The impact of macroscopic epistasis on long-term evolutionary dynamics

TL;DR

This study investigates how macroscopic epistasis influences long-term evolutionary dynamics in E. coli, using a computational framework to analyze extensive experimental data over 50,000 generations.

Contribution

The paper introduces a computational approach to evaluate epistatic models against long-term evolution data, identifying the two-epoch model as consistent with observed patterns.

Findings

Decelerating fitness trajectories alone are insufficient to distinguish epistasis models.

Combining fitness and mutation trajectories constrains possible epistasis models.

Data support a two-epoch model with initial diminishing returns followed by steady mutation accumulation.

Abstract

Genetic interactions can strongly influence the fitness effects of individual mutations, yet the impact of these epistatic interactions on evolutionary dynamics remains poorly understood. Here we investigate the evolutionary role of epistasis over 50,000 generations in a well-studied laboratory evolution experiment in E. coli. The extensive duration of this experiment provides a unique window into the effects of epistasis during long-term adaptation to a constant environment. Guided by analytical results in the weak-mutation limit, we develop a computational framework to assess the compatibility of a given epistatic model with the observed patterns of fitness gain and mutation accumulation through time. We find that a decelerating fitness trajectory alone provides little power to distinguish between competing models, including those that lack any direct epistatic interactions between mutations. However, when combined with the mutation trajectory, these observables place strong constraints on the set of possible models of epistasis, ruling out many existing explanations of the data. Instead, we find that the data are consistent with "two-epoch" model of adaptation, in which an initial burst of diminishing returns epistasis is followed by a steady accumulation of mutations under a constant distribution of fitness effects. Our results highlight the need for additional DNA sequencing of these populations, as well as for more sophisticated models of epistasis that are compatible with all of the experimental data.