Taylor's power law rules the dynamics of allele frequencies during viral evolution in response to host changes

Abstract

Sudden and gradual changes in host species composition --transitioning from more permissive to less permissive hosts-- have been shown to influence viral fitness, virulence, and rates of molecular evolution. In this study, we analyzed the roles of stochasticity and selection using previously published time-series data from evolving populations of Sindbis virus under different rates of host replacement. First, an approximate Markov model within the Wright-Fisher diffusion framework revealed a reduction in effective population size by approximately half in scenarios involving sudden host changes. These scenarios were also associated with fewer and generally weaker beneficial mutations. Second, genetic distance analysis between populations at consecutive time points indicated that populations undergoing gradual host changes evolved steadily until the original host was no longer present. Distances to the ancestral sequence in these cases exhibited occasional leapfrog phenomena, where the rise of certain haplotypes is not predictable based solely on their relatedness to previously dominant ones. In contrast, populations exposed to sudden host changes displayed less stable compositions and diverged from the ancestral sequence at a more constant rate. Third, we observed that allele frequencies distribution followed a power law consistent with Taylors law. Both treatments exhibited high levels of allele aggregation with significant fluctuations, where neutral, beneficial, and deleterious alleles could be distinguished by their general behavior and their position on Taylors plot. Finally, we found evidence that the host replacement regime influences the temporal distribution of mutations across the genome.