Fitness Inference in Presence of Migrations between Coupled Evolving Populations

TL;DR

This paper extends Quasi-Linkage Equilibrium (QLE) theory to coupled populations with migration, enabling accurate inference of fitness and epistasis from genome data.

Contribution

It introduces a theoretical extension of QLE to migrating populations and derives inference methods for fitness and epistasis estimation.

Findings

QLE persists at low migration rates

Analytical inference relations enable accurate estimation of fitness

Validated with whole-genome time-series data

Abstract

The phase of Quasi-Linkage Equilibrium (QLE) in evolutionary populations is analogous to the thermal equilibrium state in statistical mechanics, a concept pioneered by Kimura in 1965 for two-locus two-allele models. QLE describes a stationary state maintained by the interplay of selection, mutation, recombination and genetic drift. Here we extend QLE theory to populations connected by migration, a fundamental evolutionary force that couples the evolutionary dynamics of interacting subpopulations. Specifically, we examine two populations interacting via symmetric or asymmetric migration while evolving under multi-locus selection. Using whole-genome time-series data generated through FFPopSim, we demonstrate that the QLE phase persists under conditions of sufficiently low migration rates. In this regime, we derive analytical inference relations that allow for the accurate and quantitative estimation of both additive fitness and epistatic interactions.