Abstract
The interesting history of Southern Africa has put the region in the spotlight for population medical genetics. Major events including the Bantu expansion and European colonialism have imprinted unique genetic signatures within autochthonous populations of Southern Africa, this resulting in differential allele frequencies across the region. This genetic structure has potential implications on susceptibility and resistance to infectious diseases such as human immunodeficiency virus (HIV) infection. Southern Africa is the region affected worst by HIV. Here, we discuss advances made in genome-wide association studies (GWAS) of HIV-1 in the past 12 years and dissect population diversity within Southern Africa. Our findings accentuate that a plethora of factors such as migration, language and culture, admixture, and natural selection have profiled the genetics of the people of Southern Africa. Genetic structure has been observed among the Khoe-San, among Bantu speakers, and between the Khoe-San, Coloureds, and Bantu speakers. Moreover, Southern African populations have complex admixture scenarios. Few GWAS of HIV-1 have been conducted in Southern Africa, with only one of these identifying two novel variants (HCG22rs2535307 and CCNG1kgp22385164) significantly associated with HIV-1 acquisition and progression. High genetic diversity, multi-wave genetic mixture and low linkage disequilibrium of Southern African populations constitute a challenge in identifying genetic variants with modest risk or protective effect against HIV-1. We therefore posit that it is compelling to assess genome-wide contribution of ancestry to HIV-1 infection. We further suggest robust methods that can pin-point population-specific variants that may contribute to the control of HIV-1 in Southern Africa.
Highlights
Southern Africa extends across a 2.7 million km2 land in the southernmost part of Africa and is the home to about 66 million people (Worldometers, 2019)
HapMap annotation of about 3 million human SNPs has facilitated the development of highdensity arrays with 500,000 to 1,000,000 variants that could be utilized in the screening of variants associated with any disease (The International HapMap Consortium, 2003; Hutcheson et al, 2008; Winkler, 2008); this set the stage for human immunodeficiency virus (HIV)-1 genome-wide association studies (GWAS)
Southern Africans harbor ancient genetic diversity, as well as historical admixture, which can lead to complexities in (a) the design of studies assessing the genetic determinants of diseases and human variation, and (b) approaches for reconstructing DNA segments and variant discovery
Summary
Southern Africa extends across a 2.7 million km land in the southernmost part of Africa and is the home to about 66 million people (Worldometers, 2019). Within the pastoralists group, -14010*C was observed at the highest frequency of 36% in the Nama population This further shows the implication of migration and gene flow from the east of Africa into Southern Africa through Khoe speakers. Whole genome sequences of Southern African populations revealed genetic variation among the Bantu of South Africa and among Khoe-San groups. A genetic component common in Southeastern Bantu speakers was observed in most Khoe-San groups from Botswana, Lesotho, and South Africa (Montinaro et al, 2017). The SAC show the highest level of intercontinental admixture, with high levels of Southern African Khoisan, Niger-Khodofanian, Indian, and European ancestries and low levels of Asian and Cushitic ancestries (Tishkoff et al, 2009) Consistent to this insight, a multi-faceted admixture scenario (five-way admixture) has been documented in a study that sought to develop a method (PROXYANC) that could detect the best proxy ancestry in admixture in the SAC population (Chimusa et al, 2013a). HapMap annotation of about 3 million human SNPs has facilitated the development of highdensity arrays with 500,000 to 1,000,000 variants that could be utilized in the screening of variants associated with any disease (The International HapMap Consortium, 2003; Hutcheson et al, 2008; Winkler, 2008); this set the stage for HIV-1 GWAS
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