Title: Broad-scale variation in human genetic diversity levels is predicted by purifying selection on coding and non-coding elements
Description: Genome-wide neutral diversity levels are shaped by both positive and purifying selection on linked sites. In humans like most species, the relative importance of these types of selection in shaping patterns of neutral diversity remains an open question. We can infer their relative contribution from observed patterns of neutral diversity by using information about recombination rates and targets of natural selection. To this end, I fit a joint model of the effects of positive selection (selective sweeps) and purifying selection (background selection) to genetic polymorphism data from the 1000 Genomes Project. I show that a model of the effects of background selection provides a good fit to patterns in diversity data and that incorporating the effects of selective sweeps does not improve the fit. Using my approach, the effects of background selection explain up to 60% of the variation in neutral diversity levels on the 1Mb scale and account for patterns in the data for which positive selection via selective sweeps had been invoked as explanations.

I find that over 80% of the selected regions affecting neutral diversity levels are located outside of exons and that phylogenetic conservation is the best predictor of the source of selection in these regions. My results show that the genome-wide effects of background selection are pervasive, with measurable reductions in neutral diversity throughout almost the entirety of the autosomes. I provide maps of the effects of background selection and software for making similar inferences, which should provide important tools for future research that relies on interpreting patterns in neutral diversity levels.