Genomic evidence for shared common ancestry of East African hunting-gathering populations and insights into local adaptation

Abstract

Anatomically modern humans arose in Africa ∼300,000 years ago, but the demographic and adaptive histories of African populations are not well-characterized. Here, we have generated a genome-wide dataset from 840 Africans, residing in western, eastern, southern, and northern Africa, belonging to 50 ethnicities, and speaking languages belonging to four language families. In addition to agriculturalists and pastoralists, our study includes 16 populations that practice, or until recently have practiced, a hunting-gathering (HG) lifestyle. We observe that genetic structure in Africa is broadly correlated not only with geography, but to a lesser extent, with linguistic affiliation and subsistence strategy. Four East African HG (EHG) populations that are geographically distant from each other show evidence of common ancestry: the Hadza and Sandawe in Tanzania, who speak languages with clicks classified as Khoisan; the Dahalo in Kenya, whose language has remnant clicks; and the Sabue in Ethiopia, who speak an unclassified language. Additionally, we observed common ancestry between central African rainforest HGs and southern African San, the latter of whom speak languages with clicks classified as Khoisan. With the exception of the EHG, central African rainforest HGs, and San, other HG groups in Africa appear genetically similar to neighboring agriculturalist or pastoralist populations. We additionally demonstrate that infectious disease, immune response, and diet have played important roles in the adaptive landscape of African history. However, while the broad biological processes involved in recent human adaptation in Africa are often consistent across populations, the specific loci affected by selective pressures more often vary across populations.

Keywords: African diversity; African hunter-gatherers; human evolution; natural selection; population genetics.

Fig. 1.

Geographic distribution of populations studied and summaries of population structure. (A) The geographic distribution of populations included in the study presented on a map of Africa. The legend indicates the colors assigned to each language family and the number and unique combination of color and symbol for each ethno-linguistic population. (B) PCA was performed using individuals’ genotypes; PC1, which explains 2.11% of the genotypic variance and shows a North–South cline, was plotted against PC2, which explains 0.91% of the genotypic variance and separates individuals with NC ancestry. (C) Hadza and Sabue individuals cluster at one extreme end of PC3, which explains 0.73% of variance in individuals’ genotypes; NS-speaking individuals are also found clustering near the Hadza and Sabue. (D) Population structure was inferred using the STRUCTURE software using 20,000 unlinked loci; results are shown from K = 2 to K = 9, the latter of which was identified as having the best, most stable fit to the data. The STRUCTURE analysis revealed K = 9 AAC. Supporting the PCA, two AAC’s corresponded to NC ancestry (orange); that is, correlated with the Bantu expansion, and North African ancestry (blue). In addition, the other AACs identify structure between HG populations: San (light green), WRHG (dark green), Hadza (yellow), Dahalo (light purple), and Sabue (light blue). Results from K = 2 to K = 8 are discussed in SI Appendix.

Fig. 2.

Population trees. (A) An NJ population tree was inferred using estimates of pairwise genetic distances between populations based on F_ST values scaled by N_e. Populations largely cluster by geography or language affiliation, with the notable exceptions of the clade consisting of the Hadza, Sabue, Sandawe, and Dahalo and the clade consisting of the WRHG, ERHG, and San, whose populations cluster together despite being geographically distant. (B) An NJ population tree based on pairwise distances based on the ratio of within-population to between-population haplotype sharing (i.e., IBD); this statistic is more sensitive to recent demographic events, such as gene flow than F_ST. The EHG cluster most closely with neighboring populations.

Fig. 3.

Divergence time estimates. The maximum a posteriori estimates and 95% credible intervals for pairwise divergence time estimates are displayed for each set of population samples. Estimates incorporated shared gene flow with the Yoruba, Iraqw, and Dinka, representing NC, AA, and NS source populations, and are color-coded as yellow, purple, and red, respectively. The closed circles represent population combinations for which we believe the included source population likely contributed migrants to either HG population in the past.

Fig. 4.

Signatures of selection shared among population groupings. These shared signals among population groupings include candidate loci in the top 0.01% of the empirical distribution of each neutrality test statistic (D, iHS, XP-CLR, respectively). The HLA and IGKV gene families are displayed along the x axis for each neutrality test. The y axis displays the number of population groupings that share signatures of selection at these loci.