Fluctuating selection models and McDonald-Kreitman type analyses

TL;DR

This paper examines how fluctuating selection pressures impact the detection and estimation of adaptive evolution using McDonald-Kreitman analyses, revealing that such fluctuations can lead to false signals and underestimation of adaptation rates.

Contribution

It demonstrates that fluctuating selection can produce false evidence of adaptation and biases in MK-based estimates, highlighting the need to account for temporal variability in selection.

Findings

Fluctuating selection can mimic signals of adaptive evolution.

Mutations that fluctuate to positive values tend to reach higher frequencies.

MK methods underestimate the true rate of adaptive evolution under fluctuating selection.

Abstract

It is likely that the strength of selection acting upon a mutation varies through time due to changes in the environment. However, most population genetic theory assumes that the strength of selection remains constant. Here we investigate the consequences of fluctuating selection pressures on the quantification of adaptive evolution using McDonald-Kreitman (MK) style approaches. In agreement with previous work, we show that fluctuating selection can generate evidence of adaptive evolution even when the expected strength of selection on a mutation is zero. However, we also find that the mutations, which contribute to both polymorphism and divergence tend, on average, to be positively selected during their lifetime, under fluctuating selection models. This is because mutations that fluctuate, by chance, to positive selected values, tend to reach higher frequencies in the population than those that fluctuate towards negative values. Hence the evidence of positive adaptive evolution detected under a fluctuating selection model by MK type approaches is genuine since fixed mutations tend to be advantageous on average during their lifetime. Never-the-less we show that methods tend to underestimate the rate of adaptive evolution when selection fluctuates.