title: Estimation of the ancestral effective population sizes of African great apes under different selection regimes.
abstract: Reliable estimates of ancestral effective population sizes are necessary to unveil the population-level phenomena that shaped the phylogeny and molecular evolution of the African great apes. Although several methods have previously been applied to infer ancestral effective population sizes, an analysis of the influence of the selective regime on the estimates of ancestral demography has not been thoroughly conducted. In this study, three independent data sets under different selective regimes were used were composed to tackle this issue. The results showed that selection had a significant impact on the estimates of ancestral effective population sizes of the African great apes. The inference of the ancestral demography of African great apes was affected by the selection regime. The effects, however, were not homogeneous along the ancestral populations of great apes. The effective population size of the ancestor of humans and chimpanzees was more impacted by the selection regime when compared to the same parameter in the ancestor of humans, chimpanzees and gorillas. Because the selection regime influenced the estimates of ancestral effective population size, it is reasonable to assume that a portion of the discrepancy found in previous studies that inferred the ancestral effective population size may be attributable to the differential action of selection on the genes sampled.
authors.affiliation: Departamento de Genética, CCS, A2-092, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rua Prof. Rodolpho Paulo Rocco, SN, Cidade Universitária, Rio de Janeiro, RJ, CEP: 21941-617, Brazil, carlos.schrago@gmail.com.
authors.forename: Carlos G
authors.initials: CG
authors.lastname: Schrago
mesh_terms: D000349:Africa; D000818:Animals; D019143:Evolution, Molecular; D049810:Genetic Speciation; D015186:Hominidae / Q000235:genetics*; D011153:Population / Q000235:genetics; D012641:Selection, Genetic