RapamycinFungusV1, Main, Exploration, bibRecord, 000238

Shared Molecular Targets Confer Resistance over Short and Long Evolutionary Timescales.

Identifieur interne : 000238 ( Main/Exploration ); précédent : 000237; suivant : 000239

Shared Molecular Targets Confer Resistance over Short and Long Evolutionary Timescales.

Auteurs : Jing Li [France] ; Ignacio Vázquez-García [Royaume-Uni, États-Unis] ; Karl Persson [Suède] ; Asier González [Suisse] ; Jia-Xing Yue [France] ; Benjamin Barré [France] ; Michael N. Hall [Suisse] ; Anthony Long [États-Unis] ; Jonas Warringer [Suède] ; Ville Mustonen [Finlande] ; Gianni Liti [France]

Source :

Molecular biology and evolution [ 1537-1719 ] ; 2019.

RBID : pubmed:30657986

Descripteurs français

English descriptors

KwdEn :
- Biological Evolution (MeSH), Cell Cycle Proteins (genetics), Drug Resistance, Fungal (genetics), Hydroxyurea (MeSH), Mutation (MeSH), Phosphatidylinositol 3-Kinases (genetics), Quantitative Trait Loci (MeSH), Saccharomyces cerevisiae (genetics), Saccharomyces cerevisiae Proteins (genetics), Selection, Genetic (MeSH), Sirolimus (MeSH).
MESH :
- chemical , genetics : Cell Cycle Proteins, Phosphatidylinositol 3-Kinases, Saccharomyces cerevisiae Proteins.
- genetics : Drug Resistance, Fungal, Saccharomyces cerevisiae.
- Biological Evolution, Hydroxyurea, Mutation, Quantitative Trait Loci, Selection, Genetic, Sirolimus.

Abstract

Pre-existing and de novo genetic variants can both drive adaptation to environmental changes, but their relative contributions and interplay remain poorly understood. Here we investigated the evolutionary dynamics in drug-treated yeast populations with different levels of pre-existing variation by experimental evolution coupled with time-resolved sequencing and phenotyping. We found a doubling of pre-existing variation alone boosts the adaptation by 64.1% and 51.5% in hydroxyurea and rapamycin, respectively. The causative pre-existing and de novo variants were selected on shared targets: RNR4 in hydroxyurea and TOR1, TOR2 in rapamycin. Interestingly, the pre-existing and de novo TOR variants map to different functional domains and act via distinct mechanisms. The pre-existing TOR variants from two domesticated strains exhibited opposite rapamycin resistance effects, reflecting lineage-specific functional divergence. This study provides a dynamic view on how pre-existing and de novo variants interactively drive adaptation and deepens our understanding of clonally evolving populations.

DOI: 10.1093/molbev/msz006
PubMed: 30657986
PubMed Central: PMC6445301

Affiliations:

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Le document en format XML

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<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Biological Evolution (MeSH)</term>
<term>Cell Cycle Proteins (genetics)</term>
<term>Drug Resistance, Fungal (genetics)</term>
<term>Hydroxyurea (MeSH)</term>
<term>Mutation (MeSH)</term>
<term>Phosphatidylinositol 3-Kinases (genetics)</term>
<term>Quantitative Trait Loci (MeSH)</term>
<term>Saccharomyces cerevisiae (genetics)</term>
<term>Saccharomyces cerevisiae Proteins (genetics)</term>
<term>Selection, Genetic (MeSH)</term>
<term>Sirolimus (MeSH)</term>
</keywords>
<keywords scheme="KwdFr" xml:lang="fr"><term>Hydroxy-urée (MeSH)</term>
<term>Locus de caractère quantitatif (MeSH)</term>
<term>Mutation (MeSH)</term>
<term>Phosphatidylinositol 3-kinases (génétique)</term>
<term>Protéines de Saccharomyces cerevisiae (génétique)</term>
<term>Protéines du cycle cellulaire (génétique)</term>
<term>Résistance des champignons aux médicaments (génétique)</term>
<term>Saccharomyces cerevisiae (génétique)</term>
<term>Sirolimus (MeSH)</term>
<term>Sélection génétique (MeSH)</term>
<term>Évolution biologique (MeSH)</term>
</keywords>
<keywords scheme="MESH" type="chemical" qualifier="genetics" xml:lang="en"><term>Cell Cycle Proteins</term>
<term>Phosphatidylinositol 3-Kinases</term>
<term>Saccharomyces cerevisiae Proteins</term>
</keywords>
<keywords scheme="MESH" qualifier="genetics" xml:lang="en"><term>Drug Resistance, Fungal</term>
<term>Saccharomyces cerevisiae</term>
</keywords>
<keywords scheme="MESH" qualifier="génétique" xml:lang="fr"><term>Phosphatidylinositol 3-kinases</term>
<term>Protéines de Saccharomyces cerevisiae</term>
<term>Protéines du cycle cellulaire</term>
<term>Résistance des champignons aux médicaments</term>
<term>Saccharomyces cerevisiae</term>
</keywords>
<keywords scheme="MESH" xml:lang="en"><term>Biological Evolution</term>
<term>Hydroxyurea</term>
<term>Mutation</term>
<term>Quantitative Trait Loci</term>
<term>Selection, Genetic</term>
<term>Sirolimus</term>
</keywords>
<keywords scheme="MESH" xml:lang="fr"><term>Hydroxy-urée</term>
<term>Locus de caractère quantitatif</term>
<term>Mutation</term>
<term>Sirolimus</term>
<term>Sélection génétique</term>
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<front><div type="abstract" xml:lang="en">Pre-existing and de novo genetic variants can both drive adaptation to environmental changes, but their relative contributions and interplay remain poorly understood. Here we investigated the evolutionary dynamics in drug-treated yeast populations with different levels of pre-existing variation by experimental evolution coupled with time-resolved sequencing and phenotyping. We found a doubling of pre-existing variation alone boosts the adaptation by 64.1% and 51.5% in hydroxyurea and rapamycin, respectively. The causative pre-existing and de novo variants were selected on shared targets: RNR4 in hydroxyurea and TOR1, TOR2 in rapamycin. Interestingly, the pre-existing and de novo TOR variants map to different functional domains and act via distinct mechanisms. The pre-existing TOR variants from two domesticated strains exhibited opposite rapamycin resistance effects, reflecting lineage-specific functional divergence. This study provides a dynamic view on how pre-existing and de novo variants interactively drive adaptation and deepens our understanding of clonally evolving populations.</div>
</front>
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<DateCompleted><Year>2019</Year>
<Month>06</Month>
<Day>28</Day>
</DateCompleted>
<DateRevised><Year>2020</Year>
<Month>08</Month>
<Day>27</Day>
</DateRevised>
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<JournalIssue CitedMedium="Internet"><Volume>36</Volume>
<Issue>4</Issue>
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<Month>04</Month>
<Day>01</Day>
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<Title>Molecular biology and evolution</Title>
<ISOAbbreviation>Mol Biol Evol</ISOAbbreviation>
</Journal>
<ArticleTitle>Shared Molecular Targets Confer Resistance over Short and Long Evolutionary Timescales.</ArticleTitle>
<Pagination><MedlinePgn>691-708</MedlinePgn>
</Pagination>
<ELocationID EIdType="doi" ValidYN="Y">10.1093/molbev/msz006</ELocationID>
<Abstract><AbstractText>Pre-existing and de novo genetic variants can both drive adaptation to environmental changes, but their relative contributions and interplay remain poorly understood. Here we investigated the evolutionary dynamics in drug-treated yeast populations with different levels of pre-existing variation by experimental evolution coupled with time-resolved sequencing and phenotyping. We found a doubling of pre-existing variation alone boosts the adaptation by 64.1% and 51.5% in hydroxyurea and rapamycin, respectively. The causative pre-existing and de novo variants were selected on shared targets: RNR4 in hydroxyurea and TOR1, TOR2 in rapamycin. Interestingly, the pre-existing and de novo TOR variants map to different functional domains and act via distinct mechanisms. The pre-existing TOR variants from two domesticated strains exhibited opposite rapamycin resistance effects, reflecting lineage-specific functional divergence. This study provides a dynamic view on how pre-existing and de novo variants interactively drive adaptation and deepens our understanding of clonally evolving populations.</AbstractText>
<CopyrightInformation>© The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.</CopyrightInformation>
</Abstract>
<AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Li</LastName>
<ForeName>Jing</ForeName>
<Initials>J</Initials>
<AffiliationInfo><Affiliation>Université Côte d'Azur, CNRS, Inserm, IRCAN, Nice, France.</Affiliation>
</AffiliationInfo>
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<Author ValidYN="Y"><LastName>Vázquez-García</LastName>
<ForeName>Ignacio</ForeName>
<Initials>I</Initials>
<AffiliationInfo><Affiliation>Wellcome Trust Sanger Institute, Cambridge, United Kingdom.</Affiliation>
</AffiliationInfo>
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	Serveur d'exploration sur la rapamycine et les champignons
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Shared Molecular Targets Confer Resistance over Short and Long Evolutionary Timescales.

Shared Molecular Targets Confer Resistance over Short and Long Evolutionary Timescales.

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