Corded Ware ancestry in North Eurasia and the Uralic expansion


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 neighbor interpolation of Srubnaya ancestry among modern populations. See full map.
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:

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.

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 neighbor interpolation of LBK EN ancestry among modern populations. See full map.
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).

Natural neighbor interpolation of WHG ancestry among modern populations. See full map.
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

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

ANE ancestry

Natural neighbor interpolation of ANE ancestry among modern populations. See full map.
Kriging interpolation of ANE ancestry among modern populations. See full map.

Nganasan ancestry

Natural neighbor interpolation of Nganasan ancestry among modern populations. See full map.
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:

Natural neighbor interpolation of Iran Neolithic ancestry among modern populations. See full map.
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.


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

Natufian ancestry

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

WHG ancestry

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

Baikal HG ancestry

Natural neighbor interpolation of Baikal hunter-gatherer ancestry among modern populations, data from Damgaard et al. (2018). See full map.
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.

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

Natural neighbor interpolation of Srubnaya ancestry among Bronze Age populations. See full map.

Nganasan-like ancestry

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

Baikal HG ancestry

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

Afontova Gora 3 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.

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:

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:

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.

Natural neighbor interpolation of WHG ancestry among Iron Age populations. See full map.


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.


Iron Age Tocharians of Yamnaya ancestry from Afanasevo show hg. R1b-M269 and Q1a1

New open access Ancient Genomes Reveal Yamnaya-Related Ancestry and a Potential Source of Indo-European Speakers in Iron Age Tianshan, by Ning et al. Current Biology (2019).

Interesting excerpts (emphasis mine, changes for clarity):

Here, we report the first genome-wide data of 10 ancient individuals from northeastern Xinjiang. They are dated to around 2,200 years ago and were found at the Iron Age Shirenzigou site. We find them to be already genetically admixed between Eastern and Western Eurasians. We also find that the majority of the East Eurasian ancestry in the Shirenzigou individuals is related to northeastern Asian populations, while the West Eurasian ancestry is best presented by ∼20% to 80% Yamnaya-like ancestry. Our data thus suggest a Western Eurasian steppe origin for at least part of the ancient Xinjiang population. Our findings furthermore support a Yamnaya-related origin for the now extinct Tocharian languages in the Tarim Basin, in southern Xinjiang.


The dominant mtDNA lineages of the Shirenzigou people are commonly found in modern and ancient West Eurasian populations, such as U4, U5, and H, while they also have East Eurasian-specific haplogroups A, D4, and G3, preliminarily documenting admixed ancestry from eastern and western Eurasia.

The admixture profile is also shown on the paternal Y chromosome side that 4 out of 6 males in Shirenzigou (Figure S2) belong to the West Eurasian-specific haplogroup R1b (n = 2) and East Eurasian-specific haplogroup Q1a (n = 2), the former is predominant in ancient Yamnaya and nearly 100% in Afanasievo, different from the Middle and Late Bronze Age Steppe groups (Steppe_MLBA) such as Andronovo, [Potapovka], Srubnaya, and Sintashta whose Y chromosomal haplogroup is mainly R1a.



We first carried out principal component analysis (PCA) to assess the genetic affinities of the ancient individuals qualitatively by projecting them onto present-day Eurasian variation (Figure 2). We observed a distinct separation between East and West Eurasians. Our ancient Shirenzigou samples and present-day populations from Central Asia and northwestern China form a genetic cline from East to West in the first PC. The distribution of Shirenzigou samples on the cline is relatively scattered with two major clusters, one being closer to modern-day Uygurs and Kazakhs and the other being closer to recently published ancient Saka and Huns from the Tianshan in Kazakhstan (…).

We applied a formal admixture test using f3 statistics in the form of f3 (Shirenzigou; X, Y) where X and Y are worldwide populations that might be the genetic sources for the Shirenzigou individuals. We observed the most significant signals of admixture in the Shirenzigou samples when using Yamnaya_Samara or Srubnaya as the West Eurasian source and some Northern Asians or Koreans as the East Eurasian source (Table S1). We also plotted the outgroup f3 statistics in the form of f3 (Mbuti; X, Anatolia_Neolithic) and f3 (Mbuti; X, Kostenki14) to visualize the allele sharing between population X and Anatolian farmers. As shown in Figure S3, the Steppe_MLBA populations including Srubnaya, Andronovo, and Sintashta were shifted toward farming populations compared with Yamnaya groups and the Shirenzigou samples. This observation is consistent with ADMIXTURE analysis that Steppe_MLBA populations have an Anatolian and European farmer-related component that Yamnaya groups and the Shirenzigou individuals do not seem to have. The analysis consistently suggested Yamnaya-related Steppe populations were the better source in modeling the West Eurasian ancestry in Shirenzigou.

PCA and ADMIXTURE for Shirenzigou Samples. Modified from the original to include in black squares samples related to Yamnaya.

Genetic Composition of Iron Age Shirenzigou Individuals

We continued to use qpAdm to estimate the admixture proportions in the Shirenzigou samples by using different pairs of source populations, such as Yamnaya_Samara, Afanasievo, Srubnaya, Andronovo, BMAC culture (Bustan_BA and Sappali_Tepe_BA) and Tianshan_Hun as the West Eurasian source and Han, Ulchi, Hezhen, Shamanka_EN as the East Eurasian source. In all cases, Yamnaya, Afanasievo, or Tianshan_Hun always provide the best model fit for the Shirenzigou individuals, while Srubnaya, Andronovo, Bustan_BA and Sappali_Tepe_BA only work in some cases. The Yamnaya_Samara or Afanasievo-related ancestry ranges from ∼20% to 80% in different Shirenzigou individuals, consistent with the scattered distribution on the East-West cline in the PCA


(…) we then modeled Shirenzigou as a three-way admixture of Yamnaya_Samara, Ulchi (or Hezhen) and Han to infer the source from the East Eurasia side that contributed to Shirenzigou. We found the Ulchi or Hezhen and Han-related ancestry had a complicated and unevenly distribution in the Shirenzigou samples. The most Shirenzigou individuals derived the majority of their East Eurasian ancestry from Ulchi or Hezhen-related populations, while the following two individuals M820 and M15-2 have more Han related than Ulchi/Hezhen-related ancestry.

One important question remains, though: how and when did these Proto-Tocharian speakers migrate from the Afanasevo culture in the Altai into the Tarim Basin? The traditional answer, now more likely than ever, is through the Chemurchek culture. See e.g. A re-analysis of the Qiemu’erqieke (Shamirshak) cemeteries, Xinjiang, China, by Jia and Betts JIES (2010) 38(4).

Also, given the apparent lack of (extra farmer ancestry that characterizes) Corded Ware ancestry, if the results were already suspicious before, how likely are now the published R1a(xZ93) and/or radiocarbon dates of the Xiaohe mummies from Li et al. (2010, 2015)? Because, after all, one should have expected in such a late date a generalized admixture with neighbouring Srubna/Andronovo-like populations.


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.


Y-DNA haplogroups of Tuvinian tribes show little effect of the Mongol expansion


Open access Estimating the impact of the Mongol expansion upon the gene pool of Tuvans, by Balanovskaya et al., Vavilov Journal of genetics and breeding (2018), 22(5):611-619.

Abstract (emphasis mine):

With a view to trace the Mongol expansion in Tuvinian gene pool we studied two largest Tuvinian clans – those in which, according to data of humanities, one could expect the highest Central Asian ancestry, connected with the Mongol expansion. Thus, the results of Central Asian ancestry in these two clans component may be used as upper limit of the Mongol influence upon the Tuvinian gene pool in a whole. According to the data of 59 Y-chromosomal SNP markers, the haplogroup spectra in these Tuvinian tribal groups (Mongush, N = 64, and Oorzhak, N = 27) were similar. On average, two-thirds of their gene pools (63 %) are composed by North Eurasian haplogroups (N*, N1a2, N3a, Q) connected with autochtonous populations of modern area of Tuvans. The Central Asian haplogroups (C2, O2) composed less then fifth part (17 %) of gene pools of the clans studied. The opposite ratio was revealed in Mongols: there were 10 % North Eurasian haplogroups and 75 % Central Asian haplogroups in their gene pool. All the results derived – “genetic portraits”, the matrix of genetic distances, the dendrogram and the multidimensional scaling plot, which mirror the genetic connections between Tuvinian clans and populations of South Siberia and East Asia, demonstrated the prominent similarity of the Tuvinian gene pools with populations from and Khakassia and Altai. It could be therefore assumed that Tuvinian clans Mongush and Oorzhak originated from autochtonous people (supposedly, from the local Samoyed and Kets substrata). The minor component of Central Asian haplogroups in the gene pool of these clans allowed to suppose that Mongol expansion did not have a significant influence upon the Tuvinan gene pool at a whole.


Interesting excerpts:

Haplogroup C2 peaks in Central Asia (Wells et al., 2001; Zerial et al., 2003), though its variants are abundant in other peoples of Siberia and Far East. For instance, in one of Buryat clans, namely Ekhirids, hg C2 frequency is 88 % (Y-base); in Kazakhs from different regions of Kazakhstan, total occurrence of hg C2 variants averages between 17 and 81 % (Abilev et al., 2012; Zhabagin et al., 2013, 2014, 2017), in populations of the Amur River (such as Nanais, Negidals, Nivkhs, Ulchs) – between 40 and 65 %, in Evenks – up to 68 % (Y-base), in Kyrgyz people of Pamir-Alay – up to 22 %, correspondingly; of all Turkic peoples of Altai, relatively high hg C2 frequency (16 %) is detected only in Telengits (Balanovskaya et al., 2014; Balaganskaya et al., 2011a, 2016). In Tuvinian clans under the study, hg C2 frequency is rather low – 19 % in Mongush and 11 % in Oorzhak, while in Mongols it makes up almost two thirds of the entire gene pool an comprises different genetic lines (subhaplogroups).

Y-chromosomal haplogroup spectra in gene pools of Tuvinian Oorzhak and Mongush clans and of the neighboring populations of South Siberia and Central Asia.

Haplogroup N is abundant all over North Eurasia from Scandinavia to Far East (Rootsi et al., 2007). The study on whole Y-chromosome sequencing conducted with participation of our group (Ilumäe et al., 2016) subdivided this haplogroup into several branches with their regional distribution. In gene pools of the Tuvans involved, hg N was represented by two sub-clades, namely N1a2 and N3a.

Sub-clade N1a2 peaks in populations of West Siberia (in Nganasans, frequency is 92 %) and South Siberia (in Khakas 34 %, in Tofalars 25 %) (Y-base). In Tuvans, N1a2 occurrence is nearly 16 % in Mongush and 15 % in Oorzhak clans, respectively, while in Mongols, the frequency is three times less (5 %). Hg N1a2 is supposed to display the impact of the Samoyedic component to the gene pool of Tuvinian clans (Kharkov et al., 2013).

Sub-clade N3a is major in the Oorzhak clan comprising almost half of the gene pool (45 %); it is represented by two sub-clades, namely N3a* and N3a5. The same sub-branches are specific to the Mongush clan as well, though with lower frequencies: N3a* – 9 % and N3a5 – 14 % (see Table). In Khori-Buryats from the Transbaikal region, a high frequency is observed – 82 % (Kharkov et al., 2014), while in Mongols, N3a5 occurs rather rarely (6 %). Hg N3a* was detected in populations of South Siberia only, and was widely spread in Khakas-Sagays and Shors (up to 40 %) (Ilumäe et al., 2016) (Y-base).

Map of distribution of Samoyedic languages (red) in the XVII century (approximate; hatching) and in the end of XX century (continuous background). Modified from Wikipedia, with the Tuva region labelled.

Within the pan-Eurasian haplogroup R1a1a, two large genetic lines (sub-haplogroups) are identified: “European” (marker M458) and “Asian” (marker Z93) the latter almost never occurring in Europe (Balanovsky, 2015) but abundant in South Siberia and northern Hindustan. In the Altai-Sayan region, high frequencies of the “Asian” branch are spread in many peoples – Shors, Tubalars, Altai-Kizhi people, Telengits, Sagays, Kyzyl Khakas, Koibals, Teleuts (Y-base) (Kharkov et al., 2009). Hg R1a1a comprises perceptible parts of gene pools of Tuvinian clans (19 % in Mongush, and 15 % in Oorzhak), though its occurrence in Mongols is much lower (6 %). Those results also count in favor of the hypothesis of autochtonous component dominance even in the gene pools of clans potentially most influenced by Mongolian ancestry. If we add R1a1a variants to the “North Eurasian” haplogroups, the “not-Central Asian” component will compose average four fifth of the entire gene pools for Tuvinian clans (in Mongush 77 %, and in Oorzhak 81 %), being only 16 % in Mongols. Such data are definitely contrary to the hypothesis of a crucial influence of the Mongol expansion upon the development of Tuvinian gene pool.

I found interesting the high proportion of R1a-Z93 subclades among Sagays in Khakhasia, which stem from a local Samoyed substratum, as described by the paper…

Featured Image: Map of Uralic and Altaic languages, from Wikipedia.


Close inbreeding and low genetic diversity in Inner Asian human populations despite geographical exogamy


Open access Close inbreeding and low genetic diversity in Inner Asian human populations despite geographical exogamy, by Marchi et al. Scientific Reports (2018) 8:9397.

Abstract (emphasis mine):

When closely related individuals mate, they produce inbred offspring, which often have lower fitness than outbred ones. Geographical exogamy, by favouring matings between distant individuals, is thought to be an inbreeding avoidance mechanism; however, no data has clearly tested this prediction. Here, we took advantage of the diversity of matrimonial systems in humans to explore the impact of geographical exogamy on genetic diversity and inbreeding. We collected ethno-demographic data for 1,344 individuals in 16 populations from two Inner Asian cultural groups with contrasting dispersal behaviours (Turko-Mongols and Indo-Iranians) and genotyped genome-wide single nucleotide polymorphisms in 503 individuals. We estimated the population exogamy rate and confirmed the expected dispersal differences: Turko-Mongols are geographically more exogamous than Indo-Iranians. Unexpectedly, across populations, exogamy patterns correlated neither with the proportion of inbred individuals nor with their genetic diversity. Even more surprisingly, among Turko-Mongols, descendants from exogamous couples were significantly more inbred than descendants from endogamous couples, except for large distances (>40 km). Overall, 37% of the descendants from exogamous couples were closely inbred. This suggests that in Inner Asia, geographical exogamy is neither efficient in increasing genetic diversity nor in avoiding inbreeding, which might be due to kinship endogamy despite the occurrence of dispersal.

Interesting excerpts:

Two cultural groups, which matrimonial systems are reported to differ, coexist in Inner Asia: Turko-Mongols are described as mainly exogamous while Indo-Iranians are thought to be mainly endogamous45. However, it is not always clear if exogamy refers to clan (ethnic) or village (geographical) exogamy. Here, we used a dataset of 16 populations representing 11 different ethnic groups from both cultural groups and we quantified geographical exogamy rates and distances in each population. Using an empirical threshold of 4 km, we confirmed that matrimonial behaviours differ as described in the literature, even though we found some exceptions: three Turko-Mongol populations (out of 14) have less than 50% exogamy, whereas one Indo-Iranian population (out of four) has more than 50% exogamy.(…).

Geographical distances between the birth places of couples in Turko-Mongols and Indo-Iranians. The geographical distances are plotted in log scale (km). Their densities are represented by population (dashed lines) or for the Indo-Iranian and Turko-Mongol groups (solid lines). We represented the average distances within couples per population using a Kernel’s density estimate implemented in R with a smoothing bandwidth of 0.2. See Supplementary Table 1B for population codes.

An additional important result of our study is that geographical distances are not negatively correlated with inbreeding, as could have been expected under an isolation-by-distance model65. Interestingly, a recent study based on a large genealogical dataset, collected across Western Europe and North America, and including birth places information, similarly found an absence of correlation between relatedness and the distance between couples, for the cohorts born before 185066. Our analyses within present-day Turko-Mongols reveal more specifically that the structure of the relationship between geographical distance and mating choice inbreeding is not linear, but rather tends to be bell-shaped, and thus cannot be correctly assessed with a single correlation test. Indeed, descendants from parents born 4 to 40 km apart are more inbred than descendants from endogamous couples (≤4 km) or from long-range exogamous ones (>40 km). As a consequence, close inbreeding exists despite geographical exogamy, and about a third of descendants from exogamous couples are inbred.

These results, in addition to those obtained by [Kaplanis et al. 2018]66, highlight the importance of using geographic distances rather than exogamy rates to characterize the impact of exogamy on inbreeding, as already described when studying patrilocality67. Indeed, when we compare mating choice inbreeding patterns for descendants from exogamous and endogamous couples defined for thresholds of 4, 10, 20 and 30 km, we find no significant differences (for number and total length of class C-ROHs and F-Median coefficient: MWU test p-values > 0.1). We only detect significantly lower values in descendants from exogamous couples for larger distances above 40 and 50 km (p-values < 0.03).

Genetic diversity (A) and inbreeding patterns (B,C) within populations. Grey lines in (B) represent inbreeding values corresponding to second-cousins and first-cousins. The grey line in (C) represents the homozygosity population baseline expected under panmixia. The number of samples per population is indicated between parentheses. See Supplementary Table 1B for population codes.

Our results also challenge the intuition that exogamy necessarily increases the genetic diversity within a population and therefore reduces drift inbreeding. Indeed, we found that Turko-Mongol populations have a lower genetic diversity (as measured by the mean haplotypic heterozygosity) and more intermediate ROHs associated with drift inbreeding than those of Indo-Iranians despite higher exogamous rates. (…)

Overall, this research sheds light on mating choice preferences: we showed that two thirds of partners that have not dispersed did mate with unrelated individuals, and that drift and mating choice inbreeding is variable, even among close-by populations. We also provide new insights into the relationship between dispersal and inbreeding in humans, based on genetic data, and demonstrate that geographical exogamy is not necessarily negatively associated with mating choice inbreeding, but rather can have a more complex non-linear relationship. Contrary to the common situation in many animals, this finding suggests that Inner Asian human populations who practise exogamy at small geographical scales might be focused on alliance strategies that result in kinship endogamy. (…)


On Latin, Turkic, and Celtic – likely stories of mixed societies and little genetic impact


Recent article on The Conversation, The Roman dead: new techniques are revealing just how diverse Roman Britain was, about the paper (behind paywall) A Novel Investigation into Migrant and Local Health-Statuses in the Past: A Case Study from Roman Britain, by Redfern et al. Bioarchaeology International (2018), among others.

Interesting excerpts about Roman London:

We have discovered, for example, that one middle-aged woman from the southern Mediterranean has black African ancestry. She was buried in Southwark with pottery from Kent and a fourth century local coin – her burial expresses British connections, reflecting how people’s communities and lives can be remade by migration. The people burying her may have decided to reflect her life in the city by choosing local objects, but we can’t dismiss the possibility that she may have come to London as a slave.

The evidence for Roman Britain having a diverse population only continues to grow. Bioarchaeology offers a unique and independent perspective, one based upon the people themselves. It allows us to understand more about their life stories than ever before, but requires us to be increasingly nuanced in our understanding, recognising and respecting these people’s complexities.

We already have a more or less clear idea about how little the Roman conquest may have shaped the genetic map of Europe, Africa, or the Middle East, in contrast to other previous or later migrations or conquests.

Also, on the Turkic expansion, the recent paper of Damgaard et al. (Nature 2018) stated:

In the sixth century AD, the Hunnic Empire had been broken up and dispersed as the Turkic Khaganate assumed the military and political domination of the steppes22,23. Khaganates were steppe nomad political organizations that varied in size and became dominant during this period; they can be contrasted to the previous stateless organizations of the Iron Age24. The Turkic Khaganate was eventually replaced by a number of short-lived steppe cultures25 (…).

We find evidence that elite soldiers associated with the Turkic Khaganate are genetically closer to East Asians than are the preceding Huns of the Tian Shan mountains (Supplementary Information section 3.7). We also find that one Turkic Khaganate-period nomad was a genetic outlier with pronounced European ancestries, indicating the presence of ongoing contact with Europe (…).

Analyses of Turk- and Medieval-period population clusters. a, PCA of Tian Shan Hun, Turk, Kimak, Kipchack, Karakhanid and Golden Horde, including 28 individuals analysed at 242,406 autosomal SNP positions. b, Results for model-based clustering analysis at K = 7. Here we illustrate the admixture analyses with K = 7 as it approximately identifies the major component of relevance (Anatolian/ European farmer component, Caucasian ancestry, EHG-related ancestry and East Asian ancestry).”

These results suggest that Turkic cultural customs were imposed by an East Asian minority elite onto central steppe nomad populations, resulting in a small detectable increase in East Asian ancestry. However, we also find that steppe nomad ancestry in this period was extremely heterogeneous, with several individuals being genetically distributed at the extremes of the first principal component (Fig. 2) separating Eastern and Western descent. On the basis of this notable heterogeneity, we suggest that during the Medieval period steppe populations were exposed to gradual admixture from the east, while interacting with incoming West Eurasians. The strong variation is a direct window into ongoing admixture processes and the multi-ethnic cultural organization of this period.

We already knew that the expansion of the La Tène culture, associated with the expansion of Celtic languages throughout Europe, was probably not accompanied by massive migrations (from the IEDM, 3rd ed.):

The Mainz research project of bio-archaeometric identification of mobility has not proven to date a mass migration of Celtic peoples in central Europe ca. 4th-3rd centuries BC, i.e. precisely in a period where textual evidence informs of large migratory movements (Scheeres 2014). La Tène material culture points to far-reaching inter-regional contacts and cultural transfers (Burmeister 2016).

Also, from the latest paper on Y-chromosome bottleneck:

[The hypothesis of patrilineal kin group competition] has an added benefit in that it could explain the temporal placement of the bottleneck if competition between patrilineal kin groups was the main form of intergroup competition for a limited episode of time after the Neolithic transition. Anthropologists have repeatedly noted that the political salience of unilineal descent groups is greatest in societies of ‘intermediate social scale’ (Korotayev47 and its citations on p. 2), which tend to be post-Neolithic small-scale societies that are acephalous, i.e. without hierarchical institutions48. Corporate kin groups tend to be absent altogether among mobile hunter gatherers with few defensible resource sites or little property (Kelly49 pp. 64–73), or in societies utilizing relatively unoccupied and under-exploited resource landscapes (Earle and Johnson50 pp. 157–171). Once they emerge, complex societies, such as chiefdoms and states, tend to supervene the patrilineal kin group as the unit of intergroup competition, and while they may not eradicate them altogether as sub-polity-level social identities, warfare between such kin groups is suppressed very effectively51,52.These factors restrict the social phenomena responsible for the bottleneck to the period after the initial Neolithic but before the emergence of complex societies, which would place the bottleneck-generating mechanisms in the right period of time for each region of the Old World.

Diachronic map of Late Copper Age migrations including Classical Bell Beaker (east group) expansion from central Europe ca. 2600-2250 BC

However, I recently read in a forum for linguists that the expansion of East Bell Beakers overwhelmingly of R1b-L21 subclades in the British Isles “poses a problem”, in that it should be identified with a Celtic expansion earlier than traditionally assumed…

That interpretation would be in line with the simplistic maps we are seeing right now for Bell Beakers (see below for the Copenhagen group).

If anything, the results of Bell Beaker expansions (taken alone) would seem to support a model similar to Cunliffe & Koch‘s hypotheses of a rather early Celtic expansion into Great Britain and Iberia from the Atlantic.

Spread of Indo-European languages (by the Copenhagen group).

But it doesn’t. Mallory already explained why in Cunliffe & Koch’s series Celtic from the West: the Bell Beaker expansion is too early for that; even for Italo-Celtic. It should correspond to North-West Indo-European speakers.

Not every population movement that is genetically very significant needs to be significant for the languages attested much later in the region.

This should be obvious to everyone with the many examples we already have. One of the least controversial now would probably be the expansion of R1b-DF27, widespread in Iberia probably at roughly the same time as R1b-L21 was in Great Britain, and still pre-Roman Iberians showed a mix of non-Indo-European languages, non-Celtic languages (at least Galaico-Lusitanian), and also some (certain) Celtic languages. And modern Iberians speak Romance languages, without much genetic impact from the Romans, either…

It is well-established in Academia that the expansion of La Tène is culturally associated with the spread of Celtic languages in Europe, including the British Isles and Iberia. While modern maps of U152 distribution may correspond to the migration of early Celts (or Italo-Celtic speakers) with Urnfield/Hallstatt, the great Celtic expansion across Europe need not show a genetic influence greater than or even equal to that of previous prehistoric migrations.

Post-Bell-Beaker Europe, after ca. 2200 BC.

You can see in these de novo models the same kind of invented theoretical ‘problem’ (as Iosif Lazaridis puts it) that we have seen with the Corded Ware showing steppe ancestry, with Old Hittite samples not showing EHG ancestry, or with CHG ancestry appearing north of the Caucasus but no EHG to the south.

However you may want to explain all these errors in scientific terms (selection bias, under-coverage, over-coverage, faulty statistical methods, etc.), these interpretations were simply fruit of the lack of knowledge of the anthropological disciplines at play.

Let’s hope the future paper on Celtic expansion takes this into consideration.


How an empire of steppe nomads coped with environmental stress


Recent paper (behind paywall), Environmental Stress and Steppe Nomads: Rethinking the History of the Uyghur Empire (744–840) with Paleoclimate Data, by Di Cosmo et al. JINH (2018) XLVIII(4):439-463.

Abstract (emphasis mine):

Newly available paleoclimate data and a re-evaluation of the historical and archaeological evidence regarding the Uyghur Empire (744–840)—one of several nomadic empires to emerge on the Inner Asian steppe—suggests that the assumption of a direct causal link between drought and the stability of nomadic societies is not always justified. The fact that a severe drought lasting nearly seven decades did not cause the Uyghur Empire to collapse, to wage war, or to disintegrate gives rise to speculations about which of its characteristics enabled it to withstand unfavorable climatic conditions and environmental change. More broadly, it raises questions about the complex suite of strategies and responses that may have been available to steppe societies in the face of environmental stress.

Interesting excerpts:

The heart of the matter is whether the apparent capacity to withstand adverse climatic conditions was due to a set of cultural and/or political choices, unrelated to climate, or to a modification of their nomadic ways toward a greater reliance on agriculture and trade. In support of the first alternative, the Uyghur Empire’s initial military rise and expansion (c. 744 to 780) may have been aided by conditions of high moisture that would have made the grasslands especially productive. The alliance with China, the conversion to Manichaeism, and the growing incorporation of Sogdian elites in their empire that took place during this period may have aided the Uyghurs, serendipitously, to withstand the climatic crisis. In the long run, however, some areas of society most likely suffered adverse effects, which might explain the internal splits and the final defeat at the hands of the Kirgiz. These developments owe as much to the sedentary habits of the Uyghur elites and their ineffective leadership as to the erosion of the pastoral resources that constituted the main support of a nomadic army.

The findings are based on scPDSI reconstructions at 0.5-degree grid derived from tree
ring records across Asia.

The evidence from tree-ring data points to environmental conditions that alter the historical narrative of the rise and fall of the Uyghur Empire. Although several studies have focused on how climatic extremes affected agricultural societies, the fate of complex nomadic societies did not necessarily follow the same path. Steppe empires, at least from the first Türk Empire (established in the sixth century C.E.), and possibly earlier, were based on expansive geographical networks, diversified economies, and a degree of co-dependency with merchant classes. Even though these elements varied greatly between empires, they probably reacted to climatic variability in ways radically different from the ways in which agricultural and urban polities did. Once we account for socio-economic complexity, the case of the Uyghur Empire belies the general assumption that nomadic peoples are more vulnerable to climatic stress. The severe and protracted drought did not trigger migration, pillaging, or conquest. Sudden shocks, however, could have had a devastating effect on an economy already weakened.

The catastrophic event of the winter of 839/40, which appears to be a dzud (a weather condition of extreme cold and heavy snowfall that causes high animal mortality) was likely the coup de grâce to an already compromised pastoral production. Contemporary studies of the dzud emphasize that the degree of calamity of the winter disaster is closely related to the drought conditions that preceded it. Thus, the collapse of the Uyghur Empire, generally understood as a rapidly evolving political crisis compounded by a catastrophic weather event, is also connected to multidecadal climatic change, dependency mechanisms, and geopolitical constraints.

I found it interesting mainly because of the potential application of this kind of studies to other previous steppe societies.

Discovered via news on, posted by Spencer Wells.


On the origin of R1a and R1b subclades in Greece


An article published in PLoS ONE, Y-chromosomal analysis of Greek Cypriots reveals a primarily common pre-Ottoman paternal ancestry with Turkish Cypriots, by Alexandros Heraclides and colleagues, insists on the potential origin of R1b and R1a lineages in Greece from Indo-European migrations, albeit with strong regional (and thus most likely temporal) differences. From the article’s discussion:

Although the exact origins and migratory patterns of R1a and R1b are still under rigorous investigation, it seems that they are linked to Bronze Age migrations from the Western Eurasian Steppe and Eastern Europe into Southern (including Greece) and Western Europe[61]. Apparently, such migrations (especially as regards R1a) into Cyprus were limited.

Additionally, the Greek population has received considerable migrations during the Byzantine era and the Middle Ages from other Balkanic populations, such as Slavs[62,63], Aromanians (Vlachs)[64], and Albanians (Arvanites)[65,66]. The former, is very likely to have increased R1a frequencies among Greeks. In fact, Fig 3 (also S7 Table) indicate that R1a increases gradually with increasing latitude in Greece. There is no historical evidence for such migrations into Cyprus during the same period.

The only Greek sub-population showing close genetic proximity to Cypriots (in terms of Y-haplogroup composition) is Cretan Greeks (Figs 3 and 4). It could be speculated that Cypriots and Cretans experienced very similar migratory events over the centuries, which were characterized by high influx from populations rich in haplogroups J2a and G2, and moderate in R1b, while very limited influx from populations rich in haplogroups R1a and I (Eastern and Northern/ Central Europe), as well as from populations rich in J1 (Middle East) and E-M81 (North Africa).

If R1b-M269 lineages are linked – as I have proposed – to Yamna migrations, and especially R1b-Z2103 to Palaeo-Balkan migrations, whereas R1a-M417 is to be linked to Corded Ware migrations, the reason for this latitude-dependent (and also longitude-dependent) presence of R1a-M417 subclades in Greece and is probably linked to the expansion of Slavic R1a-Z282 lineages to the north and west of Greece (and from there through intermarriages and migrations within Greece into other regions), and Iranian R1a-Z93 lineages to the east traditional Greek territory, into Asia Minor. The expansion of Balkan peoples (including Slavs, Albanian, and Aromanian peoples) might have brought with them R1b-M269*, I2, or R1a-Z282 subclades.

News of the article via Eurogenes.