{at}cshl.edu, zhanguo.xin{at}ars.usda.gov
