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Genetic Correlations Greatly Increase Mutational Robustness and Can Both Reduce and Enhance Evolvability.
Greenbury, Sam F; Schaper, Steffen; Ahnert, Sebastian E; Louis, Ard A.
Afiliação
  • Greenbury SF; Theory of Condensed Matter Group, Cavendish Laboratory, University of Cambridge, Cambridge, United Kingdom.
  • Schaper S; Rudolf Peierls Centre for Theoretical Physics, University of Oxford, Oxford, United Kingdom.
  • Ahnert SE; Theory of Condensed Matter Group, Cavendish Laboratory, University of Cambridge, Cambridge, United Kingdom.
  • Louis AA; Rudolf Peierls Centre for Theoretical Physics, University of Oxford, Oxford, United Kingdom.
PLoS Comput Biol ; 12(3): e1004773, 2016 Mar.
Article em En | MEDLINE | ID: mdl-26937652
ABSTRACT
Mutational 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.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Modelos Estatísticos / Evolução Molecular / Proteoma / Genética Populacional / Modelos Genéticos / Mutação Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Animals / Humans Idioma: En Ano de publicação: 2016 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Modelos Estatísticos / Evolução Molecular / Proteoma / Genética Populacional / Modelos Genéticos / Mutação Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Animals / Humans Idioma: En Ano de publicação: 2016 Tipo de documento: Article