Inference of Population Structure Using Multilocus Genotype Data: Linked Loci and Correlated Allele Frequencies

TLDR

The paper extends Pritchard et al.’s method for inferring population structure from multilocus genotype data. The study aims to develop methods that incorporate linkage between loci. The authors introduce a model that accounts for linkage disequilibrium in admixed populations, incorporate a new prior for allele frequencies to detect subtle substructure, and implement these methods in structure v2.0. The enhanced method detects older admixture events, identifies chromosomal origins, improves uncertainty estimates, aids admixture mapping, and successfully analyzes data from African‑American, Helicobacter pylori, and Drosophila populations.

Abstract

Abstract We describe extensions to the method of Pritchard et al. for inferring population structure from multilocus genotype data. Most importantly, we develop methods that allow for linkage between loci. The new model accounts for the correlations between linked loci that arise in admixed populations (“admixture linkage disequilibium”). This modification has several advantages, allowing (1) detection of admixture events farther back into the past, (2) inference of the population of origin of chromosomal regions, and (3) more accurate estimates of statistical uncertainty when linked loci are used. It is also of potential use for admixture mapping. In addition, we describe a new prior model for the allele frequencies within each population, which allows identification of subtle population subdivisions that were not detectable using the existing method. We present results applying the new methods to study admixture in African-Americans, recombination in Helicobacter pylori, and drift in populations of Drosophila melanogaster. The methods are implemented in a program, structure, version 2.0, which is available at http://pritch.bsd.uchicago.edu.