Between Lake Baikal and the Baltic Sea: genomic history of the gateway to Europe

Transferability of the PRS estimates for height and BMI obtained from the European ethnic groups to the Western Russian populations

Genetic data plays an increasingly important role in modern medicine. Decrease in the cost of sequencing with subsequent increase in imputation accuracy, and the accumulation of large amounts of high-quality genetic data enable the creation of polygenic risk scores (PRSs) to perform genotype-phenotype associations. The accuracy of phenotype prediction primarily depends on the overall trait heritability, Genome-wide association studies cohort size, and the similarity of genetic background between the base and the target cohort. Here we utilized 8,664 high coverage genomic samples collected across Russia by "Evogen", a Russian biomedical company, to evaluate the predictive power of PRSs based on summary statistics established on cohorts of European ancestry for basic phenotypic traits, namely height and BMI. We have demonstrated that the PRSs calculated for selected traits in three distinct Russian populations, recapitulate the predictive power from the original studies. This is evidence that GWAS summary statistics calculated on cohorts of European ancestry are transferable onto at least some ethnic groups in Russia.

Distortion of Population Statistics due to the Use of Different Methodological Approaches to the Construction of Genomic DNA Libraries

Several different methods of DNA library preparation for paleogenetic studies are now available. However, the chemical reactions underlying each of them can affect the primary sequence of ancient DNA (aDNA) in the libraries and taint the results of a statistical analysis. In this paper, we compare the results of a sequencing of the aDNA libraries of a Bronze Age sample from burials of the Caucasian burial ground Klady, prepared using three different approaches: (1) shotgun sequencing, (2) strategies for selecting target genomic regions, and (3) strategies for selecting target genomic regions, including DNA pre-treatment with a mixture of uracil-DNA glycosylase (UDG) and endonuclease VIII. The impact of the studied approaches to genomic library preparation on the results of a secondary analysis of the statistical data, namely F4 statistics, ADMIXTURE, and principal component analysis (PCA), was analyzed. It was shown that preparation of genomic libraries without the use of UDG can result in distorted statistical data due to postmortem chemical modifications of the aDNA. This distortion can be alleviated by analyzing only the single nucleotide polymorphisms caused by transversions in the genome.

Peculiarity of Pomors of Onega Peninsula and Winter Coast in the genetic context of Northern Europe

The peculiarity of the Russian North gene pool has long become scientific fact, but has yet to receive informative explanation. Genetic drift cannot be the only contributing factor in the striking genetic differences between not only northern Russian populations and the southern ones, but among individual northern populations as well. Studying Russian North gene pools previously underrepresented in scientific literature may help understand this phenomenon. The work aimed to perform a subtotal study of the gene pool of the Arkhangelsk Oblast Pomors (Onega Coast, Summer Coast, the western fragment of the Winter Coast; n = 130) using a panel of 60 Y-chromosome SNP markers through multidimensional scaling and mapping of genetic distances. The frequencies of 14 identified haplogroups differ drastically in Pomor populations: haplogroups I1, R1a, and N3 each comprise a quarter of the total Pomor gene pool, I2-P37.2, and R1b each comprise about 8%, and the rest of the haplogroups are rare. The Onega Coast Pomors showed genetic similarity to a wide range of North-Eastern Europe Finnic-speaking populations, as well as to Russian populations with a strong pre-Slavic substratum. The Summer Coast Pomors are close to the Scandinavian gene pools, and the Winter Coast Pomors are similar only to specific Finn and Swede populations. None of the Pomor populations demonstrate genetic similarity with the Novgorod Oblast Russian populations, with which the origin of the Pomors is traditionally associated. The genetic distances between Pomor populations are so great, they are comparable to the general range of variability between the Eastern Slavic, Baltic, and Finno-Ugric peoples of the region. The reasons for such pronounced originality of Pomor populations presumably include, along with genetic drift, the gene pool of each population being underlied by a different pre-Slavic substrate, with later gene flows as an additional factor.

North Asian population relationships in a global context

Population genetic studies of North Asian ethnic groups have focused on genetic variation of sex chromosomes and mitochondria. Studies of the extensive variation available from autosomal variation have appeared infrequently. We focus on relationships among population samples using new North Asia microhaplotype data. We combined genotypes from our laboratory on 58 microhaplotypes, distributed across 18 autosomes, on 3945 individuals from 75 populations with corresponding data extracted for 26 populations from the Thousand Genomes consortium and for 22 populations from the GenomeAsia 100 K project. A total of 7107 individuals in 122 total populations are analyzed using STRUCTURE, Principal Component Analysis, and phylogenetic tree analyses. North Asia populations sampled in Mongolia include: Buryats, Mongolians, Altai Kazakhs, and Tsaatans. Available Siberians include samples of Yakut, Khanty, and Komi Zyriane. Analyses of all 122 populations confirm many known relationships and show that most populations from North Asia form a cluster distinct from all other groups. Refinement of analyses on smaller subsets of populations reinforces the distinctiveness of North Asia and shows that the North Asia cluster identifies a region that is ancestral to Native Americans.

Footprints of interaction among Finniс-speaking, Slavic, and Turkic-speaking populations in modern gene pool and their reflection in pharmacogenetics

Genetic contribution of pre-Slavic populations to gene pools of modern Russia is increasingly relevant, along with genetic footprints of the Golden Horde invasion. The novel genome-wide approaches enable advanced solutions in this field. The study aimed at searching for the footprints of genetic interaction among Finnicspeaking, Slavic and Turkic-speaking populations of Central Russia and Volga Region and their reflection in pharmacogenetic landscape. Modeling ancestral components by ADMIXTURE software and their mapping involved genome-wide genotyping data for 248 individual genomes representing 47 populations of 9 ethnic groups. Of specific ancestral components identified in each of the Finnic-speaking peoples, only Mordovian ancestral components are common for all populations within the studied geographic area, regardless of their linguistic affiliation. Gene pools of Russian populations include 80% of intrinsic component, 19% contribution from Finnic-speaking peoples, and 1% of Central Asian influence. The Tatar gene pool combines all identified ancestral components, including 81% contribution from Finnic-speaking peoples and only 12% of Central Asian influence, which prevents using it as a reference for the assessment of Golden Horde footprints in Russian gene pools. A map of genetic distances from Ryazan Russians based on a panel of 42 pharmacogenetic markers reveals a landscape strikingly independent from the selectively neutral ancestral genomic patterns. For instance, populations of Mordovia, Kaluga, Smolensk, and Kostroma regions are the closest to Ryazan Russians in pharmacogenetic status, whereas populations of Ryazan and Nizhny Novgorod regions have strikingly divergent pharmacogenetic status despite the similarity of the selectively neutral ancestral genomic patterns. These findings confirm the relevance of targeted pharmacogenetic characterization for gene pools of Russia.

Genetic continuity of Indo-Iranian speakers since the Iron Age in southern Central Asia

Since prehistoric times, southern Central Asia has been at the crossroads of the movement of people, culture, and goods. Today, the Central Asian populations are divided into two cultural and linguistic groups: the Indo-Iranian and the Turko-Mongolian groups. Previous genetic studies unveiled that migrations from East Asia contributed to the spread of Turko-Mongolian populations in Central Asia and the partial replacement of the Indo-Iranian populations. However, little is known about the origin of the latters. To shed light on this, we compare the genetic data on two current-day Indo-Iranian populations — Yaghnobis and Tajiks — with genome-wide data from published ancient individuals. The present Indo-Iranian populations from Central Asia display a strong genetic continuity with Iron Age samples from Turkmenistan and Tajikistan. We model Yaghnobis as a mixture of 93% Iron Age individual from Turkmenistan and 7% from Baikal. For the Tajiks, we observe a higher Baikal ancestry and an additional admixture event with a South Asian population. Our results, therefore, suggest that in addition to a complex history, Central Asia shows a remarkable genetic continuity since the Iron Age, with only limited gene flow.

Dual origins of the Northwest Chinese Kyrgyz: the admixture of Bronze age Siberian and Medieval Niru'un Mongolian Y chromosomes

The Kyrgyz are a trans-border ethnic group, mainly living in Kyrgyzstan. Previous genetic investigations of Central Asian populations have repeatedly investigated the Central Asian Kyrgyz. However, from the standpoint of human evolution and genetic diversity, Northwest Chinese Kyrgyz is one of the more poorly studied populations. In this study, we analyzed the non-recombining portion of the Y-chromosome from 298 male Kyrgyz samples from Xinjiang Uygur Autonomous Region in northwestern China, using a high-resolution analysis of 108 biallelic markers and 17 or 24 STRs. First, via a Y-SNP-based PCA plot, Northwest Chinese Kyrgyz tended to cluster with other Kyrgyz population and are located in the West Asian and Central Asian group. Second, we found that the Northwest Chinese Kyrgyz display a high proportion of Y-lineage R1a1a1b2a2a-Z2125, related to Bronze Age Siberian, and followed by Y-lineage C2b1a3a1-F3796, related to Medieval Niru'un Mongols, such as Uissun tribe from Kazakhs. In these two dominant lineages, two unique recent descent clusters have been detected via NETWORK analysis, respectively, but they have nearly the same TMRCA ages (about 13th-14th centuries). This finding once again shows that the expansions of Mongol Empire had a striking effect on the Central Asian gene pool.

The story of the lost twins: decoding the genetic identities of the Kumhar and Kurcha populations from the Indian subcontinent

Background

The population structure of the Indian subcontinent is a tapestry of extraordinary diversity characterized by the amalgamation of autochthonous and immigrant ancestries and rigid enforcement of sociocultural stratification. Here we investigated the genetic origin and population history of the Kumhars, a group of people who inhabit large parts of northern India. We compared 27 previously published Kumhar SNP genotype data sampled from Uttar Pradesh in north India to various modern day and ancient populations.

Results

Various approaches such as Principal Component Analysis (PCA), Admixture, TreeMix concurred that Kumhars have high ASI ancestry, minimal Steppe component and high genomic proximity to the Kurchas, a small and relatively little-known population found ~ 2500 km away in Kerala, south India. Given the same, biogeographical mapping using Geographic Population Structure (GPS) assigned most Kumhar samples in areas neighboring to those where Kurchas are found in south India.

Conclusions

We hypothesize that the significant genomic similarity between two apparently distinct modern-day Indian populations that inhabit well separated geographical areas with no known overlapping history or links, likely alludes to their common origin during or post the decline of the Indus Valley Civilization (estimated by ALDER). Thereafter, while they dispersed towards opposite ends of the Indian subcontinent, their genomic integrity and likeness remained preserved due to endogamous social practices. Our findings illuminate the genomic history of two Indian populations, allowing a glimpse into one or few of numerous of human migrations that likely occurred across the Indian subcontinent and contributed to shape its varied and vibrant evolutionary past.

Whole genome sequencing of elite athletes

Whole genome sequencing (WGS) has great potential to explore all possible DNA variants associated with physical performance, psychological traits and health conditions of athletes. Here we present, for the first time, annotation of genomic variants of elite athletes, based on the WGS of 20 Tatar male wrestlers. The maximum number of high-quality variants per sample was over 3.8 M for single nucleotide polymorphisms (SNPs) and about 0.64 M for indels. The maximum number of nonsense mutations was 148 single nucleotide variants (SNVs) per individual. Athletes' genomes on average contained 18.9 nonsense SNPs in a homozygous state per sample, while non-athletes' exomes (Tatar controls, n = 19) contained 18 nonsense SNPs. Finally, we applied genomic data for the association analysis and used reaction time (RT) as an example. Out of 1884 known genome-wide significant SNPs related to RT, we identified four SNPs (KIF27 rs10125715, APC rs518013, TMEM229A rs7783359, LRRN3 rs80054135) associated with RT in wrestlers. The cumulative number of favourable alleles (KIF27 A, APC A, TMEM229A T, LRRN3 T) was significantly correlated with RT both in wrestlers (P = 0.0003) and an independent cohort (n = 43) of physically active subjects (P = 0.029). Furthermore, we found that the frequencies of the APC A (53.3 vs 44.0%, P = 0.033) and LRRN3 T (7.5 vs 2.8%, P = 0.009) alleles were significantly higher in elite athletes (n = 107) involved in sports with RT as an essential component of performance (combat sports, table tennis and volleyball) compared to less successful (n = 176) athletes. The LRRN3 T allele was also over-represented in elite athletes (7.5%) in comparison with 189 controls (2.9%, P = 0.009). In conclusion, we present the first WGS study of athletes showing that WGS can be applied in sport and exercise science.

Genomic landscape of the signals of positive natural selection in populations of Northern Eurasia: A view from Northern Russia

Natural selection of beneficial genetic variants played a critical role in human adaptation to a wide range of environmental conditions. Northern Eurasia, despite its severe climate, is home to lots of ethnically diverse populations. The genetic variants associated with the survival of these populations have hardly been analyzed. We searched for the genomic signatures of positive selection in (1) the genome-wide microarray data of 432 people from eight different northern Russian populations and (2) the whole-genome sequences of 250 people from Northern Eurasia from a public repository through testing the extended haplotype homozigosity (EHH) and direct comparison of allele frequency, respectively. The 20 loci with the strongest selection signals were characterized in detail. Among the top EHH hits were the NRG3 and NBEA genes, which are involved in the development and functioning of the neural system, the PTPRM gene, which mediates cell-cell interactions and adhesion, and a region on chromosome 4 (chr4:28.7-28.9 Mb) that contained several loci affiliated with different classes of non-coding RNAs (RN7SL101P, MIR4275, MESTP3, and LINC02364). NBEA and the region on chromosome 4 were novel selection targets that were identified for the first time in Western Siberian populations. Cross-population comparisons of EHH profiles suggested a particular role for the chr4:28.7-28.9 Mb region in the local adaptation of Western Siberians. The strongest selection signal identified in Siberian sequenced genomes was formed by six SNPs on chromosome 11 (chr11:124.9-125.2 Mb). This region included well-known genes SLC37A2 and PKNOX2. SLC37A2 is most-highly expressed in the gut. Its expression is regulated by vitamin D, which is often deficient in northern regions. The PKNOX2 gene is a transcription factor of the homeobox family that is expressed in the brain and many other tissues. This gene is associated with alcohol addiction, which is widespread in many Northern Eurasian populations.

The accuracy of predicting eye and hair pigmentation based on genetic markers in Russian populations

Prediction of eye and hair color from DNA is being increasingly employed in forensics and the studies of ancient populations. HIrisPlex-S is a prediction tool trained on the Dutch dataset and verified using a few other European populations. The accuracy of its predictions for other regions of the world has not been studied yet. Russian populations pose a special interest because, unlike the majority of world populations, their representatives can have not only dark but also light color eyes and hair. The aim of this work was to evaluate the accuracy of eye and hair color prediction in Russian populations. We recruited 144 representatives of indigenous peoples of Russia (Avar, Aleut, Buryat, Itelmen, Karelian, Koryak, Mari, Nanai, Russian, Rutulian, Chuvash, Chukchi, Evenk, and Even populations). All study participants were photographed. Eye and hair colors were identified from the anthropological images by anthropologists. The SNP markers included in the HIrisPlex system were genotyped. Phenotypes were predicted from the obtained genotypes and subsequently compared to the actual phenotypes. Quality metrics were calculated for HIrisPlex prediction accuracy in the populations of European Russia and Siberia. On the whole, HIrisPlex prediction accuracy was satisfactory, although a bit lower than in Western European datasets. Further research could focus on identifying additional markers to improve the accuracy of predictions in Russian populations.

WhoGEM: an admixture-based prediction machine accurately predicts quantitative functional traits in plants

The explosive growth of genomic data provides an opportunity to make increased use of sequence variations for phenotype prediction. We have developed a prediction machine for quantitative phenotypes (WhoGEM) that overcomes some of the bottlenecks limiting the current methods. We demonstrated its performance by predicting quantitative disease resistance and quantitative functional traits in the wild model plant species, Medicago truncatula, using geographical locations as covariates for admixture analysis. The method's prediction reliability equals or outperforms all existing algorithms for quantitative phenotype prediction. WhoGEM analysis produces evidence that variation in genome admixture proportions explains most of the phenotypic variation for quantitative phenotypes.

Y-chromosomal connection between Hungarians and geographically distant populations of the Ural Mountain region and West Siberia

Hungarians who live in Central Europe today are one of the westernmost Uralic speakers. Despite of the proposed Volga-Ural/West Siberian roots of the Hungarian language, the present-day Hungarian gene pool is highly similar to that of the surrounding Indo-European speaking populations. However, a limited portion of specific Y-chromosomal lineages from haplogroup N, sometimes associated with the spread of Uralic languages, link modern Hungarians with populations living close to the Ural Mountain range on the border of Europe and Asia. Here we investigate the paternal genetic connection between these spatially separated populations. We reconstruct the phylogeny of N3a4-Z1936 clade by using 33 high-coverage Y-chromosomal sequences and estimate the coalescent times of its sub-clades. We genotype close to 5000 samples from 46 Eurasian populations to show the presence of N3a4-B539 lineages among Hungarians and in the populations from Ural Mountain region, including Ob-Ugric-speakers from West Siberia who are geographically distant but linguistically closest to Hungarians. This sub-clade splits from its sister-branch N3a4-B535, frequent today among Northeast European Uralic speakers, 4000-5000 ya, which is in the time-frame of the proposed divergence of Ugric languages.

The genetic history of admixture across inner Eurasia

The indigenous populations of inner Eurasia, a huge geographic region covering the central Eurasian steppe and the northern Eurasian taiga and tundra, harbor tremendous diversity in their genes, cultures and languages. In this study, we report novel genome-wide data for 763 individuals from Armenia, Georgia, Kazakhstan, Moldova, Mongolia, Russia, Tajikistan, Ukraine, and Uzbekistan. We furthermore report additional damage-reduced genome-wide data of two previously published individuals from the Eneolithic Botai culture in Kazakhstan (~5,400 BP). We find that present-day inner Eurasian populations are structured into three distinct admixture clines stretching between various western and eastern Eurasian ancestries, mirroring geography. The Botai and more recent ancient genomes from Siberia show a decrease in contribution from so-called “ancient North Eurasian” ancestry over time, detectable only in the northern-most “forest-tundra” cline. The intermediate “steppe-forest” cline descends from the Late Bronze Age steppe ancestries, while the “southern steppe” cline further to the South shows a strong West/South Asian influence. Ancient genomes suggest a northward spread of the southern steppe cline in Central Asia during the first millennium BC. Finally, the genetic structure of Caucasus populations highlights a role of the Caucasus Mountains as a barrier to gene flow and suggests a post-Neolithic gene flow into North Caucasus populations from the steppe.

Exome-wide survey of the Siberian Caucasian population

BACKGROUND

Population structure is an important factor in the genetic association studies but often remains underexplored for many human populations. We identified exome variants in 39 Siberian Caucasian individuals from Novosibirsk, Russia and compared their genetic allele frequencies with European populations from 1000 Genomes Project.

METHODS

The study participants were from Novosibirsk and represented people with monogenic diabetes, healthy individuals and a cohort from the tick-borne encephalitis study. Isolated DNA was enriched using Agilent SureSelect V5 kit and sequenced on Illumina HiSeq 4000 and genetic variants were identified using GATK pipeline. To estimate the patterns of the population structure we used PCA and ADMIXTURE analysis. Pharmocogenetically and medically important variants were annotated based on PharmGKB and ClinVar databases.

RESULTS

The analysis identified low, but highly significant population differentiation attributed to numerous loci between the Siberian Caucasian population and other European population samples as well as a higher proportion of the Finnish genetic component in the studied sample. The medical and pharmacogenetic annotation of highly significantly differentiated variants between the Novosibirsk and the combined European populations revealed a number of important genetic polymorphisms located in such genes as FCGR3B, TYR, OCA2, FABP1, CHEK2 and SLC4A1.

CONCLUSIONS

The study reports for the first time an exome-wide comparison of a population from Russia with European samples and emphasizes the importance of population studies with medical annotation of variants.

Genetic history of Bashkirian Mari and Southern Mansi ethnic groups in the Ural region

According to genetic studies, the Hungarian Y-chromosomal gene pool significantly differs from other Uralic-speaking populations. Hungarians possess a significant frequency of haplogroup R1a-Z280 and a low frequency of haplogroup N-Tat, which is common among other Uralic-speaking populations. Based on this evidence, we further worked to define the links between the linguistically related Hungarian, Mansi and Bashkirian Mari populations. Samples were collected from 45 Bashkirian Mari and 36 Southern Mansi males in the Ural region. We analyzed male-specific markers including 23 STRs and 36 SNPs, which reflect past and recent paternal genetic history. We found that the haplogroup distribution of the two population samples showed high genetic similarity to each other except for the N-Tat* and R1a-Z93 haplogroups in the Bashkirian Mari males. On the MDS plots constructed from Fst- and Rst-genetic distances, the Bashkirian Mari and Southern Mansi population groups showed close genetic affinities with the Khanty, Northern Mansi, Mari, and Estonian populations. For phylogenetic studies, networks were constructed for the most frequent haplogroups in both populations together with other Eurasian populations. Both populations shared common haplotypes within haplogroups R1a-Z280 or N-L1034 with Hungarian speakers, suggesting a common paternal genetic footprint that arose in prehistoric or historic times. Overall, the Hungarian, Mansi, and Bashkirian Mari populations have a much more complex genetic history than the traditional linguistic model or history would suggest. Further studies are needed to clarify the common genetic profiles may have been acquired directly or indirectly during the more or less known their history.

Genome-wide sequence analyses of ethnic populations across Russia

The Russian Federation is the largest and one of the most ethnically diverse countries in the world, however no centralized reference database of genetic variation exists to date. Such data are crucial for medical genetics and essential for studying population history. The Genome Russia Project aims at filling this gap by performing whole genome sequencing and analysis of peoples of the Russian Federation. Here we report the characterization of genome-wide variation of 264 healthy adults, including 60 newly sequenced samples. People of Russia carry known and novel genetic variants of adaptive, clinical and functional consequence that in many cases show allele frequency divergence from neighboring populations. Population genetics analyses revealed six phylogeographic partitions among indigenous ethnicities corresponding to their geographic locales. This study presents a characterization of population-specific genomic variation in Russia with results important for medical genetics and for understanding the dynamic population history of the world's largest country.

Application of the geographic population structure (GPS) algorithm for biogeographical analyses of wild and captive gorillas

Background

The utilization of high resolution genome data has important implications for the phylogeographical evaluation of non-human species. Biogeographical analyses can yield detailed understanding of their population biology and facilitate the geo-localization of individuals to promote their efficacious management, particularly when bred in captivity. The Geographic Population Structure (GPS) algorithm is an admixture based tool for inference of biogeographical affinities and has been employed for the geo-localization of various human populations worldwide. Here, we applied the GPS tool for biogeographical analyses and localization of the ancestral origins of wild and captive gorilla genomes, of unknown geographic source, available in the Great Ape Genome Project (GAGP), employing Gorillas with known ancestral origin as the reference data.

Results

Our findings suggest that GPS was successful in recapitulating the population history and estimating the geographic origins of all gorilla genomes queried and localized the wild gorillas with unknown geographical origin < 150 km of National Parks/Wildlife Reserves within the political boundaries of countries, considered as prominent modern-day abode for gorillas in the wild. Further, the GPS localization of most captive-born gorillas was congruent with their previously presumed ancestral homes.

Conclusions

Currently there is limited knowledge of the ancestral origins of most North American captive gorillas, and our study highlights the usefulness of GPS for inferring ancestry of captive gorillas. Determination of the native geographical source of captive gorillas can provide valuable information to guide breeding programs and ensure their appropriate management at the population level. Finally, our findings shine light on the broader applicability of GPS for protecting the genetic integrity of other endangered non-human species, where controlled breeding is a vital component of their conservation.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2568-5) contains supplementary material, which is available to authorized users.

Genes reveal traces of common recent demographic history for most of the Uralic-speaking populations

BACKGROUND

The genetic origins of Uralic speakers from across a vast territory in the temperate zone of North Eurasia have remained elusive. Previous studies have shown contrasting proportions of Eastern and Western Eurasian ancestry in their mitochondrial and Y chromosomal gene pools. While the maternal lineages reflect by and large the geographic background of a given Uralic-speaking population, the frequency of Y chromosomes of Eastern Eurasian origin is distinctively high among European Uralic speakers. The autosomal variation of Uralic speakers, however, has not yet been studied comprehensively.

RESULTS

Here, we present a genome-wide analysis of 15 Uralic-speaking populations which cover all main groups of the linguistic family. We show that contemporary Uralic speakers are genetically very similar to their local geographical neighbours. However, when studying relationships among geographically distant populations, we find that most of the Uralic speakers and some of their neighbours share a genetic component of possibly Siberian origin. Additionally, we show that most Uralic speakers share significantly more genomic segments identity-by-descent with each other than with geographically equidistant speakers of other languages. We find that correlated genome-wide genetic and lexical distances among Uralic speakers suggest co-dispersion of genes and languages. Yet, we do not find long-range genetic ties between Estonians and Hungarians with their linguistic sisters that would distinguish them from their non-Uralic-speaking neighbours.

CONCLUSIONS

We show that most Uralic speakers share a distinct ancestry component of likely Siberian origin, which suggests that the spread of Uralic languages involved at least some demic component.