Dynamics of fixation probability in a population with fluctuating size

TL;DR

This study investigates how stochastic fluctuations in a linearly increasing population size influence fixation probabilities, revealing that temporal correlations significantly affect genetic drift outcomes at intermediate times.

Contribution

It introduces a model analyzing fixation probabilities in populations with linearly increasing size, highlighting the impact of temporal correlations often overlooked in population genetics.

Findings

Fixation probability approximations are valid at short and long times ignoring correlations.

Temporal correlations reduce fixation probability at intermediate times.

Population size fluctuations exhibit non-stationary, non-Gaussian behavior with specific variance dynamics.

Abstract

In many biological processes, the size of a population changes stochastically with time, and recent work in the context of cancer and bacterial growth have focused on the situation when the mean population size grows exponentially. Here, motivated by the evolutionary process of genetic hitchhiking in a selectively neutral population, we consider a model in which the mean size of the population increases linearly. We are interested in understanding how the fluctuations in the population size impact the first passage statistics, and study the fixation probability that a mutant reaches frequency one by a given time in a population whose size follows a conditional Wright-Fisher process. We find that at sufficiently short and long times, the fixation probability can be approximated by a model that ignores temporal correlations between the inverse of the population size, but at intermediate times, it is significantly smaller than that obtained by neglecting the correlations. Our analytical and numerical study of the correlation functions show that the conditional Wright-Fisher process of interest is neither a stationary nor a Gaussian process; we also find that the variance of the inverse population size initially increases linearly with time $t$ and then decreases as $t^{-2}$ at intermediate times followed by an exponential decay at longer times. Our work emphasizes the importance of temporal correlations in populations with fluctuating size that are often ignored in population-genetic studies of biological evolution.