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This paper re-derives Kimura's single-allele fixation probability formula using fluctuation theorems from non-equilibrium statistical mechanics and extends this framework to the multi-allele case, which is crucial for modeling clonal interference in asexual populations. The authors present a recursive analytical solution for multi-allele fixation probabilities, enabling exact calculations that overcome the limitations of multi-dimensional backward Kolmogorov equations. Applying this formalism to clonal interference scenarios reveals significant deviations from mean-field approximations, offering a more accurate quantitative description of evolutionary dynamics.
Exact multi-allele fixation probabilities can be derived using fluctuation theorems, revealing substantial deviations from mean-field approximations in clonal interference scenarios.
A mutant gene that appears in a finite population will, in the long run, either disappear from it or become fixed, so that all members of the population will carry a copy of the mutant gene. Determining the fixation probability of a mutant gene is thus a prerequisite for modeling evolutionary dynamics in finite populations. Within the diffusion theory framework, the mutant's competition with the wild-type genes is described by the closed-form solution of a one-dimensional backward Kolmogorov equation for the mutant fixation probability, derived by Motoo Kimura in 1962. However, in asexual populations the rate of adaptation and the relative importance of alternative evolutionary pathways are shaped by clonal interference - the competition between several lineages arising from distinct beneficial or deleterious mutations. Quantitative descriptions of clonal interference require computing fixation probabilities in populations where multiple alleles are present simultaneously - a formidable mathematical problem which amounts to solving a multi-dimensional backward Kolmogorov equation. Here, we employ fluctuation theorems (a set of exact equalities in non-equilibrium statistical mechanics) in order to re-derive Kimura's fixation probability formula. When extended to multi-allele systems, fluctuation theorems provide a constraint which must be satisfied by any valid set of fixation probabilities. Moreover, we present a recursive analytical solution of the multi-allele fixation probability problem. We use our formalism to study the fate of a novel beneficial mutation in a clonal interference scenario, discovering substantial deviations between our exact treatment and the mean-field approximation in which the target mutation competes with a single effective genotype. Our formalism can be used to replace both explicit simulations and approximate analytical results in models of asexual evolution.