Corded Ware ancestry in North Eurasia and the Uralic expansion

uralic-clines-nganasan

Now that it has become evident that Late Repin (i.e. Yamnaya/Afanasevo) ancestry was associated with the migration of R1b-L23-rich Late Proto-Indo-Europeans from the steppe in the second half of the the 4th millennium BC, there’s still the question of how R1a-rich Uralic speakers of Corded Ware ancestry expanded , and how they spread their languages throughout North Eurasia.

Modern North Eurasians

I have been collecting information from the supplementary data of the latest papers on modern and ancient North Eurasian peoples, including Jeong et al. (2019), Saag et al. (2019), Sikora et al. (2018), or Flegontov et al. (2019), and I have tried to add up their information on ancestral components and their modern and historical distributions.

Fortunately, the current obsession with simplifying ancestry components into three or four general, atemporal groups, and the common use of the same ones across labs, make it very simple to merge data and map them.

Corded Ware ancestry

There is no doubt about the prevalent ancestry among Uralic-speaking peoples. A map isn’t needed to realize that, because ancient and modern data – like those recently summarized in Jeong et al. (2019) – prove it. But maps sure help visualize their intricate relationship better:

natural-modern-srubnaya-ancestry
Natural neighbor interpolation of Srubnaya ancestry among modern populations. See full map.
kriging-modern-srubnaya-ancestry
Kriging interpolation of Srubnaya ancestry among modern populations. See full map

Interestingly, the regions with higher Corded Ware-related ancestry are in great part coincident with (pre)historical Finno-Ugric-speaking territories:

uralic-languages-modern
Modern distribution of Uralic languages, with ancient territory (in the Common Era) labelled and delimited by a red line. For more information on the ancient territory see here.

Edit (29/7/2019): Here is the full Steppe_MLBA ancestry map, including Steppe_MLBA (vs. Indus Periphery vs. Onge) in modern South Asian populations from Narasimhan et al. (2018), apart from the ‘Srubnaya component’ in North Eurasian populations. ‘Dummy’ variables (with 0% ancestry) have been included to the south and east of the map to avoid weird interpolations of Steppe_MLBA into Africa and East Asia.

modern-steppe-mlba-ancestry2
Natural neighbor interpolation of Steppe MLBA-like ancestry among modern populations. See full map.

Anatolia Neolithic ancestry

Also interesting are the patterns of non-CWC-related ancestry, in particular the apparent wedge created by expanding East Slavs, which seems to reflect the intrusion of central(-eastern) European ancestry into Finno-Permic territory.

NOTE. Read more on Balto-Slavic hydrotoponymy, on the cradle of Russians as a Finno-Permic hotspot, and about Pre-Slavic languages in North-West Russia.

natural-modern-lbk-en-ancestry
Natural neighbor interpolation of LBK EN ancestry among modern populations. See full map.
kriging-modern-lbk-en-ancestry
Kriging interpolation of LBK EN ancestry among modern populations. See full map

WHG ancestry

The cline(s) between WHG, EHG, ANE, Nganasan, and Baikal HG are also simplified when some of them excluded, in this case EHG, represented thus in part by WHG, and in part by more eastern ancestries (see below).

modern-whg-ancestry
Natural neighbor interpolation of WHG ancestry among modern populations. See full map.
kriging-modern-whg-ancestry
Kriging interpolation of WHG ancestry among modern populations. See full map.

Arctic, Tundra or Forest-steppe?

Data on Nganasan-related vs. ANE vs. Baikal HG/Ulchi-related ancestry is difficult to map properly, because both ancestry components are usually reported as mutually exclusive, when they are in fact clearly related in an ancestral cline formed by different ancient North Eurasian populations from Siberia.

When it comes to ascertaining the origin of the multiple CWC-related clines among Uralic-speaking peoples, the question is thus how to properly distinguish the proportions of WHG-, EHG-, Nganasan-, ANE or BaikalHG-related ancestral components in North Eurasia, i.e. how did each dialectal group admix with regional groups which formed part of these clines east and west of the Urals.

The truth is, one ought to test specific ancient samples for each “Siberian” ancestry found in the different Uralic dialectal groups, but the simplistic “Siberian” label somehow gets a pass in many papers (see a recent example).

Below qpAdm results with best fits for Ulchi ancestry, Afontova Gora 3 ancestry, and Nganasan ancestry, but some populations show good fits for both and with similar proportions, so selecting one necessarily simplifies the distribution of both.

Ulchi ancestry

modern-ulchi-ancestry
Natural neighbor interpolation of Ulchi ancestry among modern populations. See full map.
kriging-modern-ulchi-ancestry
Kriging interpolation of Ulchi ancestry among modern populations. See full map.

ANE ancestry

natural-modern-ane-ancestry
Natural neighbor interpolation of ANE ancestry among modern populations. See full map.
kriging-modern-ane-ancestry
Kriging interpolation of ANE ancestry among modern populations. See full map.

Nganasan ancestry

modern-nganasan-ancestry
Natural neighbor interpolation of Nganasan ancestry among modern populations. See full map.
kriging-modern-nganasan-ancestry
Kriging interpolation of Nganasan ancestry among modern populations. See full map.

Iran Chalcolithic

A simplistic Iran Chalcolithic-related ancestry is also seen in the Altaic cline(s) which (like Corded Ware ancestry) expanded from Central Asia into Europe – apart from its historical distribution south of the Caucasus:

modern-iran-chal-ancestry
Natural neighbor interpolation of Iran Neolithic ancestry among modern populations. See full map.
kriging-modern-iran-neolithic-ancestry
Kriging interpolation of Iran Chalcolithic ancestry among modern populations. See full map.

Other models

The first question I imagine some would like to know is: what about other models? Do they show the same results? Here is the simplistic combination of ancestry components published in Damgaard et al. (2018) for the same or similar populations:

NOTE. As you can see, their selection of EHG vs. WHG vs. Nganasan vs. Natufian vs. Clovis of is of little use, but corroborate the results from other papers, and show some interesting patterns in combination with those above.

EHG

damgaard-modern-ehg-ancestry
Natural neighbor interpolation of EHG ancestry among modern populations, data from Damgaard et al. (2018). See full map.
damgaard-kriging-ehg-ancestry
Kriging interpolation of EHG ancestry among modern populations. See full map.

Natufian ancestry

damgaard-modern-natufian-ancestry
Natural neighbor interpolation of Natufian ancestry among modern populations, data from Damgaard et al. (2018). See full map.
damgaard-kriging-natufian-ancestry
Kriging interpolation of Natufian ancestry among modern populations. See full map.

WHG ancestry

damgaard-modern-whg-ancestry
Natural neighbor interpolation of WHG ancestry among modern populations, data from Damgaard et al. (2018). See full map.
damgaard-kriging-whg-ancestry
Kriging interpolation of WHG ancestry among modern populations. See full map.

Baikal HG ancestry

damgaard-modern-baikalhg-ancestry
Natural neighbor interpolation of Baikal hunter-gatherer ancestry among modern populations, data from Damgaard et al. (2018). See full map.
damgaard-kriging-baikal-hg-ancestry
Kriging interpolation of Baikal HG ancestry among modern populations. See full map.

Ancient North Eurasians

Once the modern situation is clear, relevant questions are, for example, whether EHG-, WHG-, ANE, Nganasan-, and/or Baikal HG-related meta-populations expanded or became integrated into Uralic-speaking territories.

When did these admixture/migration events happen?

How did the ancient distribution or expansion of Palaeo-Arctic, Baikalic, and/or Altaic peoples affect the current distribution of the so-called “Siberian” ancestry, and of hg. N1a, in each specific population?

NOTE. A little excursus is necessary, because the calculated repetition of a hypothetic opposition “N1a vs. R1a” doesn’t make this dichotomy real:

  1. There was not a single ethnolinguistic community represented by hg. R1a after the initial expansion of Eastern Corded Ware groups, or by hg. N1a-L392 after its initial expansion in Siberia:
  2. Different subclades became incorporated in different ways into Bronze Age and Iron Age communities, most of which without an ethnolinguistic change. For example, N1a subclades became incorporated into North Eurasian populations of different languages, reaching Uralic- and Indo-European-speaking territories of north-eastern Europe during the late Iron Age, at a time when their ancestral origin or language in Siberia was impossible to ascertain. Just like the mix found among Proto-Germanic peoples (R1b, R1a, and I1)* or among Slavic peoples (I2a, E1b, R1a)*, the mix of many Uralic groups showing specific percentages of R1a, N1a, or Q subclades* reflect more or less recent admixture or acculturation events with little impact on their languages.

*other typically northern and eastern European haplogroups are also represented in early Germanic (N1a, I2, E1b, J, G2), Slavic (I1, G2, J) and Finno-Permic (I1, R1b, J) peoples.

ananino-culture-new
Map of archaeological cultures in north-eastern Europe ca. 8th-3rd centuries BC. [The Mid-Volga Akozino group not depicted] Shaded area represents the Ananino cultural-historical society. Fading purple arrows represent likely stepped movements of subclades of haplogroup N for centuries (e.g. Siberian → Ananino → Akozino → Fennoscandia [N-VL29]; Circum-Arctic → forest-steppe [N1, N2]; etc.). Blue arrows represent eventual expansions of Uralic peoples to the north. Modified image from Vasilyev (2002).

The problem with mapping the ancestry of the available sampling of ancient populations is that we lack proper temporal and regional transects. The maps that follow include cultures roughly divided into either “Bronze Age” or “Iron Age” groups, although the difference between samples may span up to 2,000 years.

NOTE. Rough estimates for more external groups (viz. Sweden Battle Axe/Gotland_A for the NW, Srubna from the North Pontic area for the SW, Arctic/Nganasan for the NE, and Baikal EBA/”Ulchi-like” for the SE) have been included to offer a wider interpolated area using data already known.

Bronze Age

Similar to modern populations, the selection of best fit “Siberian” ancestry between Baikal HG vs. Nganasan, both potentially ± ANE (AG3), is an oversimplification that needs to be addressed in future papers.

Corded Ware ancestry

bronze-age-corded-ware-ancestry
Natural neighbor interpolation of Srubnaya ancestry among Bronze Age populations. See full map.

Nganasan-like ancestry

bronze-age-nganasan-like-ancestry
Natural neighbor interpolation of Nganasan-like ancestry among Bronze Age populations. See full map.

Baikal HG ancestry

bronze-age-baikal-hg-ancestry
Natural neighbor interpolation of Baikal Hunter-Gatherer ancestry among Bronze Age populations. See full map.

Afontova Gora 3 ancestry

bronze-age-afontova-gora-ancestry
Natural neighbor interpolation of Afontova Gora 3 ancestry among Bronze Age populations. See full map.

Iron Age

Corded Ware ancestry

Interestingly, the moderate expansion of Corded Ware-related ancestry from the south during the Iron Age may be related to the expansion of hg. N1a-VL29 into the chiefdom-based system of north-eastern Europe, including Ananyino/Akozino and later expanding Akozino warrior-traders around the Baltic Sea.

NOTE. The samples from Levänluhta are centuries older than those from Estonia (and Ingria), and those from Chalmny Varre are modern ones, so this region has to be read as a south-west to north-east distribution from the Iron Age to modern times.

iron-age-corded-ware-ancestry
Natural neighbor interpolation of Srubnaya ancestry among Iron Age populations. See full map.

Baikal HG-like ancestry

The fact that this Baltic N1a-VL29 branch belongs in a group together with typically Avar N1a-B197 supports the Altaic origin of the parent group, which is possibly related to the expansion of Baikalic ancestry and Iron Age nomads:

iron-age-baikal-ancestry
Natural neighbor interpolation of Baikal HG ancestry among Iron Age populations. See full map.

Nganasan-like ancestry

The dilution of Nganasan-like ancestry in an Arctic region featuring “Siberian” ancestry and hg. N1a-L392 at least since the Bronze Age supports the integration of hg. N1a-Z1934, sister clade of Ugric N1a-Z1936, into populations west and east of the Urals with the expansion of Uralic languages to the north into the Tundra region (see here).

The integration of N1a-Z1934 lineages into Finnic-speaking peoples after their migration to the north and east, and the displacement or acculturation of Saami from their ancestral homeland, coinciding with known genetic bottlenecks among Finns, is yet another proof of this evolution:

iron-age-nganasan-ancestry
Natural neighbor interpolation of Nganasan ancestry among Iron Age populations. See full map.

WHG ancestry

Similarly, WHG ancestry doesn’t seem to be related to important population movements throughout the Bronze Age, which excludes the multiple North Eurasian populations that will be found along the clines formed by WHG, EHG, ANE, Nganasan, Baikal HG ancestry as forming part of the Uralic ethnogenesis, although they may be relevant to follow later regional movements of specific populations.

iron-age-whg-ancestry
Natural neighbor interpolation of WHG ancestry among Iron Age populations. See full map.

Conclusion

It seems natural that people used to look at maps of haplogroup distribution from the 2000s, coupled with modern language distributions, and would try to interpret them in a certain way, reaching thus the wrong conclusions whose consequences are especially visible today when ancient DNA keeps contradicting them.

In hindsight, though, assuming that Balto-Slavs expanded with Corded Ware and hg. R1a, or that Uralians expanded with “Siberian” ancestry and hg. N1a, was as absurd as looking at maps of ancestry and haplogroup distribution of ancient and modern Native Americans, trying to divide them into “Germanic” or “Iberian”…

The evolution of each specific region and cultural group of North Eurasia is far from being clear. However, the general trend speaks clearly in favour of an ancient, Bronze Age distribution of North Eurasian ancestry and haplogroups that have decreased, diluted, or become incorporated into expanding Uralians of Corded Ware ancestry, occasionally spreading with inter-regional expansions of local groups.

Given the relatively recent push of Altaic and Indo-European languages into ancestral Uralic-speaking territories, only the ancient Corded Ware expansion remains compatible with the spread of Uralic languages into their historical distribution.

Related

A Song of Sheep and Horses, revised edition, now available as printed books

cover-song-sheep-and-horses

As I said 6 months ago, 2019 is a tough year to write a blog, because this was going to be a complex regional election year and therefore a time of political promises, hence tenure offers too. Now the preliminary offers have been made, elections have passed, but the timing has slightly shifted toward 2020. So I may have the time, but not really any benefit of dedicating too much effort to the blog, and a lot of potential benefit of dedicating any time to evaluable scientific work.

On the other hand, I saw some potential benefit for publishing texts with ISBNs, hence the updates to the text and the preparation of these printed copies of the books, just in case. While Spain’s accreditation agency has some hard rules for becoming a tenured professor, especially for medical associates (whose years of professional experience are almost worthless compared to published peer-reviewed papers), it is quite flexible in assessing one’s merits.

However, regional and/or autonomous entities are not, and need an official identifier and preferably printed versions to evaluate publications, such as an ISBN for books. I took thus some time about a month ago to update the texts and supplementary materials, to publish a printed copy of the books with Amazon. The first copies have arrived, and they look good.

series-song-sheep-horses-cover

Corrections and Additions

Titles
I have changed the names and order of the books, as I intended for the first publication – as some of you may have noticed when the linguistic book was referred to as the third volume in some parts. In the first concept I just wanted to emphasize that the linguistic work had priority over the rest. Now the whole series and the linguistic volume don’t share the same name, and I hope this added clarity is for the better, despite the linguistic volume being the third one.

Uralic dialects
I have changed the nomenclature for Uralic dialects, as I said recently. I haven’t really modified anything deeper than that, because – unlike adding new information from population genomics – this would require for me to do a thorough research of the most recent publications of Uralic comparative grammar, and I just can’t begin with that right now.

Anyway, the use of terms like Finno-Ugric or Finno-Samic is as correct now for the reconstructed forms as it was before the change in nomenclature.

west-east-uralic-schema

Mediterranean
The most interesting recent genetic data has come from Iberia and the Mediterranean. Lacking direct data from the Italian Peninsula (and thus from the emergence of the Etruscan and Rhaetian ethnolinguistic community), it is becoming clearer how some quite early waves of Indo-Europeans and non-Indo-Europeans expanded and shrank – at least in West Iberia, West Mediterranean, and France.

Finno-Ugric
Some of the main updates to the text have been made to the sections on Finno-Ugric populations, because some interesting new genetic data (especially Y-DNA) have been published in the past months. This is especially true for Baltic Finns and for Ugric populations.

ananino-culture-new

Balto-Slavic
Consequently, and somehow unsurprisingly, the Balto-Slavic section has been affected by this; e.g. by the identification of Early Slavs likely with central-eastern populations dominated by (at least some subclades of) hg. I2a-L621 and E1b-V13.

Maps
I have updated some cultural borders in the prehistoric maps, and the maps with Y-DNA and mtDNA. I have also added one new version of the Early Bronze age map, to better reflect the most likely location of Indo-European languages in the Early European Bronze Age.

As those in software programming will understand, major changes in the files that are used for maps and graphics come with an increasing risk of additional errors, so I would not be surprised if some major ones would be found (I already spotted three of them). Feel free to communicate these errors in any way you see fit.

bronze-age-early-indo-european
European Early Bronze Age: tentative langage map based on linguistics, archaeology, and genetics.

SNPs
I have selected more conservative SNPs in certain controversial cases.

I have also deleted most SNP-related footnotes and replaced them with the marking of each individual tentative SNP, leaving only those footnotes that give important specific information, because:

  • My way of referencing tentative SNP authors did not make it clear which samples were tentative, if there were more than one.
  • It was probably not necessary to see four names repeated 100 times over.
  • Often I don’t really know if the person I have listed as author of the SNP call is the true author – unless I saw the full SNP data posted directly – or just someone who reposted the results.
  • Sometimes there are more than one author of SNPs for a certain sample, but I might have added just one for all.
ancient-dna-all
More than 6000 ancient DNA samples compiled to date.

For a centralized file to host the names of those responsible for the unofficial/tentative SNPs used in the text – and to correct them if necessary -, readers will be eventually able to use Phylogeographer‘s tool for ancient Y-DNA, for which they use (partly) the same data I compiled, adding Y-Full‘s nomenclature and references. You can see another map tool in ArcGIS.

NOTE. As I say in the text, if the final working map tool does not deliver the names, I will publish another supplementary table to the text, listing all tentative SNPs with their respective author(s).

If you are interested in ancient Y-DNA and you want to help develop comprehensive and precise maps of ancient Y-DNA and mtDNA haplogroups, you can contact Hunter Provyn at Phylogeographer.com. You can also find more about phylogeography projects at Iain McDonald’s website.

Graphics
I have also added more samples to both the “Asian” and the “European” PCAs, and to the ADMIXTURE analyses, too.

I previously used certain samples prepared by amateurs from BAM files (like Botai, Okunevo, or Hittites), and the results were obviously less than satisfactory – hence my criticism of the lack of publication of prepared files by the most famous labs, especially the Copenhagen group.

Fortunately for all of us, most published datasets are free, so we don’t have to reinvent the wheel. I criticized genetic labs for not releasing all data, so now it is time for praise, at least for one of them: thank you to all responsible at the Reich Lab for this great merged dataset, which includes samples from other labs.

NOTE. I would like to make my tiny contribution here, for beginners interested in working with these files, so I will update – whenever I have time – the “How To” sections of this blog for PCAs, PCA3d, and ADMIXTURE.

-iron-age-europe-romans
Detail of the PCA of European Iron Age populations. See full versions.

ADMIXTURE
For unsupervised ADMIXTURE in the maps, a K=5 is selected based on the CV, giving a kind of visual WHG : NWAN : CHG/IN : EHG : ENA, but with Steppe ancestry “in between”. Higher K gave worse CV, which I guess depends on the many ancient and modern samples selected (and on the fact that many samples are repeated from different sources in my files, because I did not have time to filter them all individually).

I found some interesting component shared by Central European populations in K=7 to K=9 (from CEU Bell Beakers to Denmark LN to Hungarian EBA to Iberia BA, in a sort of “CEU BBC ancestry” potentially related to North-West Indo-Europeans), but still, I prefer to go for a theoretically more correct visualization instead of cherry-picking the ‘best-looking’ results.

Since I made fun of the search for “Siberian ancestry” in coloured components in Tambets et al. 2018, I have to be consistent and preferred to avoid doing the same here…

qpAdm
In the first publication (in January) and subsequent minor revisions until March, I trusted analyses and ancestry estimates reported by amateurs in 2018, which I used for the text adding my own interpretations. Most of them have been refuted in papers from 2019, as you probably know if you have followed this blog (see very recent examples here, here, or here), compelling me to delete or change them again, and again, and again. I don’t have experience from previous years, although the current pattern must have been evidently repeated many times over, or else we would be still talking about such previous analyses as being confirmed today…

I wanted to be one step ahead of peer-reviewed publications in the books, but I prefer now to go for something safe in the book series, rather than having one potentially interesting prediction – which may or may not be right – and ten huge mistakes that I would have helped to endlessly redistribute among my readers (online and now in print) based on some cherry-picked pairwise comparisons. This is especially true when predictions of “Steppe“- and/or “Siberian“-related ancestry have been published, which, for some reason, seem to go horribly wrong most of the time.

I am sure whole books can be written about why and how this happened (and how this is going to keep happening), based on psychology and sociology, but the reasons are irrelevant, and that would be a futile effort; like writing books about glottochronology and its intermittent popularity due to misunderstood scientist trends. The most efficient way to deal with this problem is to avoid such information altogether, because – as you can see in the current revised text – they wouldn’t really add anything essential to the content of these books, anyway.

Continue reading

Official site of the book series:
A Song of Sheep and Horses: eurafrasia nostratica, eurasia indouralica

Sintashta diet and economy based on domesticated animal products and wild resources

indo-iranian-sintashta-uralic-migrations

New paper (behind paywall) Bronze Age diet and economy: New stable isotope data from the Central Eurasian steppes (2100-1700 BC), by Hanks et al. J. Arch. Sci (2018) 97:14-25.

Interesting excerpts (emphasis mine):

Previous research at KA-5 was carried out by A. V. Epimakhov in 1994–1995 and 2002–2003 and resulted in the excavation of three Sintashta culture barrows (kurgans) that produced 35 burial pits and a reported 100 skeletons (Epimakhov, 2002, 2005; Epimakhov et al., 2005; Razhev and Epimakhov, 2004). Seven AMS radiocarbon dates on human remains from the cemetery yielded a date range of 2040–1730 cal. BC (2 sigma), which placed the cemetery within the Sintashta phase of the regional Bronze Age (Hanks et al., 2007). Twelve recently obtained AMS radiocarbon dates, taken from short-lived wood and charcoal species recovered from the Kamennyi Ambar settlement, have provided a date range of 2050–1760 cal. BC (2 sigma). Importantly, these dates confirm the close chronological relationship between the settlement and cemetery for the Middle Bronze Age phase and discount the possibility of a freshwater reservoir effect influencing the earlier dating of the human remains from the Kamennyi Ambar 5 cemetery (Epimakhov and Krause, 2013).

Sintashta cemeteries frequently yield fewer than six barrow complexes and the number of skeletons recovered represents a fraction of the total population that would have inhabited the settlements (Judd et al., 2018; Johnson and Hanks, 2012). Scholars have suggested that only members of higher status were afforded interment in these cemeteries and that principles of social organization structured placement of individuals within central or peripheral grave pits (Fig. 2) (Koryakova and Epimakhov, 2007: 75–81). In comparison with other Sintashta cemeteries that have been excavated, KA-5 provides one of the largest skeletal inventories currently available for study.

kamenniy-ambar
Upper – plan of Kamennyi Ambar settlement and cemetery; Lower – plan views of Kurgan 2 and Kurgan 4 from KA-5 Cemetery (kurgan plans redrawn from Epimakhov, 2005: 10, 79).

The KA-5 (MBA), Bestamak (MBA) and Lisakovsk (LBA) datasets exhibited a wide range of δ13C and δ15N values for both humans and herbivores (Figs. 5 and 6 & Table 8). This diversity in isotopic signals may be evident for a variety of reasons. For example, the range of values may be associated with a broad spectrum of C3 and C4 plant diversity in the ancient site biome or herbivore grazing patterns that included more diverse environmental niche areas in the microregion around the sampled sites. Herders also may have chosen to graze animals in niche areas due to recognized territorial boundaries between settlements and concomitant patterns of mobility. Importantly, data from Bolshekaragansky represents humans with lower δ15N values that are more closely associated with δ15N values of the sampled domestic herbivores (Fig. 6). When the archaeological evidence from associated settlement sites is considered, Bolshekaragansky, Bestamak, Lisakovsk and KA-5 have been assumed to represent populations that shared similar forms of pastoral subsistence economies with significant dietary reliance upon domesticated herbivore meat and milk. Human diets have δ13C values closely related to those of local herbivores in terms of the slope of the trendline and range of values (Fig. 6). Comparatively, the cemetery of Bolshekaragansky (associated with the Arkaim settlement) reflects individuals with trend lines closer to those of cattle and caprines and may indicate a stronger reliance on subsistence products from these species with less use of wild riverine and terrestrial resources. The site of Čiča is significantly different with elevated human δ15N isotopic values and depleted δ13C values indicative of a subsistence regime more closely associated with the consumption of freshwater resources, such as fish. The stable isotopic data in this instance is strongly supported by zooarchaeological evidence recovered from the Čiča settlement and also is indicative of significant diachronic changes from the LBA phases through the Iron Age (Fig. 6).

kamenniy-ambar-isotopic-chicha-lisakovsk-bestamark
Regional analysis and comparison of stable isotope results from humans (adults) and animals recovered from MBA and LBA cemeteries in the Southern Urals (Kamennyi Ambar 5 & Bolshekaragansky) northwestern Kazakhstan (Liskovsk & Bestamak) and southwestern Siberia (Čiča).

Conclusion

(…) The isotopic results from KA-5, and recent botanical and archaeological studies from the Kamennyi Ambar settlement, have not produced any evidence for the production or use of domesticated cereals. While this does not definitively answer the question as to whether Sintashta populations engaged in agriculture and/or utilized agricultural products, it does call into serious question the ubiquity of such practices across the region and correlates well with recent archaeological, bioarchaeological, and isotopic studies of human and animal remains from the Southwestern Urals region and Samara Basin (Anthony et al., 2016; Schulting and Richards, 2016). The results substantiate a broader spectrum subsistence diet that in addition to the use of domesticated animal products also incorporated wild flora, wild fauna and fish species. These findings further demonstrate the need to draw on multiple methods and datasets for the reconstruction of late prehistoric subsistence economies in the Eurasian steppes. When possible, this should include datasets from both settlements and associated cemeteries.

Variability in subsistence practices in the central steppes region has been highlighted by other scholars and appears to be strongly correlated with local environmental conditions and adaptations. More comprehensive isotopic studies of human, animal and fish remains are of fundamental importance to achieve more robust and empirically substantiated reconstructions of local biomes and to aid the refinement of regional and micro-regional economic subsistence models. This will allow for a fuller understanding of key diachronic shifts within dietary trends and highlight regional variation of such practices. Ultimately, this will more effectively index the diverse social and environmental variables that contributed to late prehistoric lifeways and the economic strategies employed by these early steppe communities.

Social organization of Sintashta-Petrovka

Interesting to remember now the recent article by Chechushkov et al. (2018) about the social stratificaton in Sintashta-Petrovka, and how it must have caused the long-lasting, peaceful admixture process that led to the known almost full replacement of R1b-L23 (mostly R1b-Z2103) by R1a-Z645 (mostly R1a-Z93) subclades in the North Caspian steppe, coinciding with the formation of the Proto-Indo-Iranian community and language (read my thoughts on this after Damgaard et al. 2018).

Here is another relevant excerpt from Chechushkov et al. (2018), translated from Russian:

settlement-kamenniy-ambar
The map of the settlement of Kamennyi Ambar with excavations, soil cores, and test pits. Legend: a — cuts of the sides of ravines; b — test pits of 2015—2017; c — test pits of 2004; d — soil-science samples with a cultural layer; e — soil-science samples without cultural layer; f — borders of archaeological sites (interpretation of the plan of magnetic anomalies); g — boundaries of excavated structures (1, 2, 4, 5, 7 — Sintashta-Petrovka culture; 3, 6 — Srubnaya-Alakul’ culture).

The analysis suggests that the Sintashta-Petrovka societies had a certain degree of social stratification, expressed both in selective funeral rituals and in the significant difference in lifestyle between the elite and the immediate producers of the product. The data obtained during the field study suggest that the elite lived within the fortifications, while a part of the population was outside their borders, on seasonal sites, and also in stationary non-fortified settlements. Probably, traces of winter settlements can be found near the walls, while the search for summer ones is a task of a separate study. From our point of view, the elite of the early complex societies of the Bronze Age of the Eurasian steppe originated as a response to environmental challenges that created risks for cattle farming. The need to adapt the team to the harsh and changing climatic conditions created a precedent in which the settled collectives of pastoralists – hunter-gatherers could afford the content and magnificent posthumous celebration of people and their families who were not engaged in the production or extraction of an immediate product. In turn, representatives of this social group directed their efforts to the adoption of socially significant decisions, the organization of collective labor in the construction of settlement-shelters and risked their lives, acting as military leaders and fighters.

Thus, in Bronze Age steppe societies, the formation, development and decline of social complexity are directly related to the intensity of pastoralism and the development of new territories, where collectives had to survive in part a new ecological niche. At the same time, some members of the collective took upon themselves the organization of the collective’s life, receiving in return a privileged status. As soon as the conditions of the environment and management changed, the need for such functions was virtually eliminated, as a result of which the privileged members of society dissolved into the general mass, having lost their lifetime status and the right to be allocated posthumously.

Also interesting for the MLBA haplogroup bottleneck in the region is the paper by Judd et al. (2017) about fast life history in Early Indo-Iranian territories.

On the arrival of haplogroup N1c1-L392

Regarding the special position of the Chicha-1 samples in the change of diet and economy during the Iron Age, it is by now well known that haplogroup N must have arrived quite late to North-East Europe, and possibly not linked with the expansion of Siberian ancestry – or linked only with some waves of Siberian ancestry in the region, but not all of them. See Lamnidis et al. (2018) for more on this.

Also, the high prevalence of haplogroup N among Fennic and Siberian (Samoyedic) peoples is not related: while the latter reflects probably the native (Palaeo-Siberian) population that acquired their Uralic branch during the MLBA expansions associated with Corded Ware groups, the former points to the expansion of Fennic peoples into Saamic territory (i.e. after the Fenno-Saamic split) as the most likely period of expansion of N1c1-L392 subclades (see known recent bottlenecks among Finns, and on Proto-Finnic dialectalization).

Probably related to these late incomers are the ancient DNA samples from the Sargat culture during the Iron Age, which show the arrival of N subclades in the region, replacing most – but not all – R1a lineages (see Pilipenko et al. (2017)). Regarding the site of Chicha-1, the following are relevant excerpts about the cultural situation that could have allowed for such stepped, diachronic admixture events in Northern Eurasia, from the paper Stages in the settlement history of Chicha-1: The Results of ceramic analysis, by Molodin et al. (2008):

The stratigraphic data allows us to make the following inference: originally, the settlement was inhabited by people bearing the Late Irmen culture. Later, the people of the Baraba trend of the Suzgun culture arrived at the site (Molodin, Chemyakina, 1984: 40–62). The Baraba-Suzgun pottery demonstrates features similar to what has been reported from the sites of the transitional Bronze to Iron Age culture in the pre-taiga and taiga zones in the Irtysh basin (Potemkina, Korochkova, Stefanov, 1995; Polevodov, 2003). The major morphological types are slightly and well-profiled pots with a short throat. (…)

chicha-irmen-tagar-baraba-forest-siberian
Map showing the location of Chicha-1.

During the following stage of development of the site, the Chicha population increased with people who practiced cultures others than those noted in earlier collections. The ceramic materials from layer 5 provide data on possible relationships. In addition to migrants from northwestern regions practicing the Suzgun culture, there were people bearing the Krasnoozerka culture. Available data also suggests that people from the northern taiga region with the Atlym culture visited the site.

However, people from the west and southwest represent the greatest migration to the region under study. In all likelihood they moved from the northern forest-steppe zone of modern Kazakhstan and practiced the Berlik culture. The spatial distribution analysis of the Chicha-1 site suggests that the Berlik population was rather large. The Berlik people formed a single settlement with the indigenous Late Irmen people and apparently waged certain common economic activities, but preserved their own ethnic and cultural specificity (Molodin, Parzinger, 2006: 49–55). Judging by the data on the chronological sequence of deposited artifacts, migration took place roughly synchronously, hence Chicha-1 became a real cultural and economic center.

(…) In sum, the noted distribution of ceramics over the culture-bearing horizons suggests that beginning with layer 5, traditions of ceramic manufacture described above were practiced, hence the relevant population inhabited the site. Apparently, there were two predominant traditions: the local Late Irmen cultural tradition and the Berlik tradition, which was brought by the immigrants. The Late Irmen people mostly populated the citadel, while the Berlik immigrants inhabited the areas to the east and the north of the citadel.

The stratigraphic data also suggest that the Early Sargat ceramics emerged at the site likely as a part of the Late Irmen tradition (…) Early Sargat ceramics is apparently linked with the Late Irmen tradition. Artifacts associated with the Sargat culture proper have been found in several areas of Chicha-1 (e.g., in excavation area 16). However, the Sargat people appeared at the site after it had been abandoned by its previous inhabitants, and had eventually become completely desolated. This happened no earlier than the 6th cent. BC, possibly in the 5th cent. BC (in fact, the radiocarbon dates for that horizon are close to the turn of the Christian era).

Related

On the Maykop – Upper Mesopotamia cultural province, distinct from the steppe

caucasus-europe

New paper (behind paywall) The Production of Thin‐Walled Jointless Gold Beads from the Maykop Culture Megalithic Tomb of the Early Bronze Age at Tsarskaya in the North Caucasus: Results of Analytical and Experimental Research, by Trifonov et al. Archaeometry (2018)

Interesting excerpts (emphasis mine):

In 1898, two megalithic tombs containing graves of a local social elite dated to the Early Bronze Age were discovered by N. I. Veselovsky near the village of Tsarskaya (modern Novosvobodnaya, Republic of Adygeya) (Fig. 1 (a)) (Baye 1900, 43–59; IAC 1901, 33–8; Sagona 2018, 281–97).

Radiocarbon dates place both tombs within the Novosvobodnaya phase of the Maykop culture, between c. 3200 and 2900 BC (Trifonov et al. 2017). Along with the human remains (one adult individual was interred in each dolmen), the tombs yielded rich funerary offerings, including artefacts made of gold, silver and semi-precious stones. (…) This paper presents results of a technical analysis of just one type of artefact, from kurgan 2 at Tsarskaya: thin-walled jointless beads made from gold.

caucasus-beads-mesopotamia-sumeria
(a) A map of the Caucasus and part of Western Asia, showing the locations of sites mentioned in the text: 1, Tsarskaya (modern Novosvobodnaya); 2, Maykop; 3, Staromyshastovskaya; 4, Andryukovskaya; 5, Psebaiskaya; 6, Inozemtsevo; 7, Kudakhurt; 8, Soyuq Bulaq; 9, Sé Girdan; 10, Tepe Gawra. (b) The string of thin-walled jointless gold beads, silver and carnelian beads from the dolmen in kurgan 2 at Tsarskaya, Western Caucasus (1898).

Ever since M. I. Rostovtzeff noted a stylistic similarity between Maykop art and Sumerian art (Rostovtzeff 1920) and M. V. Andreeva described this phenomenon within a broad cultural and chronological context (Andreeva 1977), new archaeological studies have only extended this picture of a vast cultural province that appeared between the Caucasus and the northern fringe of Western Asia (Trifonov 1987). The discovery of the Leyla-Tepe culture (Narimanov 1987) and Maykop-type kurgans in Azerbaijan (Lyonnet et al. 2008) and adjacent Iran (Muscarella 1969, 1971, 2003; Trifonov 2000) has confirmed the spatial and temporal unity of this phenomenon as a precondition for free circulation of cultural patterns and technical innovations across vast areas of the Caucasus and Western Asia. Jewellery made of gemstones and precious metals, primarily gold, was probably one such innovation.

Attempts to demarcate the historical region where the Maykop culture emerged and developed have emphasized the role of Upper Mesopotamia in the development of the Sumerian civilization and the definition of a northern centre of urbanization, independent from the centres of the south (Rothman 2002; Oats et al. 2007). The turn of the fourth millennium BC saw the development of various cultural traditions in south-east Anatolia, north-east Syria and north-west Iran; on the northern fringe, these traditions manifested themselves through the Maykop culture. Perhaps it is no coincidence that the first high-status burials containing gold and gemstone jewellery (including carnelian, turquoise and lapis lazuli) appear in these northern, rather than southern, centres in the first quarter of 4000 BC (e.g., Tepe Gawra, graves 109, 110) (Piasnall 2002). With regard to funeral rites and stylistic characteristics of jewellery pieces, these graves have many parallels with early Maykop burials (Munchaev 1975, 329; Trifonov 1987, 20).

It still remains unclear if the goldsmiths of Upper Mesopotamia mastered the technique of making thin-walled jointless beads. The gold beads from Tepe Gawra are described as spherical or ball-shaped, but their maximum diameter (5–8mm) always exceeds the length of the bore (3–4mm) (Tobler 1950, 89, 199, pl. LV, a). On the whole, these measurements are consistent with the proportions and sizes of some Maykop beads.(…)

It is quite possible that a distinctive technique of making thin-walled jointless beads from gold was a regional technological development of Maykop culture goldsmiths, within a wider tradition of Near East metalwork, as a type of production regulated by ritual beliefs (Gell 1992; Benzel 2013).

These deep-rooted Near East traditions of ritualization of the production and use of jewellery pieces made of gold, silver and gemstones in the Maykop culture, on the one hand, maintained familiar canons of ritual behaviour and, on the other, made perception of sophisticated symbolism of gemstones more difficult for neighbouring cultures with different living standards, levels of social development and value systems to understand. The jewellery traditions of the Maykop culture had no successors in the Caucasus or the adjacent steppes. In the third millennium BC, the goldsmiths of Europe and Asia had to reinvent the technique of making thin-walled jointless gold beads from scratch (Born et al. 2009).


Also interesting is Holocene environmental history and populating of mountainous Dagestan (Eastern Caucasus, Russia), by Ryabogina et al., Quaternary International (2018).

caucasus-dagestan-climate-population
The combination of Holocene environment changes and the settlement of the territory of Dagestan.

Related excerpts, about the climate of an adjacent region of the Caucasus before, during, and after the Maykop culture:

The 7th millennium BC featured a warm and arid climate, so that time corresponds to the steppe landscapes in the final stage of the Mesolithic. It is likely that the formation of a producing economy in the mountainous zone of Dagestan gradually emerged against this background. In the Neolithic period, the area remained almost treeless, as it was still warm and quite dry. However, archaeological data indicates that long-term settlements with well-developed farming spread in the mountainous zone around 6200-5500 BC.

The beginning of increasing humidity and the appearance of deciduous forests corresponds to the early Chalcolithic period of the Eastern Caucasus. It is the most poorly studied period in the history of this region. Covering a time span of 2000 years, this period was the least saturated by archaeological sites. At the start of this period, only the stands of herdsman in the mountain zone are known, dating to the second half of the 6th millennium BC (Gadgiev, 1991). It is still not clear whether the mountains were not settled in such a favorable climatic stage. The uncertainty may be due to the fact that people have chosen other ecological niches, or it could be we simply do not have data due to the insufficient archaeological survey of the territory. It is surprising that the turn to drier climate and the reduction of deciduous forests in the inner mountainous part of Dagestan, the large, long-term settlements like Ginchi emerge with pronounced specialization in agriculture (Fig. 7 panel (2)) (Gadgiev, 1991).

After the dry climate, simultaneously with cooling, the subsequent spread of pine forests coincides with the beginning of expansion of Kura-Araxes culture from the territory of Georgia through Chechnya to the mountainous Dagestan. Debates on the impact of past climate on Kura-Araxes societies in Transcaucasus have a long history (for the comprehensive review see, for example, Connor and Kvavadze, 2014 and references therein). In general, it is clear that after 3000 BC, forest cover in most areas of the Kura-Araxes region in the Transcaucasia reached its maximum extent in the Holocene (Connor and Kvavadze, 2014). However, at the same time lakes in Central Anatolia began to dry out and Caspian Sea levels fell (Roberts et al. 2011; Leroy et al. 2013), and arid conditions were identified in mountainous Dagestan in the 4th millennium. Clearly the regional moisture balance shifted in the Eastern Caucasus only in the late 4th to early 3rd millennium BC (this study). The only available radiocarbon dating of Dagestan confirms that the agricultural settlements of the Early Bronze Age appear not in the middle of the 4th millennium BC, but in the early 3rd millennium BC; that is not earlier than the stage of increasing moistening and the appearance of pine forests.

See also:

Recent Africa origin with hybridization, and back to Africa 70,000 years ago

mtdna-l-out-of-africa-expansion

Open access Carriers of mitochondrial DNA macrohaplogroup L3 basal lineages migrated back to Africa from Asia around 70,000 years ago, by Cabrera et al. BMC Evol Biol (2018) 18(98).

Abstract (emphasis mine):

Background

The main unequivocal conclusion after three decades of phylogeographic mtDNA studies is the African origin of all extant modern humans. In addition, a southern coastal route has been argued for to explain the Eurasian colonization of these African pioneers. Based on the age of macrohaplogroup L3, from which all maternal Eurasian and the majority of African lineages originated, the out-of-Africa event has been dated around 60-70 kya. On the opposite side, we have proposed a northern route through Central Asia across the Levant for that expansion and, consistent with the fossil record, we have dated it around 125 kya. To help bridge differences between the molecular and fossil record ages, in this article we assess the possibility that mtDNA macrohaplogroup L3 matured in Eurasia and returned to Africa as basal L3 lineages around 70 kya.

Results

The coalescence ages of all Eurasian (M,N) and African (L3 ) lineages, both around 71 kya, are not significantly different. The oldest M and N Eurasian clades are found in southeastern Asia instead near of Africa as expected by the southern route hypothesis. The split of the Y-chromosome composite DE haplogroup is very similar to the age of mtDNA L3. An Eurasian origin and back migration to Africa has been proposed for the African Y-chromosome haplogroup E. Inside Africa, frequency distributions of maternal L3 and paternal E lineages are positively correlated. This correlation is not fully explained by geographic or ethnic affinities. This correlation rather seems to be the result of a joint and global replacement of the old autochthonous male and female African lineages by the new Eurasian incomers.

Conclusions

These results are congruent with a model proposing an out-of-Africa migration into Asia, following a northern route, of early anatomically modern humans carrying pre-L3 mtDNA lineages around 125 kya, subsequent diversification of pre-L3 into the basal lineages of L3, a return to Africa of Eurasian fully modern humans around 70 kya carrying the basal L3 lineages and the subsequent diversification of Eurasian-remaining L3 lineages into the M and N lineages in the outside-of-Africa context, and a second Eurasian global expansion by 60 kya, most probably, out of southeast Asia. Climatic conditions and the presence of Neanderthals and other hominins might have played significant roles in these human movements. Moreover, recent studies based on ancient DNA and whole-genome sequencing are also compatible with this hypothesis.

homo-sapiens-neandertal-denisovan

You can also read the recent interesting open access review How did Homo sapiens evolve? by Julia Galway-Witham, Chris Stringer, Science (2018) 360:6395 1296-1298.

Related:

Demographic history and genetic adaptation in the Himalayan region

Open access Demographic history and genetic adaptation in the Himalayan region inferred from genome-wide SNP genotypes of 49 populations, by Arciero et al. Mol. Biol. Evol (2018), accepted manuscript (msy094).

Abstract (emphasis mine):

We genotyped 738 individuals belonging to 49 populations from Nepal, Bhutan, North India or Tibet at over 500,000 SNPs, and analysed the genotypes in the context of available worldwide population data in order to investigate the demographic history of the region and the genetic adaptations to the harsh environment. The Himalayan populations resembled other South and East Asians, but in addition displayed their own specific ancestral component and showed strong population structure and genetic drift. We also found evidence for multiple admixture events involving Himalayan populations and South/East Asians between 200 and 2,000 years ago. In comparisons with available ancient genomes, the Himalayans, like other East and South Asian populations, showed similar genetic affinity to Eurasian hunter-gatherers (a 24,000-year-old Upper Palaeolithic Siberian), and the related Bronze Age Yamnaya. The high-altitude Himalayan populations all shared a specific ancestral component, suggesting that genetic adaptation to life at high altitude originated only once in this region and subsequently spread. Combining four approaches to identifying specific positively-selected loci, we confirmed that the strongest signals of high-altitude adaptation were located near the Endothelial PAS domain-containing protein 1 (EPAS1) and Egl-9 Family Hypoxia Inducible Factor 1 (EGLN1) loci, and discovered eight additional robust signals of high-altitude adaptation, five of which have strong biological functional links to such adaptation. In conclusion, the demographic history of Himalayan populations is complex, with strong local differentiation, reflecting both genetic and cultural factors; these populations also display evidence of multiple genetic adaptations to high-altitude environments.

himalayan-map
Population samples analysed in this study. A. Map of South and East Asia, highlighting the four regions examined, and the colour assigned to each. B. Samples from the Tibetan Plateau. C.Samples from Nepal. D. Samples from Bhutan and India. The circle areas are proportional to the sample sizes. The three letter population codes in B-D are defined in supplementary table S1.

Relevant excerpts:

Genetic affinity to ancestral populations

We explored the genetic affinity between the Himalayan populations and five ancient genomes using f3-outgroup statistics. Himalayans show greater affinity to Eurasian hunter-gatherers (MA-1, a 24,000- year-old Upper Palaeolithic Siberian), and the related Bronze Age Yamnaya, than to European farmers (5,500-4,800 years ago; Fig. 5A) or to European hunter-gatherers (La Braña, 7,000 years ago; Fig. 5B), like other South and East Asian populations. We further explored the affinity of Himalayan populations by comparing them with the 45,000-year-old Upper Palaeolithic hunter-gatherer (Ust’-Ishim) and each of MA-1, La Braña, or Yamnaya. Himalayan individuals cluster together with other East Asian populations and show equal distance from Ust’-Ishim and the other ancient genomes, probably because Ust’-Ishim belongs to a much earlier period of time (supplementary fig. S15). We also explored genetic affinity between modern Himalayan populations and five ancient Himalayans (3,150 1,250 years old) from Nepal. The ancient individuals cluster together with modern Himalayan populations in a worldwide PCA (supplementary fig. S16), and the f3-outgroup statistics show modern high-altitude populations have the closest affinity with these ancient Himalayans, suggesting that these ancient individuals could represent a proxy for the first populations residing in the region (supplementary fig. S17 and supplementary table S4). Finally, we explored the genetic affinity of Himalayan samples with the archaic genomes of Denisovans and Neanderthals (Skoglund and Jakobsson 2011), and found that they show a similar sharing pattern with Denisovans and Neanderthals to the other South and East Asian populations. Individuals belonging to four Nepalese, one Cambodian, and three Chinese populations show the highest Denisovan sharing (after populations from Australia and Papua New Guinea) but these values are not significantly greater than other South and East Asian populations (supplementary figs. S18 and S19).

himalayan-pca
Genetic structure of the Himalayan region populations from analyses using unlinked SNPs. A. PCA of the Himalayan and HGDP-CEPH populations. Each dot represents a sample, coded by region as indicated. The Himalayan region samples lie between the HGDP-CEPH East Asian and South Asian samples on the right-hand side of the plot. B. PCA of the Himalayan populations alone. Each dot represents a sample, coded by country or region as indicated. Most samples lie on an arc between Bhutanese and Nepalese samples; Toto (India) are seen as extreme outlier in the bottom left corner, while Dhimal (Nepal) and Bodo (India) also form outliers.

NOTE. The variance explained in the PCA graphics seems to be too high. This happened recently also with the Damgaard et al. (2018) papers (see here the comment by Iosif Lazaridis).

Similarities and differences between high-altitude Himalayan

The most striking example is provided by the Toto from North India, an isolated tribal group with the lowest genetic diversity of the Himalayan populations examined here, indicated by the smallest long-term Ne (supplementary fig. S5), and a reported census size of 321 in 1951 (Mitra 1951), although their numbers have subsequently increased. Despite this extreme substructure, shared common ancestry among the high-altitude populations (Fig. 2C and Fig. 3) can be detected, and the Nepalese in general are distinguished from the Bhutanese and Tibetans (Fig. 2C) and they also cluster separately (Fig. 3). In a worldwide context, they share an ancestral component with South Asians (supplementary fig. S2). On the other hand, the Tibetans do not show detectable population substructure, probably due to a much more recent split in comparison with the other populations (Fig. 2C and supplementary fig. S6). The genetic similarity between the high-altitude populations, including Tibetans, Sherpa and Bhutanese, is also supported by their clustering together on the phylogenetic tree, the PCA generated from the co-ancestry matrix generated by fineSTRUCTURE (supplementary fig. S10 and S11), the lack of statistical significance for most of the D-statistics tests (Yoruba, Han; high-altitude Himalayan 1, high-altitude Himalayan 2), and the absence of correlation between the increased genetic affinity to lowland East Asians and the spatial location of the Himalayan populations (supplementary figs. S12 and S13). Together, these results suggest the presence of a single ancestral population carrying advantageous variants for high-altitude adaptation that separated from lowland East Asians, and then spread and diverged into different populations across the Himalayan region. (…)

Recent admixture events

himalayan-admixture
Genetic structure of the Himalayan region populations from analyses using unlinked SNPs. C. ADMIXTURE (K values of 2 to 6, as indicated) analysis of the Himalayan samples. Note that most increases in the value of K result in single population being distinguished. Population codes in C are defined in supplementary table S1.

Himalayan populations show signatures of recent admixture events, mainly with South and East Asian populations as well as within the Himalayan region itself. Newar and Lhasa show the oldest signature of admixture, dated to between 2,000 and 1,000 years ago. Majhi and Dhimal display signatures of admixture within the last 1,000 years. Chetri and Bodo show the most recent admixture events, between 500 and 200 years ago (Fig. 4, supplementary tables S3). The comparison between the genetic tree and the linguistic association of each Himalayan population highlights the agreement between genetic and linguistic sub-divisions, in particular in the Bhutanese and Tibetan populations. Nepalese populations show more variability, with genetic sub-clusters of populations belonging to different linguistic affiliations (Fig. 3B). Modern high-altitude Himalayans show genetic affinity with ancient genomes from the same region (supplementary fig. S17), providing additional support for the idea of an ancient high-altitude population that spread across the Himalayan region and subsequently diverged into several of the present-day populations. Furthermore, Himalayan populations show a similar pattern of allele sharing with Denisovans as other South-East Asian populations (supplementary fig. S18 and S19). Overall, geographical isolation, genetic drift, admixture with neighbouring populations and linguistic subdivision played important roles in shaping the genetic variability we see in the Himalayan region today.

Related:

Ancient genomes document multiple waves of migration in south-east Asian prehistory

southeast-asia-reich

Open access preprint at bioRxiv Ancient genomes document multiple waves of migration in Southeast Asian prehistory, by Lipson, Cheronet, Mallick, et al. (2018).

Abstract (emphasis mine):

Southeast Asia is home to rich human genetic and linguistic diversity, but the details of past population movements in the region are not well known. Here, we report genome-wide ancient DNA data from thirteen Southeast Asian individuals spanning from the Neolithic period through the Iron Age (4100-1700 years ago). Early agriculturalists from Man Bac in Vietnam possessed a mixture of East Asian (southern Chinese farmer) and deeply diverged eastern Eurasian (hunter-gatherer) ancestry characteristic of Austroasiatic speakers, with similar ancestry as far south as Indonesia providing evidence for an expansive initial spread of Austroasiatic languages. In a striking parallel with Europe, later sites from across the region show closer connections to present-day majority groups, reflecting a second major influx of migrants by the time of the Bronze Age.

south-east-asian-admixture-graph
Schematics of admixture graph results. (A) Wider phylogenetic context. (B) Details of the Austroasiatic clade. Branch lengths are not to scale, and the order of the two events on the Nicobarese lineage in (B) is not well determined (Supplementary Text).

Featured image, from the article: “Overview of samples. (A) Locations and dates of ancient individuals. Overlapping positions are shifted slightly for visibility. (B) PCA with East and Southeast Asians. We projected the ancient samples onto axes computed using the present-day populations (with the exception of Mlabri, who were projected instead due to their large population-speci c drift). Present-day colors indicate language family affiliation: green, Austroasiatic; blue, Austronesian; orange, Hmong-Mien; black, Sino-Tibetan; magenta, Tai-Kadai.”

See also:

Ancestral heterogeneity of ancient Eurasians

Josif Lazaridis tweets about an interesting preprint at BioRxiv (eclipsed by today’s Nature papers), Ancestral heterogeneity of ancient Eurasians, by Daniel Shriner.

Abstract:

Supervised clustering or projection analysis is a staple technique in population genetic analysis. The utility of this technique depends critically on the reference panel. The most commonly used reference panel in the analysis of ancient DNA to date is based on the Human Origins array. We previously described a larger reference panel that captures more ancestries on the global level. Here, I reanalyzed DNA data from 279 ancient Eurasians using our reference panel, finding substantially more ancestral heterogeneity than has been reported. This reanalysis provides evidence against a resurgence of Western hunter-gatherer ancestry in the Middle to Late Neolithic and evidence for a common ancestor of farmers characterized by Western Asian ancestry, a transition of the spread of agriculture from demic to cultural diffusion, at least two migrations between the Pontic-Caspian steppes and Bronze Age Europe, and a sub-Saharan African component in Natufians that localizes to present-day southern Ethiopia.

phylogeography-admixture
Admixture bar plots showing projections of ancient Eurasians (Steppe peoples on the left, Bronze Age Europeans on the right) onto 21 ancestries. The 3 proportions are the raw output from ADMIXTURE. The 21 ancestral components are Southern 4 African (dark orchid), Central African (magenta), West-Central African (brown), Eastern 5 African (orange), Omotic (yellow), Northern African (purple), South Indian (slate blue), Kalash 6 (black), Japanese (red), Sino-Tibetan (green), Southeastern Asian (coral), Northern Asian 7 (aquamarine), Amerindian (gray), Oceanian (salmon), Southern European (dark olive green), 8 Northern European (blue), Western Asian (white), Arabian (light gray), Western African 9 (tomato), Circumpolar (pink), and Southern Asian (dark goldenrod).

Excerpt (emphasis mine)

Early to Middle Bronze Age Steppe Peoples
Third, we considered the Eurasian steppe peoples (See figure). The Eneolithic Samara sample had 64.4% Northern European, 18.2% Southern Asian, 8.8% Circumpolar, 4.3% Amerindian, and 4.3% Southern European ancestries. The 27 Early to Middle Bronze Age steppe individuals (Yamnaya from Kalmykia, Yamnaya from Samara, Afanasievo, Poltavka, and Potapovka) averaged 54.7% Northern European, 27.8% Southern Asian, 7.9% Southern European, 4.7% Kalash, 4.2% Amerindian, and 0.8% Western Asian ancestries. We included the Potapovka sample here because the sum of absolute differences in ancestry was greater post-Potapovka rather than post-Poltavka. The increases in Southern Asian and Southern European ancestries do not fit with a European hunter-gatherer source and more broadly do not fit with any of the samples, suggesting an unknown source population. Currently, Southern Asian ancestry co-localizes with Y DNA haplogroup L and correlates with Indo-Iranian languages.

Although there are no L haplogroups in any of these Early to Middle Bronze Age steppe individuals, the correlation with Indo-Iranian languages strengthens the connection between Early to Middle Bronze Age steppe peoples and the introduction of Indo-European languages into Europe. In the Early to Middle Bronze Age steppe peoples, 83.3% of Y DNA haplogroups were R1b and 85.2% of mitochondrial haplogroups were H, J, T, or U. Thus, Northern European ancestry was primarily associated with R1b in these peoples, rather than with I2 as in the European hunter-gatherers, while the mitochondrial lineages were more diverse than in the European hunter-gatherers but less diverse than in the Early Neolithic peoples.

It is an interesting new approach, in that it takes into account more than just adxmiture components and PCA to assess ancestral populations.

As simplistic and wrong some conclusions may seem from your point of view, you have to take into account what Iain Mathieson had to (sadly) expressly state recently:

Related: