A genomic portrait of haplotype diversity and signatures of selection in indigenous southern African populations.

Emile R Chimusa,Himla Soodyall,Milaine Tchanga,Cathal Seoighe,Nicola Mulder,Rajkumar Ramesar,Ayton Meintjies

doi:10.1371/journal.pgen.1005052

Abstract

We report a study of genome-wide, dense SNP (∼900K) and copy number polymorphism data of indigenous southern Africans. We demonstrate the genetic contribution to southern and eastern African populations, which involved admixture between indigenous San, Niger-Congo-speaking and populations of Eurasian ancestry. This finding illustrates the need to account for stratification in genome-wide association studies, and that admixture mapping would likely be a successful approach in these populations. We developed a strategy to detect the signature of selection prior to and following putative admixture events. Several genomic regions show an unusual excess of Niger-Kordofanian, and unusual deficiency of both San and Eurasian ancestry, which were considered the footprints of selection after population admixture. Several SNPs with strong allele frequency differences were observed predominantly between the admixed indigenous southern African populations, and their ancestral Eurasian populations. Interestingly, many candidate genes, which were identified within the genomic regions showing signals for selection, were associated with southern African-specific high-risk, mostly communicable diseases, such as malaria, influenza, tuberculosis, and human immunodeficiency virus/AIDs. This observation suggests a potentially important role that these genes might have played in adapting to the environment. Additionally, our analyses of haplotype structure, linkage disequilibrium, recombination, copy number variation and genome-wide admixture highlight, and support the unique position of San relative to both African and non-African populations. This study contributes to a better understanding of population ancestry and selection in south-eastern African populations; and the data and results obtained will support research into the genetic contributions to infectious as well as non-communicable diseases in the region.

Highlights

The analysis of high-throughput genotype data has revealed global patterns of human haplotype variation, casting light on the pre-history of human populations [1, 2, 3, 4, 5]
In this manuscript we report on the application of genome-wide data to southern African populations and the identification of genome-wide signatures of selection pre- and post-admixture
Consistent with previous studies, this study highlights the significance of the San in the genetics of human populations, as they are distinct from the other populations in many respects i.e. haplotype structure, locations of recombination hotspots, copy number and population structure

Summary

Introduction

The analysis of high-throughput genotype data has revealed global patterns of human haplotype variation, casting light on the pre-history of human populations [1, 2, 3, 4, 5]. Comparative genome-wide genotype data among humans, Neanderthals and Chimpanzees have shown that selection has played a significant role in human adaptation to the environment [8, 9, 10, 11] These data have provided additional support for the African origin of modern humans [12,13] and highlight the effects of migration both within Africa and out of Africa. African populations exhibit less linkage disequilibrium between adjacent markers than their non-African counterparts, consistent with a migratory bottleneck in the latter [1, 2, 5] Such differences in the extent of linkage disequilibrium have a profound effect on the power of case-control association studies, since these studies depend largely on linkage disequilibrium between disease variants and genotyped single nucleotide polymorphisms (SNPs). African populations are characterized by higher levels of genetic diversity [13, 14, 15, 16] and considerable population substructure [17, 18, 19], probably the combined result of several migration events, effective population size changes, population differentiation through genetic drift and local selective forces operating in ecologically diverse environments [18]

Methods

Results

Discussion

Conclusion