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The three-spined stickleback ( Gasterosteus aculeatus L.) is an important model organism for studying the molecular mechanisms of speciation and adaptation to salinity. Despite increased interest to micro RNA discovery and recent publication on micro RNA prediction in the three-spined stickleback using bioinformatics approaches, there is still a lack of experimental support for these data. In this paper, high-throughput sequencing technology was applied to identify micro RNA genes in gills of the three-spined stickleback. In total, 595 mi RNA genes were discovered; half of them were predicted in previous computational studies and were confirmed here as micro RNAs expressed in gill tissue. Moreover, 298 novel micro RNA genes were identified. The presence of mi RNA genes in selected 'divergence islands' was analysed and 10 mi RNA genes were identified as not randomly located in 'divergence islands'. Regulatory regions of mi RNA genes were found enriched with selective SNPs that may play a role in freshwater adaptation. [ABSTRACT FROM AUTHOR]

The Rurikids were the reigning house of Rus', its principalities and, ultimately the Tsardom of Russia, for seven centuries: from the IX to the end of the XVI century. According to the Primary Chronicle (the Tale of Bygone Years), the main chronicle of Rus', the Rurik dynasty was founded by the Varangian prince Rurik, invited to reign in Novgorod in 862, but still there is no direct genetic evidence of the origin of the early Rurikids. This research, for the first time, provides a genome-wide paleogenetic analysis of bone remains belonging to one of the Rurikids, Prince Dmitry Alexandrovich (?-1294), the son of the Grand Prince of Vladimir Alexander Yaroslavich Nevsky (1221-1263). It has been established that his Y chromosome belongs to the N1a haplogroup. Most of the modern Rurikids, according to their genealogies, belonging to the N1a haplogroup, have the most similar variants of Y chromosomes to each other, as well as to the Y chromosome of Prince Dmitry Alexandrovich. Genome-wide data of the medieval and modern Rurikids unequivocally indicates that they belong to the N1a haplogroup of the Y chromosome, starting at least from the XI century (since the time of Prince Yaroslav the Wise). All the other alleged Rurikids, both ancient and modern, being carriers of other haplogroups (R1a, I2a), possess high heterogeneity of the sequence of Y chromosomes, meaning that we cannot confirm their common ancestry. The most probable ancestors of Prince Dmitry Alexandrovich in the male line were the men who left the burial ground Bolshoy Oleny Island on the coast of the Kola Peninsula about 3,600 years ago. The reconstruction of the genome of Prince Dmitry Alexandrovich indicates the contribution of three ancestral components to his origin: (1) the early medieval population of the east of Scandinavia from the island of Oland, (2) representatives of the steppe nomadic peoples of the Eurasian steppes of the Iron Age or the early medieval population of central Europe (steppe nomads from the territory of Hungary), and (3) the ancient East-Eurasian component. Reliable statistics were also obtained when the Scandinavians were replaced with the Medieval Russian Slavic populations of the XI century. Thus, for the first time, we have shown the complex nature of interethnic interactions in the formation of the nobility of medieval Rus' on the example of the ancient Rurikid., (Copyright ® 2023 National Research University Higher School of Economics.)

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., (Copyright ® 2023 National Research University Higher School of Economics.)

DNA methylation is the most important epigenetic modification involved in the regulation of transcription, imprinting, establishment of X-inactivation, and the formation of a chromatin structure. DNA methylation in the genome is often associated with transcriptional repression and the formation of closed heterochromatin. However, the results of genome-wide studies of the DNA methylation pattern and transcriptional activity of genes have nudged us toward reconsidering this paradigm, since the promoters of many genes remain active despite their methylation. The differences in the DNA methylation distribution in normal and pathological conditions allow us to consider methylation as a diagnostic marker or a therapy target. In this regard, the need to investigate the factors affecting DNA methylation and those involved in its interpretation becomes pressing. Recently, a large number of protein factors have been uncovered, whose ability to bind to DNA depends on their methylation. Many of these proteins act not only as transcriptional activators or repressors, but also affect the level of DNA methylation. These factors are considered potential therapeutic targets for the treatment of diseases resulting from either a change in DNA methylation or a change in the interpretation of its methylation level. In addition to protein factors, a secondary DNA structure can also affect its methylation and can be considered as a therapy target. In this review, the latest research into the DNA methylation landscape in the genome has been summarized to discuss why some DNA regions avoid methylation and what factors can affect its level or interpretation and, therefore, can be considered a therapy target., (Copyright ® 2022 National Research University Higher School of Economics.)

A breakthrough in cattle breeding was achieved with the incorporation of animal genomic data into breeding programs. The introduction of genomic selection has a major impact on traditional genetic assessment systems and animal genetic improvement programs. Since 2010, genomic selection has been officially introduced in the evaluation of the breeding and genetic potential of cattle in Europe, the U.S., Canada, and many other developed countries. The purpose of this study is to develop a system for a genomic evaluation of the breeding value of the domestic livestock of Black-and-White and Russian Holstein cattle based on 3 milk performance traits: daily milk yield (kg), daily milk fat (%), and daily milk protein content (%) and 6 fertility traits: age at first calving (AFC), calving interval (CI), calving to first insemination interval (CFI), interval between first and last insemination (IFL), days open (DO), and number of services (NS). We built a unified database of breeding animals from 523 breeding farms in the Russian Federation. The database included pedigree information on 2,551,529 cows and 69,131 bulls of the Russian Holstein and Black-and-White cattle breeds, as well as information on the milk performance of 1,597,426 cows with 4,771,366 completed lactations. The date of birth of the animals included in the database was between 1975 and 2017. Genotyping was performed in 672 animals using a BovineSNP50 v3 DNA Analysis BeadChip microarray (Illumina, USA). The genomic estimated breeding value (GEBV) was evaluated only for 644 animals (427 bulls and 217 cows) using the single-step genomic best linear unbiased prediction - animal model (ssGBLUP-AM). The mean genetic potential was +0.88 and +1.03 kg for the daily milk yield, -0.002% for the milk fat content, and -0.003 and 0.001% for the milk protein content in the cows and bulls, respectively. There was negative genetic progress in the fertility traits in the studied population between 1975 and 2017. The reliability of the estimated breeding value (EBV) for genotyped bulls ranged from 89 to 93% for the milk performance traits and 85 to 90% for the fertility traits, whereas the reliability of the genomic estimated breeding value (GEBV) varied 54 to 64% for the milk traits and 23 to 60% for the fertility traits. This result shows that it is possible to use the genomic estimated breeding value with rather high reliability to evaluate the domestic livestock of Russian Holstein and Black-and-White cattle breeds for fertility and milk performance traits. This system of genomic evaluation may help bring domestic breeding in line with modern competitive practices and estimate the breeding value of cattle at birth based on information on the animal's genome., (Copyright ® 2022 National Research University Higher School of Economics.)

Gain and loss of DNA methylation in cells is a dynamic process that tends to achieve an equilibrium. Many factors are involved in maintaining the balance between DNA methylation and demethylation. Previously, it was shown that methyl-DNA protein Kaiso may attract NCoR, SMRT repressive complexes affecting histone modifications. On the other hand, the deficiency of Kaiso resulted in reduced methylation of ICR in H19/Igf2 locus and Oct4 promoter in mouse embryonic fibroblasts. However, nothing is known about how Kaiso influences DNA methylation at the genome level. Here we show that deficiency of Kaiso led to whole-genome hypermethylation, using Kaiso deficient human renal cancer cell line obtained via CRISPR/CAS9 genome editing. However, Kaiso serves to protect genic regions, enhancers, and regions with a low level of histone modifications from demethylation. We detected hypomethylation of binding sites for Oct4 and Nanog in Kaiso deficient cells. Kaiso immunoprecipitated with de novo DNA methyltransferases DNMT3a/3b, but not with maintenance methyltransferase DNMT1. Thus, Kaiso may attract methyltransferases to surrounding regions and modulate genome methylation in renal cancer cells apart from being methyl DNA binding protein.

Objectives: The outbreak of coronavirus disease 2019 (COVID-19) started in December 2019 in China and then spread worldwide over the following months, involving 188 countries. The objective of this study was to determine the molecular epidemiology of the COVID-19 outbreak in Russia., Methods: In this study, two severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strains were isolated and genetically characterized. A phylogenetic analysis of all available Russian sequences was then performed and these were compared to the epidemiological data on COVID-19 incidence to evaluate the molecular epidemiology and pattern of virus spread in the territory of Russia., Results and Conclusions: Whole genome analysis of the isolates obtained in this study and 216 others isolated in Russia revealed a set of seven common mutations when compared to the original Wuhan virus, including amino acid substitutions in spike protein S and nucleoprotein N, possibly affecting their properties. Phylogenetic analysis of all Russian sequences and 8717 sequences from other countries showed multiple importations of the virus into Russia, local circulation, and several patterns of virus spread., (Copyright © 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Renal cell carcinoma (RCC) has an undisputed genetic component and a stable 2:1 male to female sex ratio in its incidence across populations, suggesting possible sexual dimorphism in its genetic susceptibility. We conducted the first sex-specific genome-wide association analysis of RCC for men (3227 cases, 4916 controls) and women (1992 cases, 3095 controls) of European ancestry from two RCC genome-wide scans and replicated the top findings using an additional series of men (2261 cases, 5852 controls) and women (1399 cases, 1575 controls) from two independent cohorts of European origin. Our study confirmed sex-specific associations for two known RCC risk loci at 14q24.2 (DPF3) and 2p21(EPAS1). We also identified two additional suggestive male-specific loci at 6q24.3 (SAMD5, male odds ratio (OR male ) = 0.83 [95% CI = 0.78-0.89], P male  = 1.71 × 10 -8 compared with female odds ratio (OR female ) = 0.98 [95% CI = 0.90-1.07], P female  = 0.68) and 12q23.3 (intergenic, OR male  = 0.75 [95% CI = 0.68-0.83], P male  = 1.59 × 10 -8 compared with OR female  = 0.93 [95% CI = 0.82-1.06], P female  = 0.21) that attained genome-wide significance in the joint meta-analysis. Herein, we provide evidence of sex-specific associations in RCC genetic susceptibility and advocate the necessity of larger genetic and genomic studies to unravel the endogenous causes of sex bias in sexually dimorphic traits and diseases like RCC.

The myeloid translocation gene family member MTG16 is a transcriptional corepressor that relies on the DNA-binding ability of other proteins to determine specificity. One such protein is the ZBTB family member Kaiso, and the MTG16:Kaiso interaction is necessary for repression of Kaiso target genes, such as matrix metalloproteinase-7. Using the azoxymethane and dextran sodium sulfate (AOM/DSS) murine model of colitis-associated carcinoma, we previously determined that MTG16 loss accelerates tumorigenesis and inflammation. However, it was unknown whether this effect was modified by Kaiso-dependent transcriptional repression. To test for a genetic interaction between MTG16 and Kaiso in inflammatory carcinogenesis, we subjected single and double knockout (DKO) mice to the AOM/DSS protocol. Mtg16 -/- mice demonstrated increased colitis and tumor burden; in contrast, disease severity in Kaiso -/- mice was equivalent to wild-type controls. Surprisingly, Kaiso deficiency in the context of MTG16 loss reversed injury and pro-tumorigenic responses in the intestinal epithelium following AOM/DSS treatment, and tumor numbers were returned to near to wild-type levels. Transcriptomic analysis of non-tumor colon tissue demonstrated that changes induced by MTG16 loss were widely mitigated by concurrent Kaiso loss, and DKO mice demonstrated downregulation of metabolism and cytokine-associated gene sets with concurrent activation of DNA damage checkpoint pathways as compared with Mtg16 -/- . Further, Kaiso knockdown in intestinal enteroids reduced stem- and WNT-associated phenotypes, thus abrogating the induction of these pathways observed in Mtg16 -/- samples. Together, these data suggest that Kaiso modifies MTG16-driven inflammation and tumorigenesis and suggests that Kaiso deregulation contributes to MTG16-dependent colitis and CAC phenotypes.

Reprogramming of somatic cells is associated with overcoming the established epigenetic barrier. Key events in this process are changes in the DNA methylation landscape and histone modifications. Studying the factors affecting epigenetic plasticity will allow not only to reveal the principles underlying cell reprogramming but also to find possible ways to influence this process. Kaiso transcription factor is one of the protein interpreters of methylated DNA. By binding to methylated DNA, Kaiso attracts corepressor complexes affecting chromatin structure. In this work, we showed that the Kaiso gene knockout contributes to more efficient somatic reprogramming by affecting both cell proliferation and DNA methylation. The proposed mechanisms for the increase in the efficiency of somatic reprogramming associated with the Kaiso gene knockout is a decrease in the methylation level of the Oct4 promoter region in mouse embryonic fibroblasts before reprogramming.

Background: Several obesity-related factors have been associated with renal cell carcinoma (RCC), but it is unclear which individual factors directly influence risk. We addressed this question using genetic markers as proxies for putative risk factors and evaluated their relation to RCC risk in a mendelian randomization (MR) framework. This methodology limits bias due to confounding and is not affected by reverse causation., Methods and Findings: Genetic markers associated with obesity measures, blood pressure, lipids, type 2 diabetes, insulin, and glucose were initially identified as instrumental variables, and their association with RCC risk was subsequently evaluated in a genome-wide association study (GWAS) of 10,784 RCC patients and 20,406 control participants in a 2-sample MR framework. The effect on RCC risk was estimated by calculating odds ratios (ORSD) for a standard deviation (SD) increment in each risk factor. The MR analysis indicated that higher body mass index increases the risk of RCC (ORSD: 1.56, 95% confidence interval [CI] 1.44-1.70), with comparable results for waist-to-hip ratio (ORSD: 1.63, 95% CI 1.40-1.90) and body fat percentage (ORSD: 1.66, 95% CI 1.44-1.90). This analysis further indicated that higher fasting insulin (ORSD: 1.82, 95% CI 1.30-2.55) and diastolic blood pressure (DBP; ORSD: 1.28, 95% CI 1.11-1.47), but not systolic blood pressure (ORSD: 0.98, 95% CI 0.84-1.14), increase the risk for RCC. No association with RCC risk was seen for lipids, overall type 2 diabetes, or fasting glucose., Conclusions: This study provides novel evidence for an etiological role of insulin in RCC, as well as confirmatory evidence that obesity and DBP influence RCC risk., Competing Interests: I have read the journal's policy and the authors of this manuscript have the following competing interests: TE declared employment, research support, and stock in AstraZeneca and research support from Bayer and Pfizer. PCH is a population health fellow of Cancer Research UK. GDS is a member of the Editorial Board of PLOS Medicine.

Kaiso is a member of the BTB/POZ zinc finger family, which is involved in cancer progression, cell cycle control, apoptosis, and WNT signaling. Depending on promoter context, it may function as either a transcriptional repressor or activator. Previous studies found that Kaiso might be SUMOylated due to heat shock, but the biological significance of Kaiso SUMOylation is unclear. Here, we find that K42 is the only amino acid within Kaiso that is modified with SUMO. Kaiso is monoSUMOylated at lysine 42 in cell lines of kidney origin under normal physiological conditions. SUMOylated Kaiso can activate transcription from exogenous methylated promoters, wherein the deSUMOylated form of the protein kept the ability to be a repressor. Rapid Kaiso deSUMOylation occurs in response to hyperosmotic stress and is reversible upon return to an isotonic environment. DeSUMOylation occurs within minutes in HEK293 cells treated with 100 mM NaCl and relaxes in 3 h even in a salt-containing medium. Genomic editing of Kaiso by conversion of K42 into R42 (K42R) in HEK293 cells that resulted in fully deSUMOylated endogenous protein led to misregulation of genes associated with ion transport, blood pressure, and the immune response. TRIM25 was significantly repressed in two K42R HEK293 clones. By a series of rescue experiments with K42R and KO HEK293 cells, we show that TRIM25 is a direct transcriptional target for Kaiso. In the absence of Kaiso, the level of TRIM25 is insensitive to hyperosmotic stress. Extending our observations to animal models, we show that in response to a high salt diet, Kaiso knockout mice are characterized by significantly higher blood pressure increases when compared to wild-type animals. Thus, we propose a novel biological role for Kaiso in the regulation of homeostasis.

Background: The history of human populations occupying the plains and mountain ridges separating Europe from Asia has been eventful, as these natural obstacles were crossed westward by multiple waves of Turkic and Uralic-speaking migrants as well as eastward by Europeans. Unfortunately, the material records of history of this region are not dense enough to reconstruct details of population history. These considerations stimulate growing interest to obtain a genetic picture of the demographic history of migrations and admixture in Northern Eurasia., Results: We genotyped and analyzed 1076 individuals from 30 populations with geographical coverage spanning from Baltic Sea to Baikal Lake. Our dense sampling allowed us to describe in detail the population structure, provide insight into genomic history of numerous European and Asian populations, and significantly increase quantity of genetic data available for modern populations in region of North Eurasia. Our study doubles the amount of genome-wide profiles available for this region. We detected unusually high amount of shared identical-by-descent (IBD) genomic segments between several Siberian populations, such as Khanty and Ket, providing evidence of genetic relatedness across vast geographic distances and between speakers of different language families. Additionally, we observed excessive IBD sharing between Khanty and Bashkir, a group of Turkic speakers from Southern Urals region. While adding some weight to the "Finno-Ugric" origin of Bashkir, our studies highlighted that the Bashkir genepool lacks the main "core", being a multi-layered amalgamation of Turkic, Ugric, Finnish and Indo-European contributions, which points at intricacy of genetic interface between Turkic and Uralic populations. Comparison of the genetic structure of Siberian ethnicities and the geography of the region they inhabit point at existence of the "Great Siberian Vortex" directing genetic exchanges in populations across the Siberian part of Asia. Slavic speakers of Eastern Europe are, in general, very similar in their genetic composition. Ukrainians, Belarusians and Russians have almost identical proportions of Caucasus and Northern European components and have virtually no Asian influence. We capitalized on wide geographic span of our sampling to address intriguing question about the place of origin of Russian Starovers, an enigmatic Eastern Orthodox Old Believers religious group relocated to Siberia in seventeenth century. A comparative reAdmix analysis, complemented by IBD sharing, placed their roots in the region of the Northern European Plain, occupied by North Russians and Finno-Ugric Komi and Karelian people. Russians from Novosibirsk and Russian Starover exhibit ancestral proportions close to that of European Eastern Slavs, however, they also include between five to 10 % of Central Siberian ancestry, not present at this level in their European counterparts., Conclusions: Our project has patched the hole in the genetic map of Eurasia: we demonstrated complexity of genetic structure of Northern Eurasians, existence of East-West and North-South genetic gradients, and assessed different inputs of ancient populations into modern populations.