Inference of Distribution of Fitness Effects and Proportion of Adaptive Substitutions from Polymorphism Data. Issue 3 (25th September 2017)

• Record Type: Journal Article
• Authors: Tataru, Paula; Mollion, Maéva; Glémin, Sylvain; Bataillon, Thomas
• Is Part Of: Genetics. Volume 207:Issue 3(2017)
• Page Start: 1103
• Page End: 1119
• Publication Date: 2017-09-25
• Subjects: distribution of fitness effects -- rate of adaptive molecular evolution -- beneficial mutations -- polymorphism and divergence data -- Poisson random field; Genetics -- Periodicals; 576.5
• DOI: 10.1534/genetics.117.300323
• Languages: English
• ISSNs: 0016-6731

Abstract

Abstract: The distribution of fitness effects (DFE) encompasses the fraction of deleterious, neutral, and beneficial mutations. It conditions the evolutionary trajectory of populations, as well as the rate of adaptive molecular evolution ( α ). Inferring DFE and α from patterns of polymorphism, as given through the site frequency spectrum (SFS) and divergence data, has been a longstanding goal of evolutionary genetics. A widespread assumption shared by previous inference methods is that beneficial mutations only contribute negligibly to the polymorphism data. Hence, a DFE comprising only deleterious mutations tends to be estimated from SFS data, and α is then predicted by contrasting the SFS with divergence data from an outgroup. We develop a hierarchical probabilistic framework that extends previous methods to infer DFE and α from polymorphism data alone. We use extensive simulations to examine the performance of our method. While an outgroup is still needed to obtain an unfolded SFS, we show that both a DFE, comprising both deleterious and beneficial mutations, and α can be inferred without using divergence data. We also show that not accounting for the contribution of beneficial mutations to polymorphism data leads to substantially biased estimates of the DFE and α . We compare our framework with one of the most widely used inference methods available and apply it on a recently published chimpanzee exome data set.