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

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, p...

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Detalles Bibliográficos
Autores principales: Zhang, Zhi, Jung, Paul P, Grouès, Valentin, May, Patrick, Linster, Carole, Glaab, Enrico
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6571488/
https://www.ncbi.nlm.nih.gov/pubmed/31141611
http://dx.doi.org/10.1093/gigascience/giz060
Descripción
Sumario: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.