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Influence of Effective Population Size on Genes under Varying Levels of Selection Pressure

The ratio of diversities at amino acid changing (nonsynonymous) and neutral (synonymous) sites (ω = π(N)/π(S)) is routinely used to measure the intensity of selection pressure. It is well known that this ratio is influenced by the effective population size (N(e)) and selection coefficient (s). Here,...

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Detalles Bibliográficos
Autor principal: Subramanian, Sankar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5841380/
https://www.ncbi.nlm.nih.gov/pubmed/29608718
http://dx.doi.org/10.1093/gbe/evy047
Descripción
Sumario:The ratio of diversities at amino acid changing (nonsynonymous) and neutral (synonymous) sites (ω = π(N)/π(S)) is routinely used to measure the intensity of selection pressure. It is well known that this ratio is influenced by the effective population size (N(e)) and selection coefficient (s). Here, we examined the effects of effective population size on ω by comparing protein-coding genes from Mus musculus castaneus and Mus musculus musculus—two mouse subspecies with different N(e). Our results revealed a positive relationship between the magnitude of selection intensity and the ω estimated for genes. For genes under high selective constraints, the ω estimated for the subspecies with small N(e) (M. m. musculus) was three times higher than that observed for that with large N(e) (M. m. castaneus). However, this difference was only 18% for genes under relaxed selective constraints. We showed that the observed relationship is qualitatively similar to the theoretical predictions. We also showed that, for highly expressed genes, the ω of M. m. musculus was 2.1 times higher than that of M.m. castaneus and this difference was only 27% for genes with low expression levels. These results suggest that the effect of effective population size is more pronounced in genes under high purifying selection. Hence the choice of genes is important when ω is used to infer the effective size of a population.