Exploring the influence of mutation rates with stochastic perturbations on genome evolution

Authors

Bohlin, J., Pettersson, J. H.- O.

Abstract

We present a stochastic version of the classical Luria-Delbruck mutation rate model using Ito calculus. Our model is used to explore implications of population growth with randomly varying mutation rates. By comparing the Itô version of the Luria-Delbruck mutation rate model to the deterministic we find that stochastic effects can have profound implications for genome evolution. In particular, as the growth rate decreases below the population's carrying capacity, or another given threshold, we show that stochastic effects can dominate the evolution of a population in a feedback-based manner. Moreover, we find that the influence of stochastic effects increase as the population reaches its carrying capacity if not accounted for. Our model also suggests strategies for a population to overcome increasing mutational load and evolve 'robustness' to genetic drift. We discuss our methodology in light of the SARS-CoV-2 virus and implications for its molecular evolution. Finally, we conclude that Ito calculus incorporates stochastic effects in mathematical models in a way that is very natural to biological systems.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 24 Oct 2026.

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