Non-selective evolution of growing populations

TL;DR

This study demonstrates that in growing populations, non-selective effects like genetic drift lead to a steady state where trait compositions do not fixate, with growth dynamics significantly influencing genetic variability.

Contribution

The paper introduces a combined theoretical and experimental analysis showing how exponential growth halts fixation and maintains variability, contrasting with previous fixation-focused models.

Findings

Populations tend to a random steady state composition.

Growth dynamics influence the distribution of traits.

Experimental results match the Pólya urn model predictions.

Abstract

Non-selective effects, like genetic drift, are an important factor in modern conceptions of evolution, and have been extensively studied for constant population sizes. Here, we consider non-selective evolution in the case of growing populations that are of small size and have varying trait compositions (e.g. after a population bottleneck). We find that, in these conditions, populations never fixate to a trait, but tend to a random limit composition, and that the distribution of compositions 'freezes' to a steady state This final state is crucially influenced by the initial conditions. We obtain these findings from a combined theoretical and experimental approach, using multiple mixed subpopulations of two Pseudomonas putida strains in non-selective growth conditions as model system. The experimental results for the population dynamics match the theoretical predictions based on the P\'olya urn model for all analyzed parameter regimes. In summary, we show that exponential growth stops genetic drift. This result contrasts with previous theoretical analyses of non-selective evolution (e.g. genetic drift), which investigated how traits spread and eventually take over populations (fixate). Moreover, our work highlights how deeply growth influences non-selective evolution, and how it plays a key role in maintaining genetic variability. Consequently, it is of particular importance in life-cycles models of periodically shrinking and expanding populations.