title: Frequent adaptation and the McDonald-Kreitman test.
abstract: Population genomic studies have shown that genetic draft and background selection can profoundly affect the genome-wide patterns of molecular variation. We performed forward simulations under realistic gene-structure and selection scenarios to investigate whether such linkage effects impinge on the ability of the McDonald-Kreitman (MK) test to infer the rate of positive selection (α) from polymorphism and divergence data. We find that in the presence of slightly deleterious mutations, MK estimates of α severely underestimate the true rate of adaptation even if all polymorphisms with population frequencies under 50% are excluded. Furthermore, already under intermediate rates of adaptation, genetic draft substantially distorts the site frequency spectra at neutral and functional sites from the expectations under mutation-selection-drift balance. MK-type approaches that first infer demography from synonymous sites and then use the inferred demography to correct the estimation of α obtain almost the correct α in our simulations. However, these approaches typically infer a severe past population expansion although there was no such expansion in the simulations, casting doubt on the accuracy of methods that infer demography from synonymous polymorphism data. We propose a simple asymptotic extension of the MK test that yields accurate estimates of α in our simulations and should provide a fruitful direction for future studies.
authors: Department of Biology, Stanford University, Stanford, CA 94305, USA. messer@stanford.edu
authors: Philipp W
authors: PW
authors: Messer
authors: Dmitri A
authors: DA
authors: Petrov
mesh_terms: D000818:Animals; D015894:Genome, Human / Q000502:physiology*; D055106:Genome-Wide Association Study; D006801:Humans; D008957:Models, Genetic; D009154:Mutation; D011110:Polymorphism, Genetic
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