Haplotype-based inference of the distribution of fitness effects

Recent genome sequencing studies with large sample sizes in humans have discovered a vast quantity of low-frequency variants, providing an important source of information to analyze how selection is acting on human genetic variation. In order to estimate the strength of natural selection acting on low-frequency variants, we have developed a likelihood-based method that uses the lengths of pairwise identity-by-state between haplotypes carrying low-frequency variants. We show that in some nonequilibrium populations (such as those that have had recent population expansions) it is possible to distinguish between positive or negative selection acting on a set of variants. With our new framework, one can infer a fixed selection intensity acting on a set of variants at a particular frequency, or a distribution of selection coefficients for standing variants and new mutations. We show an application of our method to the UK10K phased haplotype dataset of individuals.

Automated summary

Recent genome sequencing studies have discovered a large number of low-frequency variants in humans, which provide important information for analyzing the role of selection in human genetic variation. Researchers have developed a likelihood-based method that utilizes pairwise identity-by-state lengths between haplotypes carrying low-frequency variants to estimate the strength of natural selection acting on these variants. They demonstrate that it is possible to distinguish between positive and negative selection on a set of variants in certain non-equilibrium populations. The new framework allows for the inference of a fixed selection intensity on a set of variants at a specific frequency or a distribution of selection coefficients for standing variants and new mutations. An application of this method to the UK10K phased haplotype dataset is presented.