Modeling Continuous Admixture Using Admixture-Induced Linkage Disequilibrium

Ying Zhou,Hongxiang Qiu,Shuhua Xu

doi:10.1038/srep43054

Abstract

Recent migrations and inter-ethnic mating of long isolated populations have resulted in genetically admixed populations. To understand the complex population admixture process, which is critical to both evolutionary and medical studies, here we used admixture induced linkage disequilibrium (LD) to infer continuous admixture events, which is common for most existing admixed populations. Unlike previous studies, we expanded the typical continuous admixture model to a more general scenario with isolation after a certain duration of continuous gene flow. Based on the new models, we developed a method, CAMer, to infer the admixture history considering continuous and complex demographic process of gene flow between populations. We evaluated the performance of CAMer by computer simulation and further applied our method to real data analysis of a few well-known admixed populations.

Highlights

Human migrations involve gene flow among previously isolated populations, resulting in admixed populations
Admixed populations were simulated in a forward-time way under different admixture models with the software AdmixSim20, which is under the framework of copying model that new haplotypes are assembled from the segments of the source populations’ haplotypes generation by generation4,21, and the same simulation strategy has been used in the previous work4
It could only give hybrid isolation (HI) model as the best-fit model when the simulated admixture is under gradual admixture (GA)-I or continuous gene flow (CGF)-I model. These results indicated the limitation of using the GA and CGF models in inferring admixture history, no matter the information from linkage disequilibrium (LD) or continuous ancestral tracts (CAT) is used for inference

Summary

Introduction

Human migrations involve gene flow among previously isolated populations, resulting in admixed populations. Several methods have been developed to estimate admixture time based on the hybrid isolation (HI) model or intermixture admixture model (IA), which assume that the admixed population is formed by one wave of admixture at a certain time. Weighted LD has already been used in inferring multiple-wave admixtures10,11 These methods tend to summarize the admixture into different independent events, even if the true admixture is continuous. We first developed a weighted LD-based method to infer admixture with HI, GA, and continuous gene flow (CGF) models (see Fig. 1). Both GA and CGF models assume that gene flow is a continuous process. We applied our method to a number of well-known admixed populations and provided information that would help better understanding the admixture history of these populations

Methods

Results

Conclusion