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Different sets of QTLs influence fitness variation in yeast
Most of the phenotypes in nature are complex and are determined by many quantitative trait loci (QTLs). In this study we identify gene sets that contribute to one important complex trait: the ability of yeast cells to survive under alkali stress. We carried out an in-lab evolution (ILE) experiment,...
Autores principales: | , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
European Molecular Biology Organization
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2835564/ https://www.ncbi.nlm.nih.gov/pubmed/20160707 http://dx.doi.org/10.1038/msb.2010.1 |
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author | Romano, Gal Hagit Gurvich, Yonat Lavi, Ofer Ulitsky, Igor Shamir, Ron Kupiec, Martin |
author_facet | Romano, Gal Hagit Gurvich, Yonat Lavi, Ofer Ulitsky, Igor Shamir, Ron Kupiec, Martin |
author_sort | Romano, Gal Hagit |
collection | PubMed |
description | Most of the phenotypes in nature are complex and are determined by many quantitative trait loci (QTLs). In this study we identify gene sets that contribute to one important complex trait: the ability of yeast cells to survive under alkali stress. We carried out an in-lab evolution (ILE) experiment, in which we grew yeast populations under increasing alkali stress to enrich for beneficial mutations. The populations acquired different sets of affecting alleles, showing that evolution can provide alternative solutions to the same challenge. We measured the contribution of each allele to the phenotype. The sum of the effects of the QTLs was larger than the difference between the ancestor phenotype and the evolved strains, suggesting epistatic interactions between the QTLs. In parallel, a clinical isolated strain was used to map natural QTLs affecting growth at high pH. In all, 17 candidate regions were found. Using a predictive algorithm based on the distances in protein-interaction networks, candidate genes were defined and validated by gene disruption. Many of the QTLs found by both methods are not directly implied in pH homeostasis but have more general, and often regulatory, roles. |
format | Text |
id | pubmed-2835564 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | European Molecular Biology Organization |
record_format | MEDLINE/PubMed |
spelling | pubmed-28355642010-03-11 Different sets of QTLs influence fitness variation in yeast Romano, Gal Hagit Gurvich, Yonat Lavi, Ofer Ulitsky, Igor Shamir, Ron Kupiec, Martin Mol Syst Biol Article Most of the phenotypes in nature are complex and are determined by many quantitative trait loci (QTLs). In this study we identify gene sets that contribute to one important complex trait: the ability of yeast cells to survive under alkali stress. We carried out an in-lab evolution (ILE) experiment, in which we grew yeast populations under increasing alkali stress to enrich for beneficial mutations. The populations acquired different sets of affecting alleles, showing that evolution can provide alternative solutions to the same challenge. We measured the contribution of each allele to the phenotype. The sum of the effects of the QTLs was larger than the difference between the ancestor phenotype and the evolved strains, suggesting epistatic interactions between the QTLs. In parallel, a clinical isolated strain was used to map natural QTLs affecting growth at high pH. In all, 17 candidate regions were found. Using a predictive algorithm based on the distances in protein-interaction networks, candidate genes were defined and validated by gene disruption. Many of the QTLs found by both methods are not directly implied in pH homeostasis but have more general, and often regulatory, roles. European Molecular Biology Organization 2010-02-16 /pmc/articles/PMC2835564/ /pubmed/20160707 http://dx.doi.org/10.1038/msb.2010.1 Text en Copyright © 2010, EMBO and Macmillan Publishers Limited https://creativecommons.org/licenses/by-nc-sa/3.0/This is an open-access article distributed under the terms of the Creative Commons Attribution Licence, which permits distribution and reproduction in any medium, provided the original author and source are credited. Creation of derivative works is permitted but the resulting work may be distributed only under the same or similar licence to this one. This licence does not permit commercial exploitation without specific permission. |
spellingShingle | Article Romano, Gal Hagit Gurvich, Yonat Lavi, Ofer Ulitsky, Igor Shamir, Ron Kupiec, Martin Different sets of QTLs influence fitness variation in yeast |
title | Different sets of QTLs influence fitness variation in yeast |
title_full | Different sets of QTLs influence fitness variation in yeast |
title_fullStr | Different sets of QTLs influence fitness variation in yeast |
title_full_unstemmed | Different sets of QTLs influence fitness variation in yeast |
title_short | Different sets of QTLs influence fitness variation in yeast |
title_sort | different sets of qtls influence fitness variation in yeast |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2835564/ https://www.ncbi.nlm.nih.gov/pubmed/20160707 http://dx.doi.org/10.1038/msb.2010.1 |
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