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The Effects of Mutation and Recombination Rate Heterogeneity on the Inference of Demography and the Distribution of Fitness Effects.
Soni, Vivak; Pfeifer, Susanne P; Jensen, Jeffrey D.
Afiliação
  • Soni V; School of Life Sciences, Center for Evolution & Medicine, Arizona State University, Tempe, AZ, USA.
  • Pfeifer SP; School of Life Sciences, Center for Evolution & Medicine, Arizona State University, Tempe, AZ, USA.
  • Jensen JD; School of Life Sciences, Center for Evolution & Medicine, Arizona State University, Tempe, AZ, USA.
Genome Biol Evol ; 16(2)2024 02 01.
Article em En | MEDLINE | ID: mdl-38207127
ABSTRACT
Disentangling the effects of demography and selection has remained a focal point of population genetic analysis. Knowledge about mutation and recombination is essential in this endeavor; however, despite clear evidence that both mutation and recombination rates vary across genomes, it is common practice to model both rates as fixed. In this study, we quantify how this unaccounted for rate heterogeneity may impact inference using common approaches for inferring selection (DFE-alpha, Grapes, and polyDFE) and/or demography (fastsimcoal2 and δaδi). We demonstrate that, if not properly modeled, this heterogeneity can increase uncertainty in the estimation of demographic and selective parameters and in some scenarios may result in mis-leading inference. These results highlight the importance of quantifying the fundamental evolutionary parameters of mutation and recombination before utilizing population genomic data to quantify the effects of genetic drift (i.e. as modulated by demographic history) and selection; or, at the least, that the effects of uncertainty in these parameters can and should be directly modeled in downstream inference.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Seleção Genética / Deriva Genética Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Seleção Genética / Deriva Genética Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2024 Tipo de documento: Article