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. 2020 Feb 1;37(2):406-416.
doi: 10.1093/molbev/msz224.

Along the Indian Ocean Coast: Genomic Variation in Mozambique Provides New Insights into the Bantu Expansion

Affiliations

Along the Indian Ocean Coast: Genomic Variation in Mozambique Provides New Insights into the Bantu Expansion

Armando Semo et al. Mol Biol Evol. .

Abstract

The Bantu expansion, which started in West Central Africa around 5,000 BP, constitutes a major migratory movement involving the joint spread of peoples and languages across sub-Saharan Africa. Despite the rich linguistic and archaeological evidence available, the genetic relationships between different Bantu-speaking populations and the migratory routes they followed during various phases of the expansion remain poorly understood. Here, we analyze the genetic profiles of southwestern and southeastern Bantu-speaking peoples located at the edges of the Bantu expansion by generating genome-wide data for 200 individuals from 12 Mozambican and 3 Angolan populations using ∼1.9 million autosomal single nucleotide polymorphisms. Incorporating a wide range of available genetic data, our analyses confirm previous results favoring a "late split" between West and East Bantu speakers, following a joint passage through the rainforest. In addition, we find that Bantu speakers from eastern Africa display genetic substructure, with Mozambican populations forming a gradient of relatedness along a North-South cline stretching from the coastal border between Kenya and Tanzania to South Africa. This gradient is further associated with a southward increase in genetic homogeneity, and involved minimum admixture with resident populations. Together, our results provide the first genetic evidence in support of a rapid North-South dispersal of Bantu peoples along the Indian Ocean Coast, as inferred from the distribution and antiquity of Early Iron Age assemblages associated with the Kwale archaeological tradition.

Keywords: Bantu expansion; Mozambique; admixture; migration; population structure.

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Figures

<sc>Fig</sc>. 1.
Fig. 1.
Genetic structure in Angolan and Mozambican populations. (A) Geographic locations of sampled individuals. The geographic subgroups of Bantu languages (“Guthrie zones”) following Maho (Maho 2003) are given in parentheses in the legend. (B) Principal components 1 and 2 of Angolan and Mozambican individuals rotated to fit geography (Procrustes correlation: 0.89; P < 0.001). (C) Population structure estimated with ADMIXTURE assuming 2 and 3 clusters (K). Vertical lines represent the estimated proportion of each individual’s genotypes that are derived from the assumed genetic clusters (note that the order of individuals in K = 2 is not the same as K = 3). The lowest cross-validation error (CV) was associated with K = 2 (CV values are reported in supplementary table 2, Supplementary Material online).
<sc>Fig</sc>. 2.
Fig. 2.
Genetic variation and geography in Mozambique. The plots show the correlations between latitude and (A) average PC2 scores (supplementary fig. 1B, Supplementary Material online) (B) average number of RoHs, and (C) average LD (r2). In B and C, Tswa and Ronga were lumped and are identified by the Tswa symbol (see supplementary material, Supplementary Material online).
<sc>Fig</sc>. 3.
Fig. 3.
Estimated Effective Migration Surface (EEMS) analysis. See figure 1 for legend of population symbols. (A) EEMS estimated with 12 Mozambican populations. (B, C) Major rivers (B) and mountains (C) associated with barriers and corridors of migration. The effective migration rates are presented in a log10 scale: white indicates the mean expected rate in the data set; blue and brown indicate migration rates that are X-fold higher or lower than average, respectively. The orographic map (C) was generated with the raster package (Hijmans and van Etten 2011). Altitude is given in meters.
<sc>Fig</sc>. 4.
Fig. 4.
Genetic structure in African populations. (A) Geographic locations of sampled populations. (B, C) PC plots rotated to geography using Procrustes analysis. (B) All Bantu-speaking populations (Procrustes correlation: 0.76; P < 0.001). (C) Only East Bantu-speaking populations (Procrustes correlation: 0.44; P < 0.001). The numbers in (C) refer to groups of populations that are discussed in the text. Additional PCA and ADMIXTURE plots are shown in supplementary figures 6 and 8, Supplementary Material online. (D) Population structure estimated with ADMIXTURE assuming eight clusters (K = 8), with Mozambican and Angolan groups from this study labeled in red. Vertical lines represent the estimated proportions of each individual’s genotypes that are derived from the assumed genetic clusters (CV values are reported in supplementary table 2, Supplementary Material online). The maps, obtained by interpolation, display the mean proportions of major ADMIXTURE components (K = 8) from Niger-Congo-speaking populations. The colors in the maps match the colors in the ADMIXTURE plot.
<sc>Fig</sc>. 5.
Fig. 5.
Inferred ancestry of Bantu-speaking groups from Angola, Mozambique and South Africa. (A) CHROMOPAINTER coancestry matrix based on the number of haplotype segments (chunk counts) shared between representative donor groups (columns) and recipient populations (rows) from Angola, Mozambique and South Africa. The copy profile of each recipient group is an average of the copy profiles of all individuals belonging to that group. (B) Matrix of pairwise TVDxy values based on the ancestry profiles of Angolan, Mozambican, and South African groups. The scales of chunk counts and TVDxy values are shown to the right of the matrices in (A) and (B), respectively. (C) Ancestry profiles of Angolan, Mozambican, and South African populations (pie charts) as inferred by the MIXTURE MODEL implemented in GLOBETROTTER. The colored circles indicate the most important contributing regions where best source populations were found: West Bantu-speaking groups (green); Tanzanian East Bantu-speaking groups (yellow); Great Lakes Bantu-speaking groups (red); and Khoisan groups (blue).
<sc>Fig</sc>. 6.
Fig. 6.
Inferred average ancestry of Bantu-speaking groups from South Africa. The most important contributing regions and best source populations are provided in the legend. (A) 71 source populations from Sub-Saharan Africa. (B) As in (A), but removing Mozambique from the list of sources. (C) As in (B), but removing Tanzanian Bantu speakers from the list of sources. (D) As in (C), but removing Bantu speakers from coastal Kenya from the list of sources. (E) As in (D) but removing Bantu speakers from the Great Lakes from the list of sources. Full lists of source populations are provided in supplementary table 7, Supplementary Material online.

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