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dc.contributor.authorGreenbury, Sam Fen
dc.contributor.authorSchaper, Steffenen
dc.contributor.authorAhnert, Sebastianen
dc.contributor.authorLouis, Ard Aen
dc.date.accessioned2016-02-12T12:23:43Z
dc.date.available2016-02-12T12:23:43Z
dc.date.issued2016-03-03en
dc.identifier.citationPLOS Computational Biology 2016en
dc.identifier.issn1553-734X
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/253728
dc.description.abstractMutational neighbourhoods in genotype-phenotype (GP) maps are widely believed to be more likely to share characteristics than expected from random chance. Such genetic correlations should strongly influence evolutionary dynamics. We explore and quantify these intuitions by comparing three GP maps—a model for RNA secondary structure, the HP model for protein tertiary structure, and the Polyomino model for protein quaternary structure—to a simple random null model that maintains the number of genotypes mapping to each phenotype, but assigns genotypes randomly. The mutational neighbourhood of a genotype in these GP maps is much more likely to contain genotypes mapping to the same phenotype than in the random null model. Such neutral correlations can be quantified by the robustness to mutations, which can be many orders of magnitude larger than that of the null model, and crucially, above the critical threshold for the formation of large neutral networks of mutationally connected genotypes which enhance the capacity for the exploration of phenotypic novelty. Thus neutral correlations increase evolvability. We also study non-neutral correlations: Compared to the null model, i) If a particular (non-neutral) phenotype is found once in the 1-mutation neighbourhood of a genotype, then the chance of finding that phenotype multiple times in this neighbourhood is larger than expected; ii) If two genotypes are connected by a single neutral mutation, then their respective non-neutral 1-mutation neighbourhoods are more likely to be similar; iii) If a genotype maps to a folding or self-assembling phenotype, then its non-neutral neighbours are less likely to be a potentially deleterious non-folding or non-assembling phenotype. Non-neutral correlations of type i) and ii) reduce the rate at which new phenotypes can be found by neutral exploration, and so may diminish evolvability, while non-neutral correlations of type iii) may instead facilitate evolutionary exploration and so increase evolvability.
dc.description.sponsorshipThis work was funded under EP/P504287/1 by the Engineering and Physical Sciences Research Council (https://www.epsrc.ac.uk). SEA is supported by The Royal Society (https://royalsociety.org/).
dc.languageEnglishen
dc.language.isoenen
dc.publisherPLOS
dc.rightsAttribution 2.0 UK: England & Wales*
dc.rights.urihttp://creativecommons.org/licenses/by/2.0/uk/*
dc.subjectgenotype-phenotype mapen
dc.subjectneutral correlationsen
dc.subjectneutral networksen
dc.subjectRNA secondary structureen
dc.subjectprotein quaternary structureen
dc.subjectPolyominoen
dc.subjectHP lattice modelen
dc.titleGenetic Correlations Greatly Increase Mutational Robustness and Can Both Reduce and Enhance Evolvabilityen
dc.typeArticle
dc.description.versionThis is the final version of the article. It first appeared from PLOS via http://dx.doi.org/10.1371/journal.pcbi.1004773en
prism.numbere1004773en
prism.publicationDate2016en
prism.publicationNamePLOS Computational Biologyen
prism.volume12en
dc.rioxxterms.funderEPSRC
dc.rioxxterms.projectidEP/P504287/1
dcterms.dateAccepted2016-01-24en
rioxxterms.versionofrecord10.1371/journal.pcbi.1004773en
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2016-03-03en
dc.identifier.eissn1553-7358
rioxxterms.typeJournal Article/Reviewen
cam.orpheus.successThu Jan 30 12:55:12 GMT 2020 - The item has an open VoR version.*
rioxxterms.freetoread.startdate2100-01-01


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Attribution 2.0 UK: England & Wales
Except where otherwise noted, this item's licence is described as Attribution 2.0 UK: England & Wales