Evidence of the interplay of genetics and culture in Ethiopia

Abstract

The rich linguistic, ethnic and cultural diversity of Ethiopia provides an unprecedented opportunity to understand the level to which cultural factors correlate with–and shape–genetic structure in human populations. Using primarily new genetic variation data covering 1,214 Ethiopians representing 68 different ethnic groups, together with information on individuals’ birthplaces, linguistic/religious practices and 31 cultural practices, we disentangle the effects of geographic distance, elevation, and social factors on the genetic structure of Ethiopians today. We provide evidence of associations between social behaviours and genetic differences among present-day peoples. We show that genetic similarity is broadly associated with linguistic affiliation, but also identify pronounced genetic similarity among groups from disparate language classifications that may in part be attributable to recent intermixing. We also illustrate how groups reporting the same culture traits are more genetically similar on average and show evidence of recent intermixing, suggesting that shared cultural traits may promote admixture. In addition to providing insights into the genetic structure and history of Ethiopia, we identify the most important cultural and geographic predictors of genetic differentiation and provide a resource for designing sampling protocols for future genetic studies involving Ethiopians.

Whole-genome sequencing of Bantu-speakers from Angola and Mozambique reveals complex dispersal patterns and interactions throughout sub-Saharan Africa

“…To further explore the fine-scale population structure of Angola and Mozambique alongside neighbouring groups, we merged our extended WGS dataset with a curated selection of modern and ancient individuals genotyped at SNP sites present on the Human Origins Array (HOA) [31][32][33][34][35][36][37][38][39][40][41] (Supplementary Table 6).…”

“…The genetic architecture of sub-Saharan Africa has been shaped by admixture involving Bantu migrants and autochthonous populations [18][35][40] . Consistent with a history involving almost complete replacement of local genetic diversity across large parts of Central Africa [15][16][17] [34} , ADMIXTURE [25] (Supplementary Figure 3) and SOURCEFIND [43] (Supplementary Figure 4) analyses performed using our extended HOA dataset (Supplementary Table 6) suggests that Angolans and Mozambicans are best represented as having 98% (minimum (min) = 89%, maximum (max) = 100%, standard deviation (sd) ± 2%) and 97% (min = 92%, max = 99%, sd ± 2%) West African (Bantu-related) ancestry respectively.…”

“…SNP genotypes generated as part of our Angolan and Mozambican call-set were combined with either (a) genotype data from 2,824 individuals sequenced and genotyped as part of The 1000 Genomes Project Phase 3 (1000G) [12] and the African Genome Variation Project (AGVP) [13] (Supplementary Table 2) (henceforth referred to as the WGS dataset) or (b) an additional 2,394 modern and ancient individuals from 261 populations genotyped at 594,924 autosomal SNPs present in the Human Origins Array panel (HOA) described in many previous studies [31][32][33][34][36][37][39][40][41] (Supplementary Table 6) (henceforth referred to as the HOA dataset). Included in the HOA dataset were three high-coverage ancient genomes: a 2,000-year-old individual from South Africa (Ballito Bay; baa001) [35] , a 4,500-year-old individual from Ethiopia (Mota; GB20) [33] and an 8,000-year-old individual from Cameroon (Shum Laka; I10871) [39] .…”

“…After phasing genotypes using SHAPEITv2 [78] and following the stepwise procedure to estimate global mutation/emission (-M) and switch rate (-n) parameters as outlined in previous studies [40][79][80] CHROMOPAINTERv2 [42] was run on all diploid individuals within our HOA dataset (Supplementary Table 6) using two distinct donor-recipient population configurations: (a) all individuals and/or populations in the dataset are included as both recipients and donors of shared haplotypes (henceforth referred to as the ‘all-copying model’ ) and (b) as in (a) but with all Bantu-speaking groups other than the Cameroonian Lemande (used to describe Bantu-related ancestry in previous studies [36][39] ) excluded as donor populations (henceforth referred to as the ‘no-Bantu-copying model’ ).…”

Genomic analysis reveals geography rather than culture as the predominant factor shaping genetic variation in northern Kenyan human populations

“…Among Bantu‐speaking groups in Mozambique, genetic differentiation was found to be primarily determined by language rather than geography (Semo et al, 2020). Among ethnic groups in Ethiopia, genetic variation has been found to be associated with linguistic affiliation and shared culture (López et al, 2021). In many cases geography acts as the main determinant of genetic structuring, however, this is not always the case.…”