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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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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
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author Zhang, Zhi
Jung, Paul P
Grouès, Valentin
May, Patrick
Linster, Carole
Glaab, Enrico
author_facet Zhang, Zhi
Jung, Paul P
Grouès, Valentin
May, Patrick
Linster, Carole
Glaab, Enrico
author_sort Zhang, Zhi
collection PubMed
description 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.
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spelling pubmed-65714882019-06-19 BSA4Yeast: Web-based quantitative trait locus linkage analysis and bulk segregant analysis of yeast sequencing data Zhang, Zhi Jung, Paul P Grouès, Valentin May, Patrick Linster, Carole Glaab, Enrico Gigascience Technical Note 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. Oxford University Press 2019-05-29 /pmc/articles/PMC6571488/ /pubmed/31141611 http://dx.doi.org/10.1093/gigascience/giz060 Text en © The Author(s) 2019. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Technical Note
Zhang, Zhi
Jung, Paul P
Grouès, Valentin
May, Patrick
Linster, Carole
Glaab, Enrico
BSA4Yeast: Web-based quantitative trait locus linkage analysis and bulk segregant analysis of yeast sequencing data
title BSA4Yeast: Web-based quantitative trait locus linkage analysis and bulk segregant analysis of yeast sequencing data
title_full BSA4Yeast: Web-based quantitative trait locus linkage analysis and bulk segregant analysis of yeast sequencing data
title_fullStr BSA4Yeast: Web-based quantitative trait locus linkage analysis and bulk segregant analysis of yeast sequencing data
title_full_unstemmed BSA4Yeast: Web-based quantitative trait locus linkage analysis and bulk segregant analysis of yeast sequencing data
title_short BSA4Yeast: Web-based quantitative trait locus linkage analysis and bulk segregant analysis of yeast sequencing data
title_sort bsa4yeast: web-based quantitative trait locus linkage analysis and bulk segregant analysis of yeast sequencing data
topic Technical Note
url 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
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