Prospective avenues for human population genomics and disease mapping in southern Africa

Abstract

Population substructure within human populations is globally evident and a well-known confounding factor in many genetic studies. In contrast, admixture mapping exploits population stratification to detect genotype-phenotype correlations in admixed populations. Southern Africa has untapped potential for disease mapping of ancestry-specific disease risk alleles due to the distinct genetic diversity in its populations compared to other populations worldwide. This diversity contributes to a number of phenotypes, including ancestry-specific disease risk and response to pathogens. Although the 1000 Genomes Project significantly improved our understanding of genetic variation globally, southern African populations are still severely underrepresented in biomedical and human genetic studies due to insufficient large-scale publicly available data. In addition to a lack of genetic data in public repositories, existing software, algorithms and resources used for imputation and phasing of genotypic data (amongst others) are largely ineffective for populations with a complex genetic architecture such as that seen in southern Africa. This review article, therefore, aims to summarise the current limitations of conducting genetic studies on populations with a complex genetic architecture to identify potential areas for further research and development.

Keywords: Admixture mapping; Disease risk alleles; Population genetics; Southern Africa.

Fig. 1

Flow diagram indicating resources and software used for admixture mapping. Black blocks indicate the analysis steps, orange blocks represent the software used to conduct the relevant step, blue blocks indicate the resource required for the step and green blocks indicate software or approaches used for visualization. The red stars indicate missing or inadequate resources for executing the analysis step in South African populations