The cradle of Russians, an obvious Finno-Volgaic genetic hotspot


First look of an accepted manuscript (behind paywall), Genome-wide sequence analyses of ethnic populations across Russia, by Zhernakova et al. Genomics (2019).

Interesting excerpts:

There remain ongoing discussions about the origins of the ethnic Russian population. The ancestors of ethnic Russians were among the Slavic tribes that separated from the early Indo-European Group, which included ancestors of modern Slavic, Germanic and Baltic speakers, who appeared in the northeastern part of Europe ca. 1,500 years ago. Slavs were found in the central part of Eastern Europe, where they came in direct contact with (and likely assimilation of) the populations speaking Uralic (Volga-Finnish and Baltic- Finnish), and also Baltic languages [11–13]. In the following centuries, Slavs interacted with the Iranian-Persian, Turkic and Scandinavian peoples, all of which in succession may have contributed to the current pattern of genome diversity across the different parts of Russia. At the end of the Middle Ages and in the early modern period, there occurred a division of the East Slavic unity into Russians, Ukrainians and Belarusians. It was the Russians who drove the colonization movement to the East, although other Slavic, Turkic and Finnish peoples took part in this movement, as the eastward migrations brought them to the Ural Mountains and further into Siberia, the Far East, and Alaska. During that interval, the Russians encountered the Finns, Ugrians, and Samoyeds speakers in the Urals, but also the Turkic, Mongolian and Tungus speakers of Siberia. Finally, in the great expanse between the Altai Mountains on the border with Mongolia, and the Bering Strait, they encountered paleo-Asiatic groups that may be genetically closest to the ancestors of the Native Americans. Today’s complex patchwork of human diversity in Russia has continued to be augmented by modern migrations from the Caucasus, and from Central Asia, as modern economic migrations take shape.

Sample relatedness based on genotype data. Eurasia: Principal Component plot of 574 modern Russian genomes. Colors reflect geographical regions of collection; shapes reflect the sample source. Red circles show the location of Genome Russia samples.

In the current study, we annotated whole genome sequences of individuals currently living on the territory of Russia and identifying themselves as ethnic Russian or as members of a named ethnic minority (Fig. 1). We analyzed genetic variation in three modern populations of Russia (ethnic Russians from Pskov and Novgorod regions and ethnic Yakut from the Sakha Republic), and compared them to the recently released genome sequences collected from 52 indigenous Russian populations. The incidence of function-altering mutations was explored by identifying known variants and novel variants and their allele frequencies relative to variation in adjacent European, East Asian and South Asian populations. Genomic variation was further used to estimate genetic distance and relationships, historic gene flow and barriers to gene flow, the extent of population admixture, historic population contractions, and linkage disequilibrium patterns. Lastly, we present demographic models estimating historic founder events within Russia, and a preliminary HapMap of ethnic Russians from the European part of Russia and Yakuts from eastern Siberia.

Sample relatedness based on genotype data. Western Russia and neighboring countries: Principal Component plot of 574 modern Russian genomes. Colors reflect geographical regions of collection; shapes reflect the sample source. Red circles show the location of Genome Russia samples.

The collection of identified SNPs was used to inspect quantitative distinctions among 264 individuals from across Eurasia (Fig. 1) using Principal Component Analysis (PCA) (Fig. 2). The first and the second eigenvectors of the PCA plot are associated with longitude and latitude, respectively, of the sample locations and accurately separate Eurasian populations according to geographic origin. East European samples cluster near Pskov and Novgorod samples, which fall between northern Russians, Finno-Ugric peoples (Karelian, Finns, Veps etc.), and other Northeastern European peoples (Swedes, Central Russians, Estonian, Latvians, Lithuanians, and Ukrainians) (Fig. 2b). Yakut individuals map into the Siberian sample cluster as expected (Fig. 2a). To obtain an extended view of population relationships, we performed a maximum likelihood-based estimation of ancestry and population structure using ADMIXTURE [46](Fig. 2c). The Novgorod and Pskov populations show similar profiles with their Northeastern European ancestors while the Yakut ethnic group showed mixed ancestry similar to the Buryat and Mongolian groups.

Population structure across samples in 178 populations from five major geographic regions (k=5). Samples are pooled across three different studies that covered the territory of Russian Federation (Mallick et al. 2016 [36], Pagani et al. 2016 [37], this study). The optimal k-value was selected by value of cross validation error. Russian samples from all studies (highlighted in bold dark blue) show a slight gradient from Eastern European (Ukrainian, Belorussian, Polish) to North European (Estonian Karelian, Finnish) structures, reflecting population history of northward expansion. Yakut samples from different studies (highlighted in bold red) also show a slight gradient from Mongolian to Siberian people (Evens), as expected from their original admixture and northward expansions. The samples originated from this study are highlighted, and plotted in separated boxes below.

Possible admixture sources of the Genome Russia populations were addressed more formally by calculating F3 statistics, which is an allele frequency-based measure, allowing to test if a target population can be modeled as a mixture of two source populations [48]. Results showed that Yakut individuals are best modeled as an admixture of Evens or Evenks with various European populations (Supplemental Table S4). Pskov and Novgorod showed admixture of European with Siberian or Finno-Ugric populations, with Lithuanian and Latvian populations being the dominant European sources for Pskov samples.

The heatmaps of gene flow barriers show for each point at the geographical map the interpolated differences in allele frequencies (AF) between the estimated AF at the point with AFs in the vicinity of this point. The direction of the maximal difference in allele frequencies is coded by colors and arrows.

So, Russians expanding in the Middle Ages as acculturaded Finno-Volgaic peoples.

Or maybe the true Germano-Slavonic™-speaking area was in north-eastern Europe, until the recent arrival of Finno-Permians with the totally believable Nganasan-Saami horde, whereas Yamna -> Bell Beaker represented Vasconic-Caucasian expanding all over Europe in the Bronze Age. Because steppe ancestry in Fennoscandia and Modern Basques in Iberia.

A really hard choice between equally plausible models.


R1a-Z280 and R1a-Z93 shared by ancient Finno-Ugric populations; N1c-Tat expanded with Micro-Altaic

Two important papers have appeared regarding the supposed link of Uralians with haplogroup N.

Avars of haplogroup N1c-Tat

Preprint Genetic insights into the social organisation of the Avar period elite in the 7th century AD Carpathian Basin, by Csáky et al. bioRxiv (2019).

Interesting excerpts (emphasis mine):

After 568 AD the Avars settled in the Carpathian Basin and founded the Avar Qaganate that was an important power in Central Europe until the 9th century. Part of the Avar society was probably of Asian origin, however the localisation of their homeland is hampered by the scarcity of historical and archaeological data.

Here, we study mitogenome and Y chromosomal STR variability of twenty-six individuals, a number of them representing a well-characterised elite group buried at the centre of the Carpathian Basin more than a century after the Avar conquest.

The Y-STR analyses of 17 males give evidence on a surprisingly homogeneous Y chromosomal composition. Y chromosomal STR profiles of 14 males could be assigned to haplogroup N-Tat (also N1a1-M46). N-Tat haplotype I was found in four males from Kunpeszér with identical alleles on at least nine loci. The full Y-STR haplotype I, reconstructed from AC17 with 17 detected STRs, is rare in our days. Only nine matches were found among haplotypes in YHRD database, such as samples from the Ural Region, Northern Europe (Estonia, Finland), and Western Alaska (Yupiks). We performed Median Joining (MJ) network analysis using N-Tat haplotypes with ten shared STR loci (Fig. 3, Table S9). All modern N-Tat samples included in the network had derived allele of L708 as well. Haplotype I (Cluster 1 in Fig. 3) is shared by eight populations on the MJ network among the 24 identical haplotypes. Cluster 1 represents the founding lineage, as it is described in Siberian populations, because this haplotype is shared by the most populations and it is more diverse than Cluster 2.

Nine males share N-Tat haplotype II (on a minimum of eight detected alleles), all of them buried in the Danube-Tisza Interfluve. We found 30 direct matches of this N-Tat haplotype II in the YHRD database, using the complete 17 STR Y-filer profile of AC1, AC12, AC14, AC15, AC19 samples. Most hits came from Mongolia (seven Buryats and one Khalkh) and from Russia (six Yakuts), but identical haplotypes also occur in China (five in Xinjiang and four in Inner Mongolia provinces). On the MJ network, this haplotype II is represented by Cluster 2 and is composed of 45 samples (including 32 Buryats) from six populations (Fig. 3).

Median Joining network of 162 N-Tat Y-STR haplotypes Allelic information of ten Y-STR loci were used for the network. Only those Avar samples were included, which had results for these ten Y-STR loci. The founder haplotype I (Cluster 1) is shared by eight populations including three Mongolian, three Székely, three northern Mansi, two southern Mansi, two Hungarian, eight Khanty, one Finn and two Avar (AC17, AC26) chromosomes. Haplotype II (Cluster 2) includes 45 haplotypes from six populations studied: 32 Buryats, two Mongolians, one Székely, one Uzbek, one Uzbek Madjar, two northern Mansi and six Avars (AC1, AC12, AC14, AC15, AC19 and KSZ 37). Haplotype III (indicated by a red arrow) is AC8. Information on the modern reference samples is seen in Table S9.

A third N-Tat lineage (type III) was represented only once in the Avar dataset (AC8), and has no direct modern parallels from the YHRD database. This haplotype on the MJ network (see red arrow in Fig. 3) seems to be a descendent from other haplotype cluster that is shared by three populations (two Buryat from Mongolia, three Khanty and one Northern Mansi samples). This haplotype cluster also differs one molecular step (locus DYS393) from haplotype II. We classified the Avar samples to downstream subgroup N-F4205 within the N-Tat haplogroup, based on the results of ours and Ilumäe et al.18 and constructed a second network (Fig. S4). The N-F4205 network results support the assumption that the N-Tat Avar samples belong to N-F4205 subgroup (see SI chapter 1d for more details).

Based on our calculation, the age of accumulated STR variance (TMRCA) within N-Tat lineage for all samples is 7.0 kya (95% CI: 4.9 – 9.2 kya), considering the core haplotype (Cluster 1) to be the founding lineage. Y haplogroup N-Tat was not detected by large scale Eurasian ancient DNA studies but it occurs in late Bronze Age Inner Mongolia and late medieval Yakuts, among them N-Tat has still the highest frequency.

Two males (AC4 and AC7) from the Transtisza group belong to two different haplotypes of Y-haplogroup Q1. Both Q1a-F1096 and Q1b-M346 haplotypes have neither direct nor one step neighbour matches in the worldwide YHRD database. A network of the Q1b-M346 haplotype shows that this male had a probable Altaian or South Siberian paternal genetic origin.

EDIT (5 APR 2019): The paper offers an interesting late sample before the arrival of Hungarian conquerors, although we don’t know which precise lineage the sample belongs to:

One sample in our dataset (HC9) comes from this population, and both his mtDNA (T1a1b) and Y chromosome (R1a) support Eastern European connections. (…) Furthermore, we excluded sample HC9 from population-genetic statistical analyses because it belongs to a later period (end of 7th – early 9th centuries)

Apparently, then, results are consistent with what was already known from studies of modern populations:

According to Ilumäe et al. study, the frequency peak of N-F4205 (N3a5-F4205) chromosomes is close to the Transbaikal region of Southern Siberia and Mongolia, and we conclude that most Avar N-Tat chromosomes probably originated from a common source population of people living in this area, completely in line with the results of Ilumäe et al.

Geographic-Distribution Map of hg N3 from Ilumäe et al.

Finno-Ugrians share haplogroup R1a-Z280

Another paper, behind paywall, Genetic history of Bashkirian Mari and Southern Mansi ethnic groups in the Ural region, by Dudás et al. Molecular Genetics and Genomics (2019).

Interesting excerpts (emphasis mine):

Y‑chromosome diversity

The most frequent haplogroups of the Bashkirian Maris were N1b-P43 (42%), R1a-Z280 (16%), R1a-Z93 (16%), N1c-Tat (13%), and J2-M172 (7%). Furthermore, subgroup R1b-M343 accounted for 4% and I2a-P37 covered 2% of the lineages. None of the Mari N1c Y chromosomes belonged to the N1c subgroups investigated (L1034, VL29, Z1936).

In the case of the Southern Mansi males, the most frequent haplogroups were N1b-P43 (33%), N1c-L1034 (28%) and R1a-Z280 (19%). The frequencies of the remaining haplogroups were as follows: R1a-M458 (6%), I1-L22 (3%), I2a-P37 (3%), and R1b-P312 (3%). The haplotype and haplogroup diversities of the Bashkirian Mari group were 0.9929 and 0.7657, whereas these values for the Southern Mansi were 0.9984 and 0.7873, respectively. The results show that, in both populations, haplotypes are much more diverse than haplogroups.

Haplogroup frequencies of the Bashkirian Mari and the Southern Mansi ethnic groups in Ural region

Genetic structure

(..) the studied Bashkirian Mari and Southern Mansi population groups formed a compact cluster along with two Khanty, Northern Mansi, Mari, and Estonian populations based on close Fst-genetic distances (< 0.05), with nonsignificant p values (p > 0.05) except for the Estonian population. All of these populations belong to the Finno-Ugric language family. Interestingly, the other Mansi population studied by Pimenoff et al. (2008) (pop # 38) was located a great distance from the Southern Mansi group (0.268). In addition, the Bashkir population (pop # 6) did not show a close genetic affinity to the Bashkirian Mari group (0.194), even though it is the host population. However, the Russian population from the Eastern European region of Russia (pop # 49) showed a genetic distance of 0.055 with the Southern Mansi group. All Hungarian speaking populations (pops 13, 22, 23, 24, 50, and 51) showed close genetic affinities to each other and to the neighbouring populations, but not to the two studied populations.

Multidimensional scaling (MDS) plot constructed on Fstgenetic distances of Y haplogroup frequencies of 63 populations compared. The haplogroup frequency data used for population comparison together with references are seen in Online Resource 2 (ESM_2). Pairwise Fst-genetic distances and p values between 63 populations were calculated as shown in Online Resource 3 (ESM_3) Fig. 4 Multidimensional scaling (MDS) plot constructed on Rstgenetic distances of 10 STR-based Y haplotype frequencies of 21 populations compared. Image modified to include labels of modern populations.

Phylogenetic analysis

Median-joining networks were constructed for:

N-P43 (earlier N1b):

(…) TMRCA estimates for this haplogroup were made for all P43 samples (n = 157) 8.7 kya (95% CI 6.7–10.8 kya), for the N-P43 Asian.


(…) 75% of Buryats belonged to Haplotype 2, indicating that the Buryats studied by us is a young and isolated population (Bíró et al. 2015). Bashkirian Mari samples derive from Haplotype 2 via Haplotype 3 (see dark purple circles on the top of Fig. 6a). Haplotype 3 contained six males (2 Buryat, 1 Northern Mansi, and 3 Khanty samples from Pimenoff et al. 2008). The biggest Bashkirian Mari haplotype node (3 Mari samples) was positioned three mutational steps away from Haplotype 1 and the remaining Mari samples can be derived from this haplotype. Southern Mansi haplotypes were scattered within the network except for two, which formed a smaller haplotype node with two Northern Mansi and two Khanty samples from Pimenoff et al. (2008).

Median-Joining Networks (MJ) of 153 N-Tat (a) and 26 N-L1034 (b) haplotypes constructed. The circle sizes are proportional to the haplotype frequencies. The smallest area is equivalent to one individual. For N-Tat network, we used data from Southern Mansi (n = 11), Bashkirian Mari (n = 6) samples with Hungarian (n = 12), Hungarian speaking Székely (n = 6), Northern Mansi (n = 14), Mongolian (n = 16), Buryat (n = 44), Finnish (n = 13), Uzbek Madjar (n = 2), Uzbek (n = 3), Khanty (n = 4) populations studied earlier by us (Fehér et al. 2015; Bíró et al. 2015) and Khanty (n = 18) and Mansi (n = 4) studied by Pimenoff et al. (2008)

R1a-Z280 haplotypes, shared by Maris, Mansis, and Hungarians, hence ancient Finno-Ugrians:

The founder R1a-Z280 haplotype was shared by four samples from four populations (1 Bashkirian Mari; 1 Southern Mansi; 1 Hungarian speaking Székely; and 1 Hungarian), as presented in Fig. 7 (Haplotype 1). Haplotype 2 included five males (3 Bashkirian Mari and 2 Hungarian), as it can be seen in Fig. 7. Haplotype 4 included two shared haplotypes (1 Bashkirian Mari and one Hungarian speaking Csángó). The remaining two Bashkirian Mari haplotypes differ from the founder haplotype (Haplotype 1) by two mutational steps via Hungarian or Hungarian and Bashkirian Mari shared haplotypes. Beside Haplotype 1, the remaining Southern Mansi haplotypes were shared with Hungarians (Haplotype 5 or turquoise blue and red-coloured circles above Haplotype 7) or with Hungarians and Hungarian speaking Székely group (Haplotypes 3, 5, and 6). Haplotype 7 included ten Hungarian speakers (Hungarian, Székely, and Csángó). One Hungarian and one Uzbek Khwarezm shared haplotype can be found in Fig. 7 as well (red and white-coloured circle). All the other haplotypes were scattered in the network. The age of accumulated STR variation within R1a-Z280 lineage for 93 samples is estimated to be 9.4 kya (95% CI 6.5–12.4 kya) considering Haplotype 1 (Fig. 7) to be the founder.

Median-Joining Networks (MJ) of 93 R1a-Z280 haplotypes constructed. The circle sizes are proportional to the haplotype frequencies. The smallest area is equivalent to one individual. We used haplotype data from Bashkirian Mari (n = 7), Southern Mansi (n = 7), Hungarian (n = 52), Hungarian speaking Székely (n = 11), Hungarian speaking Csángó (n = 10), Uzbek Ferghana (n = 2), Uzbek Tashkent (n = 1), Uzbek Khwarezm (n = 1) and Northern Mansi (n = 2) populations

R1a-Z93 as isolated lineages among Permic and Ugric populations:

Figure 8 depicts an MJ network of R1a-Z93* samples using 106 haplotypes from the 14 populations (Fig. 8). All of the Bashkirian Mari samples (7 haplotypes) formed a very isolated branch and differed from the one Hungarian haplotype (Fig. 8, see Haplotype 1) by seven mutational steps as well from two Uzbek Tashkent samples (see Haplotype 3). Another Hungarian sample shared two haplotypes of Uzbek Khwarezm samples in Haplotype 4. This haplotype can be derived from Haplotype 3 (Uzbek Tashkent). Haplotype 2 included one Hungarian and one Khakassian male. The remaining three Hungarian haplotypes are outliers in the network and are not shared by any sample. The other population samples included in the network either form independent clusters such as Altaians, Khakassians, Khanties, and Uzbek Madjars or were scattered in the network. The age of accumulated STR variation (TMRCA) within R1a-Z93* lineage for 106 samples is estimated as 11.6 kya (95% CI 9.3–14.0 kya) considering an Armenian haplotype (Fig. 8, “A”) to be the founder and the median haplotype.

Median-Joining Networks (MJ) of 106 R1a-Z93 haplotypes constructed. The circle sizes are proportional to the haplotype frequencies. The smallest area is equivalent to one individual. We used the next haplotype data: 7 Bashkirian Mari, 6 Khanty, 4 Uzbek Madjar, 5 Uzbek Ferghana, 9 Uzbek Tashkent, 7 Uzbek Khwarezm, 2 Mongolian, 2 Buryat, 6 Hungarian samples tested by us for this study or published earlier (Bíró et al. 2015) and populations (3 Armenian; 3 Afghan Tajik;
16 Altaian; 24 Khakassian; 12 Kyrgyz) from Underhill et al. (2015)


The results of modern populations for N (especially N1c) subclades show really wide clusters and ancient TMRCA, consistent with their known ancient and wide distribution in northern and eastern Eurasian groups, and thus with infiltration of different lineages with eastern nomads (and northern Arctic populations) coupled with later bottlenecks, as well as acculturation of groups.

EDIT (2 APR): Interesting is the specific subclade to which ancient Mongolic-speaking Avars belong (information from Yfull) N1c-F4205 (TMRCA ca. 500 BC), subclade of N1c-Y6058 (formed ca. 2800 BC, TMRCA ca. 2800 BC). This branch also gives the “European” branch N1c-CTS10760 (formed ca. 2800 BC, TMRCA ca. 2100 BC), and is subclade of a branch of N1c-L392 (formed ca. 4400 BC, TMRCA ca. 2800 BC). A northern expansion of N1c-L392 is probably represented by its branch N1c-Z1936 (formed ca. 2800, TMRCA ca. 2100 BC), the most likely candidate to appear in the Kola Peninsula in the Bronze Age as the Palaeo-Laplandic population (see here). Read more about potential routes of expansion of haplogroup N.

On the other hand, R1a-Z280 lineages form a tight cluster connecting Permic with Ugric groups, with R1a-Z93 showing early isolation (probably) between Cis-Urals and Trans-Urals regions. While both Corded Ware lineages in Finno-Ugrians are most likely related to the Abashevo expansion through Seima-Turbino and the Andronovo-like Horizon (and potentially later Eurasian expansions), a plausible hypothesis would be that Finno-Ugrians are related to an expansion of R1a-Z283 haplogroups (we already knew about the Finno-Permic connection), while the ancient connection between Permians and Hungarians with R1a-Z93 would correspond to this haplogroup’s potentially tighter link with an early Samoyedic split.

I don’t think that an explosive expansion of eastern Corded Ware groups of R1a-Z645 lineages will show a clear-cut division of haplogroups among Eastern Uralic groups, though, and culturally I doubt we will have such a clear image, either (similar to how the explosive expansion of Bell Beakers cannot be easily divided by regional/language group into R1b-L151 subclades before the known bottlenecks). Relevant in this regard are the known Z93 samples from the Árpád dynasty.

Nevertheless, this data may represent a slightly more recent wave of R1a-Z280 lineages linked to the expansion of Ugric into the Trans-Uralian region, after their split from Finno-Permic, still in close contact with Indo-Iranians in Poltavka and Sintashta-Potapovka, evident from the early and late Indo-Iranian borrowings, during a common period when Samoyedic had already separated.

Such a “Z283 over Z93” layer in the Trans-Urals (and Cis-Urals?) forest-steppes would be similar to the apparent replacement of Z284 by Z282 in the Eastern Baltic during the Bronze Age (possibly with the second or Estonian Battle Axe wave or, much more likely during later population movements). Such an early R1a-Z93 split could potentially be supported also by the separation into bottlenecks under “Northern” (R1a-Z283) Finno-Ugric-speaking Abashevo-related groups and “Southern” (R1a-Z93) acculturated Indo-Iranian-speaking Abashevo migrants developing Sintashta-Potapovka admixing with Poltavka R1b-Z2103 herders.

Modified image, from Underhill et al. (2015). Spatial frequency distributions of Z282 (green) and Z93 (blue) affiliated haplogroups.. Notice the potential Finno-Ugric-associated distribution of Z282 (especially R1a-M558, a Z280 subclade), the expansion of R1a-Z2123 subclades with Central Asian forest-steppe groups.


Let’s review some of the most common myths about Hungarians (and Finno-Ugrians in general) repeated ad nauseam, side by side with my assertions:

❌ N (especially N1c-Tat) in ancient and modern samples represent the True Uralic™ N1c peoples including Magyar tribes? Nope.

✅ Ancient N (especially N1c-Tat) lineages among Uralic populations expanded relatively recently, and differently in different regions (including eastern steppe nomads and northern arctic populations) not associated with a particular language or language group? Yep (read the series on Corded Ware = Uralic expansion).

❌ Modern Hungarian R1a-Z280 lineages represent the majority of the native population, poor Slavic ‘peasants’ from the Carpathian Basin, forcibly acculturated by a minority of bad bad Hungarian hordes? Nope.

✅ Modern Hungarian R1a-Z280 subclades represent Ugric lineages in common with ancient R1a-Z645 Finno-Ugric populations from north-eastern Europe and the Trans-Urals? Yep (see Avars and Ugrians).

❌ Modern Hungarian R1a-Z93 lineages represent acculturated Iranian/Turkic peoples from the steppes? Not likely.

✅ Modern Hungarian R1a-Z93 lineages represent a remnant of the expansion of Corded Ware to the east, potentially more clearly associated with Samoyedic? Much more likely.

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).

Sooo, the theory of a “diluted” Y-DNA in Modern Hungarians from originally fully N-dominated conquerors subjugating native R1a-Z280 Slavs from the Carpathian Basin is not backed up by genetic studies? The ethnic Iranian-Turkic R1a-Z93 federation in the steppes that ended up speaking Magyar is not real?? Who would’ve thunk.

Another true story whose rejection in genetics could not be predicted, like, not at all.

Totally unexpected, too, the drift of “R1a=IE” fans with the newest genetic findings towards a Molgen-like “Yamna/R1b = Vasconic-Caucasian”, “N1c = Uralic-Altaic”, and “R1a = the origin of the white world in Mother Russia”. So much for the supposed interest in “Steppe ancestry” and fancy statistics.


Genetic landscape and past admixture of modern Slovenians


Open access Genetic Landscape of Slovenians: Past Admixture and Natural Selection Pattern, by Maisano Delser et al. Front. Genet. (2018).

Interesting excerpts (emphasis mine):


Overall, 96 samples ranging from Slovenian littoral to Lower Styria were genotyped for 713,599 markers using the OmniExpress 24-V1 BeadChips (Figure 1), genetic data were obtained from Esko et al. (2013). After removing related individuals, 92 samples were left. The Slovenian dataset has been subsequently merged with the Human Origin dataset (Lazaridis et al., 2016) for a total of 2163 individuals.

Y chromosome

First, Y chromosome genetic diversity was assessed. A total of 52 Y chromosomes were analyzed for 195 SNPs. The majority of individuals (25, 48.1%) belong to the haplogroup R1a1a1a (R-M417) while the second major haplogroup is represented by R1b (R-M343) including 15 individuals (28.8%). Twelve samples are assigned to haplogroup I (I M170): five and two samples belong to haplogroup I2a (I L460) and I1 (I M253), respectively, while the remaining five samples did not have enough information to be further assigned.

PCA of Slovenian samples with European populations (Slovenian_HO_EU dataset). For details regarding the populations included, see Supplementary Table 1.


Considering the unbalanced sample size of the Slovenian population compared to the other populations included in the dataset, a subset of 20 Slovenian individuals randomly sampled was used.

All Slovenian samples group together with Hungarians, Czechs, and some Croatians (“Central-Eastern European” cluster) as also suggested by the PCA. All Basque individuals with few French and Spanish cluster together (“Basque” cluster) while a “Northern-European” cluster is made of the majority of French, English, Icelanders, Norwegians, and Orcadians. Five populations contributed to the “Eastern-European” cluster including Belarusians, Estonians, Lithuanians, Mordovians, and Russians. Western and South Europe is split into two cluster: the first (“Western European” cluster) includes all Spanish individuals, few French, and some Italians (North Italy) while the second (“Southern-European” cluster) groups Sicilians, Greeks, some Croatians, Romanians, and some Italians (North Italy).

Admixture Pattern and Migration

Modified image, from the paper (Central-East Europeans marked). Unsupervised admixture analysis of Slovenians. Results for K = 5 are showed as it represents the lowest cross-validation error. Slovenian samples show an admixture pattern similar to the neighboring populations such as Croatians and Hungarians. The major ancestral components are: the blue one which is shared with Lithuanians and Russians, followed by the dark green one that is mostly present in Greek samples and the light blue which characterizes Orcadians and English. For population acronyms see Supplementary Table 1.

All Slovenian individuals share common pattern of genetic ancestry, as revealed by ADMIXTURE analysis. The three major ancestry components are the North East and North West European ones (light blue and dark blue, respectively, Figure 3), followed by a South European one (dark green, Figure 3). Contribution from the Sardinians and Basque are present in negligible amount. The admixture pattern of Slovenians mimics the one suggested by the neighboring Eastern European populations, but it is different from the pattern suggested by North Italian populations even though they are geographically close.

Using ALDER, the most significant admixture event was obtained with Russians and Sardinians as source populations and it happened 135 ± 9.31 generations ago (Z-score = 11.54). (…) When tested for multiple admixture events (MALDER), we obtained evidence for one admixture event 165.391 ± 17.1918 generations ago corresponding to ∼2620 BCE (CI: 3101–2139) considering a generation time of 28 years (Figure 4), with Kalmyk and Sardinians as sources.

We then modeled the Slovenian population as target of admixture of ancient individuals from Haak et al. (2015) while computing the f3(Ancient 1, Ancient 2, Slovenian) statistic. The most significant signal was obtained with Yamnaya and HungaryGamba_EN (Z-score = -10.66), followed by MA1 with LBK_EN (Z-score -9.7) and Yamnaya with Stuttgart (Z-score = -8.6) used as possible source populations (Supplementary Figure 5).

We found a significant signal of admixture by using both pairs as ancient sources. Specifically, for the pair Yamnaya and Hungary_EN the admixture event is dated at 134.38 ± 23.69 generations ago (Z-score = 5.26, p-value of 1.5e-07) while for Yamnaya and LBK_EN at 153.65 ± 22.19 generations ago (Z-score = 6.92, p-value 4.4e-12). Outgroup f3 with Yamnaya put Slovenian population close to Hungarians, Czechs, and English, indicating a similar shared drift between these population with the Steppe populations (Supplementary Figure 6).

Admixture events identified with ALDER and MALDER. The gray dots represent significant admixture events detected with ALDER using Slovenians as target, the solid line represents the single admixture event detected using MALDER, dashed lines represent the confidence interval. Only the significant results after multiple testing correction are plotted. For ALDER results see Supplementary Table 5.

Not that any of this would come as a surprise, but:

  • R1a-M458 and some R1a-Z280 (xR1a-Z92) lineages (found among Slovenes) were associated with the Slavic expansion, likely with the Prague-Korchak culture, originally stemming probably from peoples of the Lusatian culture. Other R1a-Z280 lineages remained associated with Uralic peoples, and some became Slavicized only recently.
  • PCA keeps supporting the common cluster of certain West, South, and East Slavs in a “Central-Eastern European” cluster, distinct from the “North-Eastern European” cluster formed by modern Finno-Ugrians, as well as ancient Finno-Ugrians of north-eastern Europe who were only recently Slavicized.
  • Admixture supports the same ancient ‘western’ (a core West+South+East Slavic) cluster, and the admixture event with Yamna + Hungary_EN is logically a proxy for Yamna Hungary being at the core of ancestral Central-East population movements related to Bell Beakers in the mid- to late 3rd millennium.

The theory that East Slavs are at the core of the Slavic expansion makes no sense, in terms of archaeology (see Florin Curta’s dismissal of those recent eastern ‘Slavic’ finds, his commentary on 19th century Pan-Slavic crap, or his book on Slavic migrations), in terms of ancient DNA (the earliest Slavs sampled cluster with modern West Slavs, distant from the steppe cluster, unlike Finno-Ugrians), or in terms of modern DNA.

I don’t know where exactly this impulse for the theory of Russia being the cradle of Slavs comes from today (although there are some obvious political trends to revive 19th c. ideas), but it was always clear for everyone, including Russians, that East Slavs had migrated to the east and north and assimilated indigenous Finno-Ugrians, apart from Turkic-, Iranian-, and Caucasian-speaking peoples to the east. Genetics is only confirming what was clear from other disciplines long ago.


The traditional multilingualism of Siberian populations


New paper (behind paywall) A case-study in historical sociolinguistics beyond Europe: Reconstructing patterns of multilingualism in a linguistic community in Siberia, by Khanina and Meyerhoff, Journal of Historical Sociolinguistics (2018) 4(2).

The Nganasans have been eastern neighbours of the Enets for at least several centuries, or even longer, as indicated in Figures 2 and 3.10 They often dwelled on the same grounds and had common households with the Enets. Nganasans and Enets could intermarry (Dolgikh 1962a), while the Nganasans did not marry representatives of any other ethnic groups. As a result, it was not unusual for Enets and Nganasans to live in the same tent and/or to have common relatives. Such close contact must clearly have favoured acquisition of Nganasan by Enets children and of Enets by Nganasan children from an early age.

The Nenets have been close neighbours of all the Enets groups more recently (Figures 2 and 3). In the seventeenth century, there were only warlike contacts between the Nenets and the Enets, while in the eighteenth century the Nenets started to live on the traditional Enets lands, on the western bank of the Yenisey river, with more peaceful interactions reported. (…) Since then the same situation of intermarriages and common households has been attested for these western Enets neighbours as with the Nganasans (Dolgikh 1962a), and this has also created conditions favouring early acquisition of both languages by children.

The Enets and neighbouring peoples in the middle of the seventeenth century; map by Yuri Koryakov (, adapted from Dolgikh (1960).

As for the Evenkis and the Selkups, the Enets had regular contact with these peoples (Figures 2 and 3), though they were not their close neighbours: in fact, geographically, the Selkups were not neighbours at all by the end of the nineteenth century. The Evenkis had always been direct south-eastern neighbours (…) Contacts with Selkups could be trade based, or they could simply be occasional encounters on adjacent lands. (…) [With Evenkis] some sporadic contacts were similar in nature to those with the Selkups, however many other contacts were war-like. Traditionally, the Enets considered the Evenkis to have a martial spirit, and the Evenkis were known as being accustomed to stealing Enets women. A number of stories in Dolgikh (1961) concern Evenkis stealing Enets women and Enets men going to Evenki lands to find and return them. It is clear, therefore, that if Evenki or Selkup were acquired by the Enets, this happened later in life, and this acquisition required particular conditions for it, i. e. it was not readily acquired through regular or harmonious contact (as with Nganasan).

In a pattern similar to the situation with Nganasan, in the second half of the twentieth century most Enets elders could speak Nenets (Vasil’jev 1963; Eugen Helimski p.c., the lead author’s fieldwork experience).

The Enets and neighbouring indigenous peoples: end of the nineteenth century – beginning of the twentieth century; map by Yuri Koryakov (, adapted from
Bruk (1961).

At the start of the period studied, in the 1850s, the Enets linguistic community could be characterized as multilingual in the following five languages: Enets, Nganasan, Nenets, Evenki, and Russian (Figure 4). The number of Enets individuals who were able to converse in each of the other four languages differed and generally was a property of the individuals who had regular social contact with speakers of the other four languages. (…) Note that in all cases of interethnic communication there could well be a lack of perfect proficiency in a language for which the multilingualism is ascribed to the Enets community or Enets individuals: as Braunmüller and Ferraresi (2003: 3) put it: “Nobody would ever have expected to know other languages ‘perfectly’ (whatever that may mean in detail). This expectation seems to be a quite modern idea when discussing issues of bilingualism or multilingualism in general”.

The complex interactions of Siberian populations during the 17th-19th centuries offer a reasonably good picture of the life in the centuries before these accounts, when Samoyedic peoples migrated northwards, and Palaeo-Siberian and Tungusic populations were gradually assimilated into their Uralic culture and language, through intermarriage and close contacts among naturally nomadic populations.

You can read more about the origin of Nganasans – and other modern Samoyedic-speaking peoples – as Palaeo-Siberian populations (hence probably speaking Palaeo-Siberian languages more or less related to each other) who adopted Samoyedic languages in Wikipedia, which offers a summary of Boris Dolgikh’s On the Origin of the Nganasans (1962). Dolgikh is one of the main sources of information for these Siberian groups, as is reflected in this paper, too.

Map of distribution of Samoyedic languages (red) in the XVII century (approximate; hatching) and in the end of XX century (continuous background). Notice late expansion to north and west into the typical territory where Nomadic peoples roamed. Modified from Wikipedia, with the Tuva region labelled (see a recent genetic study on the Tuva region, one of the most likely to be originally Samoyedic-speaking).

Why some geneticists are using Nganasans – in fact the latest Palaeo-Siberians to learn Samoyedic, already during historic times – as a model for the expansion of Uralic? I have never understood that. Among the many cases of circular reasoning based on modern populations that have been created since the start of population genomics, the use of Nganasans as a model of ‘true Uralians’ is probably the most clearly frontally opposed to what was well known in anthropology before geneticists started this new field.

If Kallio is right, most “eastern homeland” proposals are due to the interest of Russian nationalism, which is sadly quite likely to be influencing genetic research, too. It’s like letting Hindu nationalists influence publications on steppe-related migrations. As David Reich puts it in his book:

The tensest twenty-four hours of my scientific career came in October 2008, when my collaborator Nick Patterson and I traveled to Hyderabad to discuss these initial results with Singh and Thangaraj.

Our meeting on October 28 was challenging. Singh and Thangaraj seemed to be threatening to nix the whole project. Prior to the meeting, we had shown them a summary of our findings, which were that Indians today descend from a mixture of two highly divergent ancestral populations, one being “West Eurasians.” Singh and Thangaraj objected to this formulation because, they argued, it implied that West Eurasian people migrated en masse into India. They correctly pointed out that our data provided no direct evidence for this conclusion. They even reasoned that there could have been a migration in the other direction, of Indians to the Near East and Europe. (…) They also implied that the suggestion of a migration from West Eurasia would be politically explosive. They did not explicitly say this, but it had obvious overtones of the idea that migration from outside India had a transformative effect on the subcontinent.

If you add the nation-building myths in Eastern Europe (like the Russian Euro-Asian movements) to the now prevalent Indo-European—CWC idea, and a Siberian ancestry peaking in the Arctic, with little demographic or political relevance of modern Uralic-speaking peoples, you have clearly an explosive sociopolitical mix (based on a mythical Pan-Eurasian Indo-Slavonic) in the making…

Russia as the Euro-Asian Empire. Source: A. Dugin (1999), p. 415. From Eberhardt (2018).


New monograph on The Tale of Igor’s Campaign (in Russian)


Sergej Nikolaev has published a new monograph on The Tale of Igor’s Campaign (you should download and open it in a PDF viewer to view some special characters correctly):

Слово о полку Игореве»: реконструкция стихотворного текста, by С.Л. Николаев (2018).

Abstract (in Russian).

Текст «Слова о полку Игореве» (далее «Слово») дошел до нас в двух неточных (отредактированных) копиях со списка нач. XVI в. и нескольких выписках из него. Наслоения, привнесенные переписчиком нач. XVI в. (или несколькими переписчиками) – редактура в русле 2 го южнославянского влияния и поздние диалектизмы – непоследовательны (§9.3.1) и не настолько исказили стихотворный текст рубежа XII–XIII вв., чтобы сделать невозможной его реконструкцию. «Слово» по своему жанру (светская поэзия) не принадлежит к текстам, которые по многу раз переписывались в монастырских скрипториях. Поэтому не исключено, что рукопись нач. XVI в. является хотя и небрежной, но первой по счету копией древнерусского оригинала.

«Слово» могло звучать приблизительно так, как я предлагаю в своей реконструкции, морфология и акцентология языка его автора могли быть устроены так, как я предполагаю, и оно могло быть создано в реконструируемой мною системе стихосложения. Однако в действительности многое могло быть устроено иначе. Реконструкция акцентологической системы и две другие гипотезы (о неравносложной силлаботонике и об опциональном прояснении слабых редуцированных) замкнуты друг на друге и образуют circulus in probando. Реконструируемая для «Слова» акцентологическая система выводится из праславянской реконструкции и подтверждается данными современных диалектов, однако она не засвидетельствована в древнерусских памятниках. Слабым местом моей реконструкции является прояснение слабых редуцированных в позициях, где оно нужно исключительно из метрических соображений. В работе, подобной этой, невозможно избежать домыслов и рискованных допущений, ряд выдвинутых гипотез находится «на грани фола», однако в целом моя реконструкция построена на фактах и их интерпретациях, являясь таким образом научным исследованием. В работе используютмя результаты смежных наук ‒ в первую очередь стиховедения. Представленная в настоящей книге реконструкция «Слова» является первым опытом системного моделирования стихотворного текста на гипотетическом древнерусском диалекте XII‒XIII в., существование которого весьма вероятно. Мне хотелось бы надеяться, что моя работа внесет свою скромную лепту в изучение великого памятника древнерусской литературы.

The Tale of Igor’s Campaign is probably the oldest Slavic epic available, recorded later than what oral tradition and linguistic details reflect, like the oldest Indo-Iranian texts. It contains many details interesting for Proto-Slavic (and North-West Indo-European) language and culture reconstruction.

For those confusing recent attestation of languages with their relevance for comparative grammar, I would suggest Martin Joachim Kümmel‘s article Is ancient old and modern new? Fallacies of attestation and reconstruction (with special focus on Indo-Iranian).

Featured image: Viktor Vasnetsov. After Igor Svyatoslavich’s fighting with the Polovtsy (Photographer, referenced in Wikipedia).


WordPress Translation Plugin – now using Google Translation from and into Swedish, Finnish, Danish, Norwegian, Polish, Czech, Romanian, Bulgarian, Hindi, Arabic, Japanese, Chinese, etc.

The latest improvements added to the Indoeuropean Translator Widget have been included in the simpler WordPress Translation Plugin available in this personal blog.

It now includes links to automatic translations from and into all language pairs offered by Google Translation Engine, apart from other language pairs (from individual languages, like English or Spanish) into other online machine translators, viz Tranexp or Translendium.

Available language pairs now include English, Arabic, Bulgarian, Catalan*, Czech, Chinese (traditional/simplified), Welsh*, Danish, German, Greek, Spanish, Persian*, French, Hindi, Croatian, Icelandic*, Italian, Hebrew*, Latin*, Korean, Hungarian*, Dutch, Japanese, Norwegian (Bokmål), Polish, Portuguese (Brazilian Portuguese*), Romanian, Russian, Slovenian*, Serbian*, Swedish, Finnish, Tagalog*, Turkish* and Ukrainian*.

WordPress Translation Plugin: ‘Indoeuropean Translator Widget’ – now also Swedish, Danish, Norwegian, Polish, Greek, Russian, Polish, Romanian, Finnish, Chinese, Japanese, Korean, …

The latest upgrades are only available in the simpler WordPress Translation Widget Plugin.

You can download it from the official WordPress Plugin Repository site. New upgrades will automatically appear on your WordPress blog dashboard.

As always, this widget plugin, when activated from the Design tab of your WordPress blog dashboard, will put links – with the tag rel="nofollow", so that search engines don’t follow them – to automatic translations of that website by mainly Google Translation Engine language pairs, to and from (at least) all of these ones into each other, all in all 24×23 language pairs [more or less the number of language translations needed in the European Union…]

The widget offers translations from and into these languages:

English, German, French, Spanish, Italian, Portuguese, Dutch, Arabic, Bulgarian, Czech, Chinese (traditional and simplified), Danish, Greek, Croatian, Hindi, Korean, Japanese, Norwegian, Polish, Romanian, Russian, Swedish and Finnish.

For the latest changes in version 1.1.1 – following Google Translation Engine changes and improvements, you can visit the official release note.

Upgrades for the simple WordPress plugin available in this blog are therefore discontinued not discontinued, due to the need expressed by some bloggers to have this simpler PHP code inserted in their themes, instead of the less flexible widget.

Thanks for the support.

How ‘difficult’ (using Esperantist terms) is an inflected language like Proto-Indo-European for Europeans?

For native speakers of most modern Romance languages (apart from some reminiscence of the neuter case), Nordic (Germanic) languages, English, Dutch, or Bulgarian, it is usually considered “difficult” to learn an inflected language like Latin, German or Russian: cases are a priori felt as too strange, too “archaic”, too ‘foreign’ to the own system of expressing ideas. However, for a common German, Baltic, Slavic, Greek speaker, or for non-IE speakers of Basque or Uralic languages (Finnish, Hungarian, Estonian), cases are the only way to express common concepts and ideas, and it was also the common way of expression for speakers of older versions of those very uninflected languages, like Old English, Old Norse or Classical Latin; and their speakers didn’t consider their languages “difficult” …

Therefore, to use different cases is the normal way to express concepts that non-inflected languages express in different ways – i.e. not “more easily”, but “differently”. That’s the point Esperantism has lost in its struggle to convince the world of its “easiness”. In fact, the idea that cases are difficult is so impregnated in Esperantism, that some did create “an old version” [probably deemed “more difficult”] of Esperanto called Arcaicam Esperantom, as a fiction of evolution from an older language…

Thus, among the European population (more than 700 million inhabitants), just around 200 million speak non-inflected languages, while the rest use at least 4 cases to express every possible concept. Within the current EU, more or less half of its speakers speak an inflected language – like German, Polish, Czech, Greek, Lithuanian, Slovenian, or non-IE Hungarian, Finnish, etc. – as their mother tongue.

For example, the literal sentence “I go to-the-house” [not exactly the common expression “I go home” which is expressed differently in each language] would be said in Spanish “voy a-la-casa”, or in French “je vais a-la-maison”, in Italian “vado a-la-casa”, etc. Therefore, in an “easy conlang” for Western European speakers, say in something called Esperanto, a sentence like “io vo a-lo-haus” is apparently “easy”, because the syntactical structure is similar to those non-inflected languages.

NOTE: In fact, there are other interesting concepts behind the use of the obligatory subject before the verb in languages like English or Esperanto, that appears usually in those languages that have reduced the verbal system; therefore, the subject is necessary only in those languages whose verbal inflection becomes too simple to express an idea that must still be expressed some way – more or less like different combinations of prepositions and articles are often needed to substitute the lost nominal inflection, as we discuss here. In those ‘less innovative’ languages that retain a rich verbal system, the subject appears for some reason, as e.g. in Spanish “yo voy a la casa”, which must be expressed differently in innovative languages, using different linguistic resources, like e.g. Eng. “I myself go to the house” (or maybe “it’s me who…“), or French “moi, je vais a la maison”. Is that obligatory subject and ‘simplified’ verbal system of Esperanto “easier”, and therefore “better”…? I guess not. It’s just an imitation of French or English that Mr. Zamenhoff deemed “better” for his creation to succeed, given the relevance of those languages (and its speakers’ acceptance) back in 1900…

On the other hand, in German it would be “Ich gehe nach-Haus-e”, in Latin, it is “vado ad-domu-m”; in Polish “idę do-dom-u” etc. The use of declensions, if compared to uninflected languages, is usually made of just a simple change of “preposition+article” -> “declension” – or, in the ‘worst’ case (as it is shown here), by a “preposition+article” -> “preposition+declension”.

To sum up, can some languages be considered “more difficult” than others? Yes, indeed. If seen from a European point of view, some linguistic features are not easy to learn: the Arab writing system, Chinese unending kanjis, Sino-Tibetan or Vietnamese tones, etc. can cause headaches to [adult] speakers willing to learn them… Also, from an English, French or Spanish point of view, learning a language like Esperanto might seem “better” because of its apparent and equivocal “easiness”… But, between (a) all Indo-European speakers learning a non-inflected language like English [or ‘easy’ Esperanto], or (b) all Indo-European speakers learning an inflected one like Proto-Indo-European?; I guess there is no language “easier” than other, and therefore the “better” option should come from other rational considerations, not just faith in the absurd ramblings of an illuminated Polish ophthalmologist.

Therefore, the question remains still the same: why on earth should any European willing to speak a common language select an invented one (from the thousand “super easy” ones available) than a natural one, like the ancestor of most of their mother tongues, Proto-Indo-European?