Stochastic dynamics of three competing clones: Conditions and times for invasion, coexistence and fixation

TL;DR

This paper develops a stochastic model to analyze the complex dynamics of three competing clones, exploring conditions for coexistence, invasion, and fixation, and estimating the timescales and likelihoods of these outcomes in large clonal populations.

Contribution

It introduces a comprehensive stochastic framework for three-clone competition, integrating invasion, fixation, and coexistence scenarios, including intransitive interactions and mutation effects.

Findings

Stable coexistence is likely when mutations influence competitive interactions.

Invasion and fixation times vary significantly with complex competitive interactions.

The model predicts diverse population outcomes depending on parameter distributions.

Abstract

In large clonal populations, several clones generally compete which results in complex evolutionary and ecological dynamics: experiments show successive selective sweeps of favorable mutations as well as long-term coexistence of multiple clonal strains. The mechanisms underlying either coexistence or fixation of several competing strains have rarely been studied altogether. Conditions for coexistence have mostly been studied by population and community ecology, while rates of invasion and fixation have mostly been studied by population genetics. In order to provide a global understanding of the complexity of the dynamics observed in large clonal populations, we develop a stochastic model where three clones compete. Competitive interactions can be intransitive and we suppose that strains enter the population via mutations or rare immigrations. We first describe all possible final states of the population, including stable coexistence of two or three strains, or the fixation of a single strain. Second, we give estimate of the invasion and fixation times of a favorable mutant (or immigrant) entering the population in a single copy. We show that invasion and fixation can be slower or faster when considering complex competitive interactions. Third, we explore the parameter space assuming prior distributions of reproduction, death and competitive rates and we estimate the likelihood of the possible dynamics. We show that when mutations can affect competitive interactions, even slightly, stable coexistence is likely. We discuss our results in the context of the evolutionary dynamics of large clonal populations.