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The ensemble of gene regulatory networks at mutation-selection balance.
Yang, Chia-Hung; Scarpino, Samuel V.
Afiliação
  • Yang CH; Network Science Institute, Northeastern University, Boston, MA, USA.
  • Scarpino SV; Network Science Institute, Northeastern University, Boston, MA, USA.
J R Soc Interface ; 20(198): 20220075, 2023 01.
Article em En | MEDLINE | ID: mdl-36596452
ABSTRACT
The evolution of diverse phenotypes both involves and is constrained by molecular interaction networks. When these networks influence patterns of expression, we refer to them as gene regulatory networks (GRNs). Here, we develop a model of GRN evolution analogous to work from quasi-species theory, which is itself essentially the mutation-selection balance model from classical population genetics extended to multiple loci. With this GRN model, we prove that-across a broad spectrum of selection pressures-the dynamics converge to a stationary distribution over GRNs. Next, we show from first principles how the frequency of GRNs at equilibrium is related to the topology of the genotype network, in particular, via a specific network centrality measure termed the eigenvector centrality. Finally, we determine the structural characteristics of GRNs that are favoured in response to a range of selective environments and mutational constraints. Our work connects GRN evolution to quasi-species theory-and thus to classical populations genetics-providing a mechanistic explanation for the observed distribution of GRNs evolving in response to various evolutionary forces, and shows how complex fitness landscapes can emerge from simple evolutionary rules.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Redes Reguladoras de Genes / Modelos Genéticos Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Redes Reguladoras de Genes / Modelos Genéticos Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article