Population Size, Sex and Purifying Selection

• Autor(a) principal: Koufopanou, Vassiliki
• Data de Publicação: 2020
• Outros Autores: Lomas, Susan, Pronina, Olga, Almeida, Pedro, Sampaio, José Paulo, Mousseau, Timothy, Liti, Gianni, Burt, Austin
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10362/141362
• topic: Genetic Fitness; Genetic Variation; Genome, Fungal; Mutation Accumulation; Recombination, Genetic; Saccharomyces/genetics; Selection, Genetic

This study uses population genomic data to estimate demographic and selection parameters in two sister lineages of the wild yeast Saccharomyces paradoxus and compare their evolution. We first estimate nucleotide and recombinational diversities in each of the two lineages to infer their population size and frequency of sex and then analyze the rate of mutation accumulation since divergence from their inferred common ancestor to estimate the generation time and efficacy of selection. We find that one of the lineages has significantly higher silent nucleotide diversity and lower linkage disequilibrium, indicating a larger population with more frequent sexual generations. The same lineage also shows shorter generation time and higher efficacy of purifying selection, the latter consistent with the finding of larger population size and more frequent sex. Similar analyses are also performed on the ancestries of individual strains within lineages and we find significant differences between strains implying variation in rates of mitotic cell divisions. Our sample includes some strains originating in the Chernobyl nuclear-accident exclusion zone, which has been subjected to high levels of radiation for nearly 30 years now. We find no evidence, however, for increased rates of mutation. Finally, there is a positive correlation between rates of mutation accumulation and length of growing period, as measured by latitude of the place of origin of strains. Our study illustrates the power of genomic analyses in estimating population and life history parameters and testing predictions based on population genetic theory.