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Post by Admin on Dec 26, 2023 0:45:55 GMT
Results and discussion Genetic admixture between populations leaves traces in the genomes of subsequent generations, whereas linguistic contacts appear as alterations in languages.7 In human history, the spread of languages has often coincided with the movement of people, but each can occur without the other.8 Thus, inferring past population contacts based on either the current distributions of languages or genetic ancestry components alone can be misleading. Ancient DNA studies allow us to directly observe changes in a population’s gene pool through time and to resolve the correlations between genetic, archaeological, and historical linguistic data. Studies on modern genomes have shown that most present-day Uralic speakers, ranging from the Baltic Sea to western Siberia, share a modern-Siberian-like ancestry component.9,10 One notable feature in the Uralic languages’ current spatial distribution is the gap in the northwestern and central European Russia (Figure 1A). Evidence from historical linguistics suggests that Uralic speakers inhabited this area too, before the spread of Slavic, and historical sources name many of these groups.1,2,3 Despite the language extinction, present-day northwestern Russians show pronounced affinity to their Uralic-speaking neighbors, suggesting a genetic contribution from the preceding Uralic-speaking population.9,11  Figure 1. Geographic locations, radiocarbon dates, and PCA and ADMIXTURE results of the 32 samples from the Volga-Oka interfluve (A) Locations of the archaeological sites included in this study and the speaker areas of extant Uralic branches.12,13 The Hungarian speaker area resides south of the map. (B) Calibrated radiocarbon dates of the samples (see also Figures S1A–S1C and Data S1A). Bars indicate mean calibrated radiocarbon date ± 2σ. (C) PCA of 164 present-day Eurasian groups (gray). Labels indicate median coordinates of the groups. Ancient populations (colored symbols) are projected on the present-day variation. Circles indicate 31 new samples from this study; upward triangles indicate previously published samples (see also Figure S3 and Data S1B). Vertical bars show the ADMIXTURE result at K = 9 for the 31 samples (full results in Figure S2). BA, Bronze Age; IA, Iron Age; MAs, Middle Ages; H, historical. We studied 32 ancient individuals from six archaeological sites located in the Suzdal region in the Volga-Oka interfluve, using DNA sequencing and radiocarbon dating (Figures 1A, 1B, and S1A–S1C; Data S1A; STAR Methods): Bolshoye Davydovskoye 2 (BOL), representing an Iron Age culture (3rd–4th cc.; n = 9)14; Shekshovo 9 (SHE), a burial site of a large medieval settlement (10th–12th cc.; n = 9)15; Shekshovo 2 (SHK), a later burial ground of the same settlement (late 12th–13th cc.; n = 2); and post-medieval burials from Kibol 3 (KBL) (18th c.; n = 3), Kideksha (KED) (15th–18th cc.; n = 4), and Krasnoe 3 (KRS) (14th c.; n = 1). Additionally, we included one kurgan burial (GOR) (12th c.) and three medieval flat burials (GOS) (12th–13th cc.) from the town of Gorokhovets in the eastern part of the Vladimir region. We also measured stable isotope ratios of carbon and nitrogen from Bolshoye Davydovskoye 2 and Shekshovo 2 and 9 to reconstruct changes in diet and lifestyle (Figure S1D; STAR Methods). |
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Post by Admin on Dec 26, 2023 22:03:37 GMT
Genetic shift in the Volga-Oka region in the Iron Age-medieval transition
We used an in-solution capture of 1.2 million genome-wide markers and obtained 0.06–4× on-target coverage from 31 samples that had sufficient DNA preservation (STAR Methods). To view our samples in the context of present-day genetic variation, we performed principal-component analysis (PCA). In a Eurasian-wide PCA, PC1 separates West Eurasia from East Asia, which are connected by three genetic clines, separated by PC2 (Figure 1C). These clines roughly correspond to ecoregions of Central Eurasia; the uppermost cline follows to the forest-tundra biome, and most Uralic-speakers fall on that cline.10 Consistent with their geography, the Iron Age individuals from Bolshoye Davydovskoye fall on this cline, between the Russians from the coast of the White Sea (Arkhangelsk region) and the present-day Volga populations. The results of ADMIXTURE16 also showed that Bolshoye Davydovskoye individuals carried Siberian ancestry, as do most present-day Uralic-speakers (Figures 1C and S2). This ancestry component is maximized in present-day Nganasans from the Taymyr Peninsula, but it may have been more widespread in the past.
The post-Iron Age samples from Shekshovo 9, Gorokhovets, Kibol, Kideksha, and Krasnoe fall closer to the West European cluster on the PCA than the Bolshoye Davydovskoye group, indicating a genetic shift after the Iron Age (Figures 1C and S3). However, approximately half of the medieval individuals still fall close to Bolshoye Davydovskoye individuals, whereas the other half cluster with present-day East Slavs. This pattern suggests an ongoing admixture or presence of two distinct populations at the time. Post-medieval individuals fall largely among modern south-central European Russians and did not show similar variation in ancestry as their predecessors.
The results from the dietary isotope analysis also reflect a shift between the Iron Age and medieval times (Figure S1D). The Bolshoye Davidovskoye individuals showed a diet with a high protein consumption and C4 plant use (likely millet), whereas the Shekshovo 9 individuals had a C3-plant-based diet. Despite genetic scattering of the Shekshovo 9 samples, isotopic values indicate a similar diet within this group.
For downstream analyses, we assigned our samples to four analysis clusters based on archaeological context, radiocarbon date, and the PCA and ADMIXTURE results (Figure S3; Data S1A): Iron Age (VolgaOka_IA, n = 7), medieval Iron Age-like (VolgaOka_MA1, n = 4), medieval East European-like (VolgaOka_MA2, n = 6), and post-medieval individuals from Kideksha and Kibol (VolgaOka_H, n = 4) (Figure S3). Two samples were excluded from the analysis clusters due to their close genetic relatedness to other individuals—one due to contamination and seven because they were genetic or chronological outliers.
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Post by Admin on Dec 27, 2023 21:38:41 GMT
Iron Age Volga population shows genetic affinities to Siberia To measure allele sharing between our analysis clusters and present-day populations, we calculated outgroup f3 statistics. The results indicated high levels of allele sharing with Lithuanians for all analysis clusters (Data S2A). For each analysis cluster, we tested the symmetry of relatedness (cladality) with relevant present-day populations (“Target”) by calculating f4 statistics “f4(Mbuti, Modern_group; Analysis_cluster, Target)” (Figure 2A; Data S2B; STAR Methods). We found that VolgaOka_MA2 was cladal with non-Russian East Slavs (Belarusians, Ukrainians, and North Ukrainians) and present-day Russians from the Ryazan region, whereas VolgaOka_H was cladal only with the Ryazan Russians. VolgaOka_IA and VolgaOka_MA1 were not cladal with any of the tested Targets; however, they had the smallest number of significantly non-zero estimates with present-day Russians from Archangelsk region, suggesting that northern European Russians are their closest contemporary relatives.  Figure 2. Results from f4 statistics (A) Tests for cladality with Lithuanians compared with 400 present-day populations. Outlined circles indicate statistically significant (|Z| ≥ 3) estimates of f4 (see also Data S2B). Blue hues indicate that the analysis cluster shares more alleles with the tested modern group than present-date Lithuanians, and red hues indicate vice versa. (B) Relative affinity of ancient and present-day groups to Siberian ancestry (Krasnoyarsk_Krai_BA; left panel) and EEHG ancestry (right panel) in ancient and modern groups (see also Data S2C). Present-day populations are colored by their language group. Ancient groups are ordered by time and present-day groups by their Siberian affinity. Error bars indicate three standard errors to show statistically significant deviations from 0. The cladality tests revealed an allele sharing boundary between the East Eurasians and VolgaOka_IA and VolgaOka_MA1 (Figure 2A). The boundary approximately corresponds to the Ural Mountains: VolgaOka_IA and VolgaOka_MA1 shared significantly more alleles with the populations east of the Urals than present-day Lithuanians. Nganasans gave the lowest f4 estimate for both VolgaOka_IA and VolgaOka_MA1, suggesting that the observed eastern affinity stems from the same Siberian ancestry we saw in the ADMIXTURE analysis (Figure S2; Data S2B). A similar but more subtle pattern in allele sharing was also observed for VolgaOka_H, but not for VolgaOka_MA2, indicating that VolgaOka_MA2 does not carry additional Siberian ancestry. To study the relative affinity to Siberian ancestry (using a Bronze Age southern Siberian genome17 as a proxy) in our study populations, we calculated “f4(Mbuti, Krasnoyarsk_Krai_BA; Test, Lithuanian)”, where “Test” was substituted with selected modern and ancient populations, including our analysis clusters. The results show that in terms of allele sharing with Krasnoyarsk_Krai_BA, VolgaOka_IA and VolgaOka_MA1 fall in the same range with North Russians from Archangelsk and Vologda, Veps, Karelians, Finns, and Mordovians (Figure 2B; Data S2C). The Volga-Oka region is close to the area that was inhabited by East European hunter-gatherers (EEHGs) during the Mesolithic. This group contributed ancestry to many later populations. To examine the relative affinity to EEHG, we calculated “f4(Mbuti, EEHG; Test, Lithuanian)”. The results indicated excess EEHG ancestry in VolgaOka_IA, Estonia_BA, and Russia_Kola_BA, although the sharing was statistically significant only for Russia_Kola_BA (Figure 2B; Data S2C). |
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Post by Admin on Dec 31, 2023 1:07:23 GMT
Central Russian population formed as a product of local admixture To model the ancestry composition of our analysis clusters and other relevant populations, we used qpAdm. First, we constructed a consistent distal model with five sources (Krasnoyarsk_Krai_BA, West European hunter-gatherers [WEHGs], EEHG, Yamnaya_Samara, and European Neolithic farmers [LBK_EN]) across all groups, followed by proximal models customized for each analysis cluster (STAR Methods). In the distal model, only VolgaOka_IA, VolgaOka_MA1, and present-day Udmurt had the best fit with all five sources (Figure 3A; Data S3A). For most populations, a four-way model without EEHG was a better fit. Finland_Levanluhta_IA and Russia_Kola_BA also harbored EEHG ancestry, but unlike VolgaOka_IA, VolgaOka_MA1, and Udmurt, they were best modeled without WEHG and Steppe ancestry. The EEHG component is also present in Shekshovo 2 outliers, but we caution that our model is targeted to populations of north-western Eurasia and may not provide meaningful results for these outliers.  Figure 3. Results from qpAdm analyses (A) Distal model fitted on selected ancient and present-day groups. Ancient populations are in the order from the oldest to youngest as indicated by an arrow. Present-day groups are in the descending order by Siberian ancestry. Error bars indicate one standard error. p values from chi-square test for each model are shown inside the square brackets. We show models that have a p value ≥ 0.01. Right populations used: Ethiopia_4500BP.SG, CHG, Raqefet_M_Natufian, Onge, Villabruna, ANE, Mixe, and SHG (see also Data S3A). (B) Sequential proximal models for the Volga-Oka time transect groups. Right populations: Ethiopia_4500BP.SG, Krasnoyarsk_Krai_BA, WEHG, EEHG, Yamnaya_Samara, and LBK_EN. LBK_EN, European Neolithic farmers; EEHGs, East European hunter-gatherers; WEHGs, West European hunter-gatherers (see also Data S3B and S3C). To pinpoint temporally or geographically proximate populations that may have contributed to VolgaOka_IA, we tested several potential models. We used proxy sources due to sparse sampling of the area. We used Russia_Kola_BA as the source of Siberian ancestry because it harbored both Siberian and EEHG components, which we detected in VolgaOka_IA. As Western sources, we tested ancient Baltic populations and Fatyanovo, and for Steppe ancestry, we used Iron Age and Middle-Late Bronze Age Steppe groups from surrounding regions. The best-fitting models indicated that VolgaOka_IA shared approximately half of its ancestry with a population related to Baltic Iron Age individuals (800 BCE–50 CE), and 25% of its ancestry related to Russia_Kola_BA and 25% to Iron Age Steppe (Figure 3B; Data S3B). Thus, the Volga-Oka interfluve appears to have been at the crossroads of gene flow from several directions, although we do note that the proximal origin of these components in the Suzdal Iron Age gene pool may lie elsewhere. Interestingly, Fatyanovo did not provide a feasible ancestry source for VolgaOka_IA in any of the tested models, indicating a lack of genetic contribution from the Fatyanovo people who inhabited the Volga-Oka region in the Bronze Age. We used VolgaOka_IA in turn as a source to model the medieval admixture between early Slavs and Uralic-speaking groups. Lacking ancient DNA data from early Slavs, we tested modern populations to approximate Slavic ancestry: Belarusian, Ukrainian, and North Ukrainian (East Slavs) and Polish and Sorb (West Slavs). East Slavs generally provided a better source of Slavic ancestry than West Slavs. We found that VolgaOka_MA2 could be sufficiently modeled with Slavs as the sole source, supporting the idea that VolgaOka_MA2 represents an unadmixed early Slavic population (Figure 3B; Data S3B). On the contrary, VolgaOka_MA1 required a substantial contribution from VolgaOka_IA. Post-medieval VolgaOka_H also required VolgaOka_IA-related ancestry, but in a smaller proportion. Alternatively, VolgaOka_H could be modeled as a mixture of VolgaOka_MA1 and VolgaOka_MA2 clusters, consistent with local admixture. According to this model, the Slavic-like VolgaOka_MA2 contributed approximately 70% of ancestry to the post-medieval population. We extended the above mixture models to individual level to assess variation in the admixture proportions in post-Iron Age individuals. Consistent with the cluster-level models, most individuals assigned to the VolgaOka_MA2 cluster could be modeled without any VolgaOka_IA ancestry (Data S3D). However, individuals assigned to the VolgaOka_MA1 cluster all carried varying proportions (35%–75%) of VolgaOka_IA ancestry. Finally, we dated the arrival of the Siberian ancestry into our analysis clusters using DATES.18 We used Nganasans and Lithuanians as proxy sources for Siberian and European ancestries. VolgaOka_IA and VolgaOka_MA1 had admixture times that corresponded to Bronze Age and Iron Age, respectively (Data S3E). Meanwhile, VolgaOka_MA2 and VolgaOka_H had more recent admixture times: the mean admixture dates (assuming a 29-year generation time) fell on the 8th and 9th centuries, respectively, corresponding well with the assumed beginning of the Slavic settlement in the Volga-Oka region. |
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Post by Admin on Jan 1, 2024 0:24:48 GMT
Outliers highlight the connectedness of the medieval Suzdal
We detected several genetic outliers in our dataset. On the West Eurasian PCA, one individual from Bolshoye Davydovskoye 2 (BOL006) falls closer to their medieval successors than the main VolgaOka_IA group (Figure S3). Similarly, one individual from Shekshovo 9 (SHE008) falls closer to Central and West Europeans than the rest of the Shekshovo 9 individuals. Most strikingly, both individuals from Shekshovo 2 (SHK001 and SHK002) fell far from other individuals in our dataset, closer to East Asia and the “forest-steppe cline” in the Eurasian-wide PCA (Figure 1C). Their closest PCA neighbors were Kazakhs, Karakalpaks, Siberian Tatars, and other Turkic-speaking groups from Central Asia and Siberia. Both individuals also carried mitochondrial haplogroups that are more common in Asia than in Europe.19,20 In cladality f4 tests, we found the smallest number of significantly non-zero estimates with Karakalpaks, suggesting genetic similarity (Data S2B). In a previous study, their strontium values indicated a non-local origin,21 further supporting the interpretation that these individuals had moved to the Volga area in their adulthood. These two men, who died at a young age, may represent Turkic-speaking groups whose members were in the military service in Kievan Rus’, mostly guarding its southern borders.22,23
Lastly, the earliest individual from Kideksha (KED004) carried an intriguing mixture of ancestries. On the West Eurasian PCA, this individual falls within the space between European and Iranian clines (Figure S3). This individual also carried a geographically unusual mitochondrial haplogroup F2e, mostly found in present-day East Asians and mainland Southeast Asians.24 ADMIXTURE suggested that this individual has genetic affinity to ancient and present-day Iranians, and thus we fitted qpAdm models with temporally proximate Iranian-related sources (Figure S2; Data S3D). The best model included medieval Alans from northern Caucasus in addition to VolgaOka_IA and Slavic-like ancestry. These findings highlight the connectedness and importance of the Volga-Oka interfluve during the medieval era.
Parallel development of genes and languages in the Volga-Oka interfluve
The past 1,500 years of history of the Volga-Oka interfluve are characterized by a gradual language shift from Uralic to Slavic.3 A corresponding pattern emerged from our genetic data. The Iron Age inhabitants of the Volga-Oka interfluve carried Siberian ancestry, which places them on the same genetic continuum with most present-day Uralic-speaking populations. In our modeling framework, the local Iron Age group provided a fitting source of Siberian ancestry for most of our medieval individuals. However, archaeological evidence suggests that the Bolshoye Davydovskoye people represented a unique culture that disappeared already by the 7th century,11 making them an unlikely candidate for the direct ancestors of medieval groups. Thus, although the Bolshoye Davydovskoye group may have contributed to the later population, the Uralic-speaking people who lived in the Volga-Oka interfluve at the time of the Slavic migration likely represented a closely related but separate group. One such group could be Meryans, a now-extinct Uralic-speaking group mentioned in the Chronicles, whose reconstructed speaker area covered the Suzdal region.25,26
Slavic migrations in the latter half of the first millennium shaped the linguistic landscape of northwestern Russia.1,5,27 In the 10th–12th centuries, Slavic and Uralic-speaking groups often formed multilingual communities in the northeastern regions of Kievan Rus’, where Suzdal lies. Concordantly, our dataset captures the arrival of the Slavic ancestry component and the medieval coexistence of Slavic-like and Uralic-like groups. In Shekshovo 9, we detected approximately equal numbers of individuals from both genetic groups, and their burial placement showed no apparent distinction between them. Moreover, some individuals with Uralic-like ancestry were buried with “Slavic” grave goods or a mixture of Slavic and “Uralic” items, indicating cultural integration of the groups. However, our model suggests that the Slavic-like group contributed a major proportion (70%) of ancestry to the later population. Obviously, our medieval sample may be too small to be fully representative, but the difference could also suggest additional contribution from the surrounding Slavic population in the Late Middle Ages.
Whereas historical sources indicate strong Scandinavian influence in early Rus’, we did not detect Scandinavian ancestry in our medieval individuals, which may suggest that the majority of the population in medieval Suzdal comprised of Uralic and Slavic peoples. Alternatively, the individuals with Scandinavian ancestry may have been less frequently buried in the cemeteries we sampled.
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