Search

Currently available genetic tools effectively distinguish between different continental origins. However, North Eurasia, which constitutes one-third of the world’s largest continent, remains severely underrepresented. The dataset used in this study represents 266 populations from 12 North Eurasian countries, including most of the ethnic diversity across Russia’s vast territory. A total of 1,883 samples were genotyped using the Illumina Infinium Omni5Exome-4 v1.3 BeadChip. Three principal components were computed for the entire dataset using three iterations for outlier removal. It allowed the merging of 266 populations into larger groups while maintaining intragroup homogeneity, so 29 ethnic geographic groups were formed that were genetically distinguishable enough to trace individual ancestry. Several feature selection methods, including the random forest algorithm, were tested to estimate the number of genetic markers needed to differentiate between the groups; 5,229 ancestry-informative SNPs were selected. We tested various classifiers supporting multiple classes and output values for each class that could be interpreted as probabilities. The logistic regression was chosen as the best mathematical model for predicting ancestral populations. The machine learning algorithm for inferring an ancestral ethnic geographic group was implemented in the original software “Homeland” fitted with the interface module, the prediction module, and the cartographic module. Examples of geographic maps showing the likelihood of geographic ancestry for individuals from different regions of North Eurasia are provided. Validating methods show that the highest number of ethnic geographic group predictions with almost absolute accuracy and sensitivity was observed for South and Central Siberia, Far East, and Kamchatka. The total accuracy of prediction of one of 29 ethnic geographic groups reached 71%. The proposed method can be employed to predict ancestries from the populations of Russia and its neighbor states. It can be used for the needs of forensic science and genetic genealogy.

The Slavic branch of the Balto-Slavic sub-family of Indo-European languages underwent rapid divergence as a result of the spatial expansion of its speakers from Central-East Europe, in early medieval times. This expansion-mainly to East Europe and the northern Balkans-resulted in the incorporation of genetic components from numerous autochthonous populations into the Slavic gene pools. Here, we characterize genetic variation in all extant ethnic groups speaking Balto-Slavic languages by analyzing mitochondrial DNA (n = 6,876), Y-chromosomes (n = 6,079) and genome-wide SNP profiles (n = 296), within the context of other European populations. We also reassess the phylogeny of Slavic languages within the Balto-Slavic branch of Indo-European. We find that genetic distances among Balto-Slavic populations, based on autosomal and Y-chromosomal loci, show a high correlation (0.9) both with each other and with geography, but a slightly lower correlation (0.7) with mitochondrial DNA and linguistic affiliation. The data suggest that genetic diversity of the present-day Slavs was predominantly shaped in situ, and we detect two different substrata: 'central-east European' for West and East Slavs, and 'south-east European' for South Slavs. A pattern of distribution of segments identical by descent between groups of East-West and South Slavs suggests shared ancestry or a modest gene flow between those two groups, which might derive from the historic spread of Slavic people.

Y-chromosomal haplogroup G1 is a minor component of the overall gene pool of South-West and Central Asia but reaches up to 80% frequency in some populations scattered within this area. We have genotyped the G1-defining marker M285 in 27 Eurasian populations (n= 5,346), analyzed 367 M285-positive samples using 17 Y-STRs, and sequenced ~11 Mb of the Y-chromosome in 20 of these samples to an average coverage of 67X. This allowed detailed phylogenetic reconstruction. We identified five branches, all with high geographical specificity: G1-L1323 in Kazakhs, the closely related G1-GG1 in Mongols, G1-GG265 in Armenians and its distant brother clade G1-GG162 in Bashkirs, and G1-GG362 in West Indians. The haplotype diversity, which decreased from West Iran to Central Asia, allows us to hypothesize that this rare haplogroup could have been carried by the expansion of Iranic speakers northwards to the Eurasian steppe and via founder effects became a predominant genetic component of some populations, including the Argyn tribe of the Kazakhs. The remarkable agreement between genetic and genealogical trees of Argyns allowed us to calibrate the molecular clock using a historical date (1405 AD) of the most recent common genealogical ancestor. The mutation rate for Y-chromosomal sequence data obtained was 0.78×10-9 per bp per year, falling within the range of published rates. The mutation rate for Y-chromosomal STRs was 0.0022 per locus per generation, very close to the so-called genealogical rate. The "clan-based" approach to estimating the mutation rate provides a third, middle way between direct farther-to-son comparisons and using archeologically known migrations, whose dates are subject to revision and of uncertain relationship to genetic events.

North East Europe harbors a high diversity of cultures and languages, suggesting a complex genetic history. Archaeological, anthropological, and genetic research has revealed a series of influences from Western and Eastern Eurasia in the past. While genetic data from modern-day populations is commonly used to make inferences about their origins and past migrations, ancient DNA provides a powerful test of such hypotheses by giving a snapshot of the past genetic diversity. In order to better understand the dynamics that have shaped the gene pool of North East Europeans, we generated and analyzed 34 mitochondrial genotypes from the skeletal remains of three archaeological sites in northwest Russia. These sites were dated to the Mesolithic and the Early Metal Age (7,500 and 3,500 uncalibrated years Before Present). We applied a suite of population genetic analyses (principal component analysis, genetic distance mapping, haplotype sharing analyses) and compared past demographic models through coalescent simulations using Bayesian Serial SimCoal and Approximate Bayesian Computation. Comparisons of genetic data from ancient and modern-day populations revealed significant changes in the mitochondrial makeup of North East Europeans through time. Mesolithic foragers showed high frequencies and diversity of haplogroups U (U2e, U4, U5a), a pattern observed previously in European hunter-gatherers from Iberia to Scandinavia. In contrast, the presence of mitochondrial DNA haplogroups C, D, and Z in Early Metal Age individuals suggested discontinuity with Mesolithic hunter-gatherers and genetic influx from central/eastern Siberia. We identified remarkable genetic dissimilarities between prehistoric and modern-day North East Europeans/Saami, which suggests an important role of post-Mesolithic migrations from Western Europe and subsequent population replacement/extinctions. This work demonstrates how ancient DNA can improve our understanding of human population movements across Eurasia. It contributes to the description of the spatio-temporal distribution of mitochondrial diversity and will be of significance for future reconstructions of the history of Europeans.

In Europe, the Neolithic transition (8,000-4,000 B.C.) from hunting and gathering to agricultural communities was one of the most important demographic events since the initial peopling of Europe by anatomically modern humans in the Upper Paleolithic (40,000 B.C.). However, the nature and speed of this transition is a matter of continuing scientific debate in archaeology, anthropology, and human population genetics. To date, inferences about the genetic make up of past populations have mostly been drawn from studies of modern-day Eurasian populations, but increasingly ancient DNA studies offer a direct view of the genetic past. We genetically characterized a population of the earliest farming culture in Central Europe, the Linear Pottery Culture (LBK; 5,500-4,900 calibrated B.C.) and used comprehensive phylogeographic and population genetic analyses to locate its origins within the broader Eurasian region, and to trace potential dispersal routes into Europe. We cloned and sequenced the mitochondrial hypervariable segment I and designed two powerful SNP multiplex PCR systems to generate new mitochondrial and Y-chromosomal data from 21 individuals from a complete LBK graveyard at Derenburg Meerenstieg II in Germany. These results considerably extend the available genetic dataset for the LBK (n = 42) and permit the first detailed genetic analysis of the earliest Neolithic culture in Central Europe (5,500-4,900 calibrated B.C.). We characterized the Neolithic mitochondrial DNA sequence diversity and geographical affinities of the early farmers using a large database of extant Western Eurasian populations (n = 23,394) and a wide range of population genetic analyses including shared haplotype analyses, principal component analyses, multidimensional scaling, geographic mapping of genetic distances, and Bayesian Serial Simcoal analyses. The results reveal that the LBK population shared an affinity with the modern-day Near East and Anatolia, supporting a major genetic input from this area during the advent of farming in Europe. However, the LBK population also showed unique genetic features including a clearly distinct distribution of mitochondrial haplogroup frequencies, confirming that major demographic events continued to take place in Europe after the early Neolithic.

Lypd6 is a GPI-tethered protein from the Ly-6/uPAR family expressed in the brain. Lypd6 enhances the Wnt/β-catenin signaling, although its action on nicotinic acetylcholine receptors (nAChRs) have been also proposed. To investigate a cholinergic activity of Lypd6, we studied a recombinant water-soluble variant of the human protein (ws-Lypd6) containing isolated “three-finger” LU-domain. Experiments at different nAChR subtypes expressed in Xenopus oocytes revealed the negative allosteric modulatory activity of ws-Lypd6. Ws-Lypd6 inhibited ACh-evoked currents at α3β4- and α7-nAChRs with IC50 of ∼35 and 10 μM, respectively, and the maximal amplitude of inhibition of 30–50%. EC50 of ACh at α3β4-nAChRs (∼30 μM) was not changed in the presence of 35 μM ws-Lypd6, while the maximal amplitude of ACh-evoked current was reduced by ∼20%. Ws-Lypd6 did not elicit currents through nAChRs in the absence of ACh. Application of 1 μM ws-Lypd6 significantly inhibited (up to ∼28%) choline-evoked current at α7-nAChRs in rat hippocampal slices. Similar to snake neurotoxin α-bungarotoxin, ws-Lypd6 suppressed the long-term potentiation (LTP) in mouse hippocampal slices. Colocalization of endogenous GPI-tethered Lypd6 with α3β4- and α7-nAChRs was detected in primary cortical and hippocampal neurons. Ws-Lypd6 interaction with the extracellular domain of α7-nAChR was modeled using the ensemble protein-protein docking protocol. The interaction of all three Lypd6 loops (“fingers”) with the entrance to the orthosteric ligand-binding site and the loop C of the primary receptor subunit was predicted. The results obtained allow us to consider Lypd6 as the endogenous negative modulator involved in the regulation of the cholinergic system in the brain.