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dc.contributor.authorSteinacher, A
dc.contributor.authorBates, DG
dc.contributor.authorAkman, OE
dc.contributor.authorSoyer, OS
dc.date.accessioned2017-03-09T11:00:09Z
dc.date.issued2016-04-15
dc.description.abstractCellular phenotypes underpinned by regulatory networks need to respond to evolutionary pressures to allow adaptation, but at the same time be robust to perturbations. This creates a conflict in which mutations affecting regulatory networks must both generate variance but also be tolerated at the phenotype level. Here, we perform mathematical analyses and simulations of regulatory networks to better understand the potential trade-off between robustness and evolvability. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics, through the creation of regions presenting sudden changes in phenotype with small changes in genotype. For genotypes embedding low levels of nonlinearity, robustness and evolvability correlate negatively and almost perfectly. By contrast, genotypes embedding nonlinear dynamics allow expression levels to be robust to small perturbations, while generating high diversity (evolvability) under larger perturbations. Thus, nonlinearity breaks the robustness-evolvability trade-off in gene expression levels by allowing disparate responses to different mutations. Using analytical derivations of robustness and system sensitivity, we show that these findings extend to a large class of gene regulatory network architectures and also hold for experimentally observed parameter regimes. Further, the effect of nonlinearity on the robustness-evolvability trade-off is ensured as long as key parameters of the system display specific relations irrespective of their absolute values. We find that within this parameter regime genotypes display low and noisy expression levels. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics. Our results provide a possible solution to the robustness-evolvability trade-off, suggest an explanation for the ubiquity of nonlinear dynamics in gene expression networks, and generate useful guidelines for the design of synthetic gene circuits.en_GB
dc.description.sponsorshipThis work was funded by the UK Engineering and Physical Sciences Research Council, grant number EP/I017445/1.en_GB
dc.identifier.citationVol. 11 (4), article e0153295en_GB
dc.identifier.doi10.1371/journal.pone.0153295
dc.identifier.urihttp://hdl.handle.net/10871/26368
dc.language.isoenen_GB
dc.publisherPublic Library of Scienceen_GB
dc.rightsCopyright: © 2016 Steinacher et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.en_GB
dc.titleNonlinear Dynamics in Gene Regulation Promote Robustness and Evolvability of Gene Expression Levelsen_GB
dc.typeArticleen_GB
dc.date.available2017-03-09T11:00:09Z
dc.contributor.editorProulx, SRen_GB
dc.descriptionThis is the final version of the article. Available from Public Library of Science via the DOI in this record.en_GB
dc.identifier.journalPLoS ONEen_GB


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