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Orlov YL, Tatarinova TV, Oparina NY, Galieva ER, Baranova AV. Editorial: Bioinformatics of Genome Regulation, Volume I. Front Genet 2021; 12:803273. [PMID: 34938326 PMCID: PMC8687738 DOI: 10.3389/fgene.2021.803273] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 11/08/2021] [Indexed: 11/23/2022] Open
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Orlov YL, Anashkina AA, Tatarinova TV, Baranova AV. Editorial: Bioinformatics of Genome Regulation, Volume II. Front Genet 2021; 12:795257. [PMID: 34819949 PMCID: PMC8606529 DOI: 10.3389/fgene.2021.795257] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 10/25/2021] [Indexed: 12/17/2022] Open
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Baranova AV, Leberfarb EY, Lebedev GS, Orlov YL. Medical genetics studies at the SBB-2019 and MGNGS-2019 conferences. BMC MEDICAL GENETICS 2020; 21:186. [PMID: 33092553 PMCID: PMC7579857 DOI: 10.1186/s12881-020-01109-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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Nikogosov DA, Shevlyakov AD, Baranova AV. Comment on "ApoE e4e4 Genotype and Mortality With COVID-19 in UK Biobank" by Kuo et al. J Gerontol A Biol Sci Med Sci 2020; 75:2233-2234. [PMID: 32803253 PMCID: PMC7454333 DOI: 10.1093/gerona/glaa202] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Indexed: 11/13/2022] Open
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Krivosheeva IA, Filatova AY, Moshkovskii SA, Baranova AV, Skoblov MY. Analysis of candidate genes expected to be essential for melanoma surviving. Cancer Cell Int 2020; 20:488. [PMID: 33041669 PMCID: PMC7541296 DOI: 10.1186/s12935-020-01584-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Accepted: 09/28/2020] [Indexed: 11/10/2022] Open
Abstract
Introduction Cancers may be treated by selective targeting of the genes vital for their survival. A number of attempts have led to discovery of several genes essential for surviving of tumor cells of different types. In this work, we tried to analyze genes that were previously predicted to be essential for melanoma surviving. Here we present the results of transient siRNA-mediated knockdown of the four of such genes, namely, UNC45A, STK11IP, RHPN2 and ZNFX1, in melanoma cell line A375, then assayed the cells for their viability, proliferation and ability to migrate in vitro. In our study, the knockdown of the genes predicted as essential for melanoma survival does not lead to statistically significant changes in cell viability. On the other hand, for each of the studied genes, mobility assays showed that the knockdown of each of the target genes accelerates the speed of cells migrating. Possible explanation for such counterintuitive results may include insufficiency of the predicting computational models or the necessity of a multiplex knockdown of the genes. Aims To examine the hypothesis of essentiality of hypomutated genes for melanoma surviving we have performed knockdown of several genes in melanoma cell line and analyzed cell viability and their ability to migrate. Methods Knockdown was performed by siRNAs transfected by Metafectene PRO. The levels of mRNAs before and after knockdown were evaluated by RT-qPCR analysis. Cell viability and proliferation were assessed by MTT assay. Cell migration was assessed by wound healing assay. Results The knockdown of the genes predicted as essential for melanoma survival does not lead to statistically significant changes in cell viability. On the other hand, for each of the studied genes, mobility assays showed that the knockdown of each of the target genes accelerates the speed of cells migrating. Conclusion Our results do not confirm initial hypothesis that the genes predicted essential for melanoma survival as a matter of fact support the survival of melanoma cells.
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Orlov YL, Voropaeva EN, Chen M, Baranova AV. Medical genomics at the Systems Biology and Bioinformatics (SBB-2019) school. BMC Med Genomics 2020; 13:127. [PMID: 32948185 PMCID: PMC7500028 DOI: 10.1186/s12920-020-00786-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
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Tatarinova TV, Baranova AV, Anashkina AA, Orlov YL. Genomics and Systems Biology at the "Century of Human Population Genetics" conference. BMC Genomics 2020; 21:592. [PMID: 32912158 PMCID: PMC7487983 DOI: 10.1186/s12864-020-06993-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
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Danilov KA, Nikogosov DA, Musienko SV, Baranova AV. A comparison of BeadChip and WGS genotyping outputs using partial validation by sanger sequencing. BMC Genomics 2020; 21:528. [PMID: 32912136 PMCID: PMC7488117 DOI: 10.1186/s12864-020-06919-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Accepted: 07/17/2020] [Indexed: 11/30/2022] Open
Abstract
Background Head-to-head comparison of BeadChip and WGS/WES genotyping techniques for their precision is far from straightforward. A tool for validation of high-throughput genotyping calls such as Sanger sequencing is neither scalable nor practical for large-scale DNA processing. Here we report a cross-validation analysis of genotyping calls obtained via Illumina GSA BeadChip and WGS (Illumina HiSeq X Ten) techniques. Results When compared to each other, the average precision and accuracy of BeadChip and WGS genotyping techniques exceeded 0.991 and 0.997, respectively. The average fraction of discordant variants for both platforms was found to be 0.639%. A sliding window approach was utilized to explore genomic regions not exceeding 500 bp encompassing a maximal amount of discordant variants for further validation by Sanger sequencing. Notably, 12 variants out of 26 located within eight identified regions were consistently discordant in related calls made by WGS and BeadChip. When Sanger sequenced, a total of 16 of these genotypes were successfully resolved, indicating that a precision of WGS and BeadChip genotyping for this genotype subset was at 0.81 and 0.5, respectively, with accuracy values of 0.87 and 0.61. Conclusions We conclude that WGS genotype calling exhibits higher overall precision within the selected variety of discordantly genotyped variants, though the amount of validated variants remained insufficient.
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Orlov YL, Baranova AV. Editorial: Bioinformatics of Genome Regulation and Systems Biology. Front Genet 2020; 11:625. [PMID: 32849761 PMCID: PMC7399369 DOI: 10.3389/fgene.2020.00625] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2020] [Accepted: 05/26/2020] [Indexed: 12/31/2022] Open
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Baranova AV, Skoblov MY, Voropaeva EN, Shanmughavel P, Orlov YL. Medical genetics studies at BGRS conference series. BMC MEDICAL GENETICS 2019; 20:50. [PMID: 30967129 PMCID: PMC6454589 DOI: 10.1186/s12881-019-0769-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
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Baranova AV, Klimontov VV, Letyagin AY, Orlov YL. Medical genomics research at BGRS-2018. BMC Med Genomics 2019; 12:36. [PMID: 30871564 PMCID: PMC6416836 DOI: 10.1186/s12920-019-0480-0] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
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Orlov YL, Hofestädt R, Baranova AV. Systems biology research at BGRS-2018. BMC SYSTEMS BIOLOGY 2019; 13:21. [PMID: 30836966 PMCID: PMC6399810 DOI: 10.1186/s12918-019-0685-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
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Orlov YL, Baranova AV, Kolchanov NA, Moroz LL. Evolutionary biology and biodiversity research at BGRS-2018. BMC Evol Biol 2019; 19:43. [PMID: 30813910 PMCID: PMC6391745 DOI: 10.1186/s12862-019-1368-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
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Orlov YL, Baranova AV, Chen M, Salina EA. Plant Biology at Belyaev Conference - 2017. BMC PLANT BIOLOGY 2017; 17:257. [PMID: 29297331 PMCID: PMC5751566 DOI: 10.1186/s12870-017-1189-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
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Orlov YL, Baranova AV, Tatarinova TV, Kolchanov NA. Genetics at Belyaev Conference - 2017: introductory note. BMC Genet 2017; 18:116. [PMID: 29297300 PMCID: PMC5751695 DOI: 10.1186/s12863-017-0577-4] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
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Orlov YL, Baranova AV, Hofestädt R, Kolchanov NA. Computational genomics at BGRS\SB-2016: introductory note. BMC Genomics 2016; 17:996. [PMID: 28105925 PMCID: PMC5249040 DOI: 10.1186/s12864-016-3350-6] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
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Kural KC, Tandon N, Skoblov M, Kel-Margoulis OV, Baranova AV. Pathways of aging: comparative analysis of gene signatures in replicative senescence and stress induced premature senescence. BMC Genomics 2016; 17:1030. [PMID: 28105936 PMCID: PMC5249001 DOI: 10.1186/s12864-016-3352-4] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Background In culturing normal diploid cells, senescence may either happen naturally, in the form of replicative senescence, or it may be a consequence of external challenges such as oxidative stress. Here we present a comparative analysis aimed at reconstruction of molecular cascades specific for replicative (RS) and stressinduced senescence (SIPS) in human fibroblasts. Results An involvement of caspase-3/keratin-18 pathway and serine/threonine kinase Aurora A/ MDM2 pathway was shared between RS and SIPS. Moreover, stromelysin/MMP3 and N-acetylglucosaminyltransferase enzyme MGAT1, which initiates the synthesis of hybrid and complex Nglycans, were identified as key orchestrating components in RS and SIPS, respectively. In RS only, Aurora-B driven cell cycle signaling was deregulated in concert with the suppression of anabolic branches of the fatty acids and estrogen metabolism. In SIPS, Aurora-B signaling is deprioritized, and the synthetic branches of cholesterol metabolism are upregulated, rather than downregulated. Moreover, in SIPS, proteasome/ubiquitin ligase pathways of protein degradation dominate the regulatory landscape. This picture indicates that SIPS proceeds in cells that are actively fighting stress which facilitates premature senescence while failing to completely activate the orderly program of RS. The promoters of genes differentially expressed in either RS or SIPS are unusually enriched by the binding sites for homeobox family proteins, with particular emphasis on HMX1, IRX2, HDX and HOXC13. Additionally, we identified Iroquois Homeobox 2 (IRX2) as a master regulator for the secretion of SPP1-encoded osteopontin, a stromal driver for tumor growth that is overexpressed by both RS and SIPS fibroblasts. The latter supports the hypothesis that senescence-specific de-repression of SPP1 aids in SIPS-dependent stromal activation. Conclusions Reanalysis of previously published experimental data is cost-effective approach for extraction of additional insignts into the functioning of biological systems. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-3352-4) contains supplementary material, which is available to authorized users.
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Orlov YL, Baranova AV, Markel AL. Computational models in genetics at BGRS\SB-2016: introductory note. BMC Genet 2016; 17:155. [PMID: 28105935 PMCID: PMC5249000 DOI: 10.1186/s12863-016-0465-3] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
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Orlov YL, Baranova AV, Salina EA. Computational plant bioscience at BGRS\SB-2016: introductory note. BMC PLANT BIOLOGY 2016; 16:243. [PMID: 28105950 PMCID: PMC5123298 DOI: 10.1186/s12870-016-0923-0] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
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Skoblov MY, Scobeyeva VA, Baranova AV. [The Mechanisms of Transgenerational Inheritance and Their Potential Contribution to Human Phenotypes]. GENETIKA 2016; 52:283-292. [PMID: 27281848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
As of today, classical genetics has already completed the majority of groundwork to describe the laws of inheritance, identify the causes of many human diseases, and dissect the mechanisms of transfer of genetic information from parents to offspring. However, recent studies indicate that inheritance of phenotypic traits may also occur through nongenetic factors, in particular, through epigenetic factors, that manifest their effects in a transgenerational fashion. This review discusses findings in the area of transgenerational inheritance that open a new era in modern genetics. We discuss the mechanisms of transgenerational inheritance, including DNA methylation, histone modifications, and noncoding RNA transfer, and give an overview of the approaches to detect transgenerational effects in humans.
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Jacobsen KH, Aguirre AA, Bailey CL, Baranova AV, Crooks AT, Croitoru A, Delamater PL, Gupta J, Kehn-Hall K, Narayanan A, Pierobon M, Rowan KE, Schwebach JR, Seshaiyer P, Sklarew DM, Stefanidis A, Agouris P. Lessons from the Ebola Outbreak: Action Items for Emerging Infectious Disease Preparedness and Response. ECOHEALTH 2016; 13:200-212. [PMID: 26915507 PMCID: PMC7087787 DOI: 10.1007/s10393-016-1100-5] [Citation(s) in RCA: 49] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/07/2015] [Revised: 09/30/2015] [Accepted: 01/06/2016] [Indexed: 05/29/2023]
Abstract
As the Ebola outbreak in West Africa wanes, it is time for the international scientific community to reflect on how to improve the detection of and coordinated response to future epidemics. Our interdisciplinary team identified key lessons learned from the Ebola outbreak that can be clustered into three areas: environmental conditions related to early warning systems, host characteristics related to public health, and agent issues that can be addressed through the laboratory sciences. In particular, we need to increase zoonotic surveillance activities, implement more effective ecological health interventions, expand prediction modeling, support medical and public health systems in order to improve local and international responses to epidemics, improve risk communication, better understand the role of social media in outbreak awareness and response, produce better diagnostic tools, create better therapeutic medications, and design better vaccines. This list highlights research priorities and policy actions the global community can take now to be better prepared for future emerging infectious disease outbreaks that threaten global public health and security.
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