Empirical mean-noise fitness landscapes reveal the fitness impact of gene expression noise

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  • dc.contributor.author Schmiedel, Jörn M.
  • dc.contributor.author Carey, Lucas, 1980-
  • dc.contributor.author Lehner, Ben, 1978-
  • dc.date.accessioned 2019-09-10T14:10:06Z
  • dc.date.available 2019-09-10T14:10:06Z
  • dc.date.issued 2019
  • dc.description.abstract The effects of cell-to-cell variation (noise) in gene expression have proven difficult to quantify because of the mechanistic coupling of noise to mean expression. To independently quantify the effects of changes in mean expression and noise we determine the fitness landscapes in mean-noise expression space for 33 genes in yeast. For most genes, short-lived (noise) deviations away from the expression optimum are nearly as detrimental as sustained (mean) deviations. Fitness landscapes can be classified by a combination of each gene's sensitivity to protein shortage or surplus. We use this classification to explore evolutionary scenarios for gene expression and find that certain landscape topologies can break the mechanistic coupling of mean and noise, thus promoting independent optimization of both properties. These results demonstrate that noise is detrimental for many genes and reveal non-trivial consequences of mean-noise-fitness topologies for the evolution of gene expression systems.
  • dc.description.sponsorship This work was supported by a European Research Council Consolidator grant (616434), the Spanish Ministry of Economy and Competitiveness (BFU2011–26206 and SEV-2012–0208), the AXA Research Fund, Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR, 2014SGR831), FP7 project 4DCellFate (277899), the EMBL-CRG Systems Biology Program (all to B.L.), an EMBO Long-Term Fellowship (ALTF 857–2016), the European Union’s Horizon 2020 research and innovation programme (Marie Skłodowska-Curie grant agreement No 752809) (both to J.M.S.) an AGAUR grant (2014SGR0974) and a MINECO grant (BFU2015–68351-P) (both to L.B.C.). The authors acknowledge support from the Spanish Ministry of Economy, Industry and Competitiveness (MEIC) to the EMBL partnership, the Centro de Excelencia Severo Ochoa, and the CERCA Programme / Generalitat de Catalunya.
  • dc.format.mimetype application/pdf
  • dc.identifier.citation Schmiedel JM, Carey LB, Lehner B. Empirical mean-noise fitness landscapes reveal the fitness impact of gene expression noise. Nat Commun. 2019;10(1):3180. DOI: 10.1038/s41467-019-11116-w
  • dc.identifier.doi http://dx.doi.org/10.1038/s41467-019-11116-w
  • dc.identifier.issn 2041-1723
  • dc.identifier.uri http://hdl.handle.net/10230/42260
  • dc.language.iso eng
  • dc.publisher Nature Research
  • dc.relation.ispartof Nature Communications. 2019;10(1):3180
  • dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/616434
  • dc.relation.projectID info:eu-repo/grantAgreement/ES/3PN/BFU2011–26206
  • dc.relation.projectID info:eu-repo/grantAgreement/ES/3PN/SEV-2012–0208
  • dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/277899
  • dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/752809
  • dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/BFU2015-68351-P
  • dc.rights © The Author(s) 2019. Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.
  • dc.rights.accessRights info:eu-repo/semantics/openAccess
  • dc.rights.uri http://creativecommons.org/licenses/by/4.0/
  • dc.subject.keyword Cellular noise
  • dc.subject.keyword Evolution
  • dc.subject.keyword Evolvability
  • dc.subject.keyword Gene expression
  • dc.title Empirical mean-noise fitness landscapes reveal the fitness impact of gene expression noise
  • dc.type info:eu-repo/semantics/article
  • dc.type.version info:eu-repo/semantics/publishedVersion

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