Genetic homogeneity across Bantu-speaking groups from Mozambique and Angola challenges early split scenarios between East and West Bantu populations

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

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.

Revising the Bantu tree

Phylogenetic methods offer a promising advance for the historical study of language and cultural relationships. Applications to date, however, have been hampered by traditional approaches dependent on unfalsifiable authority statements: in this regard, historical linguistics remains in a similar position to evolutionary biology prior to the cladistic revolution. Influential phylogenetic studies of Bantu languages over the last two decades, which provide the foundation for multiple analyses of Bantu sociocultural histories, are a major case in point. Comparative analyses of basic lexica, instead of directly treating written words, use only numerical symbols that express non-replicable authority opinion about underlying relationships. Building on a previous study of Uto-Aztecan, here we analyse Bantu language relationships with methods deriving from DNA sequence optimization algorithms, treating basic vocabulary as sequences of sounds. This yields finer-grained results that indicate major revisions to the Bantu tree, and enables more robust inferences about the history of Bantu language expansion and/or migration throughout sub-Saharan Africa. "Early-split" versus "late-split" hypotheses for East and West Bantu are tested, and overall results are compared to trees based on numerical reductions of vocabulary data. Reconstruction of language histories is more empirically based and robust than with previous methods.

Genome-wide diversity and demographic dynamics of Cameroon goats and their divergence from east African, north African, and Asian conspecifics

Indigenous goats make significant contributions to Cameroon’s national and local economy, but little effort has been devoted to identifying the populations. Here, we assessed the genetic diversity and demographic dynamics of Cameroon goat populations using mitochondrial DNA (two populations) and autosomal markers (four populations) generated with the Caprine 50K SNP chip. To infer genetic relationships at continental and global level, genotype data on six goat populations from Ethiopia and one population each from Egypt, Morocco, Iran, and China were included in the analysis. The mtDNA analysis revealed 83 haplotypes, all belonging to haplogroup A, in Cameroon goats. Four haplotypes were shared between goats found in Cameroon, Mozambique, Namibia, Zimbabwe, Kenya, and Ethiopia. Analysis of autosomal SNPs in Cameroon goats revealed the lowest H_O (0.335±0.13) and H_E (0.352±0.15) in the North-west Highland and Central Highland populations, respectively. Overall, the highest H_O (0.401±0.12) and H_E (0.422±0.12) were found for Barki and Iranian goats, respectively. Barki goats had the highest average MAF, while Central Highland Cameroon goats had the lowest. Overall, Cameroon goats demonstrated high F_IS. AMOVA revealed that 13.29% of the variation was explained by genetic differences between the six population groups. Low average F_ST (0.01) suggests intermixing among Cameroon goats. All measures indicated that Cameroon goats are closer to Moroccan goats than to other goat populations. PCA and STRUCTURE analyses poorly differentiated the Cameroon goats, as did genetic distance, Neighbor-Net network, and neighbor-joining tree analyses. The haplotype analysis of mtDNA showed the initial dispersion of goats to Cameroon and central Africa from north-east Africa following the Nile Delta. Whereas, the approximate Bayesian computation indicated Cameroon goats were separated from Moroccan goats after 506 generations in later times (~1518 YA), as supported by the phylogenetic net-work and admixture outputs. Overall, indigenous goats in Cameroon show weak phylogenetic structure, suggesting either extensive intermixing.

G1 is the major APOL1 risk allele for hypertension-attributed nephropathy in Central Africa

Background

Sub-Saharan Africans exhibit a higher frequency of chronic kidney disease (CKD) than other populations. In this study, we sought to determine the frequency of apolipoprotein L1 (APOL1) genotypes in hypertension-attributed CKD in Kinshasa, Democratic Republic of the Congo.

Methods

We performed a case-control study identifying 162 subjects: 79 with hypertension-attributed CKD and 83 controls living in Kinshasa who were genotyped for APOL1 risk variants between July 2013 and November 2016. We selected control subjects from the general population and matched them with the cases according to age. Logistic regression analysis was used to examine the relationship between APOL1 high-risk genotypes and CKD.

Results

The frequencies of the APOL1 G1 and G2 alleles were 19.1 and 7.1%, respectively. The number of individuals with the G1 and G2 risk alleles was significantly higher in the CKD group (12.7%) than in the control group (2.4%), particularly in individuals with end-stage kidney disease (14.3%). Subjects carrying two risk alleles was strongly and independently associated with hypertension-attributed nephropathy, with an adjusted odds ratio of 7.7 (95% confidence interval 1.5-39.7; P = 0.014). The high-risk APOL1 genotypes were G1/G1 and G1/G2, whereas G2/G2 was not found in the study population.

Conclusions

The results of this study demonstrate the association of high-risk APOL1 genotypes with kidney disease in Kinshasa. The absence of G2/G2 may be consistent with powerful selective sweeps induced by Trypanosoma brucei gambiense infection. In contrast, the presence of APOL1 G2/G2 among individuals of African ancestry in the USA may indicate relaxation of natural selection in a trypanosome-free environment.

Tales of Human Migration, Admixture, and Selection in Africa

In the last three decades, genetic studies have played an increasingly important role in exploring human history. They have helped to conclusively establish that anatomically modern humans first appeared in Africa roughly 250,000–350,000 years before present and subsequently migrated to other parts of the world. The history of humans in Africa is complex and includes demographic events that influenced patterns of genetic variation across the continent. Through genetic studies, it has become evident that deep African population history is captured by relationships among African hunter–gatherers, as the world's deepest population divergences occur among these groups, and that the deepest population divergence dates to 300,000 years before present. However, the spread of pastoralism and agriculture in the last few thousand years has shaped the geographic distribution of present-day Africans and their genetic diversity. With today's sequencing technologies, we can obtain full genome sequences from diverse sets of extant and prehistoric Africans. The coming years will contribute exciting new insights toward deciphering human evolutionary history in Africa.

The archaeological evidence for the appearance of pastoralism and farming in southern Africa

This paper is a response to the growing reference to archaeological evidence by linguists and geneticists interested in the spread of early farmers and pastoralists in southern Africa. It presents two databases. The first contains the archaeological evidence for pastoralism and farming in southern Africa, for the period 550 BC to AD 1050. This is the first time that the seven different types of archaeological evidence that have traditionally been used to identify both spread events are presented together at this scale. This was stimulated by our interest in investigating the antiquity of an early 'Iron Age package' relative to the spread of single archaeological traits. The analysis shows that the package appears approximately 700 years after sites containing pottery, cattle and sheep, without agriculture, appear in the drier parts of the sub-continent. It post-dates the appearance of earlier sites with pottery associated with farmers, metal-working and cultivation in the eastern half of the sub-continent. While poor preservation undoubtedly explains the absence of some parts of the package, the analysis suggests that other explanations should be considered. The second database is a quantitative, spatial study of archaeological publications on southern African farming and pastoralism for the period 1950 to 2016, covering the same geographical area and archaeological timeframe. This is presented as a proxy for research-intensive areas in attempt to show the gaps in archaeological fieldwork and knowledge.

Comparison between an African town and a neighbouring village shows delayed, but not decreased, sleep during the early stages of urbanisation

The well-established negative health outcomes of sleep deprivation, and the suggestion that availability of electricity may enable later bed times without compensating sleep extension in the morning, have stimulated interest in studying communities whose sleep pattern may resemble a pre-industrial state. Here, we describe sleep and activity in two neighbouring communities, one urban (Milange) and one rural (Tengua), in a region of Mozambique where urbanisation is an ongoing process. The two communities differ in the amount and timing of daily activity and of light exposure, with later bedtimes (≈1 h) associated with more evening and less daytime light exposure seen in the town of Milange. In contrast to previous reports comparing communities with and without electricity, sleep duration did not differ between Milange (7.28 h) and Tengua (7.23 h). Notably, calculated sleep quality was significantly poorer in rural Tengua than in Milange, and poor sleep quality was associated with a number of attributes more characteristic of rural areas, including more intense physical labour and less comfortable sleeping arrangements. Thus, whilst our data support the hypothesis that access to electricity delays sleep timing, the higher sleep quality in the urban population also suggests that some aspects of industrialisation are beneficial to sleep.

Food and pathogen adaptations in the Angolan Namib desert: Tracing the spread of lactase persistence and human African trypanosomiasis resistance into southwestern Africa

OBJECTIVES

We investigated the frequency distribution and haplotype diversity of human African trypanosomiasis (HAT) resistance and lactase persistence (LP) variants in populations from the Angolan Namib to trace the spread of these genetic adaptations into southwestern Africa.

MATERIALS AND METHODS

We resequenced two fragments of the LCT enhancer and the APOL1 gene and genotyped flanking short tandem repeat loci in six groups with different subsistence traditions living in the Angolan Namib, and in a comparative dataset including other populations from Africa and Europe. LP in the Angolan Namib is represented by the -14010*C allele, which is associated with a predominant haplotype that is shared with other southern and eastern African populations. While LP was found to be more frequent in foragers than in pastoralists, the frequencies of the two APOL1 variants associated with HAT-resistance (G1 and G2) did not differ between the two groups. The G1 allele is mostly associated with a single widespread haplotype. The G2 allele is linked to several haplotypes that are molecularly related to haplotypes found in other African Bantu-speaking populations. The putatively archaic G3 variant displayed more intra-allelic diversity in Africa than in Europe.

DISCUSSION

The LP adaptation was carried to southern Africa by non-Bantu speaking pastoralists from eastern Africa, but an obvious link between its presence in southern Angola and groups speaking languages of the Khoe-Kwadi family, as previously found in other areas, could not be confirmed. The presence of APOL1 variants G1 and G2 is linked to the Bantu expansions. Our results suggest that the G3 variant was retained in modern humans by incomplete lineage sorting.

At the southeast fringe of the Bantu expansion: genetic diversity and phylogenetic relationships to other sub-Saharan tribes

Here, we present 12 loci paternal haplotypes (Y-STR profiles) against the backdrop of the Y-SNP marker system of Bantu males from the Maputo Province of Southeast Africa, a region believed to represent the southeastern fringe of the Bantu expansion. Our Maputo Bantu group was analyzed within the context of 27 geographically relevant reference populations in order to ascertain its genetic relationship to other Bantu and non Bantu (Pygmy, Khoisan and Nilotic) sub-equatorial tribes from West and East Africa. This study entails statistical pair wise comparisons and multidimensional scaling based on YSTR Rst distances, network analyses of Bantu (B2a-M150) and Pygmy (B2b-M112) lineages as well as an assessment of Y-SNP distribution patterns. Several notable findings include the following: 1) the Maputo Province Bantu exhibits a relatively close paternal affinity with both east and west Bantu tribes due to high proportion of Bantu Y chromosomal markers, 2) only traces of Khoisan (1.3%) and Pygmy (1.3%) markers persist in the Maputo Province Bantu gene pool, 3) the occurrence of R1a1a-M17/M198, a member of the Eurasian R1a-M420 branch in the population of the Maputo Province, may represent back migration events and/or recent admixture events, 4) the shared presence of E1b1b1-M35 in all Tanzanian tribes examined, including Bantu and non-Bantu groups, in conjunction with its nearly complete absence in the West African populations indicate that, in addition to a shared linguistic, cultural and genetic heritage, geography (e.g., east vs. west) may have impacted the paternal landscape of sub-Saharan Africa, 5) the admixture and assimilation processes of Bantu elements were both highly complex and region-specific.

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Maputo Bantus exhibit close affinities with other West and East African Bantus.

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Traces of Khoisan and Pygmy markers persist in the Maputo Province Bantus.

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R1a1a-M17/M198 in the Maputo Province may represent back or recent migration.

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Linguistic, cultural and genetic heritages are reflected in Maputo's gene pool.

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Admixture and assimilation processes of Bantu elements were region-specific.

Genetic variation reveals large-scale population expansion and migration during the expansion of Bantu-speaking peoples

The majority of sub-Saharan Africans today speak a number of closely related languages collectively referred to as 'Bantu' languages. The current distribution of Bantu-speaking populations has been found to largely be a consequence of the movement of people rather than a diffusion of language alone. Linguistic and single marker genetic studies have generated various hypotheses regarding the timing and the routes of the Bantu expansion, but these hypotheses have not been thoroughly investigated. In this study, we re-analysed microsatellite markers typed for large number of African populations that-owing to their fast mutation rates-capture signatures of recent population history. We confirm the spread of west African people across most of sub-Saharan Africa and estimated the expansion of Bantu-speaking groups, using a Bayesian approach, to around 5600 years ago. We tested four different divergence models for Bantu-speaking populations with a distribution comprising three geographical regions in Africa. We found that the most likely model for the movement of the eastern branch of Bantu-speakers involves migration of Bantu-speaking groups to the east followed by migration to the south. This model, however, is only marginally more likely than other models, which might indicate direct movement from the west and/or significant gene flow with the western Branch of Bantu-speakers. Our study use multi-loci genetic data to explicitly investigate the timing and mode of the Bantu expansion and it demonstrates that west African groups rapidly expanded both in numbers and over a large geographical area, affirming the fact that the Bantu expansion was one of the most dramatic demographic events in human history.

Migration and interaction in a contact zone: mtDNA variation among Bantu-speakers in Southern Africa

Bantu speech communities expanded over large parts of sub-Saharan Africa within the last 4000–5000 years, reaching different parts of southern Africa 1200–2000 years ago. The Bantu languages subdivide in several major branches, with languages belonging to the Eastern and Western Bantu branches spreading over large parts of Central, Eastern, and Southern Africa. There is still debate whether this linguistic divide is correlated with a genetic distinction between Eastern and Western Bantu speakers. During their expansion, Bantu speakers would have come into contact with diverse local populations, such as the Khoisan hunter-gatherers and pastoralists of southern Africa, with whom they may have intermarried. In this study, we analyze complete mtDNA genome sequences from over 900 Bantu-speaking individuals from Angola, Zambia, Namibia, and Botswana to investigate the demographic processes at play during the last stages of the Bantu expansion. Our results show that most of these Bantu-speaking populations are genetically very homogenous, with no genetic division between speakers of Eastern and Western Bantu languages. Most of the mtDNA diversity in our dataset is due to different degrees of admixture with autochthonous populations. Only the pastoralist Himba and Herero stand out due to high frequencies of particular L3f and L3d lineages; the latter are also found in the neighboring Damara, who speak a Khoisan language and were foragers and small-stock herders. In contrast, the close cultural and linguistic relatives of the Herero and Himba, the Kuvale, are genetically similar to other Bantu-speakers. Nevertheless, as demonstrated by resampling tests, the genetic divergence of Herero, Himba, and Kuvale is compatible with a common shared ancestry with high levels of drift, while the similarity of the Herero, Himba, and Damara probably reflects admixture, as also suggested by linguistic analyses.

Modelling the spread of farming in the Bantu-speaking regions of Africa: an archaeology-based phylogeography

We use archaeological data and spatial methods to reconstruct the dispersal of farming into areas of sub-Saharan Africa now occupied by Bantu language speakers, and introduce a new large-scale radiocarbon database and a new suite of spatial modelling techniques. We also introduce a method of estimating phylogeographic relationships from archaeologically-modelled dispersal maps, with results produced in a format that enables comparison with linguistic and genetic phylogenies. Several hypotheses are explored. The ‘deep split’ hypothesis suggests that an early-branching eastern Bantu stream spread around the northern boundary of the equatorial rainforest, but recent linguistic and genetic work tends not to support this. An alternative riverine/littoral hypothesis suggests that rivers and coastlines facilitated the migration of the first farmers/horticulturalists, with some extending this to include rivers through the rainforest as conduits to East Africa. More recently, research has shown that a grassland corridor opened through the rainforest at around 3000–2500 BP, and the possible effect of this on migrating populations is also explored. Our results indicate that rivers and coasts were important dispersal corridors, but do not resolve the debate about a ‘Deep Split’. Future work should focus on improving the size, quality and geographical coverage of the archaeological ¹⁴C database; on augmenting the information base to establish descent relationships between archaeological sites and regions based on shared material cultural traits; and on refining the associated physical geographical reconstructions of changing land cover.

Mitochondrial DNA diversity in two ethnic groups in southeastern Kenya: perspectives from the northeastern periphery of the Bantu expansion

The Bantu languages are widely distributed throughout sub-Saharan Africa. Genetic research supports linguists and historians who argue that migration played an important role in the spread of this language family, but the genetic data also indicates a more complex process involving substantial gene flow with resident populations. In order to understand the Bantu expansion process in east Africa, mtDNA hypervariable region I variation in 352 individuals from the Taita and Mijikenda ethnic groups was analyzed, and we evaluated the interactions that took place between the Bantu- and non-Bantu-speaking populations in east Africa. The Taita and Mijikenda are Bantu-speaking agropastoralists from southeastern Kenya, at least some of whose ancestors probably migrated into the area as part of Bantu migrations that began around 3,000 BCE. Our analyses indicate that they show some distinctive differences that reflect their unique cultural histories. The Taita are genetically more diverse than the Mijikenda with larger estimates of genetic diversity. The Taita cluster with other east African groups, having high frequencies of haplogroups from that region, while the Mijikenda have high frequencies of central African haplogroups and cluster more closely with central African Bantu-speaking groups. The non-Bantu speakers who lived in southeastern Kenya before Bantu speaking groups arrived were at least partially incorporated into what are now Bantu-speaking Taita groups. In contrast, gene flow from non-Bantu speakers into the Mijikenda was more limited. These results suggest a more complex demographic history where the nature of Bantu and non-Bantu interactions varied throughout the area.

Evidence from Y-chromosome analysis for a late exclusively eastern expansion of the Bantu-speaking people

The expansion of the Bantu-speaking people (EBSP) during the past 3000-5000 years is an event of great importance in the history of humanity. Anthropology, archaeology, linguistics and, in recent decades, genetics have been used to elucidate some of the events and processes involved. Although it is generally accepted that the EBSP has its origin in the so-called Bantu Homeland situated in the area of the border between Nigeria and the Grassfields of Cameroon, and that it followed both western and eastern routes, much less is known about the number and dates of those expansions, if more than one. Mitochondrial, Y-chromosome and autosomal DNA analyses have been carried out in attempts to understand the demographic events that have taken place. There is an increasing evidence that the expansion was a more complex process than originally thought and that neither a single demographic event nor an early split between western and eastern groups occurred. In this study, we analysed unique event polymorphism and short tandem repeat variation in non-recombining Y-chromosome haplogroups contained within the E1b1a haplogroup, which is exclusive to individuals of recent African ancestry, in a large, geographically widely distributed, set of sub-Saharan Africans (groups=43, n=2757), all of whom, except one Nilo-Saharan-speaking group, spoke a Niger-Congo language and most a Bantu tongue. Analysis of diversity and rough estimates of times to the most recent common ancestors of haplogroups provide evidence of multiple expansions along eastern and western routes and a late, exclusively eastern route, expansion.

Bringing together linguistic and genetic evidence to test the Bantu expansion

The expansion of Bantu languages represents one of the most momentous events in the history of Africa. While it is well accepted that Bantu languages spread from their homeland (Cameroon/Nigeria) approximately 5000 years ago (ya), there is no consensus about the timing and geographical routes underlying this expansion. Two main models of Bantu expansion have been suggested: The 'early-split' model claims that the most recent ancestor of Eastern languages expanded north of the rainforest towards the Great Lakes region approximately 4000 ya, while the 'late-split' model proposes that Eastern languages diversified from Western languages south of the rainforest approximately 2000 ya. Furthermore, it is unclear whether the language dispersal was coupled with the movement of people, raising the question of language shift versus demic diffusion. We use a novel approach taking into account both the spatial and temporal predictions of the two models and formally test these predictions with linguistic and genetic data. Our results show evidence for a demic diffusion in the genetic data, which is confirmed by the correlations between genetic and linguistic distances. While there is little support for the early-split model, the late-split model shows a relatively good fit to the data. Our analyses demonstrate that subsequent contact among languages/populations strongly affected the signal of the initial migration via isolation by distance.

An early divergence of KhoeSan ancestors from those of other modern humans is supported by an ABC-based analysis of autosomal resequencing data

Sub-Saharan Africa has consistently been shown to be the most genetically diverse region in the world. Despite the fact that a substantial portion of this variation is partitioned between groups practicing a variety of subsistence strategies and speaking diverse languages, there is currently no consensus on the genetic relationships of sub-Saharan African populations. San (a subgroup of KhoeSan) and many Pygmy groups maintain hunter-gatherer lifestyles and cluster together in autosomal-based analysis, whereas non-Pygmy Niger-Kordofanian speakers (non-Pygmy NKs) predominantly practice agriculture and show substantial genetic homogeneity despite their wide geographic range throughout sub-Saharan Africa. However, KhoeSan, who speak a set of relatively unique click-based languages, have long been thought to be an early branch of anatomically modern humans based on phylogenetic analysis. To formally test models of divergence among the ancestors of modern African populations, we resequenced a sample of San, Eastern, and Western Pygmies and non-Pygmy NKs individuals at 40 nongenic (∼2 kb) regions and then analyzed these data within an Approximate Bayesian Computation (ABC) framework. We find substantial support for a model of an early divergence of KhoeSan ancestors from a proto-Pygmy-non-Pygmy NKs group ∼110 thousand years ago over a model incorporating a proto-KhoeSan-Pygmy hunter-gatherer divergence from the ancestors of non-Pygmy NKs. The results of our analyses are consistent with previously identified signals of a strong bottleneck in Mbuti Pygmies and a relatively recent expansion of non-Pygmy NKs. We also develop a number of methodologies that utilize "pseudo-observed" data sets to optimize our ABC-based inference. This approach is likely to prove to be an invaluable tool for demographic inference using genome-wide resequencing data.