ASoSaH Reread (I): Y-DNA haplogroups among Indo-Europeans (apart from R1b-L23)


Given my reduced free time in these months, I have decided to keep updating the text on Indo-European and Uralic migrations and/or this blog, simultaneously or alternatively, to make the most out of the time I can dedicate to this. I will add the different ‘A Song of Sheep and Horses (ASoSaH) reread’ posts to the original post announcing the books. I would be especially interested in comments and corrections to the book chapters rather than the posts, but any comments are welcome (including in the forum, where comments are more likely to stick).

This is mainly a reread of iv.2. Indo-Anatolians and vi.1. Disintegrating Indo-Europeans.

Indo-Anatolians and Late Indo-Europeans

I have often written about R1b-L23 as the majority haplogroup among Late Proto-Indo-Europeans (see my predictions for 2018 and my summary of 2018), but always expected other haplogroups to pop up somewhere along the way, in Khvalynsk, in Repin, in Yamna, and in Bell Beakers (see e.g. the post on common fallacies of R1a/IE-fans).

Luckily enough – for those of us who want precise answers to our previous infinite models of Indo-European language expansions (viz. GAC-associated expansion, IE-speaking Old Europe, Anatolian homeland, Iran homeland, Maykop as Proto-Anatolian, Palaeolithic Continuity Theory, Celtic in the Atlantic façade, etc.) – the situation has been more clear-cut than expected: it turns out that, especially during population expansions, acute Y-chromosome bottlenecks were very common in the past, at least until the Iron Age.

Khvalynsk and Repin-Yamna expansions were no different, and that seems quite natural in hindsight, given the strong familial ties and aversion to foreigners proper of the Late Proto-Indo-European society and culture – probably not really that different from other contemporary societies, like the neighbouring Late Proto-Uralic or Trypillian ones.

Y-DNA samples from Khvalynsk and neighbouring cultures. See full version here.

Y-DNA haplogroups

During the expansion of early Khvalynsk, the most likely Indo-Anatolian culture, the society of the Don-Volga area was probably made up of different lineages including R1b-V1636, R1b-M269, R1a-YP1272, Q1a-M25, and I2a-L699 (and possibly some R1b-V88?), a variability possibly greater than that of the contemporary north Pontic area, probably a sign of this region being a sink of different east and west migrations from steppe and forest areas.

During its expansion, the Khvalynsk society saw its haplogroup variability reduced, as evidenced by the succeeding expansive Repin culture:

Afanasevo, representing Pre-Tocharian (the earliest Late PIE dialect to branch off), expanded with R1b-L23 – especially R1b-Z2103 – lineages, while early Yamna expanded with R1b-L23 and I2a-L699 lineages, which suggests that these are the main haplogroups that survived the Y-DNA bottleneck undergone during the Khvalynsk expansion, and especially later during the late Repin expansion. Nevertheless, other old haplogroups might still pop up during the Repin and early Yamna period, such as the R1b-V1636 sample from Yamna in the Northern Caucasus.

It is still unclear if R1b-L23 sister clade R1b-PF7562 (formed ca. 4400 BC, TMRCA ca. 3400 BC), prevalent among modern Albanians, expanded with Yamna migrants, or if it was part of an earlier expansion of R1b-M269 into the Balkans, and represent thus Indo-Anatolian speakers who later hitchhiked the expansion of the Late PIE language from the north or west Pontic area. The early TMRCA seems to suggest an association with Repin (and therefore Yamna), rather than later movements in the Balkans.

Y-DNA samples from Yamnaya and neighbouring cultures. See full version here.

‘Yamnaya’ or ‘steppe’ ancestry?

After the early years when population genetics relied mainly on modern Y-DNA haplogroups, geneticists and amateurs have been recently playing around with testing “ancestry percentages”, based on newly developed free statistical tools, which offer obviously just one among many types of data to achieve a proper interpretation of the past.

Today we have quite a lot Y-DNA haplogroups reported for ancient samples of more recent prehistoric periods, and they seem to offer (at least since the 2015 papers, but more evidently since the 2018 papers on Bell Beakers and Europeans, Corded Ware, or Fennoscandia among others) the most straightforward interpretation of all results published in population genomics research.

NOTE. The finding of a specific type of ancestry in one isolated 40,000-year-old sample from Tianyuan can offer very interesting information on potential population movements to the region. However, the identification of ethnolinguistic communities and their migrations among neighbouring groups in Neolithic or Bronze Age groups is evidently not that simple.

Yamnaya (Indo-European peoples) and their evolution in the steppes, together with North Pontic (eventually Uralic) peoples.Notice how little Indo-European ancestry changes from Khvalynsk (Indo-Anatolian) to Yamna Hungary (North-West Indo-Europeans) Image modified from Wang et al. (2018). See more on the evolution of “steppe ancestry”.

It is becoming more and more clear with each paper that the true “Yamnaya ancestry” – not the originally described one – was in fact associated with Indo-Europeans (see more on the very Yamnaya-like Yamna Hungary and early East Bell Beaker R1b samples, all of quite similar ancestry and PCA cluster before their further admixture with EEF- and CWC-like groups).

The so-called “steppe ancestry”, on the other hand, reflects the contribution of a Northern Caucasus-related ancestry to expanding Khvalynsk settlers, who spread through the steppes more than a thousand years before the expansion of Late Proto-Indo-Europeans with late Repin, and can thus be found among different groups related to the Pontic-Caspian steppes (see more on the emergence and evolution of “steppe ancestry”).

In fact, after the Yamna/Indo-European and Corded Ware/Uralic expansions, it is more likely to find “steppe ancestry” to the north and east in territories traditionally associated with Uralic languages, whereas to the south and west – i.e. in territories traditionally associated with Indo-European languages – it is more likely to find “EEF ancestry” with diminished “steppe ancestry”, among peoples patrilineally descended from Yamna settlers.

Y-DNA haplogroups, the only uniparental markers (see exceptions in mtDNA inheritance) – unlike ancestry percentages based on the comparison of a few samples and flawed study designs – do not admix, do not change, and therefore they do not lend themselves to infinite pet theories (see e.g. what David Reich has to say about R1b-P312 in Iberia directly derived from Yamna migrants in spite of their predominant EEF ancestry): their cultural continuity can only be challenged with carefully threaded linguistic, archaeological, and genetic data.


Biparental inheritance of mitochondrial DNA in humans


New paper Biparental Inheritance of Mitochondrial DNA in Humans, by Luo et al. PNAS (2018).

Interesting excerpts (emphasis mine):


Although there has been considerable debate about whether paternal mitochondrial DNA (mtDNA) transmission may coexist with maternal transmission of mtDNA, it is generally believed that mitochondria and mtDNA are exclusively maternally inherited in humans. Here, we identified three unrelated multigeneration families with a high level of mtDNA heteroplasmy (ranging from 24 to 76%) in a total of 17 individuals. Heteroplasmy of mtDNA was independently examined by high-depth whole mtDNA sequencing analysis in our research laboratory and in two Clinical Laboratory Improvement Amendments and College of American Pathologists-accredited laboratories using multiple approaches. A comprehensive exploration of mtDNA segregation in these families shows biparental mtDNA transmission with an autosomal dominantlike inheritance mode. Our results suggest that, although the central dogma of maternal inheritance of mtDNA remains valid, there are some exceptional cases where paternal mtDNA could be passed to the offspring. Elucidating the molecular mechanism for this unusual mode of inheritance will provide new insights into how mtDNA is passed on from parent tooffspring and may even lead to the development of new avenues for the therapeutic treatment for pathogenic mtDNA transmission.

An example

Compared with Family A, a strikingly similar mtDNA transmission pattern was demonstrated in Families B and C. Taking Family B for illustration, II-3 having 29 heteroplasmic and seven homoplasmic variants should have inherited mtDNA from both his father (I-1, haplogroup of K1b2a) and his mother (I-10, haplogroup of H), who were supposed to possess 34 and nine homoplasmic variants, respectively. II-3 further transmitted his mtDNA that he inherited from I-1 to his son (III-2), who also inherited all of his mother’s mtDNA (II-30, carrying 34 variants and a haplogroup of T2a1a). However, III-2’s sister (III-1) and half-brother (III-5) only inherited the maternal mtDNA. Fresh blood sampling and repeated mtDNA sequencing in a second independent laboratory were also performed to rule out the possibility of sample mix-up for III-2 (III-2, column F-G and H-I). Additionally, these samples were further verified using Pacific Bio single molecular sequencing (see Materials and Methods) and by restriction fragment length polymorphism (RFLP) analysis of Family A, and these results were fully consistent with the previous sequencing.

Biparental mtDNA inheritance pattern shown in Family B. (A) Pedigree of Family B. The black filled symbols indicate the two family members (II-3 and III-2) showing biparental mtDNA transmission. The IDs of five family members tested by whole mtDNA sequencing analysis have been underlined in the pedigree. (B) Schematic of the mtDNA genotype defined by the homoplasmic and/or heteroplasmic variants aligned from the reference mitochondrial genome. Blue bars represent the genotype of paternally derived mtDNA, whereas purple-red and orange-red bars represent maternally derived mtDNA. Entries labeled (D) represent deduced mtDNA genotypes. (C) Summary of the haplogroup and mtDNA variant numbers in Family B.

A Resurgence of the Paternal Transmission Hypothesis

The results presented in this paper make a robust case for paternal transmission of mtDNA. Here, we report biparental mtDNA inheritance (either directly or indirectly) in 17 members in three multigeneration families. Thirteen of these individuals were identified directly by sequencing of the mitochondrial genome, whereas four could be inferred based on preexisting maternal heteroplasmy caused by biparental inheritance in the previous generation.

To further confirm these remarkable results and to exclude the possibility of sample mix-up and/or contamination, the whole mtDNA sequencing procedure was repeated independently in at least two different laboratories by different laboratory technicians with newly obtained blood samples. All results were reproducible, indicating no artifacts or contamination exist. More importantly, the multiple mtDNA variants that were paternally transmitted differ in both number and position among each of these three families as well as the related haplogroup (R0a1 in Family A, K1b2a in Family B, and K2b1a1a in Family C, respectively), providing two distinct forms of evidence supporting transmission of the paternal mtDNA.

Therefore, we have unequivocally demonstrated the existence of biparental mtDNA inheritance as evidenced by the high number and level of mtDNA heteroplasmy in these three unrelated multigeneration families. Most interestingly, the mixed haplogroups in these samples are very reminiscent of the mixed haplogroups found in the 20 studies that were dismissed by Bandelt et al. as due to contamination or sample mix-up. One is forced to wonder how many other instances of individuals with biparental mtDNA inheritance have been dismissed as technical errors, and whether Schwartz and Vissing’s original discovery has really been given the proper follow-up that it deserves. We suspect that these results will initiate a broader reassessment of the topic.

We propose that the paternal mtDNA transmission in these families should be accompanied by segregation of a mutation in one nuclear gene involved in paternal mitochondrial elimination and that there is a high probability that the gene in question operates through one of the pathways identified above.

If I have to be honest, I was stuck with the paternal transmission hypothesis which we were taught in class long ago. I didn’t know it was controversial or dismissed, I just thought it was really exceptional, and I never thought about learning more on the subject.

This paper proves it may be more complicated than that, especially for population genomics purposes, because biparental mtDNA transmission with autosomal dominant-like inheritance puts a serious barrier to a general, simplistic interpretation of mtDNA.

I don’t think it is a blow to all interpretations based on mtDNA, though, because the traditional interpretation should often work statistically. However, one has to be always very careful when saying “if it’s mtDNA from region X, it’s about female exogamy”, especially when samples are from neighbouring regions and similar periods.

The term “uniparental marker” for mtDNA is obviously misleading and shouldn’t be used, and many research papers and interpretations taking mtDNA as strictly uniparental should be taken with a pinch of salt.


Waves of Palaeolithic ANE ancestry driven by P subclades; new CWC-like Finnish Iron Age

New preprint The population history of northeastern Siberia since the Pleistocene, by Sikora et al. bioRxiv (2018).

Interesting excerpts (emphasis mine; most internal references removed):

ANE ancestry

The earliest, most secure archaeological evidence of human occupation of the region comes from the artefact-rich, high-latitude (~70° N) Yana RHS site dated to ~31.6 kya (…)

The Yana RHS human remains represent the earliest direct evidence of human presence in northeastern Siberia, a population we refer to as “Ancient North Siberians” (ANS). Both Yana RHS individuals were unrelated males, and belong to mitochondrial haplogroup U, predominant among ancient West Eurasian hunter-gatherers, and to Y chromosome haplogroup P1, ancestral to haplogroups Q and R, which are widespread among present-day Eurasians and Native Americans.

Symmetry tests using f4 statistics reject tree-like clade relationships with both Early West Eurasians (EWE; Sunghir) and Early East Asians (EEA; Tianyuan); however, Yana is genetically closer to EWE, despite its geographic location in northeastern Siberia

Using admixture graphs (qpGraph) and outgroup-based estimation of mixture proportions (qpAdm), we find that Yana can be modelled as EWE with ~25% contribution from EEA

Among all ancient individuals, Yana shares the most genetic drift with Mal’ta, and f4 statistics show that Mal’ta shares more alleles with Yana than with EWE (e.g. f4(Mbuti,Mal’ta;Sunghir,Yana) = 0.0019, Z = 3.99). Mal’ta and Yana also exhibit a similar pattern of genetic affinities to both EWE and EEA, consistent with previous studies.The ANE lineage can thus be considered a descendant of the ANS lineage, demonstrating that by 31.6 kya early representatives of this lineage were widespread across northern Eurasia, including far northeastern Siberia.


Ancient Palaeosiberian

(…) the 9.8 kya Kolyma1 individual, representing a group we term “Ancient Paleosiberians” (AP). Our results indicate that AP are derived from a first major genetic shift observed in the region. Principal component analysis (PCA), outgroup f3-statistics and mtDNA and Y chromosome haplogroups (G1b and Q1a1a, respectively) demonstrate a close affinity between AP and present-day Koryaks, Itelmen and Chukchis, as well as with Native Americans.

For both AP and Native Americans, ANS ancestry appears more closely related to Mal’ta than Yana, therefore rejecting a direct contribution of Yana to later AP or Native American groups.

Lake Baikal Neolithic – Bronze Age

(…) the newly reported genomes from Ust’Belaya and recently published neighbouring Neolithic and Bronze Age sites show a succession of three distinct genetic ancestries over a ~6 ky time span. The earliest individuals show predominantly East Asian ancestry, closely related to the ancient individuals from DGC. In the early Bronze Age (BA), we observe a resurgence of AP ancestry (up to ~50% ancestry fraction), as well as influence of West Eurasian Steppe ANE ancestry represented by the early BA individuals from Afanasievo in the Altai region (~10%) This is consistent with previous reports of gene flow from an unknown ANE-related source into Lake Baikal hunter-gatherers.

Our results suggest a southward expansion of AP as a possible source, which is also consistent with the replacement of Y chromosome lineages observed at Lake Baikal, from predominantly haplogroup N in the Neolithic to haplogroup Q in the BA. Finally, the most recent individual from Ust’Belaya, dated to ~600 years ago, falls along the Neosiberian cline, similar to the ~760 year-old ‘Young Yana’ individual from northeastern Siberia, demonstrating the widespread distribution of Neosiberian ancestry in the most recent epoch.

Genetic structure of ancient northeast Siberians. PCA of ancient individuals projected onto a set of modern Eurasian and American individuals. Abbreviations in group labels: UP – Upper Palaeolithic; LP – Late Palaeolithic; M – Mesolithic; EN – Early Neolithic; MN – Middle Neolithic; LN – Late Neolithic; EBA – Early Bronze Age; LBA – Late Bronze Age; IA – Iron Age; PE – Paleoeskimo; MED – Medieval

Finland Saami

At the western edge of northern Eurasia, genetic and strontium isotope data from ancient individuals at the Levänluhta site documents the presence of Saami ancestry in Southern Finland in the Late Holocene 1.5 kya. This ancestry component is currently limited to the northern fringes of the region, mirroring the pattern observed for AP ancestry in northeastern Siberia. However, while the ancient Saami individuals harbour East Asian ancestry, we find that this is better modelled by DGC rather than AP, suggesting that AP influence was likely restricted to the eastern side of the Urals. Comparison of ancient Finns and Saami with their present-day counterparts reveals additional gene flow over the past 1.6 kya, with evidence for West Eurasian admixture into modern Saami. The ancient Finn from Levänluhta shows lower Siberian ancestry than modern Finns .

EDIT (27 OCT 2018): By comparing the three, I see these are samples published already (at least two) in Lamnidis et al. (2018), but here with added (1) specific radiocarbon dates, (2) comparison with Neosiberian populations and (3) strontium isotope analyses.

Finnish_IA (ca. 350 AD) is probably a Saami-speaking individual, just like the Saami_IA with newly reported radiocarbon dates from Levänluhta ca. 400-600 AD (since Fennic peoples were then likely around the Gulf of Finland).

The conflicting strontium isotope data on marine dietary resources on certain samples from the supplementary material hint at possible external origin of the diet of some of the previously reported (and possibly one newly reported) Saami Iron Age individuals, from some 25-30 km. to the northwest through the river up to hundreds of km. to the southwest of Levänluhta (i.e. the whole coast of the Bothnian Sea). It is unclear why they would prefer an origin of the dietary source in southern Baltic regions instead of some km. to the west, though, unless that’s what they want to propose based on the sample’s admixture…

The coast of the Bothnian Sea (=the northern part of the Baltic Sea, between Sweden and Finland) lay only 25-30 km to the northwest, and accessible to the Iron Age people of the Levänluhta region via the Kyrönjoki river. (…) For individual JA2065/DA236, the low 87Sr/86Sr value (0.71078) would imply an exceptionally heavy reliance on Baltic Sea resources. The δ13C and δ15N values of the individual are near comparable (especially considering within-Baltic latitudinal gradients in δ13C; Torniainen et al. 2017) to the δ13C and δ15N values of a Middle Neolithic population on the Baltic island of Gotland (Eriksson, 2004) interpreted to have subsisted primarily on seals.

These new data on the samples give us some more information than what we already had, because the early date of Finnish_IA implies that there was few East Asian admixture (if any at all) in west Finland during the Roman Iron Age, which pushes still farther forward in time the expected appearance of Siberian ancestry among Saamic (first) and Fennic populations (later). It is unclear whether this East Asian ancestry found in Finnish_IA is actually related to DGC, or it is rather related to the ENA-like ancestry found already in Baltic hunter-gatherers (i.e. in some EHG samples from Karelia), for which Baikal_EN is a good proxy in Lazaridis et al. (2018).

Since Bronze Age and Iron Age samples from Estonia show more Baltic_HG drift compared to Corded Ware samples, it is likely that this supposedly DGC-related ancestry (here considered part of the ‘Siberian ancestry’) is actually an EHG-related ENA component of north-east European hunter-gatherers, with whom Finno-Saamic peoples admixed during the expansion of the Corded Ware culture into Finland.

The paper finds thus increased (probably the actual) Siberian ancestry in modern Finns compared to this Iron Age Saami individual. Coupled with the later Saami Iron Age samples, from between one to three centuries later – showing the start of Siberian ancestry influx – , we can begin to establish when the expansion of Siberian ancestry happened in central Finland, and thus quite likely when the Saami began to expand to the north and east and admix with Palaeo-Laplandic peoples.

Admixture modelling using qpAdm. Maps showing locations and ancestry proportions of ancient (left) and modern (right) groups.

One sample of haplogroup N1a1a1a1a4a1-M1982, Yana_MED, is found in the Arctic region (north-eastern Yakutia) ca. 1100 AD. Since it is derived from N1a1a1a1a-L392, it might be a surprise for some to find it in a clearly non-Uralic speaking environment at the same time other subclades of this haplogroup were admixing in the west with well-established Finno-Saamic, Volga-Finnic, Ugric, and Samoyedic populations…

On the growing doubts that these data – contradicting the CWC=IE theory – are creating among geneticists (from the supplementary materials):

NOTE. This paper comes from the Copenhagen group, also signed by Kristiansen, one of today’s strongest supporters of this connection

The Proto-Saami language evolved in southern Finland and Karelia in the Early Iron Age, an area now host to Finnish and the closely related Karelian, but with Saami toponyms showing that the latter two languages are intrusive here (Saarikivi 2004). Saami-speaking populations are thought to have retreated to Lapland during the Middle Iron Age (300–800 AD), where it diverged into the modern Saami dialects. Genetically, the northward retreat of the Saami language correlates with the documented decrease of Saami ancestry in Southern Finland between the Iron Age and the modern period (cf. Lamnidis et al. 2018).

On the way to Lapland, the Saami replaced at least two linguistically obscure groups. This can be inferred from 1) an influx of non-Uralic loanwords into Proto-Saami in the Finnish Lakeland area, and 2) an influx of non-Uralic, non-Germanic words into Saami dialects in Lapland (Aikio 2012). Both of these borrowing events imply contact with non-Saami-speaking groups, e.g. non-Uralic-speaking hunter-gatherers that may have left a genetic and linguistic footprint on modern Saami populations.

The linguistic prehistory of Finland thus does not allow for a straightforward interpretation of the genetic data. The detection of East Asian ancestry in the genetically Saami individual is indicative of a population movement from the east (cf. Lamnidis et al. 2018, Rootsi et al. 2007), one that given the affinities with the ~7.6 ky old individuals from the Devil’s Gate Cave may have been a western extension of the Neosiberian turnover. However, it remains unclear whether this gene flow should be associated with the arrival of Uralic speakers, thus providing further support for a Uralic homeland in Eastern Eurasia, or with an earlier immigration of pre-Uralic, so-called “Paleo-Lakelandic” groups.

I think the genetic interpretation is already straightforward, though. We had a sneak peek at how this late admixture with non-Uralians (mainly Palaeo-Lakelandic and Palaeo-Laplandic peoples from Lovozero and related asbestos ware cultures) is going to unfold among expanding Saami-speaking populations thanks to Lamnidis et al. (2018):

PCA plot of 113 Modern Eurasian populations, with individuals from this study projected on the principal components. Uralic speakers are highlighted in light purple. Image modified from Lamnidis et al. (2018)

Also, still no trace of R1a in far East Asia (reported as M17 ca. 5300 BC near Lake Baikal by Moussa et al. 2016), so I still have doubts about my previous assessment that R1a split into M17 (and thus also M417) in Siberia, with those expanding hunter-gatherer pottery.


The genetic makings of South Asia – IVC as Proto-Dravidian


Review (behind paywall) The genetic makings of South Asia, by Metspalu, Monda, and Chaubey, Current Opinion in Genetics & Development (2018) 53:128-133.

Interesting excerpts (emphasis mine):

(…) the spread of agriculture in Europe was a result of the demic diffusion of early Anatolian farmers, it was discovered that the spread of agriculture to South Asia was mediated by a genetically completely different farmer population in the Zagros mountains in contemporary Iran (IF). The ANI-ASI cline itself was interpreted as a mixture of three components genetically related to Iranian agriculturalists, Onge and Early and Middle Bronze Age Steppe populations (Steppe_EMBA).

The first ever autosomal aDNA from South Asia comes from Northern Pakistan (Swat Valley, early Iron Age). This study presented altogether 362 aDNA samples from the broad South and Central Asia and contributes substantially to our understanding of the evolutionary past of South and Central Asia. The study redefines the three genetic strata that form the basis of the Indian Cline. The Indus Periphery (IP) component is composed of (varying proportions of): first, IF, second, Ancient Ancestral South Asians (AASI), which represents an ancient branch of human genetic variation in Asia arising from a population split contemporaneous with the splits of East Asian, Onge and Australian Aboriginal ancestors and third, West_Siberian Hunter gatherers (WS_HG).

The authors argue that IP could have formed the genetic base of the Indus Valley Civilization (IVC). Upon the collapse of the IVC IP contributes to the formation of both ASI and ANI. ASI is formed as IP admixes further with AASI. ANI in turn forms when IP admixes with the incoming Middle and Late Bronze Age Steppe (Steppe_MLBA) component, (rather than the Steppe_EMBA groups suggested earlier)

A sketch of the peopling history of South Asia. Depicting the full complexity of available reconstructions is not attempted. Placing of population labels does not indicate precise geographic location or range of the population in question. Rather we aim to highlight the essentials of the recent advancements in the field. We divide the scenario into three time horizons: Panels (a) before 10 000 BCE (pre agriculture era.); (b) 10 000 BCE to 3000 BCE (agriculture era) and (c) 3000 BCE to prehistoric era/modern era. (iron age).

Dating of the arrival of the Austro-Asiatic speakers in South Asia-based on Y chromosome haplogroup O2a1-M95 expansion estimates yielded dates between 3000 and 2000 BCE [30]. However, admixture LD decay-based approach on genome-wide data suggests the admixture between South Asian and incoming Austro-Asiatic speakers occurred slightly later between 1800 and 0 BCE (Tätte et al. submitted). It is interesting that while the mtDNA variants of the Mundas are completely South Asian, the Y chromosome variation is dominated at >60% by haplogroup O2a which is phylogeographically nested in East Asian-specific paternal lineages.

In India, the speakers of Tibeto-Burman (TB) languages live in the Seven Sisters States in Northeast India and in the very north of the country. Genetically they show a clear East Asian origin and around 20% of subsequent admixture with South Asians within the last 1000 years.The genetic flavour of East Asia in TB is different from that in Munda speakers as the best surrogates for the East Asian admixing component are contemporary Han Chinese.

I found the simplistic migration maps especially interesting to illustrate ancient population movements. The emergence of EHG is supposed to involve a WHG:ANE cline, though, and this isn’t clear from the map. Also, there is new information on what may be at the origin of WHG and Anatolian hunter-gatherers.

From the recent Reich’s session on South Asia at ISBA 8:

– Tale of three clines, with clear indication that “Indus Periphery” samples drawn from an already-cosmopolitan and heterogeneous world of variable ASI & Iranian ancestry. (I know how some people like to pore over these pictures – so note red dots = just dummy data for illustration.)
– Some more certainty about primary window of steppe ancestry injection into S. Asia: 2000-1500 BC
Alexander M. Kim

Featured image: map of South Asian languages from


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.


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.