Genetic relationships between Eurasian steppe nomads and present-day populations

PCA on the autosomal genomic data (Fig. 1C and table S5) revealed the following: (i) Srubnaya-Alakulskaya individuals exhibited genetic affinity to northern and northeastern present-day Europeans (fig. S3), and these results were also consistent with outgroupf3 statistics (table S6 and fig. S4A). (ii) The Cimmerian individuals, representing the time period of transition from Bronze to Iron Age, were not homogeneous regarding their genetic similarities to present-day populations according to the PCA.F3 statistics confirmed the heterogeneity of these individuals in comparison with present-day populations (table S6 and figs. S3 and S4C). (iii) The Scythians reported in this study, from the core Scythian territory in the North Pontic steppe (12), showed high intragroup diversity. In the PCA, they are positioned as four visually distinct groups compared to the gradient of present-day populations (Fig. 1C): (i) A group of three individuals (scy009, scy010, and scy303) showed genetic affinity to north European populations, hereafter referred to as a north European (NE) cluster. (ii) A group of four individuals (scy192, scy197, scy300, and scy305) showed genetic similarities to southern European populations, hereafter referred to as a south European (SE) cluster. (iii) A group of three individuals (scy006, scy011, and scy193) located between the genetic variation of Mordovians and populations of the North Caucasus, hereafter referred to as a steppe cluster (SC). In addition, one Srubnaya-Alakulskaya individual (kzb004), the most recent Cimmerian (cim357), and all Sarmatians fell within this cluster. In contrast to the Scythians, and despite being from opposite ends of the Pontic-Caspian steppe, the five Sarmatians grouped close together in this cluster. (iv) A group of three Scythians (scy301, scy304, and scy311) formed a discrete group between the SC and SE and had genetic affinities to present-day Bulgarian, Greek, Croatian, and Turkish populations, hereafter referred to as a central cluster (CC). All PCA results were consistent with outgroupf3 statistics (table S6 and figs. S3 and S4, B and D). Finally, one individual from a Scythian cultural context (scy332) is positioned outside of the modern West Eurasian genetic variation (Fig. 1C) but shared genetic drift with East Asian populations (table S6 and fig. S4B).

Genetic relationships between Srubnaya-Alakulskaya and other ancient populations

The Bronze Age in Eurasia was a dynamic period with several human groups participating in different migratory processes. As a result, there were extensive interactions between European Bronze Age populations (3). The Srubnaya-Alakulskaya individuals, originating from a site of cultural dualism in the forest steppe of the Trans-Volga region, were genetically similar to the previously published Srubnaya and Andronovo individuals from the Pontic-Kazakh steppe (3,9) and to the European Bronze Age groups, including individuals of the Corded Ware, Unetice, and Bell Beaker complexes (Fig. 1C and fig. S5). Consistent with other Bronze Age populations, the Srubnaya-Alakulskaya individuals were positioned between the genetic variation of the European Mesolithic and the Near East Neolithic populations, being closer to the former and especially to the east European hunter-gatherers (Fig. 1C and figs. S6 and S8). These individuals had higher genetic affinity to Scythians compared to other Iron Age groups (fig. S9). To test whether our Bronze Age sample from a cultural mixing zone between the Srubnaya and the Alakulskaya complexes shared more genetic drift with previously published representatives of Srubnaya, we calculatedf4 statistics off4(Yoruba, SrubnayaX, SrubnayaY, BronzeX), where “BronzeX” refers to a Bronze Age Russian population. The test revealed that the Srubnaya-Alakulskaya population formed a clade together with Andronovo, Afanasievo, and Sintashta to the exclusion of the previously published data of other Srubnaya individuals (tables S7 and S8). Furthermore, to trace the plausible origin the Caucasus genetic component identified in Srubnaya-Alakulskaya individuals, we adopt thef4 statistics in the form off4(Yoruba, Srubnaya-Alakulskaya, PopulationX, Yamnaya), wherePopulationX was one of the Eurasian Bronze Age populations. The results showed that Srubnaya-Alakulskaya formed a clade together with Yamnaya to the exclusion of other Bronze Age populations from Russia, Armenia, Jordan, and Hungary. This finding indicates that the Caucasus genetic contribution to the Srubnaya-Alakulskaya individuals was mediated by steppe ancestry instead of originating from the Levant (table S9). Both meanf3 statistics within populations and conditional nucleotide diversity (21) revealed that the genetic diversity was highest in the LBA Srubnaya-Alakulskaya population from the southern Ural region compared to all other Eurasian Bronze Age populations (Fig. 2, A and B, and table S10).

To evaluate the ancestral components of Srubnaya-Alakulskaya, we conducted ADMIXTURE analysis forK = 2 toK = 15 ancestral clusters (fig. S10A).K = 15 clusters revealed that Srubnaya-Alakulskaya individuals consisted of two major ancestral components; first, an “orange” component predominantly found in west and NE hunter-gatherers (WHG) and in present-day NE populations, and second, a “light green” component typical of Caucasus hunter-gatherers (CHG) found in south Asian (SA) modern populations. The component associated with Neolithic groups and present-day Near Eastern populations (NEN, “dark red”) contributed less to our Srubnaya-Alakulskaya individuals compared to the European Bronze Age populations (Fig. 2C and fig. S10B).

Genetic relationships between the Iron Age nomads and other ancient populations

In the 10th century BCE, during the transition from the Bronze Age to the Iron Age, the Cimmerians appear in the Pontic-Caspian steppe. In the PCA, the chronologically youngest Cimmerian individual (cim357) grouped within the SC including all Sarmatians, one Srubnaya-Alakulskaya individual, and three Scythian individuals. The other Cimmerian individuals were positioned in close proximity to a number of eastern Iron Age individuals from the Altai region (3), as well as Aldy-Bel and Zevakino-Chillikta individuals of the Altai and Western Mongolia regions (Fig. 1C and fig. S9) (12). We tested whether Cimmerians formed a clade with the subsequent Iron Age populations including Scythians and Sarmatians, to the exclusion of Bronze Age populations by calculatingf4 statistics in the form off4(Yoruba, Cimmerians; Srubnaya&Scythians&Sarmatians, BronzeAgePopulation), showing that the Cimmerians shared more drift with the Bronze Age populations of Russia compared to the Srubnaya/-Alakulskaya but not compared to Scythians or Sarmatians (Fig. 3A and tables S11, S12, and S16). The Cimmerians shared more drift with the far eastern Karasuk population compared to the geographically more closely located Srubnaya/-Alakulskaya population (table S16), corroborating the existence of the “Karasuk-Cimmerian cultural-historical community” (22). Pairwise mismatch estimates revealed a slightly higher genetic diversity in Cimmerians compared to that of the Srubnaya-Alakulskaya population (table S10). ADMIXTURE analysis (K = 15) revealed that Cimmerian individuals carried predominantly the WHG and CHG components similar to the Srubnaya individuals, but they also carried other ancestral components including NEN (dark red), Northeast Asian (NEA) (“dark green”), and Southeast Asian (SEA, “light blue”) components. From the oldest to the most recent sample, the amount of NEN component increased, while the NEA and SEA components decreased through time in the Cimmerians (Fig. 3D and fig. S10). The admixture results were further tested withf3 statistics, which were consistent with the observed pattern by means of shared genetic drift between the Cimmerians and the tested populations used as proxies for different genetic components identified in admixture analyses (table S13). These results implicate a more eastern origin of the Cimmerians compared to that of the Srubnaya-Alakulskaya population and an increased amount of NEN-originated admixture in these individuals through time.

In the seventh century BCE, the Scythians appeared in the North Pontic region. Iron Age western Scythians displayed slightly higher intragroup diversity compared to that of the Bronze Age groups and formed four discrete clusters including NE, SE, SC, and CC clusters (Fig. 1C and table S10). Scythians belonging to the SE cluster were closer to Hungarian Bronze Age and Iron Age individuals including Vatya and Maros. The NE Scythian cluster fell close to the Iron Age individuals from modern-day Montenegro and Sweden (fig. S9). The SC Scythians further grouped with Early Sarmatians (12) and the Iron Age Scythian from modern-day Hungary (23). It has been hypothesized by Terenozhkin that Scythians reached the Pontic-Caspian steppe region from Central Asia (for example, from Andronovo) (7). To formally test this hypothesis, we calculatedf4 statistics in the form off4(Yoruba, Scythian, Srubnaya, BronzeAgeX), where “BronzeAgeX” refers to either Andronovo, Sintashta, or Afanasievo. This analysis revealed that the western Scythians (tested either as a single population or four different clusters) formed a clade together with Andronovo and two other Andronovo-originated populations to the exclusion of Srubnaya-Alakulskaya from the southern Urals (Fig. 3B and table S14), supporting the Central Asian origin of the western Scythians. Furthermore, the western Scythians shared more drift with Andronovo, Afanasievo, Sintashta, and Mezhovskaya to the exclusion of Yamnaya (table S15). While the eastern Scythians from an earlier study (12) formed a clade together with Srubnaya-Alakulskaya to the exclusion of Yamnaya, the western Scythians of the present study did not show this pattern. Only when compared with Karasuk and Okunevo, Yamnaya seemed closer (although scy332 is an exception), which is in line with a shared steppe origin of the Yamanya and the western nomads (table S15). ADMIXTURE analysis atK = 15 revealed that the Scythians belonging to the NE cluster had a more visible West Eurasian component that is highest in the northern populations, while Scythians that belong to the SE cluster had a more visible NEN genetic component, most commonly found in Neolithic Anatolian individuals. The NEN component was also found in individuals falling into the CC, who additionally carried an SA component (“lilac”) shared with the Cimmerians, Sarmatians, and two more Scythian individuals (scy193 and scy006). Scy332 had a SEA (“light blue”) component and was most similar to the Karasuk individuals (Fig. 3 and fig. S10, A and B).

The five Sarmatians grouped close together in the SC (Fig. 1C), but they also had the highest pairwise mismatch estimates compared to other Iron Age nomads, suggesting a larger effective population size (table S10).F4(Yoruba, Sarmatians, PopulationX, Cimmerian), where thePopulationX is Yamnaya, Srubnaya, or Karasuk, revealed that Sarmatians formed a clade together with all these three populations to the exclusion of Cimmerians (table S18). Multiwayf4 statistics testing the relationships between Srubnaya/-Alakulskaya, Cimmerians, and Scythians revealed that both Scythians and Cimmerians formed a clade together with Srubnaya/-Alakulskaya to the exclusion of the other population and that Srubnaya/-Alakulskaya was closer to Scythians among the two (Fig. 3C and table S17). The results point to the presence of a deep shared ancestry of all Iron Age nomadic groups associated with Bronze Age populations of the steppe, which, however, is not equivalent with a direct genetic continuity between Srubnaya-Alakulskaya and the western Scythians.

The origins of the four steppe populations

The Bronze Age Srubnaya-Alakulskaya individuals from Kazburun 1/Muradym 8 presented genetic similarities to the previously published Srubnaya individuals. However, inf4 statistics, they shared more drift with representatives of the Andronovo and Afanasievo populations compared to the published Srubnaya individuals. Those apparently West Eurasian people lacked significant Siberian components (NEA and SEA) in ADMIXTURE analyses but carried traces of the SA component that could represent an earlier connection to ancient Bactria. The presence of an SA component (as well as finding of metals imported from Tien Shan Mountains in Muradym 8) could therefore reflect a connection to the complex networks of the nomadic transmigration patterns characteristic of seasonal steppe population movements [see (2), figure 6.1, p. 205]. These movements, although dictated by the needs of the nomads and their animals, shaped the economic and social networks linking the outskirts of the steppe and facilitated the flow of goods between settled, semi-nomadic, and nomadic peoples. In contrast, all Cimmerians carried the Siberian genetic component. Both the PCA andf4 statistics supported their closer affinities to the Bronze Age western Siberian populations (including Karasuk) than to Srubnaya. It is noteworthy that the oldest of the Cimmerians studied here (cim357) carried almost equal proportions of Asian and West Eurasian components, resembling the Pazyryks, Aldy-Bel, and Iron Age individuals from Russia and Kazakhstan (12). The second oldest Cimmerian (cim358) was also the only one with both uniparental markers pointing toward East Asia. The Q1* Y chromosome sublineage of Q-M242 is widespread among Asians and Native Americans and is thought to have originated in the Altai Mountains (24). It has previously been identified in numerous ancient samples from Siberia, the Americas, and in representatives of the Siberian Bronze Age and nomadic populations (4,24). This is the first indication that Cimmerians did not originate in the PCS region but were nomads tracing their origin to the Far East.

The origins of Scythians of the western Pontic-Caspian steppe are difficult to resolve. We identified four different clusters within our geographically continuous sample set, which likely represent a varying gradient of different genetic components: the Northern cluster, SC, CC, and SE cluster. The latter was characterized by the presence of the NEN component representing local semi-nomadic Scythians with clear genetic uptake from the locals and possibly from other settlers such as the Greeks around the Black Sea region. Finally, the Sarmatians fell between all other nomads that form the bulk of the SC, suggesting that southern Urals is where the continuity of western nomads was sustained.

Intragroup genetic diversity of the steppe populations

The diversity of Srubnaya-Alakulskaya individuals was on par with that of Sarmatians and Scythians (table S10) and was also the highest among all published Bronze Age individuals. The Muradym 8/Kazburun 1 site is a unique cultural mixing zone with an unusual number of culturally distinct burials of two different traditions (Srubnaya-Alakulskaya), but the individuals are genetically uniform across the time span of the sites, suggesting that diffusion may have been the main mode of cultural dispersal in the LBA.

Cimmerians resemble individuals within the SC and had higher diversity compared to that of the Srubnaya-Alakulskaya individuals. Despite clustering tightly on the PCA plot, the Cimmerians and Sarmatians had the highest pairwise mismatch estimates among the nomads studied (Fig. 1C and table S10). Although the Scythians showed high variation based on the PCA, their intragroup genetic diversity was comparatively lower than that of the Cimmerians and Sarmatians. This observation is best explained by a smaller ancestral Scythian population base in western Pontic-Caspian steppe than in Sarmatians of the southern Urals. When compared with published Early Sarmatians from the same region (12), the Sarmatians studied here seem to have remained genetically uniform through an approximately 300- to 500-year time span. This might suggest the genetic continuity of Sarmatians in the southern Urals despite a distinct cultural shift and a suspected earlier population replacement between Early and Middle/Late Sarmatians in the region. Thus, the observed high genetic diversity in the Sarmatians could result from a large effective population size rather than gene flow into the region.

Mutual relations and shared ancestry between steppe populations

Our results suggest that the Cimmerians were largely similar to the more eastern Sarmatians (cim357) albeit with an increased amount of a Siberian (NEA) component (cim358 and cim359), thus representing a genetic link between the Iron Age people of the Kazakh steppe region. Similar to the cis-Uralic Srubnaya-Alakulskaya, Cimmerians were not direct ancestors of the Scythians in the Pontic-Caspian steppe; however, all those populations shared a common ancestral gene pool.

Scythians who were thought to have displaced the Cimmerians from the Pontic-Caspian steppe region differed from both Cimmerians and the later Sarmatians. However, it is unclear whether the observed pattern resulted from replacement, since the genetic composition of Cimmerians may have undergone a temporal change, as witnessed by the observed temporal reduction of the NEA and the SEA components in more recent individuals. It has previously been noted that Scythians were not uniform across Eurasia, exhibiting distinct differences between Eastern/Western Eurasian groups (12). In contrast to the eastern steppe Scythians (Pazyryks and Aldy-Bel) that were closely related to Yamnaya, the western North Pontic Scythians were instead more closely related to individuals from Afanasievo and Andronovo groups. Some of the Scythians of the western Pontic-Caspian steppe lacked the SA and the East Eurasian components altogether and instead were more similar to a Montenegro Iron Age individual (3), possibly indicating assimilation of the earlier local groups by the Scythians. Finally, one individual from Nesterivka (scy011), which was the most recent of the Scythians, and possibly representing a transition between different groups, carried a distinct resemblance to the later steppe Sarmatians, corroborating the idea of a more “stable”/”common” steppe signature shared with all Sarmatians or reflecting physical/social connection to the southern Ural steppe zone maintained within the western nomadic world. Toward the end of the Scythian period (fourth century CE), a possible direct influx from the southern Ural steppe zone took place, as indicated by scy332. However, it is possible that this individual might have originated in a different nomadic group despite being found in a Scythian cultural context. This individual instead resembles, genetically, the early eastern Altai Scythians, albeit with even higher contribution of the NEA and the SEA genetic components. This result suggests the presence of a continuous connection between the Western fringes of the Scythian empire and central parts of Eurasia or maybe even the source region in the Altai Mountains. Such a connection could reflect communication associated with population exchange and internal high mobility among the Scythians.

In conclusion, our genomic analyses revealed that both the Bronze Age and Iron Age were highly dynamic periods in the Pontic-Caspian steppe. The time span between 1800 BCE and 400 CE was characterized by mobility, population movements, and replacements, which shaped the complex demography of the region through time. Our results showed that the Western Eurasian steppe nomads were not direct descendants of the Bronze Age Srubnaya-Alakulskaya individuals but shared elements of common ancestry with contribution from different peoples. The early nomads could thus be referred to as a “cultural and chronological horizon” represented by various cultures of the Scythian-Siberian world that was not composed of a genetically homogeneous and/or isolated group. Quite the contrary is observed. We observe little evidence of mobility from the Far East, suggesting that the main source of most Western nomads is likely found in eastern Pontic-Caspian steppe and southern Urals. Thus, we propose that the region, similar to the so-called Mongolian steppe generator of peoples during the Middle Ages, served as the generator of the west nomadic peoples that sustained the western nomadic horizon in the Iron Age.

Ancient DNA extraction

DNA extraction of the Srubnaya (n = 13), Sarmatian (n = 5), and four Scythian individuals was done at the Archaeological Research Laboratory at Stockholm University, specially equipped for ancient DNA work. The remaining Scythians from Moldova (n = 10) and Cimmerians (n = 3) underwent DNA extraction in ancient DNA facilities at the Adam Mickiewicz University in Poland. The surface of the material was cleaned mechanically and was further subjected to ultraviolet light (265 nm J/cm²) on each side before sampling. The teeth were additionally pretreated with bleach solution (0.5 to 1% NaOCl) and purified double-distilled H₂O (ddH₂O). The amount of bone powder used varied between 80 and 150 mg. DNA extraction and library preparation was performed in a separate ancient DNA laboratory in laminar flow hoods. The extraction was done following a silica column–based extraction procedure (25) with adaptations (26). The extraction buffer that we used contained 1000 μl of 0.5 M EDTA (pH 8.0), 1 M urea, and 10 μl of proteinase K (10 mg/ml). After digestion, 1 ml of extract was concentrated to 100 μl using Amicon Ultra centrifugal filters and purified to 110 μl of cleaned product using a MinElute kit (Qiagen).

Library preparation and sequencing

Blunt-end, double-stranded libraries were built from 20 μl of DNA extract following Meyer and Kircher (27). The libraries were assessed using real-time quantitative polymerase chain reaction (qPCR). With 1 μl of DNA library, 12.5 μl of 1× Maxima SYBR Green Master Mix, 10.5 μl of dH₂O, and 1 μl of each of the 10 μM primers (IS7 and IS8 primers) were ran in duplicates. The libraries were thereafter amplified in five separate PCR reactions with AmpliTaq Gold (Applied Biosystems). PCR products were pooled and cleaned with magnetic beads (Agencourt AMPure XP, Beckman Coulter). We received estimates of the concentration and molarity of the DNA in the cleaned DNA libraries using the 2100 Bioanalyzer Instrument (Agilent Technologies). Consequently, libraries were shotgun-sequenced on Illumina HiSeq 2500 [2 × 125 base pairs (bp), pair-end (PE)] and HiSeq X (2 × 150 bp, PE) platforms at the Science for Life Laboratory (SciLifeLab) facilities in Uppsala (SNP&SEQ Technology Platform, Uppsala University) and Stockholm [National Genomics Infrastructure (NGI) Stockholm]. The base calling was performed using an Illumina CASAVA software, and reads were demultiplexed on the basis of six nucleotide index sequences used in library preparation (27).

UDG-treated libraries

On the basis of screening results of conventional blunt-end libraries, one individual from Kazburun 1 (kzb002) was identified as having exceptional preservation. To use the individual in a future high-coverage genome database, we commenced production of libraries with repaired damages using uracil-DNA-glycosylase (UDG) treatment to remove deaminated cytosine sites (28). Two new libraries were prepared using the standard blunt-end protocol listed above (27) albeit with an additional 3-hour incubation step at 37°C with 3 μl of Uracil-Specific Excision Reagent (USER) enzyme (New England Biolabs) instead of T4 DNA polymerase. After the incubation, 1 μl of T4 DNA Polymerase (Thermo Fisher Scientific) was added to the mix, and the mix was further incubated at 25°C for 15 min and at 12°C for 5 min. The libraries were tested using qPCR (as above) and subsequently amplified in five separate reactions of 25 μl with 1 μl of each 10 μM PCR primer (index primer P7 and IS4), 2.5 μl of an AccuPrime Pfx buffer, 0.5 μl of Herculase II Fusion DNA Polymerase (Agilent Technologies), 16 to 17 μl of ddH₂O, and 4 μl of repaired DNA library. The thermocycling conditions consisted of an initial denaturation at 95°C for 2 min, 10 to 14 cycles of 95°C for 15 s, 60°C for 30 s, 68°C for 1 min, and a final extension at 68°C for 5 min. The libraries were pooled, cleaned with magnetic beads (Agencourt AMPure XP, Beckman Coulter), and quantified using the 2100 Bioanalyzer Instrument (Agilent Technologies).

Whole-genome capture

One individual, scy006, underwent whole-genome capture using 7 μl of previously screened library. Hybridization capture reaction was performed using commercially biotinylated probes for human from MYcroarray (www.mycroarray.com). The reactions conducted at 60°C for 40 hours in a final volume of 30 μl. Captured library was purified with Dynabeads MyOne Streptavidin C1 magnetic beads (Invitrogen) following the manufacturer’s protocol (version 3.1) and was subsequently eluted in 30 μl of 1× tris-EDTA buffer with 0.05% Tween 20 (TET) buffer. Postcapture amplification was performed in five separate reactions with 1 μl of each 10 μM PCR primer (IS5 and IS6), 10 μl of 5× Herculase II amplification buffer, 1 μl of Herculase II Fusion DNA Polymerase (Agilent Technologies), 0.5 μl of deoxynucleotide triphosphates (dNTPs) (25 mM), 32.5 μl of ddH₂O, and 5 μl of captured DNA library. The thermocycling conditions consisted of an initial denaturation at 98°C for 30 s, 16 cycles of 98°C for 20 s, 60°C for 30 s, 72°C for 30 s, and a final extension at 72°C for 5 min. After postcapture amplification, the five amplified samples per reaction were pooled and purified with the use of MinElute spin columns (Qiagen) following the manufacturer’s instructions. Despite successful library preparation, we did not observe much improvement in terms of single-nucleotide polymorphism (SNP) yield in the capture library. The screening results from captured library were merged with previous results obtained from conventional blunt-end libraries to increase the final coverage to the level used in this paper.

Sequence data processing

Using MergeReadsFastQ_cc.py, paired-end reads were merged by requiring at least an 11-bp overlap, and residual adapter sequences were trimmed (29). Merged reads were aligned to the human reference genome (version hs37d5) in single-end mode using Burrows-Wheeler Aligner (BWA) “aln” (version 0.7.12) (30) with parameters “-l 16500 -n 0.01 -o 2” and using BWA “samse.” For individuals with more than one library sequenced, Binary Alignment Map (BAM) files from different libraries were merged with SAMtools “merge” (version 1.3) (30). PCR duplicates were removed using a modified version of FilterUniqSAMCons_cc.py as in (31). Using SAMtools “calmd” (version 1.3) (30), MD tags in BAM files were generated. Finally, sequences that are shorter than 35 bp and that contain more than 10% mismatches to the reference genome were filtered using a custom script. Ancient genome sequence data of previously published individuals in table S5 were processed following the same procedure to prevent bias in comparative analysis. Genomic coverage was calculated using “genomeCoverageBed” module of BEDTools (32).

Molecular sex estimation

Molecular sex of each individual was estimated using the Ry method reported in (33). Briefly, the method is based on dividing the number of sequences mapped to the Y chromosome to the number of those mapped to X and Y chromosomes. For this calculation, only sequences with mapping quality of minimum 30 were considered.

Authenticity testing

Authenticity of the sequences was firstly evaluated on the basis of the presence of ancient DNA-specific damage patterns including increased frequency of C to T type transitions at 5′ end of the sequences due to deamination and based on short mean sequence length due to fragmentation (14,34). PMDtools (35) was used to assess the nucleotide misincorporation patterns at the 5′ ends of the reads. All sequence data showed increased C to T frequencies at 5′ ends. The sequencing statistics of all libraries are listed in table S3. mtDNA contamination was estimated using two different methods (15,16). In the first method (15), private or near-private alleles (less than 5% in 311 modern mtDNA sequences) with a minimum sequencing depth of 10 and with a base quality of 30 were considered. Transition-type substitutions were filtered, and the point estimate of contamination was calculated by summing the counts of consensus and alternative alleles across all sites. For the second method (16), to calculate probabilities of being authentic based on mtDNA, SAMtools “mpileup” (30) and vcftools (36) were used. Probabilities of being authentic were calculated using “contamMix” library in R.

Uniparental markers

Mitochondrial consensus sequence per sample was called using SAMtools “mpileup” (30) and vcftools (36). Haplogroups were determined using Haplofind (37), and final assignment of haplogroups was performed on the basis of visual inspection of each consensus against PhyloTree mtDNA tree (build 17) (38). Variable site calls were prepared using MITOMASTER (39). Mitochondrial DNA genomes of a number of individuals published here were discussed in detail elsewhere (11).

Similarly, Y chromosome sequences were filtered out from BAM files aligned to the human reference genome 19 (hs37d5) using SAMtools version 0.1.19 (30). The Y chromosome haplogroups were assigned using haplogroup identifying SNPs included in minimal PhyloTree_Y (version 30-Nov-2014) (40) and ISOGG Y-DNA haplogroup tree 2017 version 12.29 (International Society of Genetic Genealogy). Only SNPs of base and mapping qualities of 30 were used. Whenever possible, the haplogroup assignment was restricted to derived transversions to avoid misclassification resulting from damage. All uniparental markers are listed in table S3.

Data sets

Population genetics analyses were restricted with known present-day genetic variation to minimize false positives. Two different present-day reference panels including (i) the Human Origins genotype data set (41,42) and (ii) the 1000 Genomes whole-genome sequence data (43) were used to call the SNPs of ancient individuals sequenced in this study and in published individuals (table S5).

Population genetics analysis

• 1.D. W. Anthony,The Horse, The Wheel, and Language : How Bronze-Age Riders From the Eurasian Steppes Shaped the Modern World (Princeton Univ. Press, 2007). [Google Scholar]
• 2.L. N. Koryakova, A. V. Epimakhov,The Urals and Western Siberia in the Bronze and Iron Ages (Cambridge Univ. Press, 2007). [Google Scholar]
• 3.Allentoft M. E., Sikora M., Sjögren K. G., Rasmussen S., Rasmussen M., Stenderup J., Damgaard P. B., Schroeder H., Ahlström T., Vinner L., Malaspinas A. S., Margaryan A., Higham T., Chivall D., Lynnerup N., Harvig L., Baron J., Della Casa P., Dąbrowski P., Duffy P. R., Ebel A. V., Epimakhov A., Frei K., Furmanek M., Gralak T., Gromov A., Gronkiewicz S., Grupe G., Hajdu T., Jarysz R., Khartanovich V., Khokhlov A., Kiss V., Kolář J., Kriiska A., Lasak I., Longhi C., McGlynn G., Merkevicius A., Merkyte I., Metspalu M., Mkrtchyan R., Moiseyev V., Paja L., Pálfi G., Pokutta D., Pospieszny Ł., Price T. D., Saag L., Sablin M., Shishlina N., Smrčka V., Soenov V. I., Szeverényi V., Tóth G., Trifanova S. V., Varul L., Vicze M., Yepiskoposyan L., Zhitenev V., Orlando L., Sicheritz-Pontén T., Brunak S., Nielsen R., Kristiansen K., Willerslev E., Population genomics of Bronze Age Eurasia. Nature522, 167–172 (2015). [DOI] [PubMed] [Google Scholar]
• 4.Haak W., Lazaridis I., Patterson N., Rohland N., Mallick S., Llamas B., Brandt G., Nordenfelt S., Harney E., Stewardson K., Fu Q., Mittnik A., Bánffy E., Economou C., Francken M., Friederich S., Pena R. G., Hallgren F., Khartanovich V., Khokhlov A., Kunst M., Kuznetsov P., Meller H., Mochalov O., Moiseyev V., Nicklisch N., Pichler S. L., Risch R., Rojo Guerra M. A., Roth C., Szécsényi-Nagy A., Wahl J., Meyer M., Krause J., Brown D., Anthony D., Cooper A., Alt K. W., Reich D., Massive migration from the steppe was a source for Indo-European languages in Europe. Nature522, 207–211 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 5.S. F. Adali, inEurasian Empires in Antiquity and the Early Middle Ages: Contact and Exchange between the Graeco-Roman World, Inner Asia and China, F. J. Vervaet, H. J. Kim, S. F. Adali, Eds. (Cambridge University Press, 2017), pp. 34–59. [Google Scholar]
• 6.S. V. Makhortykh, The North Black Sea Steppes in the Cimmerian Epoch, inImpact of the Environment on Human Migration in Eurasia, E. M. Scott, A. Y. Alekseev, G. Zaitseva, Eds. (Springer, 2005), pp. 35–44. [Google Scholar]
• 7.J. Davis-Kimball, V. A. Bashilov, L. T. Yablonski,Nomads of the Eurasian Steppes in the Early Iron Age (Zinat Press, 1995). [Google Scholar]
• 8.R. Brzeziński, M. Mielczarek,The Sarmatians 600 BC - AD 450 (Osprey Publishing, 2002). [Google Scholar]
• 9.Mathieson I., Lazaridis I., Rohland N., Mallick S., Patterson N., Roodenberg S. A., Harney E., Stewardson K., Fernandes D., Novak M., Sirak K., Gamba C., Jones E. R., Llamas B., Dryomov S., Pickrell J., Arsuaga J. L., de Castro J. M. B., Carbonell E., Gerritsen F., Khokhlov A., Kuznetsov P., Lozano M., Meller H., Mochalov O., Moiseyev V., Guerra M. A. R., Roodenberg J., Vergès J. M., Krause J., Cooper A., Alt K. W., Brown D., Anthony D., Lalueza-Fox C., Haak W., Pinhasi R., Reich D., Genome-wide patterns of selection in 230 ancient Eurasians. Nature528, 499–503 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 10.Der Sarkissian C., Balanovsky O., Brandt G., Khartanovich V., Buzhilova A., Koshel S., Zaporozhchenko V., Gronenborn D., Moiseyev V., Kolpakov E., Shumkin V., Alt K. W., Balanovska E., Cooper A., Haak W.; Genographic Consortium , Ancient DNA reveals prehistoric gene-flow from Siberia in the complex human population history of North East Europe. PLOS Genet.9, e1003296 (2013). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 11.Juras A., Krzewińska M., Nikitin A. G., Ehler E., Chyleński M., Łukasik S., Krenz-Niedbała M., Sinika V., Piontek J., Ivanova S., Dabert M., Götherström A., Diverse origin of mitochondrial lineages in Iron Age Black Sea Scythians. Sci. Rep.7, 43950 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 12.Unterländer M., Palstra F., Lazaridis I., Pilipenko A., Hofmanová Z., Groß M., Sell C., Blöcher J., Kirsanow K., Rohland N., Rieger B., Kaiser E., Schier W., Pozdniakov D., Khokhlov A., Georges M., Wilde S., Powell A., Heyer E., Currat M., Reich D., Samashev Z., Parzinger H., Molodin V. I., Burger J., Ancestry and demography and descendants of Iron Age nomads of the Eurasian Steppe. Nat. Commun.8, 14615 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 13.Alekseev A. Y., Bokovenko N. A., Boltrik Y., Chugunov K. A., Cook G., Dergachev V. A., Kovalyukh N., Possnert G., van der Plicht J., Scott E. M., Sementsov A., Skripkin V., Vasiliev S., Zaitseva G., A chronology of the Scythian antiquities of Eurasia based on new archaeological and¹⁴C data. Radiocarbon43, 1085–1107 (2001). [Google Scholar]
• 14.Hofreiter M., Jaenicke V., Serre D., von Haeseler A., Pääbo S., DNA sequences from multiple amplifications reveal artifacts induced by cytosine deamination in ancient DNA. Nucleic Acids Res.29, 4793–4799 (2001). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 15.Green R. E., Malaspinas A.-S., Krause J., Briggs A. W., Johnson P. L. F., Uhler C., Meyer M., Good J. M., Maricic T., Stenzel U., Prüfer K., Siebauer M., Burbano H. A., Ronan M., Rothberg J. M., Egholm M., Rudan P., Brajković D., Kućan Ž., Gušić I., Wikström M., Laakkonen L., Kelso J., Slatkin M., Pääbo S., A complete Neandertal mitochondrial genome sequence determined by high-throughput sequencing. Cell134, 416–426 (2008). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 16.Fu Q., Mittnik A., Johnson P. L. F., Bos K., Lari M., Bollongino R., Sun C., Giemsch L., Schmitz R., Burger J., Ronchitelli A. M., Martini F., Cremonesi R. G., Svoboda J., Bauer P., Caramelli D., Castellano S., Reich D., Pääbo S., Krause J., A revised timescale for human evolution based on ancient mitochondrial genomes. Curr. Biol.23, 553–559 (2013). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 17.Behar D. M., van Oven M., Rosset S., Metspalu M., Loogväli E.-L., Silva N. M., Kivisild T., Torroni A., Villems R., A “Copernican” reassessment of the human mitochondrial DNA tree from its root. Am. J. Hum. Genet.90, 675–684 (2012). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 18.V. I. Molodin, A. S. Pilipenko, A. G. Romaschenko, A. A. Zhuravlev, R. O. Trapezov, T. A. Chikisheva, D. V. Pozdnyakov, Human migrations in the southern region of the West Siberian Plain during the Bronze Age: Archaeological, palaeogenetic and anthropological data, inPopulation Dynamics in Prehistory and Early History. New Approaches by Using Stable Isotopes and Genetics, E. Kaiser, J. Burger, W. Schier, Eds. (De Gruyter, 2012), pp. 93–112. [Google Scholar]
• 19.Balaresque P., Poulet N., Cussat-Blanc S., Gerard P., Quintana-Murci L., Heyer E., Jobling M. A., Y-chromosome descent clusters and male differential reproductive success: Young lineage expansions dominate Asian pastoral nomadic populations. Eur. J. Hum. Genet.23, 1413–1422 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 20.Keyser C., Bouakaze C., Crubézy E., Nikolaev V. G., Montagnon D., Reis T., Ludes B., Ancient DNA provides new insights into the history of south Siberian Kurgan people. Hum. Genet.126, 395–410 (2009). [DOI] [PubMed] [Google Scholar]
• 21.Skoglund P., Malmström H., Raghavan M., Storå J., Hall P., Willerslev E., Gilbert M. T. P., Götherström A., Jakobsson M., Origins and genetic legacy of neolithic farmers and hunter-gatherers in Europe. Science336, 446–469 (2012). [DOI] [PubMed] [Google Scholar]
• 22.N. L. Chlenova,Chronology of the Monuments of the Belonging to the Karasuk Epoch (Moscow Institute of Archaeology Press, 1972). [Google Scholar]
• 23.Gamba C., Jones E. R., Teasdale M. D., McLaughlin R. L., Gonzalez-Fortes G., Mattiangeli V., Domboróczki L., Kővári I., Pap I., Anders A., Whittle A., Dani J., Raczky P., Higham T. F. G., Hofreiter M., Bradley D. G., Pinhasi R., Genome flux and stasis in a five millennium transect of European prehistory. Nat. Commun.5, 5257 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 24.Zegura S. L., Karafet T. M., Zhivotovsky L. A., Hammer M. F., High-resolution SNPs and microsatellite haplotypes point to a single, recent entry of Native American Y chromosomes into the Americas. Mol. Biol. Evol.21, 164–175 (2004). [DOI] [PubMed] [Google Scholar]
• 25.Yang D. Y., Eng B., Waye J. S., Dudar J. C., Saunders S. R., Improved DNA extraction from ancient bones using silica-based spin columns. Am. J. Phys. Anthropol.105, 539–543 (1998). [DOI] [PubMed] [Google Scholar]
• 26.Günther T., Valdiosera C., Malmström H., Ureña I., Rodriguez-Varela R., Sverrisdóttir Ó. O., Daskalaki E. A., Skoglund P., Naidoo T., Svensson E. M., de Castro J. M. B., Carbonell E., Dunn M., Storå J., Iriarte E., Arsuaga J. L., Carretero J.-M., Götherström A., Jakobsson M., Ancient genomes link early farmers from Atapuerca in Spain to modern-day Basques. Proc. Natl. Acad. Sci. U.S.A.112, 11917–11922 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 27.Meyer M., Kircher M., Illumina sequencing library preparation for highly multiplexed target capture and sequencing. Cold Spring Harb. Protoc.6, pdb.prot5448 (2010). [DOI] [PubMed] [Google Scholar]
• 28.Briggs A. W., Heyn P., Preparation of next-generation sequencing libraries from damaged DNA. Methods Mol. Biol.. 840, 143–154 (2012). [DOI] [PubMed] [Google Scholar]
• 29.M. Kircher, Analysis of high-throughput ancient DNA sequencing data, inAncient DNA. Methods in Molecular Biology, B. Shapiro, M. Hofreiter, Eds. (Humana Press, 2012), vol. 840, pp. 197–228. [DOI] [PubMed] [Google Scholar]
• 30.Li H., Handsaker B., Wysoker A., Fennell T., Ruan J., Homer N., Marth G., Abecasis G., Durbin R.; Genome Project Data Processing Subgroup , The sequence alignment/map format and SAMtools. Bioinformatics25, 2078–2079 (2009). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 31.Günther T., Malmström H., Svensson E. M., Omrak A., Sánchez-Quinto F., Kılınç G. M., Krzewińska M., Eriksson G., Fraser M., Edlund H., Munters A. R., Coutinho A., Simões L. G., Vicente M., Sjölander A., Sellevold B. J., Jørgensen R., Claes P., Shriver M. D., Valdiosera C., Netea M. G., Apel J., Lidén K., Skar B., Storå J., Götherström A., Jakobsson M., Population genomics of Mesolithic Scandinavia: Investigating early postglacial migration routes and high-latitude adaptation. PLOS Biol.16, e2003703 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 32.Quinlan A. R., Hall I. M., BEDTools: A flexible suite of utilities for comparing genomic features. Bioinformatics26, 841–842 (2010). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 33.Skoglund P., Storå J., Götherström A., Jakobsson M., Accurate sex identification of ancient human remains using DNA shotgun sequencing. J. Archaeol. Sci.40, 4477–4482 (2013). [Google Scholar]
• 34.Hansen A. J., Willerslev E., Wiuf C., Mourier T., Arctander P., Statistical evidence for miscoding lesions in ancient DNA templates. Mol. Biol. Evol.18, 262–265 (2001). [DOI] [PubMed] [Google Scholar]
• 35.Skoglund P., Northoff B. H., Shunkov M. V., Derevianko A. P., Pääbo S., Krause J., Jakobsson M., Separating endogenous ancient DNA from modern day contamination in a Siberian Neandertal. Proc. Natl. Acad. Sci. U.S.A.111, 2229–2234 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 36.Danecek P., Auton A., Abecasis G., Albers C. A., Banks E., DePristo M. A., Handsaker R. E., Lunter G., Marth G. T., Sherry S. T., McVean G., Durbin R.; 1000 Genomes Project Analysis Group , The variant call format and VCFtools. Bioinformatics27, 2156–2158 (2011). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 37.Vianello D., Sevini F., Castellani G., Lomartire L., Capri M., Franceschi C., HAPLOFIND: A new method for high-throughput mtDNA haplogroup assignment. Hum. Mutat.34, 1189–1194 (2013). [DOI] [PubMed] [Google Scholar]
• 38.van Oven M., Kayser M., Updated comprehensive phylogenetic tree of global human mitochondrial DNA variation. Hum. Mutat.30, E386–E394 (2009). [DOI] [PubMed] [Google Scholar]
• 39.Lott M. T., Leipzig J. N., Derbeneva O., Xie H. M., Chalkia D., Sarmady M., Procaccio V., Wallace D. C., mtDNA Variation and analysis using Mitomap and Mitomaster. Curr. Protoc. Bioinformatics44, 1.23.1–1.23.26 (2013). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 40.van Oven M., Van Geystelen A., Kayser M., Decorte R., Larmuseau M. H. D., Seeing the wood for the trees: A minimal reference phylogeny for the human Y chromosome. Hum. Mutat.35, 187–191 (2014). [DOI] [PubMed] [Google Scholar]
• 41.Lazaridis I., Patterson N., Mittnik A., Renaud G., Mallick S., Kirsanow K., Sudmant P. H., Schraiber J. G., Castellano S., Lipson M., Berger B., Economou C., Bollongino R., Fu Q., Bos K. I., Nordenfelt S., Li H., de Filippo C., Prüfer K., Sawyer S., Posth C., Haak W., Hallgren F., Fornander E., Rohland N., Delsate D., Francken M., Guinet J.-M., Wahl J., Ayodo G., Babiker H. A., Bailliet G., Balanovska E., Balanovsky O., Barrantes R., Bedoya G., Ben-Ami H., Bene J., Berrada F., Bravi C. M., Brisighelli F., Busby G. B. J., Cali F., Churnosov M., Cole D. E. C., Corach D., Damba L., van Driem G., Dryomov S., Dugoujon J.-M., Fedorova S. A., Romero I. G., Gubina M., Hammer M., Henn B. M., Hervig T., Hodoglugil U., Jha A. R., Karachanak-Yankova S., Khusainova R., Khusnutdinova E., Kittles R., Kivisild T., Klitz W., Kučinskas V., Kushniarevich A., Laredj L., Litvinov S., Loukidis T., Mahley R. W., Melegh B., Metspalu E., Molina J., Mountain J., Näkkäläjärvi K., Nesheva D., Nyambo T., Osipova L., Parik J., Platonov F., Posukh O., Romano V., Rothhammer F., Rudan I., Ruizbakiev R., Sahakyan H., Sajantila A., Salas A., Starikovskaya E. B., Tarekegn A., Toncheva D., Turdikulova S., Uktveryte I., Utevska O., Vasquez R., Villena M., Voevoda M., Winkler C. A., Yepiskoposyan L., Zalloua P., Zemunik T., Cooper A., Capelli C., Thomas M. G., Ruiz-Linares A., Tishkoff S. A., Singh L., Thangaraj K., Villems R., Comas D., Sukernik R., Metspalu M., Meyer M., Eichler E. E., Burger J., Slatkin M., Pääbo S., Kelso J., Reich D., Krause J., Ancient human genomes suggest three ancestral populations for present-day Europeans. Nature513, 409–413 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 42.Patterson N., Moorjani P., Luo Y., Mallick S., Rohland N., Zhan Y., Genschoreck T., Webster T., Reich D., Ancient admixture in human history. Genetics192, 1065–1093 (2012). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 43.The 1000 Genomes Project Consortium , An integrated map of genetic variation from 1,092 human genomes. Nature491, 56–65 (2012). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 44.Purcell S., Neale B., Todd-Brown K., Thomas L., Ferreira M. A. R., Bender D., Maller J., Sklar P., de Bakker P. I. W., Daly M. J., Sham P. C., PLINK: A tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet.81, 559–575 (2007). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 45.Patterson N., Price A. L., Reich D., Population structure and eigenanalysis. PLOS Genet.2, e190 (2006). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 46.Alexander D. H., Novembre J., Lange K., Fast model-based estimation of ancestry in unrelated individuals. Genome Res.19, 1655–1664 (2009). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 47.Kilinc G. M., Omrak A., Özer F., Günther T., Büyükkarakaya A. M., Bıçakçı E., Baird D., Dönertaş H. M., Ghalichi A., Yaka R., Koptekin D., Açan S. C., Parvizi P., Krzewińska M., Daskalaki E. A., Yüncü E., Dağtaş N. D., Fairbairn A., Pearson J., Mustafaoğlu G., Erdal Y. S., Çakan Y. G., Togan İ., Somel M., Storå J., Jakobsson M., Götherström A., The demographic development of the first farmers in Anatolia. Curr. Biol.26, 2659–2666 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]
• 48.Jakobsson M., Rosenberg N. A., CLUMPP: A cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure. Bioinformatics23, 1801–1806 (2007). [DOI] [PubMed] [Google Scholar]
• 49.Ramsey C. B., Bayesian analysis of radiocarbon dates. Radiocarbon51, 337–360 (2009). [Google Scholar]
• 50.Reimer P. J., Bard E., Bayliss A., Beck J. W., Blackwell P. G., Ramsey C. B., Buck C. E., Cheng H., Edwards R. L., Friedrich M., Grootes P. M., Guilderson T. P., Haflidason H., Hajdas I., Hatté C., Heaton T. J., Hoffmann D. L., Hogg A. G., Hughen K. A., Kaiser K. F., Kromer B., Manning S. W., Niu M., Reimer R. W., Richards D. A., Scott E. M., Southon J. R., Staff R. A., Turney C. S. M., van der Plicht J., IntCal13 and Marine13 radiocarbon age calibration curves 0–50,000 years cal BP. Radiocarbon55, 1869–1887 (2013). [Google Scholar]
• 51.J. van der Plicht, Radiocarbon, the calibration curve and scythian chronology, inImpact of the Environment on Human Migration in Eurasia, E. M. Scott, A. Y. Alekseev, G. Zaitseva, Eds. (Springer, 2005), pp. 45–61. [Google Scholar]
• 52.Łukasik S., Bijak J., Krenz-Niedbała M., Liczbińska G., Sinika V., Piontek J., Warriors die young: Increased mortality in early adulthood of Scythians from Glinoe, Moldova, fourth through second Centuries BC. J. Anthropol. Res.73, 584–616 (2017). [Google Scholar]
• 53.Shishlina N., Sevastyanov V., Zazovskaya E., van der Plicht J., Reservoir effect of archaeological samples from Steppe Bronze Age cultures in Southern Russia. Radiocarbon56, 767–778 (2014). [Google Scholar]
• 54.Svyatko S. V., Reimer P. J., Schulting R., Modern freshwater reservoir offsets in the Eurasian Steppe: Implications for archaeology. Radiocarbon59, 1597–1607 (2017). [Google Scholar]
• 55.Gerling C., A multi-isotopic approach to the reconstruction of prehistoric mobility and economic patterns in the West Eurasian steppes 3500 to 300 BC. eTopoi J. Ancient Stud.3, 1–21 (2014). [Google Scholar]
• 56.Shuteleva I., Sherbakov N., Gorshkov K., The archaeological study of Kazburun Barrow burial ground: Initial results reports. Eur. Archaeol., 21–23 (2010). [Google Scholar]
• 57.Sherbakov N., Shutelevaa I., Obydennovaa G., Balonovaa M., Khohlovab O., Golyevac A., Some results of the application of a complex approach to the research of the Late Bronze Age Muradymovo settlement in the Volgo-Ural region. Nat. Sci. Arc.1, 29–36 (2010). [Google Scholar]
• 58.V. S. Sinika, S. N. Razumov, S. D. Lysenko, H. P. Telnov,Report on the Activities of Dniester Archaeological Expedition on the Investigation of Barrows near Glinoe Village of Slobozia District in 2016 (Archive of the Dniester Area Archaeology Museum of Taras Shevchenko Transnistria State University, 2016), p. 95. [Google Scholar]
• 59.O. V. Nazarov, inNew research of the Scythian burial mounds in the river Ros` Basin // “Museum readings” Materials of an international scientific conference devoted to the 90th anniversary of the prominent Ukrainian archaeologist O.I.Terenozhkin (1998), pp. 77–79. [Google Scholar]
• 60.L. Kraeva, E. Kryukova, I. Shuteleva, N. Sherbakov, inArchaeological microdistricts of northern Eurasia (Omsk, 2009), pp. 78–82. [Google Scholar]

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