133 research outputs found

    The genetic history of admixture across inner Eurasia

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    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

    Uniparental Genetic Heritage of Belarusians: Encounter of Rare Middle Eastern Matrilineages with a Central European Mitochondrial DNA Pool

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    Ethnic Belarusians make up more than 80% of the nine and half million people inhabiting the Republic of Belarus. Belarusians together with Ukrainians and Russians represent the East Slavic linguistic group, largest both in numbers and territory, inhabiting East Europe alongside Baltic-, Finno-Permic- and Turkic-speaking people. Till date, only a limited number of low resolution genetic studies have been performed on this population. Therefore, with the phylogeographic analysis of 565 Y-chromosomes and 267 mitochondrial DNAs from six well covered geographic sub-regions of Belarus we strove to complement the existing genetic profile of eastern Europeans. Our results reveal that around 80% of the paternal Belarusian gene pool is composed of R1a, I2a and N1c Y-chromosome haplogroups – a profile which is very similar to the two other eastern European populations – Ukrainians and Russians. The maternal Belarusian gene pool encompasses a full range of West Eurasian haplogroups and agrees well with the genetic structure of central-east European populations. Our data attest that latitudinal gradients characterize the variation of the uniparentally transmitted gene pools of modern Belarusians. In particular, the Y-chromosome reflects movements of people in central-east Europe, starting probably as early as the beginning of the Holocene. Furthermore, the matrilineal legacy of Belarusians retains two rare mitochondrial DNA haplogroups, N1a3 and N3, whose phylogeographies were explored in detail after de novo sequencing of 20 and 13 complete mitogenomes, respectively, from all over Eurasia. Our phylogeographic analyses reveal that two mitochondrial DNA lineages, N3 and N1a3, both of Middle Eastern origin, might mark distinct events of matrilineal gene flow to Europe: during the mid-Holocene period and around the Pleistocene-Holocene transition, respectively

    Lessons from the Whole Exome Sequencing Effort in Populations of Russia and Tajikistan

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    © 2016, Springer Science+Business Media New York.In contrast with the traditional methods applied to assessment of population diversity, high-throughput sequencing technologies have a wider application in clinical practice with greater potential to find novel disease-causing variants for multifactorial disorders. Widely used test panels may not meet their goal to diagnose the patient’s condition with a full reliability since this method often does not take into account the population frequencies of analyzed genetic markers. Here, we analyzed 57 male individuals of five ethnic groups from Russia and Tajikistan using the whole exome sequencing technique (Ion AmpliSeq Exome), which resulted in detecting more than 299,000 single nucleotide polymorphisms. Samples formed clusters on the PCA plot according to the geographical location of the corresponding populations. Thereby, the methodology of whole-exome sequencing, in general, and the Ion AmpliSeq Exome panel, in particular, could be positively applied for the purposes of population genetics and for detection of the novel clinically relevant variants

    Reconstructing the genetic structure of the Kazakh from clan distribution data

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    Applying quasigenetic markers - non-biological traits which are nevertheless inherited in generations - is one of the research fields within human population genetics. For the West European, East European, and Caucasus populations, surnames are typical quasigenetic markers. For Central Asian populations, particularly Kazakh, the clan affiliation serves as a good marker: a set of papers demonstrated that many clans include mainly persons which biologically descent from a recent common ancestor. In this study, we analyzed a large (~4.2 million persons) dataset on quasigenetic markers - the geographic distribution of 50 Kazakh clans at the beginning of the 20th century, and compared the dataset with the direct data of the Y-chro-mosomal diversity in modern Kazakh populations. The analysis included three steps: the isonymy method, which is standard for quasigenetic markers, comparing frequencies of quasigenetic markers, and comparing the quasigenetic and genetic datasets. We constructed 50 maps of frequency of the distribution of each clan and revealed that these maps correlate with the maps of genetic distances. The Mantel test also demonstrated a significant correlation between geographic and quasigenetic distances (г = 0.60; p < 0.05). The analysis of inter-population variability revealed the largest diversity between geographic territories corresponding to the social-territorial groups of the Kazakh Khanate (zhuzes) rather than to other historical groups that existed on the territory of Kazakhstan in preceding and modern epochs. The same is evidenced by the principal components and multidimensional scaling plots, which grouped geographic populations into three clusters corresponding to three zhuzes. This indicates that the final structuring of the Kazakh gene pool might have occurred during the Kazakh Khanate period

    Estimating the impact of the Mongol expansion upon the gene pool of Tuvans

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    With a view to trace the Mongol expansion in Tuvinian gene pool we studied two largest Tuvinian clans – those in which, according to data of humanities, one could expect the highest Central Asian ancestry, connected with the Mongol expansion. Thus, the results of Central Asian ancestry in these two clans component may be used as upper limit of the Mongol influence upon the Tuvinian gene pool in a whole. According to the data of 59 Y-chromosomal SNP markers, the haplogroup spectra in these Tuvinian tribal groups (Mongush, N = 64, and Oorzhak, N = 27) were similar. On average, two-thirds of their gene pools (63 %) are composed by North Eurasian haplogroups (N*, N1a2, N3a, Q) connected with autochtonous populations of modern area of Tuvans. The Central Asian haplogroups (C2, O2) composed less then fifth part (17 %) of gene pools of the clans studied. The opposite ratio was revealed in Mongols: there were 10 % North Eurasian haplogroups and 75 % Central Asian haplogroups in their gene pool. All the results derived – “genetic portraits”, the matrix of genetic distances, the dendrogram and the multidimensional scaling plot, which mirror the genetic connections between Tuvinian clans and populations of South Siberia and East Asia, demonstrated the prominent similarity of the Tuvinian gene pools with populations from and Khakassia and Altai. It could be therefore assumed that Tuvinian clans Mongush and Oorzhak originated from autochtonous people (supposedly, from the local Samoyed and Kets substrata). The minor component of Central Asian haplogroups in the gene pool of these clans allowed to suppose that Mongol expansion did not have a significant influence upon the Tuvinan gene pool at a whole

    The genetic history of admixture across inner Eurasia

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    This is the author accepted manuscript. The final version is available from Nature Research via the DOI in this record.Data Availability. Genome-wide sequence data of two Botai individuals (BAM format) are available at the European Nucleotide Archive under the accession number PRJEB31152 (ERP113669). Eigenstrat format array genotype data of 763 present-day individuals and 1240K pulldown genotype data of two ancient Botai individuals are available at the Edmond data repository of the Max Planck Society (https://edmond.mpdl.mpg.de/imeji/collection/Aoh9c69DscnxSNjm?q=).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.Max Planck SocietyEuropean Research Council (ERC)Russian Foundation for Basic Research (RFBR)Russian Scientific FundNational Science FoundationU.S. National Institutes of HealthAllen Discovery CenterUniversity of OstravaCzech Ministry of EducationXiamen UniversityFundamental Research Funds for the Central UniversitiesMES R

    Genome-wide sequence analyses of ethnic populations across Russia

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    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

    Geographic population structure analysis of worldwide human populations infers their biogeographical origins

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    The search for a method that utilizes biological information to predict humans’ place of origin has occupied scientists for millennia. Over the past four decades, scientists have employed genetic data in an effort to achieve this goal but with limited success. While biogeographical algorithms using next-generation sequencing data have achieved an accuracy of 700 km in Europe, they were inaccurate elsewhere. Here we describe the Geographic Population Structure (GPS) algorithm and demonstrate its accuracy with three data sets using 40,000–130,000 SNPs. GPS placed 83% of worldwide individuals in their country of origin. Applied to over 200 Sardinians villagers, GPS placed a quarter of them in their villages and most of the rest within 50 km of their villages. GPS’s accuracy and power to infer the biogeography of worldwide individuals down to their country or, in some cases, village, of origin, underscores the promise of admixture-based methods for biogeography and has ramifications for genetic ancestry testing

    The GenoChip: A New Tool for Genetic Anthropology

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    The Genographic Project is an international effort aimed at charting human migratory history. The project is nonprofit and nonmedical, and, through its Legacy Fund, supports locally led efforts to preserve indigenous and traditional cultures. Although the first phase of the project was focused on uniparentally inherited markers on the Y-chromosome and mitochondrial DNA (mtDNA), the current phase focuses on markers from across the entire genome to obtain a more complete understanding of human genetic variation. Although many commercial arrays exist for genome-wide single-nucleotide polymorphism (SNP) genotyping, they were designed for medical genetic studies and contain medically related markers that are inappropriate for global population genetic studies. GenoChip, the Genographic Project’s new genotyping array, was designed to resolve these issues and enable higher resolution research into outstanding questions in genetic anthropology. TheGenoChip includes ancestry informativemarkers obtained for over 450 human populations, an ancient human (Saqqaq), and two archaic hominins (Neanderthal and Denisovan) and was designed to identify all knownY-chromosome andmtDNAhaplogroups. The chip was carefully vetted to avoid inclusion ofmedically relevant markers. To demonstrate its capabilities, we compared the FST distributions of GenoChip SNPs to those of two commercial arrays. Although all arrays yielded similarly shaped (inverse J) FST distributions, the GenoChip autosomal and X-chromosomal distributions had the highestmean FST, attesting to its ability to discern subpopulations. The chip performances are illustrated in a principal component analysis for 14 worldwide populations. In summary, the GenoChip is a dedicated genotyping platform for genetic anthropology. With an unprecedented number of approximately 12,000 Y-chromosomal and approximately 3,300 mtDNA SNPs and over 130,000 autosomal and X-chromosomal SNPswithout any known health,medical, or phenotypic relevance, the GenoChip is a useful tool for genetic anthropology and population genetics
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