The impact of purifying selection and genetic drift on the distribution of dominance coefficients

The relationship between dominance and selection coefficients is a long-debated topic in evolutionary genetics and important for understanding evolutionary dynamics of populations. How it evolved and how it may vary across species or populations is not fully understood. Using simulations, we investigate how purifying selection and genetic drift affect the distribution of dominance coefficients for segregating deleterious variants. We find that large populations express h-s relationships shaped by efficient selection against highly deleterious and additive mutations, resulting in excess weakly deleterious and recessive mutations. This matches the classic inverse relationship between selection and dominance. Genetic drift in small populations, however, results in a wider range of dominance coefficients for any segregating deleterious variant and reduces or removes the h-s relationship. By investigating allele fixation, we reveal a nuanced dependency on the strength of selection across different simulated selection and dominance distributions. We also compare the combined impact of genetic drift and repeated founder events in simulated range expansions and how these impact the segregating distribution of h, employing differences in effective population size between species core and edge. While dominance patterns in core populations resemble large, constant-size populations, edge populations lack recessive mutations relative to small, constant-size populations. Our findings emphasize the importance of genetic drift and purifying selection in shaping the observed negative relationship between dominance and selection coefficients in large populations. Small populations, however, show an h-s relationship closer to de novo mutations, without the effect of purifying selection. Therefore, it is important to consider population size, genetic drift, and the underlying distribution of dominance coefficients when studying the evolutionary dynamics of deleterious mutations.