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Divergent patterns of selection on metabolite levels and gene expression

BACKGROUND: Natural selection can act on multiple genes in the same pathway, leading to polygenic adaptation. For example, adaptive changes were found to down-regulate six genes involved in ergosterol biosynthesis—an essential pathway targeted by many antifungal drugs—in some strains of the yeast Sa...

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Autores principales: Kern, Alexander F., Yang, Grace Xiaolu, Khosla, Neil M., Ang, Roy Moh Lik, Snyder, Michael P., Fraser, Hunter B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8482673/
https://www.ncbi.nlm.nih.gov/pubmed/34587900
http://dx.doi.org/10.1186/s12862-021-01915-5
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author Kern, Alexander F.
Yang, Grace Xiaolu
Khosla, Neil M.
Ang, Roy Moh Lik
Snyder, Michael P.
Fraser, Hunter B.
author_facet Kern, Alexander F.
Yang, Grace Xiaolu
Khosla, Neil M.
Ang, Roy Moh Lik
Snyder, Michael P.
Fraser, Hunter B.
author_sort Kern, Alexander F.
collection PubMed
description BACKGROUND: Natural selection can act on multiple genes in the same pathway, leading to polygenic adaptation. For example, adaptive changes were found to down-regulate six genes involved in ergosterol biosynthesis—an essential pathway targeted by many antifungal drugs—in some strains of the yeast Saccharomyces cerevisiae. However, the impact of this polygenic adaptation on metabolite levels was unknown. Here, we performed targeted mass spectrometry to measure the levels of eight metabolites in this pathway in 74 yeast strains from a genetic cross. RESULTS: Through quantitative trait locus (QTL) mapping we identified 19 loci affecting ergosterol pathway metabolite levels, many of which overlap loci that also impact gene expression within the pathway. We then used the recently developed v-test, which identified selection acting upon three metabolite levels within the pathway, none of which were predictable from the gene expression adaptation. CONCLUSIONS: These data showed that effects of selection on metabolite levels were complex and not predictable from gene expression data. This suggests that a deeper understanding of metabolism is necessary before we can understand the impacts of even relatively straightforward gene expression adaptations on metabolic pathways. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12862-021-01915-5.
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spelling pubmed-84826732021-10-01 Divergent patterns of selection on metabolite levels and gene expression Kern, Alexander F. Yang, Grace Xiaolu Khosla, Neil M. Ang, Roy Moh Lik Snyder, Michael P. Fraser, Hunter B. BMC Ecol Evol Research BACKGROUND: Natural selection can act on multiple genes in the same pathway, leading to polygenic adaptation. For example, adaptive changes were found to down-regulate six genes involved in ergosterol biosynthesis—an essential pathway targeted by many antifungal drugs—in some strains of the yeast Saccharomyces cerevisiae. However, the impact of this polygenic adaptation on metabolite levels was unknown. Here, we performed targeted mass spectrometry to measure the levels of eight metabolites in this pathway in 74 yeast strains from a genetic cross. RESULTS: Through quantitative trait locus (QTL) mapping we identified 19 loci affecting ergosterol pathway metabolite levels, many of which overlap loci that also impact gene expression within the pathway. We then used the recently developed v-test, which identified selection acting upon three metabolite levels within the pathway, none of which were predictable from the gene expression adaptation. CONCLUSIONS: These data showed that effects of selection on metabolite levels were complex and not predictable from gene expression data. This suggests that a deeper understanding of metabolism is necessary before we can understand the impacts of even relatively straightforward gene expression adaptations on metabolic pathways. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12862-021-01915-5. BioMed Central 2021-09-29 /pmc/articles/PMC8482673/ /pubmed/34587900 http://dx.doi.org/10.1186/s12862-021-01915-5 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Kern, Alexander F.
Yang, Grace Xiaolu
Khosla, Neil M.
Ang, Roy Moh Lik
Snyder, Michael P.
Fraser, Hunter B.
Divergent patterns of selection on metabolite levels and gene expression
title Divergent patterns of selection on metabolite levels and gene expression
title_full Divergent patterns of selection on metabolite levels and gene expression
title_fullStr Divergent patterns of selection on metabolite levels and gene expression
title_full_unstemmed Divergent patterns of selection on metabolite levels and gene expression
title_short Divergent patterns of selection on metabolite levels and gene expression
title_sort divergent patterns of selection on metabolite levels and gene expression
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8482673/
https://www.ncbi.nlm.nih.gov/pubmed/34587900
http://dx.doi.org/10.1186/s12862-021-01915-5
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