BSA4Yeast: Web-based quantitative trait locus linkage analysis and bulk segregant analysis of yeast sequencing data

• Published in: Gigascience Vol. 8; no. 6
• Main Authors: Zhang, Zhi, Jung, Paul P, Grouès, Valentin, May, Patrick, Linster, Carole, Glaab, Enrico
• Format: Journal Article
• Language: English
• Published: United States Oxford University Press 01.06.2019
• Subjects: Annotations; Applications programs; Chromosome Mapping - methods; Data processing; Gene mapping; Genetic diversity; Genetic Linkage; Genome, Fungal; High-Throughput Nucleotide Sequencing - methods; Internet; Linkage analysis; Mapping; Next-generation sequencing; Phenotypes; Quantitative Trait Loci; Saccharomyces cerevisiae - genetics; Software; Technical Note; Yeast; QTLs; BSA; mapping
• ISSN: 2047-217X; 2047-217X
• DOI: 10.1093/gigascience/giz060

Abstract Background Quantitative trait locus (QTL) mapping using bulk segregants is an effective approach for identifying genetic variants associated with phenotypes of interest in model organisms. By exploiting next-generation sequencing technology, the QTL mapping accuracy can be improved significantly, providing a valuable means to annotate new genetic variants. However, setting up a comprehensive analysis framework for this purpose is a time-consuming and error-prone task, posing many challenges for scientists with limited experience in this domain. Results Here, we present BSA4Yeast, a comprehensive web application for QTL mapping via bulk segregant analysis of yeast sequencing data. The software provides an automated and efficiency-optimized data processing, up-to-date functional annotations, and an interactive web interface to explore identified QTLs. Conclusions BSA4Yeast enables researchers to identify plausible candidate genes in QTL regions efficiently in order to validate their genetic variations experimentally as causative for a phenotype of interest. BSA4Yeast is freely available at https://bsa4yeast.lcsb.uni.lu.