New statistical method jointly infers the genomic landscapes of genealogies, recombination rates and mutation rates. In doing so, our model captures the effects of genetic drift, linked selection and local mutation rates on patterns of genomic variation.
What shapes the distribution of nucleotide diversity along the genome? Attempts to answer this question have sparked debate about the roles of neutral stochastic processes and natural selection in molecular evolution. However, the mechanisms of evolution do not act in isolation, and integrative models that simultaneously consider the influence of multiple factors on diversity are lacking; without them, confounding factors lurk in the estimates. Here we present a new statistical method that jointly infers the genomic landscapes of genealogies, recombination rates and mutation rates. In doing so, our model captures the effects of genetic drift, linked selection and local mutation rates on patterns of genomic variation. Guided by our causal model, we use linear regression to estimate the individual contributions of these micro-evolutionary forces to levels of nucleotide diversity. Our analyses reveal the signature of selection in Drosophila melanogaster, but we estimate that the mutation landscape is the major driver of the distribution of diversity in this species. Furthermore, our simulation study suggests that in many evolutionary scenarios the mutation landscape will be a crucial force shaping diversity, depending notably on the genomic window size used in the analysis. We argue that incorporating mutation rate variation into the null model of molecular evolution will lead to more realistic inference in population genomics.