Stochastic offspring distributions amplify selection bias in mutation accumulation experiments.

Abstract

Mutation accumulation (MA) experiments play an important role in understanding evolution. For microbial populations, such experiments often involve periods of population growth, such that a single individual can make a visible colony, followed by severe bottlenecks. Previous work has quantified the effect of positive and negative selection on MA experiments, demonstrating for example that with 20 generations of growth between bottlenecks, big-benefit mutations can be over-represented by a factor of five or more (Wahl and Agashe, 2022). This previous work assumed a deterministic model for population growth. We now develop a fully stochastic model, including realistic offspring distributions that incorporate genetic drift and allow for the loss of rare lineages. We demonstrate that when stochastic offspring distributions are considered, selection bias is even stronger than previously predicted. We describe several analytical and numerical methods that offer an accurate correction for the effects of selection on the observed distribution of fitness effects, describe the practical considerations in implementing each method, and demonstrate the use of this correction on simulated MA data.