The McDonald-Kreitman Test and its Extensions under Frequent Adaptation: Problems and Solutions

TL;DR

This paper investigates how linkage effects and slightly deleterious mutations impact the accuracy of the McDonald-Kreitman test in estimating positive selection rates, proposing an asymptotic extension to improve its reliability.

Contribution

It identifies limitations of the MK test under realistic genomic scenarios and introduces a simple asymptotic extension to enhance its accuracy in the presence of linkage effects.

Findings

MK estimates underestimate true adaptation rate with deleterious mutations

Genetic draft distorts site frequency spectra at intermediate adaptation rates

Demography inference from synonymous sites can be misleading in simulations

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 (\alpha) from polymorphism and divergence data. We find that in the presence of slightly deleterious mutations, MK estimates of \alpha\ 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 \alpha\ obtain almost the correct \alpha\ 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 suggest a simple asymptotic extension of the MK test that should yield accurate estimates of \alpha\ even in the presence of linkage effects.