Munda admixture happened probably during the ANI-ASI mixture


Preprint The genetic legacy of continental scale admixture in Indian Austroasiatic speakers, by Tätte et al. bioRxiv (2018).

Interesting excerpts:

Studies analysing mtDNA and Y chromosome markers have revealed a sex-specific admixture pattern of admixture of Southeast and South Asian ancestry components for Munda speakers. While close to 100% of mtDNA lineages present in Mundas match those in other Indian populations, around 65% of their paternal genetic heritage is more closely related to Southeast Asian than South Asian variation. Such a contrasting distribution of maternal and paternal lineages among the Munda speakers is a classic example of ‘father tongue hypothesis’. However, the temporality of this expansion is contentious. Based on Y-STR data the coalescent time of Indian O2a-M95 haplogroup was estimated to be >10 KYA. Recently, the reconstructed phylogeny of 8.8 Mb region of Y chromosome data showed that Indian O2a-M95 lineages coalesce within a clade nested within East/Southeast Asian within the last ~5-7 KYA. This date estimate sets the upper boundary for the main episode of gene flow of Y chromosomes from Southeast Asia to India.

Supplementary Figure S4. First two components of principal component analysis (PCA). Individuals and population medians (circles) are marked with abbreviations from population names. Different colours represent populations from different geographic areas and/or linguistic groups as shown on the legend on the right. For the full names of populations see Supplementary Table S1. PCA was performed using software EIGENSOFT 6.1.42 on the whole filtered dataset (1072 individuals), previously LD pruned as described in the title of Supplementary Figure S1. The first two principal components describe 5.13% and 2.57% of total variance.

Admixture proportions suggest a novel scenario

Regardless of which West Asian population we used, we found that Munda speakers can be described on average as a mixture of ~19% Southeast Asian, 15% West Asian and 66% Onge (South Asian) components. Alternatively, the West and South Asian components of Munda could be modelled using a single South Asian population (Paniya), accounting on average to 77% of the Munda genome. When rescaling the West and South Asian (Onge) components to 1 to explore the Munda genetic composition prior to the introduction of the Southeast Asian component, we note that the West Asian component is lower (~19%) in Munda compared to Paniya (27%) (Supplementary Table S4: *Average_Lao=0). Consistently with qpGraph analyses in Narasimhan et al. (2018), this may point to an initial admixture of a Southeast Asian substrate with a South Asian substrate free of any West Asian component, followed by the encounter of the resulting admixed population with a Paniya-like population. Such a scenario would imply an inverse relationship between the Southeast and West Asian relative proportions in Munda or, in other words, the increase of Southeast Asian component should cause a greater reduction of the West Asian compared to the reduction in the South Asian component in Munda.

The distribution of genetic components (K=13) based on the global ADMIXTURE analysis (Supplementary Figure S1, S2, S3) for a subset of populations on a map of South and Southeast Asia. The circular legend in the bottom left corner shows the ancestral components corresponding to the colours on pie charts. The sector sizes correspond to population median.

Dating the admixture event

In this study, we have replicated a result previously reported in Chaubey et al. (2011)7 that the Mundas lack one ancestral component (k2) that is characteristic to Indian Indo-European and Dravidian speaking populations. If this component came to India through one of the Indo-Aryan migrations then it would be fair to presume that the Munda admixture happened before this component reached India or at least before it spread all over the country. However, the admixture time computed here, falls in the exact same timeframe as the ANI-ASI mixture has been estimated to have happened in India through which the k2 component probably spread. Therefore, we propose that if the Munda admixture happened at the same time, it is possible for it to have happened in the eastern part of the country, east of Bangladesh, and later when populations from East Asia moved to the area, the Mundas migrated towards central India. Such a scenario, which may be further clarified by ancient DNA analyses, seems to be further supported by the fact that Mundas harbor a smaller fraction of West Asian ancestry compared to contemporary Paniya (Supplementary Table S4) and cannot therefore be seen as a simple admixture product of Southern Indian populations with incoming Southeast Asian ancestries.

Image from Damgaard et al. (2018). A summary of the four qpAdm models fitted for South Asian populations. For each modern South Asian population. we fit different models with qpAdm to explain their ancestry composition using ancient groups and present the f irst model that we could not reject in the following priority order: 1. Namazga_CA + Onge, 2. Namazga_CA + Onge + Late Bronze Age Steppe, 3. Namazga_CA + Onge + Xiongnu_lA (East Asian proxy). and 4. Turkmenistan_lA + Xiongnu_lA. Xiongnu_lA were used here to represent East Asian ancestry. We observe that while South Asian Dravidian speakers can be modeled as a mixture of Onge and Namazga_CA. an additional source related to Late Bronze Age steppe groups is required for IE speakers. In Tibeto-Burman and Austro-Asiatic speakers. an East Asian rather than a Steppe_MLBA source is required

Linguistics and genome-wide data

(…) by and large, the linguistic classification justifies itself but Kharia and Juang do not fit in this simplification perfectly.

Once again, with the current level of detail in genetic studies, there is often no clear dialectal division possible for certain groups without fine-scale population studies, and the help from linguistics and archaeology.

Featured image from open access paper by Chaubey et al. (2011).


Haplogroup R1a and CWC ancestry predominate in Fennic, Ugric, and Samoyedic groups


Open access Genes reveal traces of common recent demographic history for most of the Uralic-speaking populations, by Tambets et al. Genome Biology (2018).

Interesting excerpts (emphasis mine):


A total of 286 samples of Uralic-speaking individuals, of those 121 genotyped in this study, were analysed in the context of 1514 Eurasian samples (including 14 samples published for the first time) based on whole genome single nucleotide polymorphisms (SNPs) (Additional file 1: Table S1). All these samples, together with the larger sample set of Uralic speakers, were characterized for mtDNA and chrY markers.

The question as which material cultures may have co-spread together with proto-Uralic and Uralic languages depends on the time estimates of the splits in the Uralic language tree. Deeper age estimates (6,000 BP) of the Uralic language tree suggest a connection between the spread of FU languages from the Volga River basin towards the Baltic Sea either with the expansion of the Neolithic culture of Combed Ware, e.g. [6, 7, 17, 26] or with the Neolithic Volosovo culture [7]. Younger age estimates support a link between the westward dispersion of Proto-Finno-Saamic and eastward dispersion of Proto-Samoyedic with a BA Sejma-Turbino (ST) cultural complex [14, 18, 27, 28] that mediated the diffusion of specific metal tools and weapons from the Altai Mountains over the Urals to Northern Europe or with the Netted Ware culture [23], which succeeded Volosovo culture in the west. It has been suggested that Proto-Uralic may have even served as the lingua franca of the merchants involved in the ST phenomenon [18]. All these scenarios imply that material culture of the Baltic Sea area in Europe was influenced by cultures spreading westward from the periphery of Europe and/or Siberia. Whether these dispersals involved the spread of both languages and people remains so far largely unknown.

The population structure of Uralic speakers

To contextualize the autosomal genetic diversity of Uralic speakers among other Eurasian populations (Additional file 1: Table S1), we first ran the principal component (PC) analysis (Fig. 2a, Additional file 3: Figure S1). The first two PCs (Fig. 2a, Additional file 3: Figure S1A) sketch the geography of the Eurasian populations along the East-West and North-South axes, respectively. The Uralic speakers, along with other populations speaking Slavic and Turkic languages, are scattered along the first PC axis in agreement with their geographic distribution (Figs. 1 and 2a) suggesting that geography is the main predictor of genetic affinity among the groups in the given area. Secondly, in support of this, we find that FST-distances between populations (Additional file 3: Figure S2) decay in correlation with geographical distance (Pearson’s r = 0.77, p < 0.0001). On the UPGMA tree based on these FST-distances (Fig. 2b), the Uralic speakers cluster into several different groups close to their geographic neighbours.

Principal component analysis (PCA) and genetic distances of Uralic-speaking populations. a PCA (PC1 vs PC2) of the Uralic-speaking populations.

We next used ADMIXTURE [48], which presents the individuals as composed of inferred genetic components in proportions that maximize Hardy-Weinberg and linkage equilibrium in the overall sample (see the ‘Methods’ section for choice of presented K). Overall, and specifically at lower values of K, the genetic makeup of Uralic speakers resembles that of their geographic neighbours. The Saami and (a subset of) the Mansi serve as exceptions to that pattern being more similar to geographically more distant populations (Fig. 3a, Additional file 3: S3). However, starting from K = 9, ADMIXTURE identifies a genetic component (k9, magenta in Fig. 3a, Additional file 3: S3), which is predominantly, although not exclusively, found in Uralic speakers. This component is also well visible on K = 10, which has the best cross-validation index among all tests (Additional file 3: S3B). The spatial distribution of this component (Fig. 3b) shows a frequency peak among Ob-Ugric and Samoyed speakers as well as among neighbouring Kets (Fig. 3a). The proportion of k9 decreases rapidly from West Siberia towards east, south and west, constituting on average 40% of the genetic ancestry of FU speakers in Volga-Ural region (VUR) and 20% in their Turkic-speaking neighbours (Bashkirs, Tatars, Chuvashes; Fig. 3a). The proportion of this component among the Saami in Northern Scandinavia is again similar to that of the VUR FU speakers, which is exceptional in the geographic context. It is also notable that North Russians, sampled from near the White Sea, differ from other Russians by sporting higher proportions of k9 (10–15%), which is similar to the values we observe in their Finnic-speaking neighbours. Notably, Estonians and Hungarians, who are geographically the westernmost Uralic speakers, virtually lack the k9 cluster membership.

Population structure of Uralic-speaking populations inferred from ADMIXTURE analysis on autosomal SNPs in Eurasian context. a Individual ancestry estimates for populations of interest for selected number of assumed ancestral populations (K3, K6, K9, K11). Ancestry components discussed in a main text (k2, k3, k5, k6, k9, k11) are indicated and have the same colours throughout. The names of the Uralic-speaking populations are indicated with blue (Finno-Ugric) or orange (Samoyedic). The full bar plot is presented in Additional file 3: Figure S3. b Frequency map of component k9

We also tested the different demographic histories of female and male lineages by comparing outgroup f3 results for autosomal and X chromosome (chrX) data for pairs of populations (Estonians, Udmurts or Khanty vs others) with high versus low probability to share their patrilineal ancestry in chrY hg N (see the ‘Methods’ section, Additional file 3: Figure S13). We found a minor but significant excess of autosomal affinity relative to chrX for pairs of populations that showed a higher than 10% chance of two randomly sampled males across the two groups sharing their chrY ancestry in hg N3-M178, compared to pairs of populations where such probability is lower than 5% (Additional file 3: Figure S13).

In sum, these results suggest that most of the Uralic speakers may indeed share some level of genetic continuity via k9, which, however, also extends to the geographically close Turkic speakers.



We found that it is the admixture with the Siberians that makes the Western Uralic speakers different from the tested European populations (Additional file 3: Figure S4A-F, H, J, L). Differentiating between Estonians and Finns, the Siberians share more derived alleles with Finns, while the geographic neighbours of Estonians (and Finns) share more alleles with Estonians (Additional file 3: Figure S4M). Importantly, Estonians do not share more derived alleles with other Finnic, Saami, VUR FU or Ob-Ugric-speaking populations than Latvians (Additional file 3: Figure S4O). The difference between Estonians and Latvians is instead manifested through significantly higher levels of shared drift between Estonians and Siberians on the one hand and Latvians and their immediate geographic neighbours on the other hand. None of the Uralic speakers, including linguistically close Khanty and Mansi, show significantly closer affinities to the Hungarians than any non-FU population from NE Europe (Additional file 3: Figure S4R).

Share of ~ 1–2 cM identity-by-descent (IBD) segments within and between regional groups of Uralic speakers. For each Uralic-speaking population representing lines in this matrix, we performed permutation test to estimate if it shows higher IBD segment sharing with other population (listed in columns) as compared to their geographic control group. Empty rectangles indicate no excess IBD sharing, rectangles filled in blue indicate comparisons when statistically significant excess IBD sharing was detected between one Uralic-speaking population with another Uralic-speaking population (listed in columns), rectangles filled in green mark the comparisons when a Uralic-speaking population shows excess IBD sharing with a non-Uralic-speaking population. For each tested Uralic speaker (matrix rows) populations in the control group that were used to generate permuted samples are indicated using small circles. For example, the rectangle filled in blue for Vepsians and Komis (A) implies that the Uralic-speaking Vepsians share more IBD segments with the Uralic-speaking Komis than the geographic control group for Vepsians, i.e. populations indicated with small circles (Central and North Russians, Swedes, Latvians and Lithuanians). The rectangle filled in green for Vepsians and Dolgans shows that the Uralic-speaking Vepsians share more IBD segments with the non-Uralic-speaking Dolgans than the geographic control group

Time of Siberian admixture

The time depth of the Globetrotter (Fig. 5b) inferred admixture events is relatively recent—500–1900 AD (see also complementary ALDER results, in Additional file 13: Table S12 and Additional file 3: Figure S7)—and agrees broadly with the results reported in Busby et al. [55]. A more detailed examination of the ALDER dates, however, reveals an interesting pattern. The admixture events detected in the Baltic Sea region and VUR Uralic speakers are the oldest (800–900 AD or older) followed by those in VUR Turkic speakers (∼1200–1300 AD), while the admixture dates for most of the Siberian populations (>1500 AD) are the most recent (Additional file 3: Figure S7). The West Eurasian influx into West Siberia seen in modern genomes was thus very recent, while the East Eurasian influx into NE Europe seems to have taken place within the first millennium AD (Fig. 5b, Additional file 3: Figure S7).

Affinities of the Uralic speakers with ancient Eurasians

We next calculated outgroup f3-statistics [48] to estimate the extent of shared genetic drift between modern and ancient Eurasians (Additional file 14: Table S13, Additional file 3: Figures S8-S9). Consistent with previous reports [45, 50], we find that the NE European populations including the Uralic speakers share more drift with any European Mesolithic hunter-gatherer group than Central or Western Europeans (Additional file 3: Figure S9A-C). Contrasting the genetic contribution of western hunter-gatherers (WHG) and eastern hunter-gatherers (EHG), we find that VUR Uralic speakers and the Saami share more drift with EHG. Conversely, WHG shares more drift with the Finnic and West European populations (Additional file 3: Figure S9A). Interestingly, we see a similar pattern of excess of shared drift between VUR and EHG if we substitute WHG with the aDNA sample from the Yamnaya culture (Additional file 3: Figure S9D). As reported before [2, 45], the genetic contribution of European early farmers decreases along an axis from Southern Europe towards the Ural Mountains (Fig. 6, Additional file 3: Figure S9E-F).

Proportions of ancestral components in studied European and Siberian populations and the tested qpGraph model. a The qpGraph model fitting the data for the tested populations. Colour codes for the terminal nodes: pink—modern populations (‘Population X’ refers to test population) and yellow—ancient populations (aDNA samples and their pools). Nodes coloured other than pink or yellow are hypothetical intermediate populations. We putatively named nodes which we used as admixture sources using the main recipient among known populations. The colours of intermediate nodes on the qpGraph model match those on the admixture proportions panel. b Admixture proportions (%) of ancestral components. We calculated the admixture proportions summing up the relative shares of a set of intermediate populations to explain the full spectrum of admixture components in the test population. We further did the same for the intermediate node CWC’ and present the proportions of the mixing three components in the stacked column bar of CWC’. Colour codes for ancestral components are as follows: dark green—Western hunter gatherer (WHG’); light green—Eastern hunter gatherer (EHG’); grey—European early farmer (LBK’); dark blue—carriers of Corded Ware culture (CWC’); and dark grey—Siberian. CWC’ consists of three sub-components: blue—Caucasian hunter-gatherer in Yamnaya (CHGinY’); light blue—Eastern hunter-gatherer in Yamnaya (EHGinY’); and light grey—Neolithic Levant (NeolL’)

We then used the qpGraph software [48] to test alternative demographic scenarios by trying to fit the genetic diversity observed in a range of the extant Finno-Ugric populations through a model involving the four basic European ancestral components: WHG, EHG, early farmers (LBK), steppe people of Yamnaya/Corded Ware culture (CWC) and a Siberian component (Fig. 6, Additional file 3: Figure S10). We chose the modern Nganasans to serve as a proxy for the latter component because we see least evidence for Western Eurasian admixture (Additional file 3: Figure S3) among them. We also tested the Khantys for that proxy but the model did not fit (yielding f2-statistics, Z-score > 3). The only Uralic-speaking population that did not fit into the tested model with five ancestral components were Hungarians. The qpGraph estimates of the contributions from the Siberian component show that it is the main ancestry component in the West Siberian Uralic speakers and constitutes up to one third of the genomes of modern VUR and the Saami (Fig. 6). It drops, however, to less than 10% in most of NE Europe, to 5% in Estonians and close to zero in Latvians and Lithuanians.


Additional file 6: Table S5. Y chromosome haplogroup frequencies in Eurasia. Modified by me: in bold haplogroup N1c and R1a from Uralic-speaking populations, with those in red showing where R1a is the major haplogroup. Observe that all Uralic subgroups – Finno-Permic, Ugric, and Samoyedic – have some populations with a majority of R1a lineages.

One of the notable observations that stands out in the fineSTRUCTURE analysis is that neither Hungarians nor Estonians or Mordovians form genetic clusters with other Uralic speakers but instead do so with a broad spectrum of geographically adjacent samples. Despite the documented history of the migration of Magyars [63] and their linguistic affinity to Khantys and Mansis, who today live east of the Ural Mountains, there is nothing in the present-day gene pool of the sampled Hungarians that we could tie specifically to other Uralic speakers.

Perhaps even more surprisingly, we found that Estonians, who show close affinities in IBD analysis to neighbouring Finnic speakers and Saami, do not share an excess of IBD segments with the VUR or Siberian Uralic speakers. This is eIn this context, it is important to remind that the limited (5%, Fig. 6) East Eurasian impact in the autosomal gene pool of modern Estonians contrasts with the fact that more than 30% of Estonian (but not Hungarian) men carry chrY N3 that has an East Eurasian origin and is very frequent among NE European Uralic speakers [36]. However, the spread of chrY hg N3 is not language group specific as it shows similar frequencies in Baltic-speaking Latvians and Lithuanians, and in North Russians, who in all our analyses are very similar to Finnic-speakers. The latter, however, are believed to have either significantly admixed with their Uralic-speaking neighbours or have undergone a language shift from Uralic to Indo-European [38].ven more striking considering that the immediate neighbours—Finns, Vepsians and Karelians—do.

With some exceptions such as Estonians, Hungarians and Mordovians, both IBD sharing and Globetrotter results suggest that there are detectable inter-regional haplotype sharing ties between Uralic speakers from West Siberia and VUR, and between NE European Uralic speakers and VUR. In other words, there is a fragmented pattern of haplotype sharing between populations but no unifying signal of sharing that unite all the studied Uralic speakers.


The paper is obviously trying to find a “N1c/Siberian ancestry = Uralic” link, but it shows (as previous papers using ancient DNA) that this identification is impossible, because it is not possible to identify “N1c=Siberian ancestry”, “N1c=Uralic”, or “Siberian ancestry = Uralic”. In fact, the arrival of N subclades and Siberian ancestry are late, both events (probably multiple stepped events) are unrelated to each other, and represent east-west demic diffusion waves (as well as founder effects) that probably coincide in part with the Scythian and Turkic (or associated) expansions, i.e. too late for any model of Proto-Uralic or Proto-Finno-Ugric expansion.

On the other hand, it shows interesting data regarding ancestry of populations that show increased Siberian influence, such as those easternmost groups admixed with Yeniseian-like populations (Samoyedic), those showing strong founder effects (Finnic), or those isolated in the Circum-Artic region with neighbouring Siberian peoples in Kola (Saami). All in all, Hungarians, Estonians and Mordovians seem to show the original situation better than the other groups, which is also reflected in part in Y-DNA, conserved as a majority of R1a lineages precisely in these groups. Just another reminder that CWC-related ancestry is found in every single Uralic group, and that it represents the main ancestral component in all non-Samoyedic groups.

Selection of the PCA, with the group of Estonians, Mordovians, and Hungarians selected.

The qpGraph shows the ancestor of Yamna (likely Khvalynsk) and Corded Ware stemming as different populations from a common (likely Neolithic) node – whose difference is based on the proportion of Anatolian-related ancestry – , that is, probably before the Indo-Hittite expansion; and ends with CWC groups forming the base for all Uralic peoples. Below is a detail of the qpGraph on the left, and my old guess (2017) on the right, for comparison:


#EDIT (22 sep 2018): I enjoyed re-reading it, and found this particular paragraph funny:

Despite the documented history of the migration of Magyars [63] and their linguistic affinity to Khantys and Mansis, who today live east of the Ural Mountains, there is nothing in the present-day gene pool of the sampled Hungarians that we could tie specifically to other Uralic speakers.

They are so obsessed with finding a link to Siberian ancestry and N1c, and so convinced of Kristiansen’s idea of CWC=Indo-European, that they forgot to examine their own data from a critical point of view, and see the clear link between all Uralic peoples with Corded Ware ancestry and R1a-Z645 subclades… Here is a reminder about Hungarians and R1a-Z282, and about the expansion of R1a-Z645 with Uralic peoples.


Palaeolithic Caucasus samples reveal the most important component of West Eurasians


Preprint Paleolithic DNA from the Caucasus reveals core of West Eurasian ancestry, by Lazaridis et al. bioRxiv (2018).

Interesting excerpts:

We analyzed teeth from two individuals 63 recovered from Dzudzuana Cave, Southern Caucasus, from an archaeological layer previously dated to ~27-24kya (…). Both individuals had mitochondrial DNA sequences (U6 and N) that are consistent with deriving from lineages that are rare in the Caucasus or Europe today. The two individuals were genetically similar to each other, consistent with belonging to the same population and we thus analyze them jointly.

(…) our results prove that the European affinity of Neolithic Anatolians does not necessarily reflect any admixture into the Near East from Europe, as an Anatolian Neolithic-like population already existed in parts of the Near East by ~26kya. Furthermore, Dzudzuana shares more alleles with Villabruna-cluster groups than with other ESHG (Extended Data Fig. 5b), suggesting that this European affinity was specifically related to the Villabruna cluster, and indicating that the Villabruna affinity of PGNE populations from Anatolia and the Levant is not the result of a migration into the Near East from Europe. Rather, ancestry deeply related to the Villabruna cluster was present not only in Gravettian and Magdalenian-era Europeans but also in the populations of the Caucasus, by ~26kya. Neolithic Anatolians, while forming a clade with Dzudzuana with respect to ESHG, share more alleles with all other PGNE (Extended Data Fig. 5d), suggesting that PGNE share at least partially common descent to the exclusion of the much older samples from Dzudzuana.

Ancient West Eurasian population structure. PCA of key ancient West Eurasians, including additional populations (shown with grey shells), in the space of outgroup f4-statistics (Methods).

Our co-modeling of Epipaleolithic Natufians and Ibero-Maurusians from Taforalt confirms that the Taforalt population was mixed, but instead of specifying gene flow from the ancestors of Natufians into the ancestors of Taforalt as originally reported, we infer gene flow in the reverse direction (into Natufians). The Neolithic population from Morocco, closely related to Taforalt is also consistent with being descended from the source of this gene flow, and appears to have no admixture from the Levantine Neolithic (Supplementary Information 166 section 3). If our model is correct, Epipaleolithic Natufians trace part of their ancestry to North Africa, consistent with morphological and archaeological studies that indicate a spread of morphological features and artifacts from North Africa into the Near East. Such a scenario would also explain the presence of Y-chromosome haplogroup E in the Natufians and Levantine farmers, a common link between the Levant and Africa.

(…) we cannot reject the hypothesis that Dzudzuana and the much later Neolithic Anatolians form a clade with respect to ESHG (P=0.286), consistent with the latter being a population largely descended from Dzudzuana-like pre-Neolithic populations whose geographical extent spanned both Anatolia and the Caucasus. Dzudzuana itself can be modeled as a 2-way mixture of Villabruna-related ancestry and a Basal Eurasian lineage.

In qpAdm modeling, a deeply divergent hunter-gatherer lineage that contributed in relatively unmixed form to the much later hunter-gatherers of the Villabruna cluster is specified as contributing to earlier hunter-gatherer groups (Gravettian Vestonice16: 35.7±11.3% and Magdalenian ElMiron: 60.6±11.3%) and to populations of the Caucasus (Dzudzuana: 199 72.5±3.7%, virtually identical to that inferred using ADMIXTUREGRAPH). In Europe, descendants of this lineage admixed with pre-existing hunter-gatherers related to Sunghir3 from Russia for the Gravettians and GoyetQ116-1 from Belgium for the Magdalenians, while in the Near East it did so with Basal Eurasians. Later Europeans prior to the arrival of agriculture were the product of re-settlement of this lineage after ~15kya in mainland Europe, while in eastern Europe they admixed with Siberian hunter-gatherers forming the WHG-ANE cline of ancestry [See PCA above]. In the Near East, the Dzudzuana-related population admixed with North African-related ancestry in the Levant and with Siberian hunter-gatherer and eastern non-African-related ancestry in Iran and the Caucasus. Thus, the highly differentiated populations at the dawn of the Neolithic were primarily descended from Villabruna Cluster and Dzudzuana-related ancestors, with varying degrees of additional input related to both North Africa and Ancient North/East Eurasia whose proximate sources may be clarified by future sampling of geographically and temporally intermediate populations.

An admixture graph model of Paleolithic West Eurasians. An automatically generated admixture graph models fits populations (worst Z-score of the difference between estimated and fitted f-statistics is 2.7) or populations (also including South_Africa_HG, worst Z-score is 3.5). This is a simplified model assuming binary admixture events and is not a unique solution (Supplementary Information section 2). Sampled populations are shown with ovals and select labeled internal nodes with rectangles.

Interesting excerpts from the supplementary materials:

From our analysis of Supplementary Information section 3, we showed that these sources are indeed complex, and only one of these (WHG, represented by Villabruna) appears to be a contributor to all the remaining sources. This should not be understood as showing that hunter-gatherers from mainland Europe migrated to the rest of West Eurasia, but rather that the fairly homogeneous post-15kya population of mainland Europe labeled WHG appear to represent a deep strain of ancestry that seems to have contributed to West Eurasians from the Gravettian era down to the Neolithic period.

Villabruna is representative of the WHG group. We also include ElMiron, the best sample from the Magdalenian era as we noticed that within the WHG group there were individuals that could not be modeled as a simple clade with Villabruna but also had some ElMiron-related ancestry. Ddudzuana is representative of the Ice Age Caucasus population, differentiated from Villabruna by Basal Eurasian ancestry. AG3 represents ANE/Upper Paleolithic Siberian ancestry, sampled from the vicinity of Lake Baikal, while Russia_Baikal_EN related to eastern Eurasians and represents a later layer of ancestry from the same region of Siberia as AG3 Finally, Mbuti are a deeply diverged African population that is used here to represent deep strains of ancestry (including Basal Eurasian) prior to the differentiation between West Eurasians and eastern non-Africans that are otherwise not accounted for by the remaining five sources. Collectively, we refer to this as ‘Basal’ or ‘Deep’ ancestry, which should be understood as referring potentially to both Basal Eurasian and African ancestry.

It has been suggested that there is an Anatolia Neolithic-related affinity in hunter-gatherers from the Iron Gates. Our analysis confirms this by showing that this population has Dzudzuana-related ancestry as do many hunter-gatherer populations from southeastern Europe, eastern Europe and Scandinavia. These populations cannot be modeled as a simple mixture of Villabruna and AG3 but require extra Dzudzuana-related ancestry even in the conservative estimates, with a positive admixture proportion inferred for several more in the speculative ones. Thus, the distinction between European hunter-gatherers and Near Eastern populations may have been gradual in pre-Neolithic times; samples from the Aegean (intermediate between those from the Balkans and Anatolia) may reveal how gradual the transition between Dzudzuana-like Neolithic Anatolians and mostly Villabruna-like hunter-gatherers was in southeastern Europe.

Modified image (cut, with important samples marked). Modeling present-day and ancient West-Eurasians. Mixture proportions computed with qpAdm (Supplementary Information section 4). The proportion of ‘Mbuti’ ancestry represents the total of ‘Deep’ ancestry from lineages that split prior to the 365 split of Ust’Ishim, Tianyuan, and West Eurasians and can include both ‘Basal Eurasian’ and other (e.g., Sub-Saharan African) ancestry. (a) ‘Conservative’ estimates. Each population 367 cannot be modeled with fewer admixture events than shown.

Villabruna: This type of ancestry differentiates between present-day Europeans and non-Europeans within West Eurasia, attaining a maximum of ~20% in the Baltic in accordance with previous observations and with the finding of a later persistence of significant hunter-gatherer ancestry in the region. Its proportion drops to ~0% throughout the Near East. Interestingly, a hint of such ancestry is also inferred in all North African populations west of Libya in the speculative proportions, consistent with an archaeogenetic inference of gene flow from Iberia to North Africa during the Late Neolithic.

ElMiron: This type of ancestry is absent in present-day West Eurasians. This may be because most of the Villabruna-related ancestry in Europeans traces to WHG populations that lacked it (since ElMiron-related ancestry is quite variable within European hunter-gatherers). However, ElMiron ancestry makes up only a minority component of all WHG populations sampled to date and WHG-related ancestry is a minority component of present-day Europeans. Thus, our failure to detect it in present day people may be simply be too little of it to detect with our methods.

Dzudzuana: Our analysis identifies Dzudzuana-related ancestry as the most important component of West Eurasians and the one that is found across West Eurasian-North African populations at ~46-88% levels. Thus, Dzudzuana-related ancestry can be viewed as the common core of the ancestry of West Eurasian-North African populations. Its distribution reaches its minima in northern Europe and appears to be complementary to that of Villabruna, being most strongly represented in North Africa, the Near East (including the Caucasus) and Mediterranean Europe. Our results here are expected from those of Supplementary Information section 3 in which we modeled ancient Near Eastern/North African populations (the principal ancestors of present-day people from the same regions) as deriving much of their ancestry from a Dzudzuana-related source. Migrations from the Near East/Caucasus associated with the spread of the Neolithic, but also the formation of steppe population introduced most of the Dzudzuana-related ancestry present in Europe, although (as we have seen above) some such ancestry was already present in some pre-agricultural hunter-gatherers in Europe.

AG3: Ancestry related to the AG3 sample from Siberia has a northern distribution, being strongly represented in both central-northern Europe and the north Caucasus.

Russia_Baikal_EN: Ancestry related to hunter-gatherers from Lake Baikal in Siberia (postdating AG3) appears to have affected primarily northeastern European populations which have been previously identified as having East Eurasian ancestry; some such ancestry is also identified for a Turkish population from Balıkesir, likely reflecting the Central Asian ancestry of Turkic speakers which has been recently confirmed directly in an Ottoman sample from Anatolia.

Some comments

So, to try and sum up:

  • Dzudzuana shares ancestry with ‘Common West Eurasian’ (CWE). the ancestor cluster of Villabruna.
  • Dzudzuana diverges from CWE because of a Basal Eurasian ancestry contribution [which supports that Basal Eurasian ancestry was a deep Middle Eastern lineage].
  • Dzudzuana is closest to Anatolia Neolithic, and close to Gravettian.
Palaeolithic migrations and clusters in Europe. See more maps.


  1. Aurignacian: First West Eurasians arrive ca. 36,000 BP, Goyet cluster expands probably with C1a2 lineages.
  2. After that, the early or ‘unmixed’ Villabruna cluster (‘hidden’ somewhere probably east of Europe, either North Eurasia or South Eurasia), lineages unknown (possibly IJ), contributes to:
    1. Gravettian (ca. 30,000 BP): Věstonice cluster expands, probably with IJ lineages.
    2. A (hidden) ‘Common West Eurasian’ population.
    3. In turn:

      • Dzudzuana ca. 26,000 BP derived from Common West Eurasian (curiously, haplogroup G seems to split in today’s subclades ca. 26,000 BP).
      • During the Gravettian (ca. 26,000 BP), an Anatolian Neolithic-like population exists already in the Near East. Both Věstonice and this Anatolian HG are close to Dzudzuana; in turn, Dzudzuana from CWE.

    4. Magdalenian (ca. 20,000 BP): El Mirón cluster expands, probably with more specific I lineages.
  3. Bølling-Allerød warming period (ca. 14,000 BP): ‘late’ Villabruna cluster or WHG (=CWE with greater affinity to Near Eastern populations) expands, probably spreading with R1b in mainland Europe and to the east (admixing with Siberian HG), creating the WHG — ANE ancestry cline, as reflected in Iron Gates HG, Baltic HG, etc.

[Here we have the possible “bidirectional gene flow between populations ancestral to Southeastern Europeans of the early Holocene and Anatolians of the late glacial or a dispersal of Southeastern Europeans into the Near East” inferred from Anatolian hunter-gatherers]

The Gravettian (30,000 to 20,000 years) is drawn in black and white; the subsequent Magdalenian (17,000 to 10,000 years) and Hamburgian (13,000-11,750 years) are in light blue and red. It is not known whether the spread of the Gravettian was a result of diffusion of people or cultures. This figure illustrates the possible monocentric origins of the Gravettian, in which the Gravettian is hypothesized to have its origin in the Middle Danube Basin, first spreading west (solid lines) and later spreading east and southeast (dashed lines). This scenario is largely based on the chronology of sites. Thus far, genome-wide data has been collected from only three of the ten< Gravettian regions indicated on the map. These regions are northern Austria (1 sample), the Czech Republic (6), southern Italy (3) and Belgium (3), indicating that they all share a genomic ancestry. However, it is unknown whether samples from the remaining regions also share a close genomic ancestry. Some skeletal remains associated with the Gravettian that could be investigated paleogenomically are from Sungir (Russia); Laghar Velho (central Portugal); Cussac Cave; Les Garennes, near Vilhonneur; and Level 2 at Abri Pataud116 (western France). Light blue and light red regions represent the approximate distributions of the Magdalenian Culture and the Hamburgian Culture (13,000-11,750 years). Figure adapted from Kozłowski. Image from Harris (2017)

The paper talks about possibilities for Common West Eurasian:

  1. Migration from mainland Europe to Near East or vice versa (not very likely);
  2. Migration from a geographically intermediate Ice Age refugium in southeast Europe, Anatolia, or the circum-Pontic region that explain post-glacial affinity of post-glacial Levantine and Anatolian populations.

It also re-states what was known:

  • EHG (ca. 8,000 BP) = between WHG — ANE (ca. 24,000 BP).
  • CHG (ca. 10,000 BP) = between EHG — Iran N.

I would say that the distinct CHG vs. Dzudzuana ancestry puts CHG probably to the south, within the Iranian Plateau, during the Gravettian, expanding probably later.

Also important, Ancestral North African probably accompanied by haplogroup E. Early expansion of North Africans into the Near East further confirms the impossibility of Afroasiatic (much younger) to be associated with these expansions, and confirms that the still unclear Green Sahara migrations are the key.


Scythians in Ukraine, Natufian and sub-Saharan ancestry in North Africa (ISBA 8, 21st Sep)


Interesting information from ISBA 8 sesions today, as seen on Twitter (see programme in PDF, and sessions from the 19th and the 20th september).

Official abstracts are listed first (emphasis mine), then reports and images and/or link to tweets. Here is the list for quick access:

Scythian population genetics and settlement patterns

Genetic continuity in the western Eurasian Steppe broken not due to Scythian dominance, but rather at the transition to the Chernyakhov culture (Ostrogoths), by Järve et al.

The long-held archaeological view sees the Early Iron Age nomadic Scythians expanding west from their Altai region homeland across the Eurasian Steppe until they reached the Ponto-Caspian region north of the Black and Caspian Seas by around 2,900 BP1. However, the migration theory has not found support from ancient DNA evidence, and it is still unclear how much of the Scythian dominance in the Eurasian Steppe was due to movements of people and how much reflected cultural diffusion and elite dominance. We present new whole-genome results of 31 ancient Western and Eastern Scythians as well as samples pre- and postdating them that allow us to set the Scythians in a temporal context by comparing the Western Scythians to samples before and after within the Ponto-Caspian region. We detect no significant contribution of the Scythians to the Early Iron Age Ponto-Caspian gene pool, inferring instead a genetic continuity in the western Eurasian Steppe that persisted from at least 4,800–4,400 cal BP to 2,700–2,100 cal BP (based on our radiocarbon dated samples), i.e. from the Yamnaya through the Scythian period.

However, the transition from the Scythian to the Chernyakhov culture between 2,100 and 1,700 cal BP does mark a shift in the Ponto-Caspian genetic landscape, with various analyses showing that Chernyakhov culture samples share more drift and derived alleles with Bronze/Iron Age and modern Europeans, while the Scythians position outside modern European variation. Our results agree well with the Ostrogothic origins of the Chernyakhov culture and support the hypothesis that the Scythian dominance was cultural rather than achieved through population replacement.

Detail of the slide with admixture of Scythian groups in Ukraine:


Interesting to read in combination with yesterday’s re-evaluation of Scythian mobility and settlement patterns in the west (showing adaptation to the different regional cultures), The Steppe was Sown – multi-isotopic research changes our understandings of Scythian diet and mobility, by Ventresca Miller et al.

Nomadic pastoralists conventionally known as the Scythians occupied the Pontic steppe during the Iron Age, c. 700-200 BC, a period of unprecedented pan-regional interaction. Popular science accounts of the Scythians promote narratives of roving bands of nomadic warriors traversing the steppe from the Altai Mountains to the Black Sea coastline. The quantity and scale of mobility in the region is usually emphasized based on the wide distribution of material culture and the characterization of Iron Age subsistence economies in the Pontic steppe and forest-steppe as mobile pastoralism. Yet, there remains a lack of systematic, direct analysis of the mobility of individuals and their animals. Here, we present a multi-isotopic analysis of humans from Iron Age Scythian sites in Ukraine. Mobility and dietary intake were documented through strontium, carbon and oxygen isotope analyses of tooth enamel. Our results provide direct evidence for mobility among populations in the steppe and forest-steppe zones, demonstrating a range of localized mobility strategies. However, we found that very few individuals came from outside of the broader vicinity of each site, often staying within a 90 km radius. Dietary intake varied at the intrasite level and was based in agro-pastoralism.

While terrestrial protein did form a portion of the diet for some individuals, there were also high levels of a 13C-enriched food source among many individuals, which has been interpreted as millet consumption. Individuals exhibiting 87Sr/86Sr ratios that fell outside the local range were more likely to have lower rates of millet consumption than those that fell within the local range. This suggests that individuals moving to the site later in life had different economic pursuits and consumed less millet. There is also strong evidence that children and infants moved at the pan-regional scale. Contrary to the popular narrative, the majority of Scythians engaged in localized mobility as part of agricultural lifeways while pan-regional movements included family groups.

North-Africans show ancestry from the ancient Near East and sub-Saharan Africa

Pleistocene North Africans show dual genetic ancestry from the ancient Near East and sub-Saharan Africa, by van de Loosdrecht et al.

North Africa, connecting sub-Saharan Africa and Eurasia, is important for understanding human history. However, the genetic history of modern humans in this region is largely unknown before the introduction of agriculture. After the Last Glacial Maximum modern humans, associated with the Iberomaurusian culture, inhabited a wide area spanning from Morocco to Libya. The Iberomaurusian is part of the early Later Stone Age and characterized by a distinct microlithic bladelet technology, complex hunter-gathering and tooth evulsion.

Here we present genomic data from seven individuals, directly dated to ~15,000-year-ago, from Grotte des Pigeons, Taforalt in Morocco. Uni-parental marker analyses show mitochondrial haplogroup U6a for six individuals and M1b for one individual, and Y-chromosome haplogroup E-M78 (E1b1b1a1) for males. We find a strong genetic affinity of the Taforalt individuals with ancient Near Easterners, best represented by ~12,000 year old Levantine Natufians, that made the transition from complex hunter-gathering to more sedentary food production. This suggests that genetic connections between Africa and the Near East predate the introduction of agriculture in North Africa by several millennia. Notably, we do not find evidence for gene flow from Paleolithic Europeans into the ~15,000 year old North Africans as previously suggested based on archaeological similarities. Finally, the Taforalt individuals derive one third of their ancestry from sub-Saharan Africans, best approximated by a mixture of genetic components preserved in present-day West Africans (Yoruba, Mende) and Africans from Tanzania (Hadza). In contrast, modern North Africans have a much smaller sub-Saharan African component with no apparent link to Hadza. Our results provide the earliest direct evidence for genetic interactions between modern humans across Africa and Eurasia.

A detail of the cultures involved in these population movements:


So, most likely, Natufian-related ancestry – as sub-Saharan ancestry – not related to the Afroasiatic expansion.

NOTE. This now probably outdated already by the new preprint on Dzudzuana samples, from the Caucasus.

Impact of colonization in north-eastern Siberia

Exploring the genomic impact of colonization in north-eastern Siberia by Seguin-Orlando et al.

Yakutia is the coldest region in the northern hemisphere, with winter record temperatures below minus 70°C. The ability of Yakut people to adapt both culturally and biologically to extremely cold temperatures has been key to their subsistence. They are believed to descend from an ancestral population, which left its original homeland in the Lake Baykal area following the Mongol expansion between the 13th and 15th centuries AD. They originally developed a semi-nomadic lifestyle, based on horse and cattle breeding, providing transportation, primary clothing material, meat, and milk. The early colonization by Russians in the first half of the 17th century AD, and their further expansion, have massively impacted indigenous populations. It led not only to massive epidemiological outbreaks, but also to an important dietary shift increasingly relying on carbohydrate-rich resources, and a profound lifestyle transition with the gradual conversion from Shamanism to Christianity and the establishment of new marriage customs. Leveraging an exceptional archaeological collection of more than a hundred of bodies excavated by MAFSO (Mission Archéologique Française en Sibérie Orientale) over the last 15 years and naturally kept frozen by the extreme cold temperatures of Yakutia, we have started to characterize the (epi)genome of indigenous individuals who lived from the 16th to the 20th century AD. Current data include the genome sequence of approximately 50 individuals that lived prior to and after Russian contact, at a coverage from 2 to 40 fold. Combined with data from archaeology and physical anthropology, as well as microbial DNA preserved in the specimens, our unique dataset is aimed at assessing the biological consequences of the social and biological changes undergone by the Yakut people following their neolithisation by Russian colons.

Also interesting to read Balanovsky’s session, and a previous paper on the expansion of Yakuts.

Expansion of haplogroup G2a in Anatolia possibly associated with the Mature Aceramic period


Preprint Late Pleistocene human genome suggests a local origin for the first farmers of central Anatolia, by Feldman et al. bioRxiv (2018).

Interesting excerpts (emphasis mine):

Anatolian hunter-gatherers experienced climatic changes during the last glaciation and inhabited a region that connects Europe to the Near East. However, interactions between Anatolia and Southeastern Europe in the later Upper Palaeolithic/Epipalaeolithic are so far not well documented archaeologically. Interestingly, a previous genomic study showed that present-day Near-Easterners share more alleles with European hunter-gatherers younger than 14,000 BP (‘Later European HG’) than with earlier ones (‘Earlier European HG’). With ancient genomic data available, we could directly compare the Near-Eastern hunter-gatherers (AHG and Natufian) with the European ones. As is the case for present-day Near-Easterners, the Near-Eastern hunter-gatherers share more alleles with the Later European HG than with the Earlier European HG, shown by the significantly positive statistic D(Later European HG, Earlier European HG; AHG/Natufian, Mbuti). Among the Later European HG, recently reported Mesolithic hunter-gatherers from the Balkan peninsula, which geographically connects Anatolia and central Europe (‘Iron Gates HG’), are genetically closer to AHG when compared to all the other European hunter-gatherers, as shown in the significantly positive statistic D(Iron_Gates_HG, European hunter-gatherers; AHG, Mbuti/Altai). Iron Gates HG are followed by Epigravettian and Mesolithic individuals from Italy and France (Villabruna and Ranchot respectively) as the next two European hunter-gatherers genetically closest to AHG. Iron Gates HG have been suggested to be genetically intermediate between WHG and eastern European hunter-gatherers (EHG) with an additional unknown ancestral component.

Ancient genomes (marked with color-filled symbols) projected onto the principal components 5 computed from present-day west Eurasians (grey circles) (fig. S4). The geographic location of each ancient group is marked in (A). Ancient individuals newly reported in this study are additionally marked with a black dot inside the symbol

We find that Iron Gates HG can be modeled as a three-way mixture of Near-Eastern hunter-gatherers (25.8 ± 5.0 % AHG or 11.1 ± 2.2 % Natufian), WHG (62.9 ± 7.4 % or 78.0 ± 4.6 % respectively) and EHG (11.3 ± 3.3 % or 10.9 ± 3 % respectively). The affinity detected by the above D-statistic can be explained by gene flow from Near-Eastern hunter-gatherers into the ancestors of Iron Gates or by a gene flow from a population ancestral to Iron Gates into the Near-Eastern hunter-gatherers as well as by a combination of both. To distinguish the direction of the gene flow, we examined the Basal Eurasian ancestry 5 component (α), which is prevalent in the Near East but undetectable in European hunter-gatherers. Following a published approach, we estimated α to be 24.8 ± 5.5 % in AHG and 38.5 ± 5.0 % in Natufians, consistent with previous estimates for the latter. Under the model of unidirectional gene flow from Anatolia to Europe, 6.4 % is expected for α of Iron Gates by calculating (% AHG in Iron Gates HG) × (α in AHG). However, Iron Gates can be modeled without any Basal Eurasian ancestry or with a non-significant proportion of 1.6 ± 2.8 %, suggesting that unidirectional gene flow from the Near East to Europe alone is insufficient to explain the extra affinity between the Iron Gates HG and the Near-Eastern hunter-gatherers. Thus, it is plausible to assume that prior to 15,000 years ago there was either a bidirectional gene flow between populations ancestral to Southeastern Europeans of the early Holocene and Anatolians of the late glacial or a dispersal of Southeastern Europeans into the Near East. Presumably, this Southeastern European ancestral population later spread into central Europe during the post-last-glacial maximum (LGM) period, resulting in the observed late Pleistocene genetic affinity between the Near East and Europe.

Basal Eurasian ancestry proportions (α) as a marker for Near-Eastern gene flow. Mixture proportions inferred by qpAdm for AHG and the Iron Gates HG are schematically represented. The lower schematic shows the expected α in Iron Gates HG under 10 assumption of unidirectional gene flow, inferred from α in the AHG source population. The observed α for Iron Gates HG is considerably smaller than expected thus, the unidirectional gene flow from the Near East to Europe is not sufficient to explain the above affinity.

While ancestry is not always relevant to distinguish certain population movements (see here), especially – as in this case – when there are few samples (thus neither geographically nor chronologically representative) and no previous model to test, it seems that ancestry and Y-DNA show a great degree of continuity in Anatolia since the Palaeolithic until the Neolithic, at least in the sampled regions. C1a2 appears in Europe since ca. 40,000 years ago (viz. Kostenki, Goyet, Vestonice, etc., and later emerges again in the Balkans after the Anatolian Neolithic expansion, probably a resurge of European groups).

The potential transition of a G2a-dominated agricultural society – that is later prevalent in Anatolian and European farmers – may have therefore happened during the Aceramic III period (ca. 8000 BC), a process of haplogroup expansion probably continuing through the early part of the Pottery Neolithic, as the society based on kinship appeared (Rosenberg and Erim-Özdoğan 2011). There is still much to know about the spread of ceramic technology and southwestern Asia domesticate complex, though.


Without a proper geographical sampling, representative of previous and posterior populations, it is impossible to say. But the expansion of R1b-L754 through Anatolia to form part of the Villabruna cluster (and also the Iron Gates HG) seems perfectly possible with this data, although this paper does not help clarify the when or how. We have seen significant changes in ancestry happen within centuries with expanding populations admixing with locals. Palaeolithic sampling – like this one – shows few individuals scattered geographically over thousands of km and chronologically over thousands of years…


The Iron Age expansion of Southern Siberian groups and ancestry with Scythians


Maternal genetic features of the Iron Age Tagar population from Southern Siberia (1st millennium BC), by Pilipenko et al. (2018).

Interesting excerpts (emphasis mine):

The positions of non-Tagar Iron Age groups in the MDS plot were correlated with their geographic position within the Eurasian steppe belt and with frequencies of Western and Eastern Eurasian mtDNA lineages in their gene pools. Series from chronological Tagar stages (similar to the overall Tagar series) were located within the genetic variability (in terms of mtDNA) of Scythian World nomadic groups (Figs 5 and 6; S4 and S6 Tables). Specifically, the Early Tagar series was more similar to western nomads (North Pontic Scythians), while the Middle Tagar was more similar to the Southern Siberian populations of the Scythian period. The Late Tagar group (Tes`culture) belonging to the Early Xiongnu period had the “western-most” location on the MDS plot with the maximal genetic difference from Xiongnu and other eastern nomadic groups (but see Discussion concerning the low sample size for the Tes`series).

In a comparison of our Tagar series with modern populations in Eurasia, we detected similarity between the Tagar group and some modern Turkic-speaking populations (with the exception of the Indo-Iranian Tajik population) (Fig 7; S2 Table). Among the modern Turkic-speaking groups, populations from the western part of the Eurasian steppe belt, such as Bashkirs from the Volga-Ural region and Siberian Tatars from the West Siberian forest-steppe zone, were more similar to the Tagar group than modern Turkic-speaking populations of the Altay-Sayan mountain system (including the Khakassians from the Minusinsk basin) (Fig 7).

Location of Tagar archaeological sites from which samples for this study were obtained. Burial grounds: 1—Novaya Chernaya-1; 2—Podgornoe Ozero, Barsuchiha-1, Barsuchiha-6, Barsuchiha-7; 3—Perevozinskiy; 4—Ulug-Kyuzyur, Kichik-Kyuzyur, Sovetskaya Khakassiya; 5—Tepsey-3, Tepsey-8, Tepsey-9; 6—Dolgiy Kurgan.

Mitochondrial DNA diversity and genetic relationships of the Tagar population

Our results are not inconsistent with the assumption of a probable role of gene flow due to the migration from Western Eurasia to the Minusinsk basin in the Bronze Age in the formation of the genetic composition of the Tagar population. Particularly, we detected many mtDNA lineages/clusters with probable West Eurasian origin that were dominant in modern populations of different parts of Europe, Caucasus, and the Near East (such as K and HV6) in our Tagar series based on a phylogeographic analysis.

We detected relatively low genetic distances between our Tagar population and two Bronze Age populations from the Minusinsk basin—the Okunevo culture population (pre-Andronovo Bronze Age) and Andronovo culture population, followed by Afanasievo population from the Minusinsk Basin and Middle Bronze Age population from the Mongolian Altai Mountains (the region adjacent to the Minusinsk basin) (Figs 3 and 6; S3 and S5 Tables). Among West Eurasian part of our Tagar series we also observed haplogroups/sub-haplogroups and haplotypes shared with Early and Middle Bronze Age populations from Minusinsk Basin and western part of Eurasian steppe belt (Fig 4; S5 Table). Thus, our results suggested a potentially significant role of the genetic components, introduced by migrants from Western Eurasia during the Bronze Age, in the formation of the genetic composition of the Tagar population. It is necessary to note the relatively small size of available mtDNA samples from the Bronze Age populations of Minusinsk basin; accordingly, additional mtDNA data for these populations are required to further confirm our inference.

Phylogenetic tree of mtDNA lineages from the Tagar population. Color coding of the Tagar stages: orange—the Early Tagar stage; blue—the Middle Tagar Stage; green—the Late Tagar stage. Color of haplogroup labels: yellow—for Western Eurasian haplogroups; red—for Eastern Eurasian haplogroups.

Another substantial part of the mtDNA pool of the Tagar and other eastern populations of the Scythian World is typical of populations in Southern Siberia and adjacent regions of Central Asia (autochthonous Central Asian mtDNA clusters). Most of these components belong to the East Eurasian cluster of mtDNA haplogroups. Moreover, the role of each of these components in the formation of the genetic composition of subsequent (to the present) populations in South Siberia and Central Asia could be very different. In this regard, cluster C4a2a (and its subcluster C4a2a1), and haplogroup A8 are of particular interest.

Genetic features of successive Tagar groups

We compared successive Tagar groups (Early, Middle, and Late Tagar) with each other and with other Iron Age nomadic populations to evaluate changes in the mtDNA pool structure. Despite the genetic similarity between the Early and Middle Tagar series and Scythian World nomadic groups (Figs 5 and 6; S4 and S6 Tables), there were some peculiarities. For example, the Early Tagar series was more similar to North Pontic Classic Scythians, while the Middle Tagar samples were more similar to the Southern Siberian populations of the Scythian period (i.e., completely synchronous populations of regions neighboring the Minusinsk basin, such as the Pazyryk population from the Altay Mountains and Aldy-Bel population from Tuva).

We observed differences in the mtDNA pool structure between the Early and the Middle chronological stages of the Tagar culture population, as evidenced by the change in the ratio of Western to Eastern Eurasian mtDNA components. The contribution of Eastern Eurasian lineages increased from about one-third (34.8%) in the Early Tagar group to almost one-half (45.8%) in the Middle Tagar group.

Results of multidimensional scaling based on matrix of Slatkin population differentiation (FST) according to frequencies of mtDNA haplogroup in Tagar populations and modern populations of Eurasia. Populations: Tagar (red pentagon) (this study); Mongolian-speaking populations: Khamnigans (Buryat Republic, Russia) [43]; Barghuts (Inner Mongolia, China) [44]; Buryats (Buryat Republic, Southern Siberia, Russia) [43]; Mongols (Mongolia) [45]. Turkic-speaking populations: Tuvinians (Tuva Republic, Russia) [43]; Tofalars (Irkutsk region, Russia) [46]; Altai-Kizhi ((Altai Republic, Russia) [43, 47]; Telenghits (Altai Republic, Russia) [43,47]; Tubalars (Altai Republic) [48]; Shors (Kemerovo region, Russia) [43, 47]; Khakassians (Khakassian Rupublic, Russia) [43, 46]; Altaian Kazakhs (Altai Republic) [49]; Kazakhs (Kazakhstan, Uzbekistan) [50, 51]; Kirghiz (Kyrgyzstan) [50, 51]; Uighurs (Kazakhstan and Xinjiang) [50, 52]; Siberian Tatars (Tyumen and Omsk regions, Russia) [53]; Tatars (Volga-Ural rigion, Russia) [54]; Bashkirs (Volga-Ural region, Russia) [55]; Uzbeks (Uzbekistan) [51, 56]; Turkmens (Turkmenistan) [51, 56]; Nogays [57]; Turkeys [58]; other populations: Evenks [43, 46]; Ulchi [59]; Koreans (South Korea) [43]; Han Chinese [60]; Zhuang (Guangxi, China) [61]; Tadjiks (Tadjikistan) [43, 51]; Iranians [60]; Russians [62].

At the level of mtDNA haplogroups, we detected a decrease in the diversity of phylogenetic clusters during the transition from the Early Tagar to the Middle Tagar. This decline in diversity equally affected the West Eurasian and East Eurasian components of the Tagar mtDNA pool. It should be noted that this decrease can be partially explained by the smaller number of Middle Tagar than Early Tagar samples. Under a simple binomial approximation the mtDNA clusters, observed at frequencies of 6.3% and 11.7%, could be lost by chance in our Early (N = 46) and Middle (N = 24) Tagar samples, respectively. However, the simultaneous lack of several such clusters, with a total frequency in the gene pool of the Early group of 34.8%, is unlikely.

The observed reduction in the genetic distance between the Middle Tagar population and other Scythian-like populations of Southern Siberia(Fig 5; S4 Table), in our opinion, is primarily associated with an increase in the role of East Eurasian mtDNA lineages in the gene pool (up to nearly half of the gene pool) and a substantial increase in the joint frequency of haplogroups C and D (from 8.7% in the Early Tagar series to 37.5% in the Middle Tagar series). These features are characteristic of many ancient and modern populations of Southern Siberia and adjacent regions of Central Asia, including the Pazyryk population of the Altai Mountains. We did not obtain strong evidence for an intensification of genetic contact between the population of the Minusinsk basin and the Altai Mountains in the Middle Tagar period compared with the Early Tagar period. Although, several archaeologists have found evidence for the intensification of contact at the level of material culture, namely, a cultural influence of the population of the Altai Mountains (represented by the Pazyryk population) on the population of the Minusinsk basin (the Saragash Tagar group) [6, 71, 72].

Another important issue is the change in the genetic structure of the Tagar population during the transition from the Middle (Saragash) to the Late (Tes`) stage. The Late Tagar stage refers to the Xiongnu period. Many archaeologists suggest that the formation of the Tes`stage involved the direct cultural influence of the Xiongnu and/or related groups of nomads from more eastern regions of Central Asia [71, 73]. Some archaeologists have even suggested renaming the Tes`stage in the Tes`culture [71], emphasizing the role of new eastern cultural elements. If this influence also existed at the genetic level, then we would expect to observe new genetic elements in the Tes`gene pool, particularly those of East Eurasian origin.

Siberian ancestry

Just a reminder of the recent session in ISBA 8 on expanding Scythians (and also Mongolians and Turks) spreading Siberian ancestry, usually (wrongly) identified as “Uralic-Yeniseian” based on modern populations (similar to how steppe ancestry is wrongly identified as “Indo-European”), see the following graphic including the Tagar population:

Very important observation with implication of population turnover is that pre-Turkic Inner Eurasian populations’ Siberian ancestry appears predominantly “Uralic-Yeniseian” in contrast to later dominance of “Tungusic-Mongolic” sort (which does sporadically occur earlier). Alexander M. Kim

And also the poster by Alexander M. Kim et al. Yeniseian hypotheses in light of genome-wide ancient DNA from historical Siberia:

The relevance of ancient DNA data to debates in historical linguistics is an emphatic strand in much recent work on the archaeogenetics of Eurasia, where the discussion has focused heavily on Indo-European (Haak et al. 2015; Narasimhan et al. 2018; de Barros Damgaard et al. 2018a,b). We present new genome-wide ancient DNA data from a historical Siberian individual in relation to Yeniseian, an isolated language “microfamily” (Vajda 2014) that nonetheless sits at the center of numerous controversial proposals in historical linguistics and cultural interaction. Yeniseian’s sole surviving representative is Ket, a critically endangered language fluently spoken by only a few dozen individuals near the Middle Yenisei River of Central Siberia.

In strong contrast to the present-day picture, river names and argued substrate influences and loanwords in languages outside the current range of Yeniseian, as well as direct records from the Russian colonial period, indicate that speakers of extinct Yeniseian languages had a formerly much broader presence in the taiga of Central Siberia as well as further south in the mountainous Altai-Sayan region – and perhaps even further afield in Inner Asia (Vajda 2010; Gorbachov 2017; Blažek 2016). The consilience of these proposals with genetic data is not straightforward (Flegontov et al. 2015, 2017) and faces a major obstacle in the lack of genetic information from verifiable speakers of Yeniseian languages other than the Kets, who have had complex ongoing interactions with speakers of non-Yeniseian languages such as the Samoyedic Selkups. We attempt to remedy this with new historical Siberian aDNA data, orienting our search for common denominators and systematic difference in a broader landscape of concordance, discordance, and uncertainty at the interface of diachronic linguistics and genetics.


Neolithic and Bronze Age Anatolia, Urals, Fennoscandia, Italy, and Hungary (ISBA 8, 20th Sep)


I will post information on ISBA 8 sesions today as I see them on Twitter (see programme in PDF, and sessions from yesterday).

Official abstracts are listed first (emphasis mine), then reports and images and/or link to tweets. Here is the list for quick access:

Russian colonization in Yakutia

Exploring the genomic impact of colonization in north-eastern Siberia, by Seguin-Orlando et al.

Yakutia is the coldest region in the northern hemisphere, with winter record temperatures below minus 70°C. The ability of Yakut people to adapt both culturally and biologically to extremely cold temperatures has been key to their subsistence. They are believed to descend from an ancestral population, which left its original homeland in the Lake Baykal area following the Mongol expansion between the 13th and 15th centuries AD. They originally developed a semi-nomadic lifestyle, based on horse and cattle breeding, providing transportation, primary clothing material, meat, and milk. The early colonization by Russians in the first half of the 17th century AD, and their further expansion, have massively impacted indigenous populations. It led not only to massive epidemiological outbreaks, but also to an important dietary shift increasingly relying on carbohydrate-rich resources, and a profound lifestyle transition with the gradual conversion from Shamanism to Christianity and the establishment of new marriage customs. Leveraging an exceptional archaeological collection of more than a hundred of bodies excavated by MAFSO (Mission Archéologique Française en Sibérie Orientale) over the last 15 years and naturally kept frozen by the extreme cold temperatures of Yakutia, we have started to characterize the (epi)genome of indigenous individuals who lived from the 16th to the 20th century AD. Current data include the genome sequence of approximately 50 individuals that lived prior to and after Russian contact, at a coverage from 2 to 40 fold. Combined with data from archaeology and physical anthropology, as well as microbial DNA preserved in the specimens, our unique dataset is aimed at assessing the biological consequences of the social and biological changes undergone by the Yakut people following their neolithisation by Russian colons.

NOTE: For another interesting study on Yakutian tribes, see Relationships between clans and genetic kin explain cultural similarities over vast distances.

Ancient DNA from a Medieval trading centre in Northern Finland

Using ancient DNA to identify the ancestry of individuals from a Medieval trading centre in Northern Finland, by Simoes et al.

Analyzing genomic information from archaeological human remains has proved to be a powerful approach to understand human history. For the archaeological site of Ii Hamina, ancient DNA can be used to infer the ancestries of individuals buried there. Situated approximately 30 km from Oulu, in Northern Finland, Ii Hamina was an important trade place since Medieval times. The historical context indicates that the site could have been a melting pot for different cultures and people of diversified genetic backgrounds. Archaeological and osteological evidence from different individuals suggest a rich diversity. For example, stable isotope analyses indicate that freshwater and marine fish was the dominant protein source for this population. However, one individual proved to be an outlier, with a diet containing relatively more terrestrial meat or vegetables. The variety of artefacts that was found associated with several human remains also points to potential differences in religious beliefs or social status. In this study, we aimed to investigate if such variation could be attributed to different genetic ancestries. Ten of the individuals buried in Ii Hamina’s churchyard, dating to between the 15th and 17th century AD, were screened for presence of authentic ancient DNA. We retrieved genome-wide data for six of the individuals and performed downstream analysis. Data authenticity was confirmed by DNA damage patterns and low estimates of mitochondrial contamination. The relatively recent age of these human remains allows for a direct comparison to modern populations. A combination of population genetics methods was undertaken to characterize their genetic structure, and identify potential familiar relationships. We found a high diversity of mitochondrial lineages at the site. In spite of the putatively distant origin of some of the artifacts, most individuals shared a higher affinity to the present-day Finnish or Late Settlement Finnish populations. Interestingly, different methods consistently suggested that the individual with outlier isotopic values had a different genetic origin, being more closely related to reindeer herding Saami. Here we show how data from different sources, such as stable isotopes, can be intersected with ancient DNA in order to get a more comprehensive understanding of the human past.

A closer look at the bottom left corner of the poster (the left columns are probably the new samples):


Plant resources processed in HG pottery from the Upper Volga

Multiple criteria for the detection of plant resources processed in hunter-gatherer pottery vessels from the Upper Volga, Russia, by Bondetti et al.

In Northern Eurasia, the Neolithic is marked by the adoption of pottery by hunter-gatherer communities. The degree to which this is related to wider social and lifestyle changes is subject to ongoing debate and the focus of a new research programme. The use and function of early pottery by pre-agricultural societies during the 7th-5th millennia BC is of central interest to this debate. Organic residue analysis provides important information about pottery use. This approach relies on the identification and isotopic characteristics of lipid biomarkers, absorbed into the pores of the ceramic or charred deposits adhering to pottery vessel surfaces, using a combined methodology, namely GC-MS, GC-c-IRMS and EA-IRMS. However, while animal products (e.g., marine, freshwater, ruminant, porcine) have the benefit of being lipid-rich and well-characterised at the molecular and isotopic level, the identification of plant resources still suffers from a lack of specific criteria for identification. In huntergatherer contexts this problem is exacerbated by the wide range of wild, foraged plant resources that may have been potentially exploited. Here we evaluate approaches for the characterisation of terrestrial plant food in pottery through the study of pottery assemblages from Zamostje 2 and Sakhtysh 2a, two hunter-gatherer settlements located in the Upper Volga region of Russia.

GC-MS analysis of the lipids, extracted from the ceramics and charred residues by acidified methanol, suggests that pottery use was primarily oriented towards terrestrial and aquatic animal products. However, while many of the Early Neolithic vessels contain lipids distinctive of freshwater resources, triterpenoids are also present in high abundance suggesting mixing with plant products. When considering the isotopic criteria, we suggest that plants were a major commodity processed in pottery at this time. This is supported by the microscopic identification of Viburnum (Viburnum Opulus L.) berries in the charred deposits on several vessels from Zamostje.

The study of Upper Volga pottery demonstrated the importance of using a multidisciplinary approach to determine the presence of plant resources in vessels. Furthermore, this informs the selection of samples, often subject to freshwater reservoir effects, for 14C dating.

Studies on hunter-gatherer pottery – appearing in eastern Europe before Middle Eastern Neolithic pottery – may be important to understand the arrival of R1a-M17 lineages to the region before ca. 7000 BC. Or not, right now it is not very clear what happened with R1b-P297 and R1a-M17, and with WHG—EHG—ANE ancestry

Bronze Age population dynamics and the rise of dairy pastoralism on the eastern Eurasian steppe

Bronze Age population dynamics and the rise of dairy pastoralism on the eastern Eurasian steppe, by Warinner et al.

Recent paleogenomic studies have shown that migrations of Western steppe herders (WSH), beginning in the Eneolithic (ca. 3300-2700 BCE), profoundly transformed the genes and cultures of Europe and Central Asia. Compared to Europe, the eastern extent of this WSH expansion is not well defined. Here we present genomic and proteomic data from 22 directly dated Bronze Age khirigsuur burials from Khövsgöl, Mongolia (ca. 1380-975 BCE). Only one individual showed evidence of WSH ancestry, despite the presence of WSH populations in the nearby Altai-Sayan region for more than a millennium. At the same time, LCMS/ MS analysis of dental calculus provides direct protein evidence of milk consumption from Western domesticated livestock in 7 of 9 individuals. Our results show that dairy pastoralism was adopted by Bronze Age Mongolians despite minimal genetic exchange with Western steppe herders.

Detail of the images:



Mitogenomes suggest rapid expansion of domesticated horse before 3500 BC

Open access Origin and spread of Thoroughbred racehorses inferred from complete mitochondrial genome sequences: Phylogenomic and Bayesian coalescent perspectives, by Yoon et al. PLOS One (2018).

Abstract (emphasis mine)

The Thoroughbred horse breed was developed primarily for racing, and has a significant contribution to the qualitative improvement of many other horse breeds. Despite the importance of Thoroughbred racehorses in historical, cultural, and economical viewpoints, there was no temporal and spatial dynamics of them using the mitogenome sequences. To explore this topic, the complete mitochondrial genome sequences of 14 Thoroughbreds and two Przewalski’s horses were determined. These sequences were analyzed together along with 151 previously published horse mitochondrial genomes from a range of breeds across the globe using a Bayesian coalescent approach as well as Bayesian inference and maximum likelihood methods. The racing horses were revealed to have multiple maternal origins and to be closely related to horses from one Asian, two Middle Eastern, and five European breeds. Thoroughbred horse breed was not directly related to the Przewalski’s horse which has been regarded as the closest taxon to the all domestic horses and the only true wild horse species left in the world. Our phylogenomic analyses also supported that there was no apparent correlation between geographic origin or breed and the evolution of global horses. The most recent common ancestor of the Thoroughbreds lived approximately 8,100–111,500 years ago, which was significantly younger than the most recent common ancestor of modern horses (0.7286 My). Bayesian skyline plot revealed that the population expansion of modern horses, including Thoroughbreds, occurred approximately 5,500–11,000 years ago, which coincide with the start of domestication. This is the first phylogenomic study on the Thoroughbred racehorse in association with its spatio-temporal dynamics. The database and genetic history information of Thoroughbred mitogenomes obtained from the present study provide useful information for future horse improvement projects, as well as for the study of horse genomics, conservation, and in association with its geographical distribution.

Bayesian skyline plot (BSP) based on mitochondrial genome sequences from 167 modern horses.
The dark line in the BSP represents the estimated effective population size through time. The green area represents the 95% highest posterior density confidence intervals for this estimate.

Interesting excerpts:

We carried out a Bayesian coalescent approach using extended mitochondrial genome sequences from 167 horses in order to further assess the timescale of horse domestication. Here, we first calculated the time of the most recent common ancestor of Thoroughbred horses. Our analysis revealed the age of the most recent common ancestor of the racing horse to be around 8,100–111,500 years old. This estimate is much younger than that of the most recent common ancestor of the global horses, which has been estimated at 0.7286 Mys old.

Bayesian maximum clade credibility phylogenomic tree on the ground of the mitochondrial genome sequences of 167 modern horses.
The data set (16,432 base pairs) was also analyzed phylogenetically using Bayesian inference (BI) and maximum likelihood (ML) methods which showed the same topologies. 95% Highest Posterior Density of node heights are shown by blue bars. Groups are marked by a “G”. Numbers at the nodes represent (left to right): posterior probabilities (≥0.80) for the BI tree and bootstrap values (≥70%) for the ML tree. The racing horses were revealed to have multiple maternal origins and to be closely related to horses from one Asian, two Middle Eastern, and five European breeds. Results of phylogenomic analyses also uncovered no apparent association between geographic origin or breed and heterogeneity of global horses. The most recent common ancestor of the Thoroughbreds lived approximately 8,100–111,500 years ago, which was significantly younger than the most recent common ancestor of modern horses (0.7286 My).

On the domestication time of modern horses, there have been several publications derived from both archaeological [49–51] and molecular [11–12, 23, 48] evidences. D’Andrade [49] reported that the origin of domestic horses was around 4,000 years ago. Ludwig et al. [50] stated the domestication time to be about 5,000 years ago, while Anthony [51] noted that horse rearing by humans may have occurred approximately 6,000 years ago. Subsequently, on the basis of mitochondrial genome sequences, Lippold et al. [11] and Achilli et al. [12] postulated domestication time to be about 6,000–8,000 and 6,000–7,000 years ago, respectively. Warmuth [48] dated domestication time to 5,500 years ago based on autosomal genotype data, while Orlando et al. [23] claimed that Przewalski’s and domestic horse populations diverged 38,000–72,000 years ago based on analysis of genome sequences. In contrast to the previous hypothesized date of horse domestication, the results of our Bayesian skyline plot (BSP) analysis depict a rapid expansion of the horse population approximately 5,500–11,000 years ago, which coincides with the start of domestication.

It seems that we will not have an update on horse aDNA from the ISBA 8, so we will have to make do with this for the moment.


Global demographic history inferred from mitogenomes

Open access Global demographic history of human populations inferred from whole mitochondrial genomes, by Miller, Manica, and Amos, Royal Society Open Science (2018).

Relevant excerpts (emphasis mine):


The Phase 3 sequence data from 20 populations, comprising five populations for each of the four main geographical regions of Europe, East Asia, South Asia and Africa, were downloaded from the 1000 Genomes Project website (, [8]), including whole mitochondrial genome data for 1999 individuals. We decided not to analyse populations from the Americas due to the region’s complex history of admixture [13,14].

The European populations were as follows: Finnish sampled in Finland (FIN); European Caucasians resident in Utah, USA (CEU); British in England and Scotland (GBR); an Iberian population from Spain (IBS) and Toscani from Italy (TSI). Representing East Asia were the Han Chinese in Beijing (CHB); Southern Han Chinese (CHS); Dai Chinese from Xishuangbanna, China (CDX); Kinh population from Ho Chi Minh City, Vietnam (KHV) and Japanese from Tokyo (JPT). The South Asian populations were Punjabi Indians from Lahore, Pakistan (PJL); Gujarati Indians in Houston, USA (GIH) as well as Indian Telugu sampled in the UK (ITU); Bengali from Bangladesh (BEB) and Sri Lankan Tamil from the UK (STU). (…)


We analysed our mtDNA data with the extended Bayesian skyline plot (EBSP) method, a Bayesian, non-parametric technique for inferring past population size fluctuations from genetic data. Building on the previous Bayesian skyline plot (BSP) approach, EBSP uses a piecewise-linear model and Markov chain Monte Carlo (MCMC) methods to reconstruct a populations’ demographic history [17] and is implemented in the software package BEAST v. 2.3.2 [11]. Alignments for each of the 20 populations were loaded separately into the Bayesian Evolutionary Analysis Utility tool (BEAUti v. 2.3.2) in NEXUS format.

Relationship between profile similarity and genetic distance, measured as Fst. Comparisons between regions, circles, are colour-coded: black ¼ AFR-EA; yellow ¼ AFR-EUR; blue ¼ AFR-SA; orange ¼ EUR-EA; green ¼ EA-SA; red ¼ EUR-SA. Comparisons within regions, squares, are coded: peach ¼ EUR; pink ¼ EA; dark blue ¼ EA; light blue ¼ AFR. Profile similarity is calculated as inferred size difference summed over 20 evenly spaced intervals (see Material and methods).

Regional demographic histories


The five European profiles are presented in figure 2. The four southerly populations all show profiles with a stable size up to approximately 14 ka followed by a sudden, rapid increase that becomes progressively less steep towards the present. There is also a north-south trend, with confidence intervals becoming broader towards the north, particularly for the oldest time-points. The Finnish population profile appears rather different, but this is to be expected both because it is so far north and because previous studies have identified Finns as a strong genetic outlier in Europe [19–22].

Inferred demographic histories of five European populations. Dotted line is the median estimate of Ne and the thin grey lines show the boundary of the 95% CPD interval. The x-axis represents time from the present in years and all plots are on the same scale. Map shows origins of sampled populations.

South Asia:

The five profiles for South Asia are shown in figure 3. All populations reveal a period of rapid growth approximately 45–40 ka which then slows. Near the present the two southerly populations, GIH and STU both show evidence of a decline. However, this may be due to these samples being drawn from populations no longer living on the subcontinent, with the downward trend capturing a bottleneck associated with moving to Europe/America, perhaps accentuated by the tendency for immigrant populations to group by region, religion and race [23].

Inferred South Asian population demographic histories. Dotted line is the median Ne estimate and the thin grey lines show the boundary of the 95% CPD intervals. The x-axis represents time from the present in thousands of years and all plots are on the same scale. The map shows location of sampled populations.


A study of genetic diversity of three isolated populations in Xinjiang using Y-SNP


New open access paper (in Chinese) A study of genetic diversity of three isolated populations in Xinjiang using Y-SNP, by liu et al. Acta Anthropologica Sinitica (2018)


The Keriyan, Lopnur and Dolan peoples are isolated populations with sparse numbers living in the western border desert of our country. By sequencing and typing the complete Y-chromosome of 179 individuals in these three isolated populations, all mutations and SNPs in the Y-chromosome and their corresponding haplotypes were obtained. Types and frequencies of each haplotype were analyzed to investigate genetic diversity and genetic structure in the three isolated populations. The results showed that 12 haplogroups were detected in the Keriyan with high frequencies of the J2a1b1 (25.64%), R1a1a1b2a (20.51%), R2a (17.95%) and R1a1a1b2a2 (15.38%) groups. Sixteen haplogroups were noted in the Lopnur with the following frequencies: J2a1 (43.75%), J2a2 (14.06%), R2 (9.38%) and L1c (7.81%). Forty haplogroups were found in the Dolan, noting the following frequencies: R1b1a1a1 (9.21%), R1a1a1b2a1a (7.89%), R1a1a1b2a2b (6.58%) and C3c1 (6.58%). These data show that these three isolated populations have a closer genetic relationship with the Uygur, Mongolian and Sala peoples. In particular, there are no significant differences in haplotype and frequency between the three isolated populations and Uygur (f=0.833, p=0.367). In addition, the genetic haplotypes and frequencies in the three isolated populations showed marked Eurasian mixing illustrating typical characteristics of Central Asian populations.

Figure 1. The populations distribution map. Left: Uluru. Center: Dali Yabuyi. Right: Kaerqu.

My knowledge of written Chinese is almost zero, so here are some excerpts with the help of Google Translate:

The source of 179 blood samples used in the study is shown in Figure 1. The Keriyan blood samples were collected from Dali Yabuyi Township, Yutian County (39 samples). The blood samples of the Lopnur people were collected from Kaerqu Township, Yuli County (64 cases); the blood samples of the Dolan people were collected from the town of Uluru, Awati County (76).

Columns one and two are the Keriyan haplotypes and frequencies, respectively; the third and fourth columns are the Lopnur haplotypes and frequencies; the last four columns are the Daolang haplotypes and frequencies.

The composition and frequency of the Keriyan people’s haplogroup are closest to those of the Uighurs, and both Principal Component Analysis and Phylogenetic Tree Analysis show that their kinship is recent. We initially infer that the Keriyan are local desert indigenous people. They have a connection with the source of the Uighurs. Chen et al. [42] studied the patriarchal and maternal genetic analysis of the Keriyan people and found that they are not descendants of the Tibetan ethnic group in the West. The Keriyan people are a mixed group of Eastern and Western Europeans, which may originate from the local Vil group. Duan Ranhui [43] and other studies have shown that the nucleotide variability and average nucleotide differences in the Keriyan population are between the reported Eastern and Western populations. The phylogenetic tree also shows that the populations in Central Asia are between the continental lineage of the eastern population and the European lineage of the western population, and the genetic distance between the Keriyan and the Uighurs is the closest, indicating that they have a close relationship.


Regarding the origin of the Lopnur people, Purzhevski judged that it was a mixture of Mongolians and Aryans according to the physical characteristics of the Lopnur people. In 1934, the Sino-Swiss delegation discovered the famous burials of the ancient tombs in the Peacock River. After research, they were the indigenous people before the Loulan period; the researcher Yang Lan, a researcher at the Institute of Cultural Relics of the Chinese Academy of Social Sciences, said that the Lopnur people were descendants of the ancient “Landan survivors”. However, the Loulan people speaking an Indo-European language, and the Lopnur people speaking Uyghur languages contradict this; the historical materials of the Western Regions, “The Geography of the Western Regions” and “The Western Regions of the Ming Dynasty” record the Uighurs who lived in Cao Cao in the late 17th and early 18th centuries. Because of the occupation of the land by the Junggar nobles and their oppression, they fled. Some of them were forced to move to the Lop Nur area. There are many similar archaeological discoveries and historical records. We have no way to determine their accuracy, but they are at different times, and there is a great difference in what is heard in the same region. (…) The genetic characteristics of modern Lopnur people are the result of the long-term ethnic integration of Uyghurs, Mongols, and Europeans. This is also consistent with the similarity of the genetic structure of the Y chromosome of Lopnur in this study with the Uighurs and Mongolians. For example, the frequency of J haplogroup is as high as 59.37%, while J and its downstream sub-haplogroup are mainly distributed in western Europe, West Asia and Central Asia; the frequency of O, R haplogroup is close to that of Mongolians.

1) KA: Keriya, LB: Rob, DL: Daolang, HTW: Hetian Uygur, HTWZ: and Uygur, TLFW: Turpan Uighur, HZ: Hui, HSKZ: Kazakh, WZBKZ: Wuhuan Others, TJKZ: Tajik, KEKZZ: Kirgiz, TTEZ: Tatar, ELSZ: Russian XBZ: Xibo, MGZ: Mongolian, SLZ: Salar, XJH: Xinjiang Han, GSH: Gansu Han, GDH: Guangdong Han SCH: Sichuan Han. 2) Reference population data source literature 19-22. After the population names in the table have been marked, all the shorthands in the text are referred to in this table. 3) Because the degree of haplotypes of each reference population is different to each sub-group branch, the sub-group branches under the same haplogroup are merged when the population haplogroup data is aggregated, for example: for haplogroup G Some people are divided into G1a and G2a levels, others are assigned to G1, G2, and G3, while some people can only determine G this time. Therefore, each subgroup is merged into a single group G.

According to Ming History·Western Biography, the Mongolians originated from the Mobei Plateau and later ruled Asia and Eastern Europe. Mongolia was established, and large areas of southern Xinjiang and Central Asia were included. Later, due to the Mongolian king’s struggle for power, it fell into a long-term conflict. People of the land fled to avoid the war, and the uninhabited plain of the lower reaches of the Yarkant River naturally became a good place to live. People from all over the world gathered together and called themselves “Dura” and changed to “Dang Lang”. The long-term local Uyghur exchanges that entered the southern Mongolian monks and “Dura” were gradually assimilated [44]. According to the report, locals wore Mongolian clothes, especially women who still maintained a Mongolian face [45]. In 1976, the robes and waistbands found in the ancient time of the Daolang people in Awati County were very similar to those of the ancients. Dalang Muqam is an important part of Daolang culture. It is also a part of the Uyghur Twelve Muqam, and it retains the ancient Western culture, but it also contains a larger Mongolian culture and relics. The above historical records show that the Daolang people should appear in the Chagatai Khanate and be formed by the integration of Mongolian and Uighur ethnic groups. Through our research, we also found that the paternal haplotype of the Daolang people is contained in both Uygur and Mongolian, and the main haplogroups are the same, whereas the frequencies are different (see Table 3). The principal component analysis and the NJ analysis are also the same. It is very close to the Uyghur and the Mongolian people, which establishes new evidence for the “mixed theory” in molecular genetics.

Genetic relationship between the three isolated populations: the Uygur and the Mongolian is the closest, and the main haplogroup can more intuitively compare the source composition of the genetic structure of each population. Haplogroups C, D, and O are mainly distributed in Asia as the East Asian characteristic haplogroup; haplogroups G, J, and R are mainly distributed in continental Europe, and the high frequency distribution is in Europe and Central Asia.

If the nomenclature follows a recent ISOGG standard, it appears that:

The presence of exclusively R1a-Z93 subclades and the lack of R1b-M269 samples is compatible with the expansion of R1a-Z93 into the area with Proto-Tocharians, at the turn of the 3rd-2nd millennium BC, as suggested by the Xiaohe samples, supposedly R1a(xZ93).

Now that it is obvious from ancient DNA (as it was clear from linguistics) that Pre-Tocharians separated earlier than other Late PIE peoples, with the expansion of late Khvalynsk/Repin into the Altai, at the end of the 4th millennium, these prevalent R1a (probably Z93) samples may be showing a replacement of Pre-Tocharian Y-DNA with the Andronovo expansion already by 2000 BC.

Lacking proper assessment of ancient DNA from Proto-Tocharians, this potential early Y-DNA replacement is still speculative*. However, if that is the case, I wonder what the Copenhagen group will say when supporting this, but rejecting at the same time the more obvious Y-DNA replacement in East Yamna / Poltavka in the mid-3rd millennium with incoming Corded Ware-related peoples. I guess the invention of an Indo-Tocharian group may be near…

*NOTE. The presence of R1b-M269 among Proto-Tocharians, as well as the presence of R1b-M269 among Tarim Basin peoples in modern and ancient times is not yet fully discarded. The prevalence of R1a-Z93 may also be the sign of a more recent replacement by Iranian peoples, before the Mongolian and Turkic expansions that probably brought R1b(xM269).

Also, the presence of R1b (xM269) samples in east Asia strengthens the hypothesis of a back-migration of R1b-P297 subclades, from Northern Europe to the east, into the Lake Baikal area, during the Early Mesolithic, as found in the Botai samples and later also in Turkic populations – which are the most likely source of these subclades (and probably also of Q1a2 and N1c) in the region.