Empirical validation of the nearly neutral theory at divergence and population genomic scale across 150 placental mammal genomes

By limiting the efficacy of selection on mutations of small effects, random drift is expected to play a major role in the evolution of genomes. Formalizing this idea, the nearly-neutral theory predicts that the proportion of non-synonymous mutations that are effectively neutral depends negatively on the effective population size (Ne). As a result, the ratio of non-synonymous over synonymous polymorphism (pN/pS) within populations, and divergence (dN/dS) between species, should both correlate negatively with Ne. Some of these predictions have previously been tested in mammals. However, most studies have either focused on dN/dS or on pN/pS and have not addressed the problem globally across evolutionary scales. Here we propose to test the nearly-neutral prediction in an integrative manner using the genomes of 150 mammals species and around 6000 orthologous genes. Our investigation spans the macro and the micro-evolutionary scale, using for the latter a measure of heterozygosity in the annotated orthologous coding sequences of the assembled diploid genomes. We confirm the positive correlation between dN/dS and life history traits. We also observe, for the first time in mammalian nuclear genomes, a relationship between pN/pS and pS. Across time scales, the correlation patterns between micro and macro-evolutionnary quantities are in agreement with the nearly-neutral predictions, although the correlation between pS and life-history traits is weaker and less robust than all other correlations. Together, these observed correlations are globally consistent with the nearly-neutral expectations and can be explained by invoking that all variables are in fact correlated with a single hidden variable: Ne.