Inferring the joint demographic history of multiple populations from multidimensional SNP frequency data

TL;DR

This paper introduces a new method for inferring complex demographic histories of multiple populations using joint frequency spectrum data, accounting for selection, migration, and other evolutionary forces, with applications to human populations.

Contribution

It develops a diffusion-based composite likelihood approach that models joint allele frequency spectra for multiple populations, including selection and linkage effects, and applies it to human demographic history.

Findings

Successfully modeled human expansion out of Africa.

Predicted frequency spectrum of nonsynonymous variants across populations.

Estimated uncertainties using bootstrap methods.

Abstract

Demographic models built from genetic data play important roles in illuminating prehistorical events and serving as null models in genome scans for selection. We introduce an inference method based on the joint frequency spectrum of genetic variants within and between populations. For candidate models we numerically compute the expected spectrum using a diffusion approximation to the one-locus two-allele Wright-Fisher process, involving up to three simultaneous populations. Our approach is a composite likelihood scheme, since linkage between neutral loci alters the variance but not the expectation of the frequency spectrum. We thus use bootstraps incorporating linkage to estimate uncertainties for parameters and significance values for hypothesis tests. Our method can also incorporate selection on single sites, predicting the joint distribution of selected alleles among populations experiencing a bevy of evolutionary forces, including expansions, contractions, migrations, and admixture. As applications, we model human expansion out of Africa and the settlement of the New World, using 5 Mb of noncoding DNA resequenced in 68 individuals from 4 populations (YRI, CHB, CEU, and MXL) by the Environmental Genome Project. We also combine our demographic model with a previously estimated distribution of selective effects among newly arising amino acid mutations to accurately predict the frequency spectrum of nonsynonymous variants across three continental populations (YRI, CHB, CEU).