Human ancestry solves language questions? New admixture citebait

human_ancestry

A paper at Scientific Reports, Human ancestry correlates with language and reveals that race is not an objective genomic classifier, by Baker, Rotimi, and Shriner (2017).

Abstract (emphasis mine):

Genetic and archaeological studies have established a sub-Saharan African origin for anatomically modern humans with subsequent migrations out of Africa. Using the largest multi-locus data set known to date, we investigated genetic differentiation of early modern humans, human admixture and migration events, and relationships among ancestries and language groups. We compiled publicly available genome-wide genotype data on 5,966 individuals from 282 global samples, representing 30 primary language families. The best evidence supports 21 ancestries that delineate genetic structure of present-day human populations. Independent of self-identified ethno-linguistic labels, the vast majority (97.3%) of individuals have mixed ancestry, with evidence of multiple ancestries in 96.8% of samples and on all continents. The data indicate that continents, ethno-linguistic groups, races, ethnicities, and individuals all show substantial ancestral heterogeneity. We estimated correlation coefficients ranging from 0.522 to 0.962 between ancestries and language families or branches. Ancestry data support the grouping of Kwadi-Khoe, Kx’a, and Tuu languages, support the exclusion of Omotic languages from the Afroasiatic language family, and do not support the proposed Dené-Yeniseian language family as a genetically valid grouping. Ancestry data yield insight into a deeper past than linguistic data can, while linguistic data provide clarity to ancestry data.

Regarding European ancestry:

Southern European ancestry correlates with both Italic and Basque speakers (r = 0.764, p = 6.34 × 10−49). Northern European ancestry correlates with Germanic and Balto-Slavic branches of the Indo-European language family as well as Finno-Ugric and Mordvinic languages of the Uralic family (r = 0.672, p = 4.67 × 10−34). Italic, Germanic, and Balto-Slavic are all branches of the Indo-European language family, while the correlation with languages of the Uralic family is consistent with an ancient migration event from Northern Asia into Northern Europe. Kalash ancestry is widely spread but is the majority ancestry only in the Kalash people (Table S3). The Kalasha language is classified within the Indo-Iranian branch of the Indo-European language family.

Sure, admixture analysis came to save the day. Yet again. Now it’s not just Archaeology related to language anymore, it’s Linguistics; all modern languages and their classification, no less. Because why the hell not? Why would anyone study languages, history, archaeology, etc. when you can run certain algorithms on free datasets of modern populations to explain everything?

What I am criticising here, as always, is not the study per se, its methods (PCA, the use of Admixture or any other tools), or its results, which might be quite interesting – even regarding the origin or position of certain languages (or more precisely their speakers) within their linguistic groups; it’s the many broad, unsupported, striking conclusions (read the article if you want to see more wishful thinking).

This is obviously simplistic citebait – that benefits only journals and authors, and it is therefore tacitly encouraged -, but not knowledge, because it is not supported by any linguistic or archaeological data or expertise.

Is anyone with a minimum knowledge of languages, or general anthropology, actually reviewing these articles?

Related:

Featured image: Ancestry analysis of the global data set, from the article.

Indo-European and Central Asian admixture in Indian population, dependent on ethnolinguistic and geodemographic divisions

indian-population-genetics

Preprint paper at BioRxiv, Dissecting Population Substructure in India via Correlation Optimization of Genetics and Geodemographics, by Bose et al. (2017), a mixed group from Purdue University and IBM TJ Watson Research Center. A rather simple paper, which is nevertheless interesting in its approach to the known multiple Indian demographic divisions, and in its short reported methods and results.

Abstract:

India represents an intricate tapestry of population substructure shaped by geography, language, culture and social stratification operating in concert. To date, no study has attempted to model and evaluate how these evolutionary forces have interacted to shape the patterns of genetic diversity within India. Geography has been shown to closely correlate with genetic structure in other parts of the world. However, the strict endogamy imposed by the Indian caste system, and the large number of spoken languages add further levels of complexity. We merged all publicly available data from the Indian subcontinent into a data set of 835 individuals across 48,373 SNPs from 84 well-defined groups. Bringing together geography, sociolinguistics and genetics, we developed COGG (Correlation Optimization of Genetics and Geodemographics) in order to build a model that optimally explains the observed population genetic sub-structure. We find that shared language rather than geography or social structure has been the most powerful force in creating paths of gene flow within India. Further investigating the origins of Indian substructure, we create population genetic networks across Eurasia. We observe two major corridors towards mainland India; one through the Northwestern and another through the Northeastern frontier with the Uygur population acting as a bridge across the two routes. Importantly, network, ADMIXTURE analysis and f3 statistics support a far northern path connecting Europe to Siberia and gene flow from Siberia and Mongolia towards Central Asia and India.

Among the most interesting results (emphasis mine):

Our meta-analysis of the ADMIXTURE output shows that the IE and DR populations across castes shared very high ancestry, indicating the autochthonous origin of the caste system in India (Figure 2). f3 statistics show that most of the castes and tribes in India are admixed, with contributions from other castes and/or tribes, across languages affiliations (Supplementary Table 4 and Supplementary Note). The geographically isolated Tibeto-Burman tribes and the Dravidian speaking tribes appear to be the most isolated in India. Linear Discriminant Analysis on the normalized data set clearly supports genetic strati cation by castes and languages in the Indian sub-continent

(…)

Our meta-analysis of the ADMIXTURE plot in Figure 4A quantifies the ADMIXTURE results (darker colors indicate higher pairwise shared ancestry). Indian populations show a greater proportion of shared ancestry with the so-called Indian Northwestern Frontier populations, namely the tribal populations spanning Afghanistan and Pakistan. Central Asian populations share higher degrees of ancestry with IE and DR Froward castes. Uygurs share high degrees of ancestry with Indian populations.

(…)

f3 statistics (all negative Z-scores are shown) indicate Chinese and Siberian ancestry contributing to the Tibeto-Burman tribal speakers. On the other hand, the Mongols and the Europeans have contributed significant amounts of ancestry to the Indo-European and Tibeto-Burman forward castes. F3 statistics also show that the Central Asians are an admixed population with signs of admixture from Caucasus and other parts of Europe.

Among the results for proportions of shared ancestry between Indians and Eurasians (FIG. 4), there is an obvious influence of European admixture (Caucasus, and Southern, Central, and Northern EU), potentially from the Yamna-Corded Ware expansion, in IE_ForwardCaste, which is lessened in IE_BackwardCaste and also in IE_Tribal, while DR_ForwardCaste shows again more admixture than IE_Tribal, but diminishing with lower castes and quite low in DR_Tribal.

Ancestry from Central Asia is strong with a similar pattern, which hints at the influence of Sintashta, Andronovo, and BMAC influence in the expansion of the Steppe component, even more than a later Turkic component.

On the other hand, the influence from Turkey is difficult to assess, given the complex genetic history of Anatolia, but the map contained in Fig. 6 doesn’t feel right, not only from a genetic viewpoint, but also from linguistic and archaeological points of view. This is the typical map created with admixture analyses that is wrong because of not taking into account anthropological theories.

Quite interesting is then the influence of admixture in these different ethnolinguistic groups, Indo-European and Dravidic, which points to an initially greater expansion of Indo-European speakers, and later resurge of Dravidian languages.

Featured image contains simplified origin and data of samples studied, from the article.

Related:

Islands across the Indonesian archipelago show complex patterns of admixture

austronesian-dna

An open access article Complex patterns of admixture across the Indonesian archipelago, by Hudjashov et al. (2017), has appeared in Molecular Biology and Evolution, and clarifies further the Austronesian (AN) expansion.

Abstract:

Indonesia, an island nation as large as continental Europe, hosts a sizeable proportion of global human diversity, yet remains surprisingly under-characterized genetically. Here, we substantially expand on existing studies by reporting genome-scale data for nearly 500 individuals from 25 populations in Island Southeast Asia, New Guinea and Oceania, notably including previously unsampled islands across the Indonesian archipelago. We use high-resolution analyses of haplotype diversity to reveal fine detail of regional admixture patterns, with a particular focus on the Holocene. We find that recent population history within Indonesia is complex, and that populations from the Philippines made important genetic contributions in the early phases of the Austronesian expansion. Different, but interrelated processes, acted in the east and west. The Austronesian migration took several centuries to spread across the eastern part of the archipelago, where genetic admixture postdates the archeological signal. As with the Neolithic expansion further east in Oceania and in Europe, genetic mixing with local inhabitants in eastern Indonesia lagged behind the arrival of farming populations. In contrast, western Indonesia has a more complicated admixture history shaped by interactions with mainland Asian and Austronesian newcomers, which for some populations occurred more than once. Another layer of complexity in the west was introduced by genetic contact with maritime travelers from South Asia and strong demographic events in isolated local groups.

Among its results (emphasis is mine):

Most eastern Indonesian populations show traces of admixture that appear to reflect an expansion of AN speakers (Figure 4B, S3). There is a striking similarity between inferred events – each admixed population includes both a Philippine non-Kankanaey and western Indonesian-like source likely representing Holocene movements of Asian farming groups, as well as a Papuan-like source representing local indigenous ancestry. One reason for the lack of clear Taiwanese sources may be because the aboriginal populations of Taiwan were heavily affected by post-AN movements from mainland East Asia, most recently sinicization by Han Chinese, and thus no longer depict the ancestral AN gene pool (Mörseburg, et al. 2016). However, this notable pattern could equally be explained by the dominance of language and culture transfers during early phases of the Neolithic expansion from Taiwan into the Philippines, followed by people with predominantly Philippine ancestry driving later demic diffusion into the Indonesian archipelago. Interestingly, Mörseburg, et al. (2016), by using a different sample set and genotype-based analytical toolkit, indicated that the Kankanaey ethnic group from the Philippines is likely the closest living proxy of the source population that gave rise to the AN expansion. We did not detect this population among sources of admixture in eastern Indonesia, and therefore suggest that the place of individual Philippine groups in the AN expansion needs to be further addressed by better sampling in the Philippine archipelago.

Sumba and Flores, the two westernmost islands to the east of Wallace’s line, display a high proportion of Java and Bali surrogates in their AN admixing source. This suggests that the AN movement into eastern Indonesia, especially for Sumba and Flores, had earlier experienced some degree of genetic contact with western Indonesian groups. In contrast, the sources of AN admixture in Lembata, Alor, Pantar and Timor are dominated by Sulawesi (Figure 4B, S3, Table S3, S5). This generally agrees with expectations from the geography of the region, whereby AN groups exiting the southern Philippines were likely funneled into at least two streams, including a western path through Borneo and a central path through Sulawesi (Blust 2014).

Point estimates of genetic admixture times in eastern Indonesia lie within a narrow timeframe ranging between ca 185 BCE to 360 CE or 75 to 56 generations ago (95% CI 510 BCE – 475 CE or 87–52 generations) (Figure 4B, Table S3). These inferred dates are younger than some previous estimates (120–200 generations ago) (Xu, et al. 2012; Sanderson, et al. 2015; Sedghifar, et al. 2015). A major analysis of admixture in Indonesia estimated the date of AN contact in the eastern part of archipelago to be around 500 to 600 CE (ca 50 generations, CI estimates between 58–42 generations ago) (Lipson, et al. 2014), surprisingly young given the archaeological evidence. However, the study pooled a very small sample of genetically heterogeneous eastern Indonesian islands including, for example, Flores and Alor. As we show here (Figure 2, 4, 5, S3, Table S3, S5, S6), while the wave of AN speakers left a common genetic trace across the whole of eastern Indonesia, the details and dates of this contact vary considerably not only between islands (e.g., Flores and Alor), but also within individual islands (e.g., Flores Rampasasa vs. Flores Bama). The genetic dates, which were obtained here by denser geographical sampling of 8 eastern islands, a much larger number of individuals (28 per island on average) and a greater number of SNPs, are up to 30 generations older, predating the Common Era in many cases.

It therefore took migrants at least half a millennium to proceed from islands around Wallace’s line to the easternmost sampled part of eastern Indonesia. Nevertheless, observed dates for AN contact in eastern Indonesia are still approximately a millennium younger than the earliest Neolithic archaeological evidence in the region, and two explanations seem most likely here. First, the AN migration may have involved several waves of people leaving Taiwan, spanning multiple generations, which would bias date estimates later than the first arrival of the Neolithic archeological assemblage (Sedghifar, et al. 2015). Second, there may have been a substantial time gap between the spread of culture and technological traditions, and the beginning of extensive genetic contact between incoming farming groups and native inhabitants in Indonesia (Lansing, et al. 2011). The lack of considerable admixture with Papuan groups was recently noted in ancient Lapita individuals from Remote Oceania, whose genomes are mostly Asian and carry little to no Papuan ancestry, suggesting limited contact as they moved through Melanesia to previously uninhabited islands in the Pacific (Skoglund, et al. 2016). A lag in admixture between local and incoming Neolithic groups has also been observed in Europe, where hunter-gatherer and farming populations initially co-existed for nearly a thousand years without substantial genetic interaction (Malmström, et al. 2015).

austronesian-admixture Ancestral genomic components in regional populations. For every K, the modal solution with the highest number of ADMIXTURE runs is shown; individual ancestry proportions were averaged across all runs from the same mode and the number of runs (out of 50) assigned to the presented solution is shown in parentheses. Average cross validation statistics were calculated across all runs from the same mode (insert). The minimum cross-validation score is observed at K=9. Note major ancestry components in Indonesia and ISEA – Papuan (light purple), mainland Asian (light yellow) and AN (light blue) – as well as major differences in the distribution of these three ancestries between eastern and western Indonesia. Populations from the Philippines and Flores are abbreviated as ‘Ph.’ and ‘Fl.’, respectively.

Featured images are taken from the article.

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

Related posts:

Two more studies on the genetic history of East Asia: Han Chinese and Thailand

chinese-eurasian-drift

A comprehensive map of genetic variation in the world’s largest ethnic group – Han Chinese, by Charleston et al. (2017).

It is believed – based on uniparental markers from modern and ancient DNA samples and array-based genome-wide data – that Han Chinese originated in the Central Plain region of China during prehistoric times, expanding with agriculture and technology northward and southward, to become the largest Chinese ethnic group.

Abstract:

As are most non-European populations around the globe, the Han Chinese are relatively understudied in population and medical genetics studies. From low-coverage whole-genome sequencing of 11,670 Han Chinese women we present a catalog of 25,057,223 variants, including 548,401 novel variants that are seen at least 10 times in our dataset. Individuals from our study come from 19 out of 22 provinces across China, allowing us to study population structure, genetic ancestry, and local adaptation in Han Chinese. We identify previously unrecognized population structure along the East-West axis of China and report unique signals of admixture across geographical space, such as European influences among the Northwestern provinces of China. Finally, we identified a number of highly differentiated loci, indicative of local adaptation in the Han Chinese. In particular, we detected extreme differentiation among the Han Chinese at MTHFR, ADH7, and FADS loci, suggesting that these loci may not be specifically selected in Tibetan and Inuit populations as previously suggested. On the other hand, we find that Neandertal ancestry does not vary significantly across the provinces, consistent with admixture prior to the dispersal of modern Han Chinese. Furthermore, contrary to a previous report, Neandertal ancestry does not explain a significant amount of heritability in depression. Our findings provide the largest genetic data set so far made available for Han Chinese and provide insights into the history and population structure of the world’s largest ethnic group.

Using Shanghai individuals as representatives, shared drift between Chinese and ancient humans are computed by calculating the outgroup f3 statistics of the form f3(Mbuty;X, Y), with ancient individuals separated into approximately Palaeolithic, Mesolithic, Neolithic , and Chalcolithic-Medieval times. it is found that modern Chinese individuals show greater shared drift with pre-Neolithic hunter-gatherers rather than Neolithic farmers (Featured image from the article).

EDIT (17/7/2017): Davidski at Eurogenes shares an interesting view on this kind of results:

These sorts of estimates always look way off. And I doubt that it’s largely the result of the Silk Road, which linked China to the Near East and Mediterranean rather than to Northern Europe. More likely it reflects gene flow from the Pontic-Caspian steppe in Eastern Europe during the Bronze and Iron ages, via the Afanasievo, Andronovo, and other closely related steppe peoples


New insights from Thailand into the maternal genetic history of Mainland Southeast Asia, by Kutanan et al. (2017)

Abstract:

Tai-Kadai (TK) is one of the major language families in Mainland Southeast Asia (MSEA), with a concentration in the area of Thailand and Laos. Our previous study of 1,234 mtDNA genome sequences supported a demic diffusion scenario in the spread of TK languages from southern China to Laos as well as northern and northeastern Thailand. Here we add an additional 560 mtDNA sequences from 22 groups, with a focus on the TK-speaking central Thai people and the Sino-Tibetan speaking Karen. We find extensive diversity, including 62 haplogroups not reported previously from this region. Demic diffusion is still a preferable scenario for central Thais, emphasizing the extension and expansion of TK people through MSEA, although there is also some support for an admixture model. We also tested competing models concerning the genetic relationships of groups from the major MSEA languages, and found support for an ancestral relationship of TK and Austronesian-speaking groups.