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Results and discussion. Y-chromosomes of the Kamchatkan Chukchi show a low diversity, being dominated by two variants N3a5b-B202 (57%) and N3*-M178* (19%), both virtually absent in the neighboring groups of Kamchatka. Phylogenetic analysis of the major lineages reveals some similarity with the populations of Chukotka (including Yupik Eskimo) at the level of clusters and closely matching haplotypes. More likely, this similarity can be explained by the gene flow from the Chukchi homeland to the south (i.e. to the northern regions of Kamchatka) over the past two centuries. The phylogenetic analysis of the N3a5b-B202 haplogroup revealed a correspondence between its two NGS-identified sub-branches (N3a5b1-B203, N3a5b2-B204) and two clusters found using STR markers. This concordance made it possible to compare the age estimates of these haplogroups obtained by different methods; the ages fell within the interval of 0.5-1.5 thousand years ago. N3*-M178* lineage is represented by a single STR-cluster (~800 years old) for which no “full-genome” analogue has yet been identified. The rest of the Chukchi paternal gene pool includes haplogroups C2-M48x (SK1066) (7%) and Q-M242 (7%), which are also present in the neighboring populations, primarily Koryaks, as well as Evens and Evenks. Conclusions. As expected, due to historical considerations, Chukchi of Kamchatka are most similar in Y-chromosome to the Chukotkan populations. The dating of the major branches of haplogroup N3 found in the Chukchi indicates a likely population growth within the past 0.5-1.5 thousand years. There is also a minor component in Chukchi, shared with the populations of Kamchatka, but its strict dating and origin is still unclear: it can be attributed both to the shared ancient NE Asian ancestry and to a recent admixture with local Kamchatkan groups.

Western Kazakhstan is populated by three clans totaling 2 million people. Since the clans are patrilineal, the Y-chromosome is the most informative genetic system for tracing their origin. We genotyped 40 Y-SNP and 17 Y-STR markers in 330 Western Kazakhs. High phylogenetic resolution within haplogroup C2a1a2-M48 was achieved by using additional SNPs. Three lines of evidence indicate that the Alimuly and Baiuly clans (but not the Zhetiru clan) have a common founder placed 700 ± 200 years back by the STR data and 500 ± 200 years back by the sequencing data. This supports traditional genealogy claims about the descent of these clans from Emir Alau, who lived 650 years ago and whose lineage might be carried by two-thirds of Western Kazakhs. There is accumulation of specific haplogroups in the subclans representing other lineages, confirming that the clan structure corresponds with the paternal genetic structure of the steppe population.

According to the data on the Y-chromosome polymorphism, an assessment of the influence of two factors (tribal (clan) and administrative (kozhuuns) subdivision) on the structure of the gene pool of Tuvans is provided. The ten most common Tuvan clans (Ak, Baraan, Irgit, Kol, Kyrgyz, Mongush, Oorzhak, Oyun, Khertek, Choodu) are included in this analysis. They cover two-thirds of the total sample (N = 545) of Tuvans from six kozhuuns (Barun-Khemchiksky, Tandinsky, Tere-Kholsky, Todzhinsky, Chaa-Kholsky, Erzinsky). Genetic portraits of clans created on the basis of 52 SNP markers of the Y chromosome reveal the founder effect for all clans, except the two largest—Kyrgyz and Mongush. Making up one-third of the sample, these two clans are conglomerates. Analysis of molecular variance (AMOVA) indicates an equal degree of genetic separation of clans (5.2%) and kozhuuns (6.8%). But the Mantel test detects a high correlation (r = 0.50) between the genetic and clan structure against the low correlation (r = 0.25) between the genetic and geographical distances. The reason for the difference between the AMOVA and Mantel test lies in the fact that the four most numerous kozhuuns are “monoclan,” in which one clan prevails, and only two kozhuuns (Todzhinsky and Tere-Kholsky) include representatives of three different clans. The selection of the western and eastern clusters on the graph of multidimensional scaling fits in well with the anthropological data (Sayansky and Katangsky anthropological types), but does not confirm any of the ethnographic versions of the Tuvan ethnogenesis (“Samoyedic,” “Mongolian,” “Turkic”). The sum of results indicates that the tribal structure most fully reflects the architectonics of the Tuvan gene pool, and for this reason, it must be taken into account in population genetic research.

Oleg Balanovsky,1– 3 Valeria Petrushenko,1,4 Karin Mirzaev,2,5 Sherzod Abdullaev,5 Igor Gorin,1,4 Denis Chernevskiy,2 Anastasiya Agdzhoyan,1,2 Elena Balanovska,2,3 Alexander Kryukov,5 Ilyas Temirbulatov,2,5 Dmitriy Sychev5 1Laboratory of Genome Geography, Vavilov Institute of General Genetics, Moscow, Russia; 2Laboratory of Human Population Genetics, Research Centre for Medical Genetics, Moscow, Russia; 3Biobank of North Eurasia, Moscow, Russia; 4Department of Bioinformatics Moscow Institute of Physics and Technology, Moscow, Russia; 5Department of Clinical Pharmacology and Therapeutics, Russian Medical Academy of Continuous Professional Education, Moscow, RussiaCorrespondence: Elena BalanovskaLaboratory of Human Population Genetics, Research Centre for Medical Genetics, Moscow, RussiaTel +7 499 612-81-79Email balanovska@mail.ruDmitriy SychevDepartment of Clinical Pharmacology and Therapeutics, Russian Medical Academy of Continuous Professional Education, Moscow, RussiaTel +7 495 680-05-99Email dmitry.alex.sychev@gmail.comBackground: Information about the distribution of clinically significant genetic markers in different populations may be helpful in elaborating personalized approaches to the clinical management of COVID-19 in the absence of consensus guidelines.Aim: Analyze frequencies and distribution patterns of two markers associated with severe COVID-19 (rs11385942 and rs657152) and look for potential correlations between these markers and deaths from COVID-19 among populations in Russia and across the world.Methods: We genotyped 1883 samples from 91 ethnic groups pooled into 28 populations representing Russia and its neighbor states. We also compiled a dataset on 32 populations from other regions using genotypes extracted or imputed from the available databases. Geographic maps showing the frequency distribution of the analyzed markers were constructed using the obtained data.Results: The cartographic analysis revealed that rs11385942 distribution follows the West Eurasian pattern: the marker is frequent among the populations of Europe, West Asia and South Asia but rare or absent in all other parts of the globe. Notably, the transition from high to low rs11385942 frequencies across Eurasia is not abrupt but follows the clinal variation pattern instead. The distribution of rs657152 is more homogeneous. The analysis of correlations between the frequencies of the studied markers and the epidemiological characteristics of COVID-19 in a population revealed that higher frequencies of both risk alleles correlated positively with mortality from this disease. For rs657152, the correlation was especially strong (r = 0.59, p = 0.02). These reasonable correlations were observed for the “Russian” dataset only: no such correlations were established for the “world” dataset. This could be attributed to the differences in methodology used to collect COVID-19 statistics in different countries.Conclusion: Our findings suggest that genetic differences between populations make a small yet tangible contribution to the heterogeneity of the pandemic worldwide.Keywords: severe COVID-19, genetic markers, AB0, rs11385942, rs657152, gene geography

The pathogenic variants of genes encoding proteins, participating in the formation and functioning of epidermis and dermo-epidermal junctions, create a large variety of clinical phenotypes from: small localized to severe generalized dermatitis, as well as early, or even, prenatal death due to extensive epidermis loss. The diagnostic panel in this study was developed for the purposes of identifying these pathogenic genetic variants in 268 Russian children, who possessed the epidermolysis bullosa symptom complex in a selection of 247 families. This panel included the targeted areas of 33 genes, which are genetic variants that can lead to the development of the phenotype mentioned above. The usage of next generation sequencing allowed the revelation of 192 various altered alleles (of which 109 alleles were novel, i.e., had not been described previously). In addition, it allowed the definition of the genetic variants that are both typical for most of the examined children and for the separate ethnic groups inhabiting modern Russia. We found that the most characteristic mutations for the Dargin and Chechen ethnic groups are the c.3577del deletion in the COL7A1 gene and the c.2488G>A missense mutation in the COL17A1 gene, respectively. In addition, the study of haplotypes of microsatellite markers, which we managed to conduct in the Dargin population, confirmed the presence of the founder effect.

Ubykh people inhabited the area of what now is Greater Sochi, one time being neighbors of the Abkhaz and Adyghe. In 1864, after the Caucasian War, a small group of Ubykh survivors migrated to Turkey. The Ubykh language is a branch of the Northwest Caucasian (Abkhazo-Adyghe) languages, which is either placed in the Abkhaz or Adyghe subgroup or distinguished in a separate subgroup, according to various classifications. All this makes Ubykhs an important but genetically unexplored part of the gene pool of the Caucasus population. We collected an exclusive sample (N = 36) of Ubykh individuals, mainly from their diaspora in Turkey. Application of a high resolution panel of Y-chromosome markers (59 SNP and 17 STR) revealed the major West Caucasus haplogroup G2 (75% of the Ubykh population) and pan-Eurasian haplogroup R1a (19%). Within the G2 haplogroup, we identified 14 branches and genotyped 14 branch-defining markers. The frequencies of the same 14 markers in 19 other populations of the Caucasus were included for comparison. Both the genetic distances and the gene geographical map of the most frequent subhaplogroup (defined by the YY1215 marker at the GRCh37 position 8903699, comprising 50% of the Ubykh sample) revealed similarity of the Ubykh and Adyghe populations. Other Abkhaz-Adyghe-speaking populations appear to be at a greater genetic distance from the Ubykhs, similar to the distance to the Turkic-speaking groups of the North Caucasus. The Ossetian gene pool has little in common with Ubykhs, thus contradicting the hypothesis of the Alanian substrate in Ubykhs. Other populations of the Caucasus and Transcaucasia (of Nakh-Daghestanian and Kartvelian linguistic groups) do not show apparent genetic similarities to Ubykhs.

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.

Archaeogenetic studies have described the formation of Eurasian ‘steppe ancestry’ as a mixture of Eastern and Caucasus hunter-gatherers. However, it remains unclear when and where this ancestry arose and whether it was related to a horizon of cultural innovations in the 4th millennium BCE that subsequently facilitated the advance of pastoral societies in Eurasia. Here we generated genome-wide SNP data from 45 prehistoric individuals along a 3000-year temporal transect in the North Caucasus. We observe a genetic separation between the groups of the Caucasus and those of the adjacent steppe. The northern Caucasus groups are genetically similar to contemporaneous populations south of it, suggesting human movement across the mountain range during the Bronze Age. The steppe groups from Yamnaya and subsequent pastoralist cultures show evidence for previously undetected farmer-related ancestry from different contact zones, while Steppe Maykop individuals harbour additional Upper Palaeolithic Siberian and Native American related ancestry., The Caucasus mountain range has impacted on the culture and genetics of the wider region. Here, the authors generate genome-wide SNP data for 45 Eneolithic and Bronze Age individuals across the Caucasus, and find distinct genetic clusters between mountain and steppe zones as well as occasional gene-flow.

The lack of information about the frequency of pharmacogenetic markers in Russia impedes the adoption of personalized treatment algorithms originally developed for West European populations. The aim of this paper was to study the distribution of some clinically significant pharmacogenetic markers across Russia. A total of 45 pharmacogenetic markers were selected from a few population genetic datasets, including ADME, drug target and hemostasis-controlling genes. The total number of donors genotyped for these markers was 2,197. The frequencies of these markers were determined for 50 different populations, comprised of 137 ethnic and subethnic groups. A comprehensive pharmacogenetic atlas was created, i.e. a systematic collection of gene geographic maps of frequency variation for 45 pharmacogenetic DNA markers in Russia and its neighbor states. The maps revealed 3 patterns of geographic variation. Clinal variation (a gradient change in frequency along the East-West axis) is observed in the pharmacogenetic markers that follow the main pattern of variation for North Eurasia (13% of the maps). Uniform distribution singles out a group of markers that occur at average frequency in most Russian regions (27% of the maps). Focal variation is observed in the markers that are specific to a certain group of populations and are absent in other regions (60% of the maps). The atlas reveals that the average frequency of the marker and its frequency in individual populations do not indicate the type of its distribution in Russia: a gene geographic map is needed to uncover the pattern of its variation.

Background Predicting the eye and hair color from genotype became an established and widely used tool in forensic genetics, as well as in studies of ancient human populations. However, the accuracy of this tool has been verified on the West and Central Europeans only, while populations from border regions between Europe and Asia (like Caucasus and Ural) also carry the light pigmentation phenotypes. Results We phenotyped 286 samples collected across North Eurasia, genotyped them by the standard HIrisPlex-S markers and found that predictive power in Caucasus/Ural/West Siberian populations is reasonable but lower than that in West Europeans. As these populations have genetic ancestries different from that of West Europeans, we hypothesized they may carry a somewhat different allele spectrum. Thus, for all samples we performed the exome sequencing additionally enriched with the 53 genes and intergenic regions known to be associated with the eye/hair color. Our association analysis replicated the importance of the key previously known SNPs but also identified five new markers whose eye color prediction power for the studied populations is compatible with the two major previously well-known SNPs. Four out of these five SNPs lie within the HERС2 gene and the fifth in the intergenic region. These SNPs are found at high frequencies in most studied populations. The released dataset of exomes from Russian populations can be further used for population genetic and medical genetic studies. Conclusions This study demonstrated that precision of the established systems for eye/hair color prediction from a genotype is slightly lower for the populations from the border regions between Europe and Asia that for the West Europeans. However, this precision can be improved if some newly revealed predictive SNPs are added into the panel. We discuss that the replication of these pigmentation-associated SNPs on the independent North Eurasian sample is needed in the future studies.

Western Kazakhstan is populated by three clans totaling 2 million people. Since the clans are patrilineal, the Y-chromosome is the most informative genetic system for tracing their origin. We genotyped 40 Y-SNP and 17 Y-STR markers in 330 Western Kazakhs. High phylogenetic resolution within haplogroup C2a1a2-M48 was achieved by using additional SNPs. Three lines of evidence indicate that the Alimuly and Baiuly clans (but not the Zhetiru clan) have a common founder placed 700 ± 200 years back by the STR data and 500 ± 200 years back by the sequencing data. This supports traditional genealogy claims about the descent of these clans from Emir Alau, who lived 650 years ago and whose lineage might be carried by two-thirds of Western Kazakhs. There is accumulation of specific haplogroups in the subclans representing other lineages, confirming that the clan structure corresponds with the paternal genetic structure of the steppe population.

The demographic parameters and Y-chromosomal variation in the Ulchi population, an indigenous ethnic group of Khabarovsk krai, were studied. The demographic portrait was compiled using the data from the books of rural household accounting (7521 records, including 1562 on Ulchi). The structure of the gene pool was characterized for 45 SNP markers of the Y chromosome: 52 DNA samples were analyzed. The total number of Ulchi in the period between the censuses of 1926–2002 showed stable growth (723–2913 individuals) and slightly decreased by 2010 (2765 individuals). The study revealed an imbalance in the sex ratio (SR = 1 : 1.7) and the age structure close to the stationary type and providing a simple type of reproduction of the Ulchi. Analysis of the marital structure demonstrated a high rate of assimilation of the Ulchi by the Russian-speaking population dominant in all places of their compact settlement. Analysis for the SNP markers of the Y chromosomes (23 haplogroups were found) revealed a strong similarity of the Ulchi to the populations of the Amur River region and Okhotsk coast and a relative proximity to the Central Asian populations as given by haplogroup C. Genotyping of five new SNP markers within haplogroup C and 17 STR markers provided a correct phylogenetic analysis of haplogroup C in the Ulchi and neighboring peoples. It did not confirm the powerful gene drift in the Ulchi, which one might expect owing to their low effective size, likely because the Ulchi population was subdivided and thus managed to retain its diversity. However, this analysis revealed traces of intense interaction of the Ulchi with the peoples of the Far East and Central Asia over the past one to three thousand years. Therefore, the results of a recent study of the similarity of the ancient genomes of Primorye with the Ulchi indicate not the uniqueness of the Ulchi but the fact that this ancient gene pool was preserved in a vast milieu of populations of the Far East interlaced with gene flows both with each other and with populations of Central Asia.

Correction: Nature communications 9 (2018), art. no. 1494 doi:10.1038/s41467-018-03872-y While the series of events that shaped the transition between foraging societies and food producers are well described for Central and Southern Europe, genetic evidence from Northern Europe surrounding the Baltic Sea is still sparse. Here, we report genome-wide DNA data from 38 ancient North Europeans ranging from similar to 9500 to 2200 years before present. Our analysis provides genetic evidence that hunter-gatherers settled Scandinavia via two routes. We reveal that the first Scandinavian farmers derive their ancestry from Anatolia 1000 years earlier than previously demonstrated. The range of Mesolithic Western hunter-gatherers extended to the east of the Baltic Sea, where these populations persisted without gene-flow from Central European farmers during the Early and Middle Neolithic. The arrival of steppe pastoralists in the Late Neolithic introduced a major shift in economy and mediated the spread of a new ancestry associated with the Corded Ware Complex in Northern Europe.

We studied the Y-chromosome pool of the ethnic Russian population of Novgorod oblast (Russia) by 49 SNP and 17 STR markers. The total sample (N = 191) consists of four populations of the Novgorod region, including its southwestern (Shelon Pyatina) and eastern (Bezhetsk Pyatina) parts. Altogether, these four populations represent both the area of the Sopki archaeological culture (supposedly linked with the Novgorod Slovens tribe known from the chronicles) and the area of the Long Barrows culture (supposedly linked with the Krivichi Slavic tribe or with Balts). The pronounced genetic differences between southern and northern Russian populations are well known from previous studies; however, the Novgorod gene pool turned out to be neither northern nor southern, but a representative of the intermediate buffer zone. This zone was identified in this study and included a set of regional Russian populations from Pskov in the west to Kostroma in the east. All four studied populations of Novgorod region are genetically similar. The minor differences among them might represent the medieval Slavic migrations along the rivers, which survived despite the massive demographic shifts during the following history. Haplogroup N3 comprises one-fifth of the Novgorod pool of paternal lineages, with conditionally “Finnic” N3a4 and conditionally “East Baltic Sea Coast” N3a3 clades being almost equally frequent. The N3a3 phylogenetic network revealed the specific “Balto-Slavic” cluster of STR haplotypes, which is frequent in Baltic-speaking Lithuanians but infrequent in Finno-Ugric speaking Estonians. The Novgorod haplotypes lie outside this cluster, indicating that the Novgorod population received both N3a3 and N3a4 from Finno-Ugric speaking populations of the region, which, in turn, acquired the Mesolithic gene pool of the Northeastern Europe.

Although mutations in the GJB2 gene sequence make up the majority of variants causing autosomal-recessive non-syndromic hearing loss, few large deletions have been shown to contribute to DFNB1 deafness. Currently, genetic testing for DFNB1 hearing loss includes GJB2 sequencing and DFNB1 deletion analysis for two common large deletions, del(GJB6-D13S1830) and del(GJB6-D13S1854). Here, we report frequency in Russia, clinical significance and evolutionary origins of a 101 kb deletion, del(GJB2-D13S175), recently identified by us. In multiethnic cohort of 1104 unrelated hearing loss patients with biallelic mutations at the DFNB1 locus, the del(GJB2-D13S175) allele frequency of up to 0.5% (11/2208) was determined and this allele was shown to be predominantly associated with profound sensorineural hearing loss. Additionally, eight previously unpublished GJB2 mutations were described in this study. All patients carrying del(GJB2-D13S175) were of the Ingush ancestry. Among normal hearing individuals, del(GJB2-D13S175) was observed in Russian Republic of Ingushetia with a carrier rate of ~1% (2/241). Analysis of haplotypes associated with the deletion revealed a common founder in the Ingushes, with age of the deletion being ~3000 years old. Since del(GJB2-D13S175) was missed by standard methods of GJB2 analysis, del(GJB2-D13S175) detection has been added to our routine testing strategy for DFNB1 hearing loss.

The Upper Volga region was an area of contacts of Finno-Ugric, Slavic, and Scandinavian speaking populations in the 8th–10th centuries AD. However, their role in the formation of the contemporary gene pool of the Russian population of the region is largely unknown. To answer this question, we studied four populations of Yaroslavl oblast (N = 132) by a wide panel of STR and SNP markers of the Y-chromosome. Two of the studied populations appear to be genetically similar: the indigenous Russian population of Yaroslavl oblast and population of Katskari are characterized by the same major haplogroup, R-M198 (xM458). Haplogroup R-M458 composes more than half of Sitskari’s gene pool. The major haplogroup in the gene pool of the population of the ancient town of Mologa is N-M178. Subtyping N-M178 by newest “genomeera” Y-SNP markers showed different pathways of entering this haplogroup into the gene pools of Yaroslavl Volga region populations. The majority of Russian populations have subvariant N3a3-CTS10760; the regular sample of Yaroslavl oblast is equally represented by subvariants N3a3-CTS10760 and N3a4-Z1936, while subvariant N3a4-Z1936 predominates in the gene pool of population of Mologa. This N3a4-Z1936 haplogroup is common among the population of the north of Eastern Europe and the Volga-Ural region. The obtained results indicate preservation of the Finno-Ugric component in the gene pool of population of Mologa and a contribution of Slavic colonization in the formation of the gene pool of the Yaroslavl Volga region populations and make it possible to hypothesize the genetic contribution of the “downstream” (Rostov- Suzdal) rather than “upstream” (Novgorod) Slavic migration wave.

The complexity of the admixture dynamics that shaped American populations is unveiled by Ongaro et al., where genetic data for more than 12,000 individuals from the continents are investigated. This study evaluates the dramatic impact of events after the colonial era, revealing a spatial and temporal heterogeneity and mirroring historical records. © 2019 Elsevier Ltd The human genetic diversity of the Americas has been affected by several events of gene flow that have continued since the colonial era and the Atlantic slave trade. Moreover, multiple waves of migration followed by local admixture occurred in the last two centuries, the impact of which has been largely unexplored. Here, we compiled a genome-wide dataset of ∼12,000 individuals from twelve American countries and ∼6,000 individuals from worldwide populations and applied haplotype-based methods to investigate how historical movements from outside the New World affected (1) the genetic structure, (2) the admixture profile, (3) the demographic history, and (4) sex-biased gene-flow dynamics of the Americas. We revealed a high degree of complexity underlying the genetic contribution of European and African populations in North and South America, from both geographic and temporal perspectives, identifying previously unreported sources related to Italy, the Middle East, and to specific regions of Africa. © 2019 Elsevier Ltd Preprint version of the article: "The genomic impact of European colonization of the Americas", posted June 28, 2019 on bioRxiv. Article is now published in Current Biology doi: [dx.doi.org/10.1016/j.cub.2019.09.076]. Published version on this repository: [http://vinar.vin.bg.ac.rs/handle/123456789/8654].

The indigenous populations of inner Eurasia—a huge geographic region covering the central Eurasian steppe and the northern Eurasian taiga and tundra—harbour 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 contributions from so-called ‘ancient North Eurasian’ ancestry over time, which is 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. Genome-wide data for 763 individuals from inner Eurasia reveal 3 admixture clines in present-day populations that mirror geography, illuminating the historic spread and mixture of peoples across the Eurasian steppe, taiga and tundra.

The human genetic diversity of the Americas has been shaped by several events of gene flow that have continued since the Colonial Era and the Atlantic slave trade. Moreover, multiple waves of migration followed by local admixture occurred in the last two centuries, the impact of which has been largely unexplored. Here we compiled a genome-wide dataset of ~12,000 individuals from twelve American countries and ~6,000 individuals from worldwide populations and applied haplotype-based methods to investigate how historical movements from outside the New World affected i) the genetic structure, ii) the admixture profile, iii) the demographic history and iv) sex-biased gene-flow dynamics, of the Americas. We revealed a high degree of complexity underlying the genetic contribution of European and African populations in North and South America, from both geographic and temporal perspectives, identifying previously unreported sources related to Italy, the Middle East and to specific regions of Africa.

The authors discussed the results of study of population genetic structure of Khakass sub-ethnic groups - indigenous population of the Republic of Khakassia. The gene pool is studied according to two classes of markers: autosomal DNA (CCR2*rs1799864, CCR5*rs333, ACE1*rs4646994, PLAT*rs4646972, noA25*rs, PV92*rs3138523, ApoA1*rs3138522, noB65*rs, no F13B*rs) and quasigenetic markers (surnames). Total sample size was 249 persons for autosomal DNA dataset, and 9693 persons for the surnames dataset. Four Khakass sub-ethnic groups - Kachins, Koybals, Kyzyls, and Sagays - were investigated. Both classes of markers provided similar results on the subdivision of Khakass sub-ethnic groups and genetic relationships between them. Analysis of autosomal DNA markers showed statistically significant differences of allele frequencies. Interpopulation genetic variation (GST) of the Khakass populations was 2.10%. The largest genetic distances were observed when comparing Sagays and Kyzyls (d = 0.032). The least genetic distances were observed when comparing samples of Kachins and Koybals (d = 0.032). According to the surnames dataset, the similarity index (Ri) is minimal in the pair "Sagays - Kyzyls" and is maximal in a pair of "Kachins - Koybals". Genetic distances characterizing the differences between sub-ethnic groups, decrease, and kinship coefficient, which reflects the similarity increases in the following series: Sagays, Kyzyls, Kachins, and Koybals.

Population biobanks are collections of thoroughly annotated biological material stored for many years. Population biobanks are a valuable resource for both basic science and applied research and are essential for extensive analysis of gene pools. Population biobanks make it possible to carry out fundamental studies of the genetic structure of populations, explore their genetic processes, and reconstruct their genetic history. The importance of biobanks for applied research is no less significant: they are essential for development of personalized medicine and genetic ecological monitoring of populations and are in high demand in forensic science. Establishment of an efficient and representative biobank requires strict observance of the principles of sample selection in populations, protocols of DNA extraction, quality control, and storage and documentation of biological materials. We reviewed regional biobanks and presented the organizational model of population biobank establishment based on the Biobank of Indigenous Population of Northern Eurasia created under supervision of E.V. Balanovska and O.P. Balanovsky. The results obtained using the biobanks in transdisciplinary research and prospective applications for the purposes of genogeography, genomic medicine, and forensic science are presented.

STR haplotypes of the Y chromosome are widely used as effective genetic markers in studies of human populations and in forensic DNA analysis. The task often arises to compare the spectrum of haplotypes in individuals or entire populations. Performing this task manually is too laborious and thus unrealistic. We propose an algorithm for counting similarity between STR haplotypes. This algorithm is suitable for massive analyses of samples. It is implemented in the computer program Haplomatch, which makes it possible to find haplotypes that differ from the target haplotype by 0, 1, 2, 3, or more mutational steps. The program may operate in two modes: comparison of individuals and comparison of populations. Flexibility of the program (the possibility of using any external database), its usability (MS Excel spreadsheets are used), and the capability of being applied to other chromosomes and other species could make this software a new useful tool in population genetics and forensic and genealogical studies. The Haplomatch software is freely available on our website www.genofond.ru. The program is applied to studying the gene pool of Cossacks. Experimental analysis of Y-chromosomal diversity in a representative set (N = 131) of Upper Don Cossacks is performed. Analysis of the STR haplotypes detects genetic proximity of Cossacks to East Slavic populations (in particular, to Southern and Central Russians, as well as to Ukrainians), which confirms the hypothesis of the origin of the Cossacks mainly due to immigration from Russia and Ukraine. Also, a small genetic influence of Turkicspeaking Nogais is found, probably caused by their occurrence in the Don Voisko as part of the Tatar layer. No similarities between haplotype spectra of Cossacks and Caucasus populations are found. This case study demonstrates the effectiveness of the Haplomatch software in analyzing large sets of STR haplotypes.

Siberian Tatars form the largest Turkic-speaking ethnic group in Western Siberia. The group has a complex hierarchical system of ethnographically diverse populations. Five subethnic groups of Tobol-Irtysh Siberian Tatars (N = 388 samples) have been analyzed for 50 informative Y-chromosomal SNPs. The subethnic groups have been found to be extremely genetically diverse (FST = 21%), so the Siberian Tatars form one of the strongly differentiated ethnic gene pools in Siberia and Central Asia. Every method employed in our studies indicates that different subethnic groups formed in different ways. The gene pool of Isker-Tobol Tatars descended from the local Siberian indigenous population and an intense, albeit relatively recent gene influx from Northeastern Europe. The gene pool of Yalutorovsky Tatars is determined by the Western Asian genetic component. The subethnic group of Siberian Bukhar Tatars is the closest to the gene pool of the Western Caucasus population. Ishtyak-Tokuz Tatars have preserved the genetic legacy of Paleo-Siberians, which connects them with populations from Southern, Western, and Central Siberia. The gene pool of the most isolated Zabolotny (Yaskolbinsky) Tatars is closest to Ugric peoples of Western Siberia and Samoyeds of the Northern Urals. Only two out of five Siberian Tatar groups studied show partial genetic similarity to other populations calling themselves Tatars: Isker-Tobol Siberian Tatars are slightly similar to Kazan Tatars, and Yalutorovsky Siberian Tatars, to Crimean Tatars. The approach based on the full sequencing of the Y chromosome reveals only a weak (2%) Central Asian genetic trace in the Siberian Tatar gene pool, dated to 900 years ago. Hence, the Mongolian hypothesis of the origin of Siberian Tatars is not supported in genetic perspective.

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 genome-wide data of two Eneolithic individuals (∽5,400 years before present) associated with the Botai culture in northern Kazakhstan. We find that inner Eurasian populations are structured into three distinct admixture clines stretching between various western and eastern Eurasian ancestries. This genetic separation is well mirrored by geography. The ancient Botai genomes suggest yet another layer of admixture in inner Eurasia that involves Mesolithic hunter-gatherers in Europe, the Upper Paleolithic southern Siberians and East Asians. Admixture modeling of ancient and modern populations suggests an overwriting of this ancient structure in the Altai-Sayan region by migrations of western steppe herders, but partial retaining of this ancient North Eurasian-related cline further to the North. 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.

Archaeogenetic studies have described the formation of Eurasian ‘steppe ancestry’ as a mixture of Eastern and Caucasus hunter-gatherers. However, it remains unclear when and where this ancestry arose and whether it was related to a horizon of cultural innovations in the 4thmillennium BCE that subsequently facilitated the advance of pastoral societies likely linked to the dispersal of Indo-European languages. To address this, we generated genome-wide SNP data from 45 prehistoric individuals along a 3000-year temporal transect in the North Caucasus. We observe a genetic separation between the groups of the Caucasus and those of the adjacent steppe. The Caucasus groups are genetically similar to contemporaneous populations south of it, suggesting that – unlike today – the Caucasus acted as a bridge rather than an insurmountable barrier to human movement. The steppe groups from Yamnaya and subsequent pastoralist cultures show evidence for previously undetected farmer-related ancestry from different contact zones, while Steppe Maykop individuals harbour additional Upper Palaeolithic Siberian and Native American related ancestry.

While the series of events that shaped the transition between foraging societies and food producers are well described for Central and Southern Europe, genetic evidence from Northern Europe surrounding the Baltic Sea is still sparse. Here, we report genome-wide DNA data from 38 ancient North Europeans ranging from ~9500 to 2200 years before present. Our analysis provides genetic evidence that hunter-gatherers settled Scandinavia via two routes. We reveal that the first Scandinavian farmers derive their ancestry from Anatolia 1000 years earlier than previously demonstrated. The range of Mesolithic Western hunter-gatherers extended to the east of the Baltic Sea, where these populations persisted without gene-flow from Central European farmers during the Early and Middle Neolithic. The arrival of steppe pastoralists in the Late Neolithic introduced a major shift in economy and mediated the spread of a new ancestry associated with the Corded Ware Complex in Northern Europe., The population history of Europe is complex and its very north has not yet been comprehensively studied at a genetic level. Here, Mittnik et al. report genome-wide data from 38 ancient individuals from the Eastern Baltic, Russia and Scandinavia to analyse gene flow throughout the Mesolithic and Bronze Age.

The territory of present-day Ukraine is subdivided into some regions with specific demographic and politic history. Nevertheless, the corresponding subdivision in genetic structure is not revealed in previous investigations: populations of Ukrainians under study were genetically homogeneous on SNP markers of Y chromosome. In the current investigation we studied the Y-chromosomal genetic structure of Transcarpathia and Bukovina populations. Several factors exist to expect the genetic specificity of these populations. Both ones are placed in the Carpathian foothills, at the south-western border of the Ukrainian area. During the last millennium these territories were the parts of different states and were open for ethnically diverse migrations. It was revealed that the major Y chromosomal haplogroups in Transcarpathia population were R1a1a1*(М198), I2a (Р37.2), R1a1a1g (М458), E1b1b1a1 (M78). The major haplogroups in Bukovina population were I2a (Р37.2), R1a1a1*(М198), R1a1a1g (М458), R1b1b2 (М269), E1b1b1a1 (M78), I1 (М253). The Bukovina population differs from the typical Ukrainian population by higher frequency of I2a (Р37.2) and lower frequency of R1a1a1*(М198). Moreover, this is the only population among ones studied in Ukraine where the most frequent haplogroup is I2a (Р37.2) but not R1a1a1*(М198). Such a deviation can be caused by possible mixing with neighbouring southern groups, and Carpathian mountains were not a border for exchange in this case. Interestingly, the haplogroup N1c (M178) is not revealed in Transcarpathia at all, obviously due to the mountain barrier. It was revealed by principal component analysis that Ukrainians from Transcarpathia and Bukovina despite some specific peculiarities are more similar to other Ukrainian populations than to the surrounding ethnic groups such as Poles, Slovaks, Hungarians, Romanians, Moldavians and Gagauzes. Ukrainians of Transcarpathia and Bukovina form the entire genetic continuum with the whole Ukraine on maps of gene distances, confirming the homogeneity of Ukrainian parental gene pool and it’s differentiation from other groups. After performing the analysis of Y-haplogroup spatial distribution, it is supposed that the northern ridges ofCarpathian mountainsare the East-European barrier decreasing the gene flow. It decreases the spreading of haplogroups N1c (М178) and R1a (М198) southward and movement of E1b (М78), R1b (М269), J (М304) and G (М201) northward.

The results of the study of Y-chromosomal polymorphisms of Russian and Ukrainian population are presented for Slobozhanshina--contemporary border region, former "Wild Field" boundary, which was inhabited in XVII-XVIII centuries by both the Russians from the north and Ukrainians from the west. In general, Ukrainian and Russian populations of Slobozhanshchina genetically are very close, their set and frequency range of Y-chromosome haplogroups are typical for the Eastern Europe. But a detailed analysis of highly informative Y-chromosome markers showed that after 3,5 centuries of coexistence on the same historical territory, the both nations retain the ethnic specificity of their gene pools: Ukrainian populations are similar to the rest of Ukraine, and Russian populations are similar to the south of the European part of Russia. The genetic differences may be due to the spatial characteristics of marriage migration and the predominant ethnic environment.

Multiple questions relating to contributions of cultural and demographical factors in the process of human geographical dispersal remain largely unanswered. India, a land of early human settlement and the resulting diversity is a good place to look for some of the answers. In this study, we explored the genetic structure of India using a diverse panel of 78 males genotyped using the GenoChip. Their genome-wide single-nucleotide polymorphism (SNP) diversity was examined in the context of various covariates that influence Indian gene pool. Admixture analysis of genome-wide SNP data showed high proportion of the Southwest Asian component in all of the Indian samples. Hierarchical clustering based on admixture proportions revealed seven distinct clusters correlating to geographical and linguistic affiliations. Convex hull overlay of Y-chromosomal haplogroups on the genome-wide SNP principal component analysis brought out distinct non-overlapping polygons of F*-M89, H*-M69, L1-M27, O2a-M95 and O3a3c1-M117, suggesting a male-mediated migration and expansion of the Indian gene pool. Lack of similar correlation with mitochondrial DNA clades indicated a shared genetic ancestry of females. We suggest that ancient male-mediated migratory events and settlement in various regional niches led to the present day scenario and peopling of India.