Features of Distribution of the Allelic Variant of the OAS1 Gene Associated with Severe Form of the Coronavirus Infection in the Russian and Global Populations

The study of the geographic distribution of the allelic variant of the OAS1 gene associated with severe form of the infections caused by RNA viruses was carried out using the rs10774671 polymorphic locus. The mutant allele encoding the p42 protein isoform was most prevalent in the Russian populations. A comparative analysis of the prevalence of the mutant allele in world populations showed that its frequency is 0.9 among the inhabitants of Northern Eurasia, while the allele encoding the p46 protein isoform is widespread among the population of West Central Africa. A cartographic analysis of the relationship between the population-frequency characteristics of the marker alleles and the geographical remoteness of the populations showed that the mutant allele is most often observed in the indigenous populations of the Far East, which suggests its East Asian origin.

Population-based biobank for analyzing the frequencies of clinically relevant DNA markers in the Russian population: bioinformatic aspects

One of the tasks of population-based biobanks is to determine the frequencies of clinically relevant genetic polymorphisms in the population. The population of Russia is very heterogeneous both ethnically and genetically. Therefore, the frequencies of genetic markers are in demand not in one sample, but in a series of samples reflecting the heterogeneity of the gene pool of different peoples and regions.

Aim. To divide the population of Russia and neighboring countries into population groups meeting certain conditions, as well as having a representative sample in existing data and biobanks.

Material and methods. We developed a method for combining populations into larger groups with maintaining intragroup homogeneity based on the principal components analysis with K-means clustering, followed by refinement of clustering for higher homogeneity and a more equal distribution of group sizes using FST distances. The technology has been adjusted using the example of the Biobank of Northern Eurasia. Therefore, the material was the genome-wide data on 4.5 million genetic markers for 1,883 samples representing 247 populations of Russia and neighboring countries from this biobank. The developed approach, the resulting set of populations and related map can be applied for other collections of biomaterials from Russian populations.

Results. Application of this approach made it possible to divide the entire population of Russia and neighboring countries into 29 ethnogeographic groups, characterized by relative genetic homogeneity. This set of populations is recommended as a baseline for population screenings to identify the frequency of any genetic markers among the population of Russia. A map has been constructed showing the division of population into 29 ethnogeographic areas.

Conclusion. On the basis of a reliable genome-wide data, the zoning of gene pool of the Russian population was carried out. We identified ethnogeographic groups with intergroup contrasting allele frequencies, but at the same time with relatively homogeneous intragroup parameters. The resulting map and register of groups can be used in population genetic, medical genetic and pharmacogenetic studies.

Cartographic atlas of frequency variation for 45 pharmacogenetic markers in populations of Russia and its neighbor states

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.

Reconstructing the genetic structure of the Kazakh from clan distribution data

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.

[Gene pool of Siberian Tatars: Five ways of origin for five subethnic groups]

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 haplomatch program for comparing Y-chromosome STR-haplotypes and its application to the analysis of the origin of Don Cossacks]

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.