Y-chromosomal variation in sub-Saharan Africa: insights into the history of Niger-Congo groups

Technological and cultural innovations as well as climate changes are thought to have influenced the diffusion of major language phyla in sub-Saharan Africa. The most widespread and the richest in diversity is the Niger-Congo phylum, thought to have originated in West Africa ～ 10,000 years ago (ya). The expansion of Bantu languages (a family within the Niger-Congo phylum) ～ 5,000 ya represents a major event in the past demography of the continent. Many previous studies on Y chromosomal variation in Africa associated the Bantu expansion with haplogroup E1b1a (and sometimes its sublineage E1b1a7). However, the distribution of these two lineages extends far beyond the area occupied nowadays by Bantu-speaking people, raising questions on the actual genetic structure behind this expansion. To address these issues, we directly genotyped 31 biallelic markers and 12 microsatellites on the Y chromosome in 1,195 individuals of African ancestry focusing on areas that were previously poorly characterized (Botswana, Burkina Faso, Democratic Republic of Congo, and Zambia). With the inclusion of published data, we analyzed 2,736 individuals from 26 groups representing all linguistic phyla and covering a large portion of sub-Saharan Africa. Within the Niger-Congo phylum, we ascertain for the first time differences in haplogroup composition between Bantu and non-Bantu groups via two markers (U174 and U175) on the background of haplogroup E1b1a (and E1b1a7), which were directly genotyped in our samples and for which genotypes were inferred from published data using linear discriminant analysis on short tandem repeat (STR) haplotypes. No reduction in STR diversity levels was found across the Bantu groups, suggesting the absence of serial founder effects. In addition, the homogeneity of haplogroup composition and pattern of haplotype sharing between Western and Eastern Bantu groups suggests that their expansion throughout sub-Saharan Africa reflects a rapid spread followed by backward and forward migrations. Overall, we found that linguistic affiliations played a notable role in shaping sub-Saharan African Y chromosomal diversity, although the impact of geography is clearly discernible.     

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.     

mtDNA variability in two Bantu‐speaking populations (Shona and Hutu) from Eastern Africa: Implications for peopling and migration patterns in sub‐Saharan Africa

In this study, we report novel data on mitochondrial DNA in two of the largest eastern Bantu‐speaking populations, the Shona from Zimbabwe and the Hutu from Rwanda. The goal is to evaluate the genetic relationships of these two ethnic groups with other Bantu‐speaking populations. Moreover, by comparing our data with those from other Niger‐Congo speaking populations, we aim to clarify some aspects of evolutionary and demographic processes accompanying the spread of Bantu languages in sub‐Saharan Africa and to test if patterns of genetic variation fit with models of population expansion based on linguistic and archeological data. The results indicate that the Shona and Hutu are closely related to the other Bantu‐speaking populations. However, there are some differences in haplogroup composition between the two populations, mainly due to different genetic contributions from neighboring populations. This result is confirmed by estimates of migration rates which show high levels of gene flow not only between pairs of Bantu‐speaking populations, but also between Bantu and non‐Bantu speakers. The observed pattern of genetic variability (high genetic homogeneity and high levels of gene flow) supports a linguistic model suggesting a gradual spread of Bantu‐speakers, with strong interactions between the different lines of Bantu‐speaker descent, and is also in agreement with recent archeological findings. In conclusion, our data emphasize the role that population admixture has played at different times and to varying degrees in the dispersal of Bantu languages. Am J Phys Anthropol, 2009. © 2009 Wiley‐Liss, Inc.     

The Bantu expansion revisited: a new analysis of Y chromosome variation in Central Western Africa

The current distribution of Bantu languages is commonly considered to be a consequence of a relatively recent population expansion (3-5kya) in Central Western Africa. While there is a substantial consensus regarding the centre of origin of Bantu languages (the Benue River Valley, between South East Nigeria and Western Cameroon), the identification of the area from where the population expansion actually started, the relation between the processes leading to the spread of languages and peoples and the relevance of local migratory events remain controversial. In order to shed new light on these aspects, we studied Y chromosome variation in a broad dataset of populations encompassing Nigeria, Cameroon, Gabon and Congo. Our results evidence an evolutionary scenario which is more complex than had been previously thought, pointing to a marked differentiation of Cameroonian populations from the rest of the dataset. In fact, in contrast with the current view of Bantu speakers as a homogeneous group of populations, we observed an unexpectedly high level of interpopulation genetic heterogeneity and highlighted previously undetected diversity for lineages associated with the diffusion of Bantu languages (E1b1a (M2) sub-branches). We also detected substantial differences in local demographic histories, which concord with the hypotheses regarding an early diffusion of Bantu languages into the forest area and a subsequent demographic expansion and migration towards eastern and western Africa.     

Genetic variation in North Africa and Eurasia: Neolithic demic diffusion vs. paleolithic colonisation

The hypothesis that both genetic and linguistic similarities among Eurasian and North African populations are due to demic diffusion of neolithic farmers is tested against a wide database of allele frequencies. Demic diffusion of farming and languages from the Near East should have determined clines in areas defined by linguistic criteria; the alternative hypothesis of cultural transmission does not predict clines. Spatial autocorrelation analysis shows significant gradients in three of the four linguistic families supposedly affected by neolithic demic diffusion; the Afroasiatic family is the exception. Many such gradients are not observed when populations are jointly analyzed, regardless of linguistic classification. This is incompatible with the hypothesis that major cultural transformations in Eurasia (diffusion of related languages and spread of agriculture) took place without major demographic changes. The model of demic diffusion seems therefore to provide a mechanism explaining coevolution of linguistic and biological traits in much of the Old World. Archaeological, linguistic, and genetic evidence agree in suggesting a multidirectional process of gene flow from the Near East in the neolithic. However, the possibility should be envisaged that some allele frequency patterns can predate the neolithic and depend on the initial spread of Homo sapiens sapiens from Africa into Eurasia. © 1994 Wiley-Liss, Inc.     

Insights into the demographic history of African Pygmies from complete mitochondrial genomes

Pygmy populations are among the few hunter-gatherers currently living in sub-Saharan Africa and are mainly represented by two groups, Eastern and Western, according to their current geographical distribution. They are scattered across the Central African belt and surrounded by Bantu-speaking farmers, with whom they have complex social and economic interactions. To investigate the demographic history of Pygmy groups, a population approach was applied to the analysis of 205 complete mitochondrial DNA (mtDNA) sequences from ten central African populations. No sharing of maternal lineages was observed between the two Pygmy groups, with haplogroup L1c being characteristic of the Western group but most of Eastern Pygmy lineages falling into subclades of L0a, L2a, and L5. Demographic inferences based on Bayesian coalescent simulations point to an early split among the maternal ancestors of Pygmies and those of Bantu-speaking farmers (～ 70,000 years ago [ya]). Evidence for population growth in the ancestors of Bantu-speaking farmers has been observed, starting ～ 65,000 ya, well before the diffusion of Bantu languages. Subsequently, the effective population size of the ancestors of Pygmies remained constant over time and ～ 27,000 ya, coincident with the Last Glacial Maximum, Eastern and Western Pygmies diverged, with evidence of subsequent migration only among the Western group and the Bantu-speaking farmers. Western Pygmies show signs of a recent bottleneck 4,000-650 ya, coincident with the diffusion of Bantu languages, whereas Eastern Pygmies seem to have experienced a more ancient decrease in population size (20,000-4,000 ya). In conclusion, the results of this first attempt at analyzing complete mtDNA sequences at the population level in sub-Saharan Africa not only support previous findings but also offer new insights into the demographic history of Pygmy populations, shedding new light on the ancient peopling of the African continent.     

Cultural phylogeography of the Bantu Languages of sub-Saharan Africa

There is disagreement about the routes taken by populations speaking Bantu languages as they expanded to cover much of sub-Saharan Africa. Here, we build phylogenetic trees of Bantu languages and map them onto geographical space in order to assess the likely pathway of expansion and test between dispersal scenarios. The results clearly support a scenario in which groups first moved south through the rainforest from a homeland somewhere near the Nigeria–Cameroon border. Emerging on the south side of the rainforest, one branch moved south and west. Another branch moved towards the Great Lakes, eventually giving rise to the monophyletic clade of East Bantu languages that inhabit East and Southeastern Africa. These phylogenies also reveal information about more general processes involved in the diversification of human populations into distinct ethnolinguistic groups. Our study reveals that Bantu languages show a latitudinal gradient in covering greater areas with increasing distance from the equator. Analyses suggest that this pattern reflects a true ecological relationship rather than merely being an artefact of shared history. The study shows how a phylogeographic approach can address questions relating to the specific histories of certain groups, as well as general cultural evolutionary processes.     

Bayesian phylogenetic analysis supports an agricultural origin of Japonic languages

Languages, like genes, evolve by a process of descent with modification. This striking similarity between biological and linguistic evolution allows us to apply phylogenetic methods to explore how languages, as well as the people who speak them, are related to one another through evolutionary history. Language phylogenies constructed with lexical data have so far revealed population expansions of Austronesian, Indo-European and Bantu speakers. However, how robustly a phylogenetic approach can chart the history of language evolution and what language phylogenies reveal about human prehistory must be investigated more thoroughly on a global scale. Here we report a phylogeny of 59 Japonic languages and dialects. We used this phylogeny to estimate time depth of its root and compared it with the time suggested by an agricultural expansion scenario for Japanese origin. In agreement with the scenario, our results indicate that Japonic languages descended from a common ancestor approximately 2182 years ago. Together with archaeological and biological evidence, our results suggest that the first farmers of Japan had a profound impact on the origins of both people and languages. On a broader level, our results are consistent with a theory that agricultural expansion is the principal factor for shaping global linguistic diversity.     

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.     

Indo-European origins: A computer-simulation test of five hypotheses

Allele frequency distributions were generated by computer simulation of five models of microevolution in European populations. Genetic distances calculated from these distributions were compared with observed genetic distances among Indo-European speakers. The simulated models differ in complexity, but all incorporate random genetic drift and short-range gene flow (isolation by distance). The best correlations between observed and simulated data were obtained for two models where dispersal of Neolithic farmers from the Near East depends only on population growth. More complex models, where the timing of the farmers' expansion is constrained by archaeological time data, fail to account for a larger fraction of the observed genetic variation; this is also the case for a model including late Neolithic migrations from the Pontic steppes. The genetic structure of current populations speaking Indo-European languages seems therefore to largely reflect a Neolithic expansion. This is consistent with the hypothesis of a parallel spread of farming technologies and a proto-Indo-European language in the Neolithic. Allele-frequency gradients among Indo-European speakers may be due either to incomplete admixture between dispersing farmers, who presumably spoke proto-Indo-European, and pre-existing hunters and gatherers (as in the traditional demic diffusion hypothesis), or to founder effects during the farmers' dispersal. By contrast, successive migrational waves from the East, if any, do not seem to have had genetic consequences detectable by the present comparison of observed and simulated allele frequencies. © 1995 Wiley-Liss, Inc.     

Bantu language trees reflect the spread of farming across sub-Saharan Africa: a maximum-parsimony analysis

Linguistic divergence occurs after speech communities divide, in a process similar to speciation among isolated biological populations. The resulting languages are hierarchically related, like genes or species. Phylogenetic methods developed in evolutionary biology can thus be used to infer language trees, with the caveat that 'borrowing' of linguistic elements between languages also occurs, to some degree. Maximum-parsimony trees for 75 Bantu and Bantoid African languages were constructed using 92 items of basic vocabulary. The level of character fit on the trees was high (consistency index was 0.65), indicating that a tree model fits Bantu language evolution well, at least for the basic vocabulary. The Bantu language tree reflects the spread of farming across this part of sub-Saharan Africa between ca. 3000 BC and AD 500. Modern Bantu subgroups, defined by clades on parsimony trees, mirror the earliest farming traditions both geographically and temporally. This suggests that the major subgroups of modern Bantu stem from the Neolithic and Early Iron Age, with little subsequent movement by speech communities.     

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. Am J Phys Anthropol 150:482–491, 2013. © 2013 Wiley Periodicals, Inc.     

Unraveling the complex maternal history of Southern African Khoisan populations

The Khoisan populations of southern Africa are known to harbor some of the deepest‐rooting lineages of human mtDNA; however, their relationships are as yet poorly understood. Here, we report the results of analyses of complete mtDNA genome sequences from nearly 700 individuals representing 26 populations of southern Africa who speak diverse Khoisan and Bantu languages. Our data reveal a multilayered history of the indigenous populations of southern Africa, who are likely to be the result of admixture of different genetic substrates, such as resident forager populations and pre‐Bantu pastoralists from East Africa. We find high levels of genetic differentiation of the Khoisan populations, which can be explained by the effect of drift together with a partial uxorilocal/multilocal residence pattern. Furthermore, there is evidence of extensive contact, not only between geographically proximate groups, but also across wider areas. The results of this contact, which may have played a role in the diffusion of common cultural and linguistic features, are especially evident in the Khoisan populations of the central Kalahari. Am J Phys Anthropol 153:435–448, 2014. © 2013 Wiley Periodicals, Inc.     

Iberia: population genetics, anthropology, and linguistics.

Basques, Portuguese, Spaniards, and Algerians have been studied for HLA and mitochondrial DNA markers, and the data analysis suggests that pre-Neolithic gene flow into Iberia came from ancient white North Africans (Hamites). The Basque language has also been used to translate the Iberian-Tartesian language and also Etruscan and Minoan Linear A. Physical anthropometry of Iberian Mesolithic and Neolithic skeletons does not support the demic replacement in Iberia of preexisting Mesolithic people by Neolithic people bearing new farming technologies from Europe and the Middle East. Also, the presence of cardial impressed pottery in western Mediterranean Europe and across the Maghreb (North Africa) coasts at the beginning of the Neolithic provides good evidence of pre-Neolithic circum-Mediterranean contacts by sea. In addition, pre-dynastic Egyptian El-Badari culture (4,500 years ago) is similar to southern Iberian Neolithic settlements with regard to pottery and animal domestication. Taking the genetic, linguistic, anthropological, and archeological evidence together with the documented Saharan area desiccation starting about 10,000 years ago, we believe that it is possible that a genetic and cultural pre-Neolithic flow coming from southern Mediterranean coasts existed toward northern Mediterranean areas, including at least Iberia and some Mediterranean islands. This model would substitute for the demic diffusion model put forward to explain Neolithic innovations in Western Europe.     

A Comparison of Y-Chromosome Variation in Sardinia and Anatolia Is More Consistent with Cultural Rather than Demic Diffusion of Agriculture

Two alternative models have been proposed to explain the spread of agriculture in Europe during the Neolithic period. The demic diffusion model postulates the spreading of farmers from the Middle East along a Southeast to Northeast axis. Conversely, the cultural diffusion model assumes transmission of agricultural techniques without substantial movements of people. Support for the demic model derives largely from the observation of frequency gradients among some genetic variants, in particular haplogroups defined by single nucleotide polymorphisms (SNPs) in the Y-chromosome. A recent network analysis of the R-M269 Y chromosome lineage has purportedly corroborated Neolithic expansion from Anatolia, the site of diffusion of agriculture. However, the data are still controversial and the analyses so far performed are prone to a number of biases. In the present study we show that the addition of a single marker, DYSA7.2, dramatically changes the shape of the R-M269 network into a topology showing a clear Western-Eastern dichotomy not consistent with a radial diffusion of people from the Middle East. We have also assessed other Y-chromosome haplogroups proposed to be markers of the Neolithic diffusion of farmers and compared their intra-lineage variation—defined by short tandem repeats (STRs)—in Anatolia and in Sardinia, the only Western population where these lineages are present at appreciable frequencies and where there is substantial archaeological and genetic evidence of pre-Neolithic human occupation. The data indicate that Sardinia does not contain a subset of the variability present in Anatolia and that the shared variability between these populations is best explained by an earlier, pre-Neolithic dispersal of haplogroups from a common ancestral gene pool. Overall, these results are consistent with the cultural diffusion and do not support the demic model of agriculture diffusion.     

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.     

Rejection of a serial founder effects model of genetic and linguistic coevolution

Recent genetic studies attribute the negative correlation between population genetic diversity and distance from Africa to a serial founder effects (SFE) evolutionary process. A recent linguistic study concluded that a similar decay in phoneme inventories in human languages was also the product of the SFE process. However, the SFE process makes additional predictions for patterns of neutral genetic diversity, both within and between groups, that have not yet been tested on phonemic data. In this study, we describe these predictions and test them on linguistic and genetic samples. The linguistic sample consists of 725 widespread languages, which together contain 908 distinct phonemes. The genetic sample consists of 614 autosomal microsatellite loci in 100 widespread populations. All aspects of the genetic pattern are consistent with the predictions of SFE. In contrast, most of the predictions of SFE are violated for the phonemic data. We show that phoneme inventories provide information about recent contacts between languages. However, because phonemes change rapidly, they cannot provide information about more ancient evolutionary processes.     

Y-chromosomal diversity in Europe is clinal and influenced primarily by geography, rather than by language

Clinal patterns of autosomal genetic diversity within Europe have been interpreted in previous studies in terms of a Neolithic demic diffusion model for the spread of agriculture; in contrast, studies using mtDNA have traced many founding lineages to the Paleolithic and have not shown strongly clinal variation. We have used 11 human Y-chromosomal biallelic polymorphisms, defining 10 haplogroups, to analyze a sample of 3,616 Y chromosomes belonging to 47 European and circum-European populations. Patterns of geographic differentiation are highly nonrandom, and, when they are assessed using spatial autocorrelation analysis, they show significant clines for five of six haplogroups analyzed. Clines for two haplogroups, representing 45% of the chromosomes, are continentwide and consistent with the demic diffusion hypothesis. Clines for three other haplogroups each have different foci and are more regionally restricted and are likely to reflect distinct population movements, including one from north of the Black Sea. Principal-components analysis suggests that populations are related primarily on the basis of geography, rather than on the basis of linguistic affinity. This is confirmed in Mantel tests, which show a strong and highly significant partial correlation between genetics and geography but a low, nonsignificant partial correlation between genetics and language. Genetic-barrier analysis also indicates the primacy of geography in the shaping of patterns of variation. These patterns retain a strong signal of expansion from the Near East but also suggest that the demographic history of Europe has been complex and influenced by other major population movements, as well as by linguistic and geographic heterogeneities and the effects of drift.     

The Genetic Legacy of the Expansion of Turkic-Speaking Nomads across Eurasia

The Turkic peoples represent a diverse collection of ethnic groups defined by the Turkic languages. These groups have dispersed across a vast area, including Siberia, Northwest China, Central Asia, East Europe, the Caucasus, Anatolia, the Middle East, and Afghanistan. The origin and early dispersal history of the Turkic peoples is disputed, with candidates for their ancient homeland ranging from the Transcaspian steppe to Manchuria in Northeast Asia. Previous genetic studies have not identified a clear-cut unifying genetic signal for the Turkic peoples, which lends support for language replacement rather than demic diffusion as the model for the Turkic language’s expansion. We addressed the genetic origin of 373 individuals from 22 Turkic-speaking populations, representing their current geographic range, by analyzing genome-wide high-density genotype data. In agreement with the elite dominance model of language expansion most of the Turkic peoples studied genetically resemble their geographic neighbors. However, western Turkic peoples sampled across West Eurasia shared an excess of long chromosomal tracts that are identical by descent (IBD) with populations from present-day South Siberia and Mongolia (SSM), an area where historians center a series of early Turkic and non-Turkic steppe polities. While SSM matching IBD tracts (> 1cM) are also observed in non-Turkic populations, Turkic peoples demonstrate a higher percentage of such tracts (p-values ≤ 0.01) compared to their non-Turkic neighbors. Finally, we used the ALDER method and inferred admixture dates (~9th–17th centuries) that overlap with the Turkic migrations of the 5th–16th centuries. Thus, our results indicate historical admixture among Turkic peoples, and the recent shared ancestry with modern populations in SSM supports one of the hypothesized homelands for their nomadic Turkic and related Mongolic ancestors.     

Genetic and linguistic coevolution in Northern Island Melanesia

Recent studies have detailed a remarkable degree of genetic and linguistic diversity in Northern Island Melanesia. Here we utilize that diversity to examine two models of genetic and linguistic coevolution. The first model predicts that genetic and linguistic correspondences formed following population splits and isolation at the time of early range expansions into the region. The second is analogous to the genetic model of isolation by distance, and it predicts that genetic and linguistic correspondences formed through continuing genetic and linguistic exchange between neighboring populations. We tested the predictions of the two models by comparing observed and simulated patterns of genetic variation, genetic and linguistic trees, and matrices of genetic, linguistic, and geographic distances. The data consist of 751 autosomal microsatellites and 108 structural linguistic features collected from 33 Northern Island Melanesian populations. The results of the tests indicate that linguistic and genetic exchange have erased any evidence of a splitting and isolation process that might have occurred early in the settlement history of the region. The correlation patterns are also inconsistent with the predictions of the isolation by distance coevolutionary process in the larger Northern Island Melanesian region, but there is strong evidence for the process in the rugged interior of the largest island in the region (New Britain). There we found some of the strongest recorded correlations between genetic, linguistic, and geographic distances. We also found that, throughout the region, linguistic features have generally been less likely to diffuse across population boundaries than genes. The results from our study, based on exceptionally fine-grained data, show that local genetic and linguistic exchange are likely to obscure evidence of the early history of a region, and that language barriers do not particularly hinder genetic exchange. In contrast, global patterns may emphasize more ancient demographic events, including population splits associated with the early colonization of major world regions.