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


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.


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.


Ancient DNA samples from Mesolithic Scandinavia show east-west genetic gradient


New pre-print article at BioRxiv, Genomics of Mesolithic Scandinavia reveal colonization routes and high-latitude adaptation, by Günther et al. (2017), from the Uppsala University (group led by Mattias Jakobsson).

Abstract (emphasis mine):

Scandinavia was one of the last geographic areas in Europe to become habitable for humans after the last glaciation. However, the origin(s) of the first colonizers and their migration routes remain unclear. We sequenced the genomes, up to 57x coverage, of seven hunter-gatherers excavated across Scandinavia and dated to 9,500-6,000 years before present. Surprisingly, among the Scandinavian Mesolithic individuals, the genetic data display an east-west genetic gradient that opposes the pattern seen in other parts of Mesolithic Europe. This result suggests that Scandinavia was initially colonized following two different routes: one from the south, the other from the northeast. The latter followed the ice-free Norwegian north Atlantic coast, along which novel and advanced pressure-blade stone-tool techniques may have spread. These two groups met and mixed in Scandinavia, creating a genetically diverse population, which shows patterns of genetic adaptation to high latitude environments. These adaptations include high frequencies of low pigmentation variants and a gene-region associated with physical performance, which shows strong continuity into modern-day northern Europeans. Finally, we were able to compute a 3D facial reconstruction of a Mesolithic woman from her high-coverage genome, giving a glimpse into an individual’s physical appearance in the Mesolithic.

Interesting is the genetic similarity found with Baltic hunter-gatherers from Zvejnieki:

To investigate the postglacial colonization of Scandinavia, we explored four hypothetical migration routes (primarily based on natural geography) linked to WHGs and EHGs, respectively (Supplementary Information 11); a) a migration of WHGs from the south, b) a migration of EHGs from the east across the Baltic Sea, c) a migration of EHGs from the east and along the north-Atlantic coast, d) a migration of EHGs from the east and south of the Baltic Sea, and combinations of these four migration routes.
The SHGs from northern and western Scandinavia show a distinct and significantly stronger affinity to the EHGs compared to the central and eastern SHGs (Fig. 1). Conversely, the SHGs from eastern and central Scandinavia were genetically more similar to WHGs compared to the northern and western SHGs (Fig. 1). Using a model-based approach (15, 16), the EHG genetic component of northern and western SHGs was estimated to 55% on average (43-67%) and significantly different (Wilcoxon test, p=0.014) from the average 35% (22-44%) in eastern and south-central SHGs. This average is similar to eastern Baltic hunter-gatherers from Latvia (28) (average 33%, Fig. 1A, Supplementary Information 6). These patterns of genetic affinity within SHGs are in direct contrast to the expectation based on geographic proximity with EHGs and WHGs and do not correlate with age of the sample.
Combining these isotopic results with the patterns of genetic variation, we suggest an initial colonization from the south, likely by WHGs. A second migration of people who were related to the EHGs – that brought the new pressure blade technique to Scandinavia and that utilized the rich Atlantic coastal marine resources –entered from the northeast moving southwards along the ice-free Atlantic coast where they encountered WHG groups. The admixture between the two colonizing groups created the observed pattern of a substantial EHG component in the northern and the western SHGs, contrary to the higher levels of WHG genetic component in eastern and central SHGs (Fig. 1, Supplementary Information 11).

From the same article, three samples with reported Y-DNA, the three of haplogroup I2 (one more specifically I2a1b). Regarding mtDNA, four samples U5a1 (two of them U5a1d), two samples U4a1, one U4a2.

Featured image: potential migration routes, taken from the supplementary material.


Islands across the Indonesian archipelago show complex patterns of admixture


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.


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.

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When linguistics does not seem to be a science


An interesting essay by Arika Okrent has appeared in Aeon – Is linguistics a science? It concerns the central position of Chomsky’s Universal Grammar to modern Linguistics, and revolves around a story in Tom Wolfe’s book The Kingdom of Speech (2016), Everett’s discovery of the Pirahã culture’s (and language’s) emphasis on the here and now: not embedding one phrase inside another, the simple kinship system, lack of numbers, and absence of fiction or creation myths. Some excerpts of the essay:

This looks suspiciously like defiance of a central feature of the scientific archetype, one first put forward by the philosopher Karl Popper: theories are not scientific unless they have the potential to be falsified. If you claim that recursion is the essential feature of language, and if the existence of a recursionless language does not debunk your claim, then what could possibly invalidate it?


In an interview with in 2007, Everett said he emailed Chomsky: ‘What is a single prediction that universal grammar makes that I could falsify? How could I test it?’ According to Everett, Chomsky replied to say that universal grammar doesn’t make any predictions; it’s a field of study, like biology.


By contrast, good theories or hypotheses are those that allow you to search for contrary evidence. Thus Albert Einstein’s theory of general relativity made a very specific prediction about the effect of gravity on light, which could be subsequently tested during the solar eclipse of 1919. Unlike astrology or Freudianism, relativity could be contradicted. It was possible to conceive of an observation that would conflict with one’s expectations (although the eclipse ultimately vindicated Einstein). The capacity to be disproved is what makes general relativity scientific.


In Chomsky’s formulation, we are not just after a set of abstract rules that account for the things we can see and hear, but one that explains why they are the way they are. In the late 1970s, Chomsky began to refer to this method of enquiry as the ‘Galilean style’


Chomsky’s Galilean vision was that our intuitive judgments about language stem from an innate language faculty, a universal grammar underlying the human capacity for language. His project is to determine the essential nature of that universal grammar – not the nature of language, but the nature of the human capacity for language. The distinction is a subtle one.

Regarding the pseudoscience claims about Linguistics, or in this case Chomsky’s Universal Grammar, and the common answer to such criticism of linguistic abstractions by their authors (asserting that they can be “neither right nor wrong” but only “fecund or sterile”), they reminded me of an old XKCD comic which sums up this line of reasoning quite well:

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


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.


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)


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.

Potential Afroasiatic Urheimat near Lake Megachad


The publication of new ancient DNA samples from Africa is near, according to people at the SMBE meeting. As reported by, a group by Pontus Skoglund has analysed new samples (complementing the study made by Carina Schlebusch), so we will have ancient samples of Africans from 300 to 6,000 years ago. They have been compared to the data of modern African populations, and among their likely conclusions (to be published):

  • Several thousand years ago, likely Tanzanian herders migrated far and wide, reaching Southern Africa centuries before the first farmers.
  • West Africans were likely early contributors to the gene pool of sub-Saharan Africans.
  • One ancient African herder showed influence from even farther abroad, with 38% of their DNA coming from outside Africa. 9-22% of the DNA of modern farmers, including the southern Khoe-San, comes from East Africans and Eurasian herders
  • Modern farmers, the ones as old as 500 years old, did have Bantu DNA in their genomes, but the ancient hunter-gatherers predated the spread of the Bantu.

Razib Khan, asked about the Afroasiatic homeland by David Reich, has taken this opportunity to publish his own hypothesis on the expansion of Afroasiatic, given the known Admixture analyses, using Y-DNA phylogeography, and with reasonable assumptions. He concludes that Afroasiatic expansion might also be associated with the western expansion of E1b1b subclades from a Levantine (“Natufian”) homeland.

I think it is necessary to remind everyone of the many problems unsolved by Indo-European studies – a much older discipline (and with more research published) than Afroasiatic studies. It is already quite revealing that we can’t still trace back Proto-Semitic to its homeland, and that Proto-Semitic is probably as old as Late Proto-Indo-European. We are talking, then, about an ancient proto-language – Afroasiatic – possibly older than Middle Indo-European (or Indo-Hittite), and whose dialects are still not well studied – but for the Semitic and Egyptian branches. Linguistic guesstimates or phylogenetic speculation date the proto-language (and thus the homeland) within a wide range, from 15,000 to 6,000 years ago.

There is an obvious trend (probably driven by Semitic and Egyptian researchers) to place the Afroasiatic Homeland near one of the many proposed Semitic homelands, i.e. in East Africa. This is similar to the trend seen in the first half of the 20th century in Indo-European studies, with most proposals locating the Proto-Indo-European homeland in Europe. European languages were the best known, and only the perceived antiquity of Vedic Sanskrit made some propose South Asian origins for the proto-language. However, it was only careful interpretation of linguistic finds, combined with archaeological data, what eventually yielded the Kurgan hypothesis, which has been since refined.

A model for the homeland and expansion of Afroasiatic, from Wikipedia

Razib Khan’s proposal makes sense in that it fits what others have proposed before, i.e. an east African or Middle Eastern Afroasiatic homeland, and that it links it with the expansion of farming. However, we have to keep in mind that until 5,000 years ago the Sahara was not the desert we know: it had certain important green corridors, humid areas between megalakes. The Sahara might not have been exactly green 10,000 to 5,000 years ago (roughly the time when Afroasiatic must have been spoken), but it had certain regions that allowed for an east-west migration. However, it also allowed for a west-east migration, and – perhaps more importantly – for a sizeable population expansion in central Saharan territory. To forget that is to allow for potentially wrong assumptions to be made.

What we expect from the next papers on ancient African DNA samples are the result of certain (more recent) population – and thus potentially ethnolinguistic – movements, but they probably won’t solve the question of the Afroasiatic homeland, which has an older time span than the samples studied. There is a wide void in African prehistory – compared with Near Eastern history – and this research will be closing that gap, just like European samples are helping close the gap in the prehistory of western, northern, and eastern Europe, compared to the history of the eastern Mediterranean regions.

Diachronic map of Paleolithic migrations of R1b lineages in Europe and Africa

I already wrote, regarding the potential ethnolinguistic link between Indo-European and Afroasiatic, that a close look at the migration of R1b-V88 lineages from Europe (through southern Italy?) into the Sahara – through the Fezzan-Chad-Chotts, and Chad-Chotts-Ahnet-Moyer megalake green corridors – could have been the key to the successful expansion of Afrasians.

Interesting aspects to take into account are the distribution of R1b-V88 lineages, compared to the location of Chadic languages (probably the most divergent and least known of the group) and to the potential North Afroasiatic (composed by Egyptian, Berber, and Semitic) and South Afroasiatic group (made of Cushitic and Omotic). Chadic has been argued to be connected variously to North Afroasiatic, or to the Berber branch, but the Northern group has also been argued to be connected with Cushitic, with Omotic as an independent branch. Also interesting would then be the potential connection between Indo-European (or Indo-Uralic) and Afroasiatic.

Modern distribution of haplogroup R1b, from Wikipedia

We could speculatively place the potential primary Afroasiatic homeland in the south-central Sahara, near the Megachad lake (i.e. near the peak of R1b-V88 lineages), with a secondary homeland in eastern Africa (as in the map above) – and maybe a tertiary homeland (of North Afroasiatic) in the Middle East, associated with the expansion of “Natufians” and E1b1b subclades. The identification of the spread of Afroasiatic languages with the expansion of R1b-V88 lineages needs an anthropological context (linguistic and archaeological) that is obviously lacking today.

It is important to keep all possibilities in sight when reviewing genetic analyses.


EDIT (16/7/2017): Added link to Neby’s post on a potential Semitic homeland, and Nature article on Schlebusch and Skoglund research.