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Antontseva EV, Degtyareva AO, Korbolina EE, Damarov IS, Merkulova TI. Human-genome single nucleotide polymorphisms affecting transcription factor binding and their role in pathogenesis. Vavilovskii Zhurnal Genet Selektsii 2023; 27:662-675. [PMID: 37965371 PMCID: PMC10641029 DOI: 10.18699/vjgb-23-77] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 03/24/2023] [Accepted: 03/30/2023] [Indexed: 11/16/2023] Open
Abstract
Single nucleotide polymorphisms (SNPs) are the most common type of variation in the human genome. The vast majority of SNPs identified in the human genome do not have any effect on the phenotype; however, some can lead to changes in the function of a gene or the level of its expression. Most SNPs associated with certain traits or pathologies are mapped to regulatory regions of the genome and affect gene expression by changing transcription factor binding sites. In recent decades, substantial effort has been invested in searching for such regulatory SNPs (rSNPs) and understanding the mechanisms by which they lead to phenotypic differences, primarily to individual differences in susceptibility to diseases and in sensitivity to drugs. The development of the NGS (next-generation sequencing) technology has contributed not only to the identification of a huge number of SNPs and to the search for their association (genome-wide association studies, GWASs) with certain diseases or phenotypic manifestations, but also to the development of more productive approaches to their functional annotation. It should be noted that the presence of an association does not allow one to identify a functional, truly disease-associated DNA sequence variant among multiple marker SNPs that are detected due to linkage disequilibrium. Moreover, determination of associations of genetic variants with a disease does not provide information about the functionality of these variants, which is necessary to elucidate the molecular mechanisms of the development of pathology and to design effective methods for its treatment and prevention. In this regard, the functional analysis of SNPs annotated in the GWAS catalog, both at the genome-wide level and at the level of individual SNPs, became especially relevant in recent years. A genome-wide search for potential rSNPs is possible without any prior knowledge of their association with a trait. Thus, mapping expression quantitative trait loci (eQTLs) makes it possible to identify an SNP for which - among transcriptomes of homozygotes and heterozygotes for its various alleles - there are differences in the expression level of certain genes, which can be located at various distances from the SNP. To predict rSNPs, approaches based on searches for allele-specific events in RNA-seq, ChIP-seq, DNase-seq, ATAC-seq, MPRA, and other data are also used. Nonetheless, for a more complete functional annotation of such rSNPs, it is necessary to establish their association with a trait, in particular, with a predisposition to a certain pathology or sensitivity to drugs. Thus, approaches to finding SNPs important for the development of a trait can be categorized into two groups: (1) starting from data on an association of SNPs with a certain trait, (2) starting from the determination of allele-specific changes at the molecular level (in a transcriptome or regulome). Only comprehensive use of strategically different approaches can considerably enrich our knowledge about the role of genetic determinants in the molecular mechanisms of trait formation, including predisposition to multifactorial diseases.
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Affiliation(s)
- E V Antontseva
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - A O Degtyareva
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - E E Korbolina
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - I S Damarov
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - T I Merkulova
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
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Bryzgalov LO, Korbolina EE, Merkulova TI. Exploring the Genetic Predisposition to Epigenetic Changes in Alzheimer's Disease. Int J Mol Sci 2023; 24:ijms24097955. [PMID: 37175659 PMCID: PMC10177989 DOI: 10.3390/ijms24097955] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 04/05/2023] [Accepted: 04/21/2023] [Indexed: 05/15/2023] Open
Abstract
Alzheimer's disease (AD) is a prevalent type of dementia in elderly populations with a significant genetic component. The accumulating evidence suggests that AD involves a reconfiguration of the epigenetic landscape, including DNA methylation, post-translational modification of histone proteins, and chromatin remodeling. Along with environmental factors, individual specific genetic features play a considerable role in the formation of epigenetic architecture. In this study, we attempt to identify the non-coding regulatory SNPs (rSNPs) able to affect the epigenetic mechanisms in AD. To this end, the multi-omics approach is used. The GEO (Gene Expression Omnibus) available data (GSE153875) for AD patients and controls are integrated to reveal the rSNPs that display allele-specific features in both ChIP-seq profiles of four histone modifications and RNA-seq. Furthermore, we analyze the presence of rSNPs in the promoters of genes reported to be differentially expressed between AD and the normal brain (AD-related genes) and involved in epigenetic regulation according to the EpiFactors database. We also searched for the rSNPs in the promoters of the genes coding for transcription regulators of the identified AD-related genes. These regulators were selected based on the corresponding ChIP-seq peaks (ENCODE) in the promoter regions of these genes. Finally, we formed a panel of rSNPs localized to the promoters of genes that contribute to the epigenetic landscape in AD and, thus, to the genetic predisposition for this disease.
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Affiliation(s)
- Leonid O Bryzgalov
- The Federal Research Center Institute of Cytology and Genetics, The Siberian Branch of the Russian Academy of Science, 10 Lavrentyeva Prospekt, 630090 Novosibirsk, Russia
- Vector-Best, 630117 Novosibirsk, Russia
| | - Elena E Korbolina
- The Federal Research Center Institute of Cytology and Genetics, The Siberian Branch of the Russian Academy of Science, 10 Lavrentyeva Prospekt, 630090 Novosibirsk, Russia
| | - Tatiana I Merkulova
- The Federal Research Center Institute of Cytology and Genetics, The Siberian Branch of the Russian Academy of Science, 10 Lavrentyeva Prospekt, 630090 Novosibirsk, Russia
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Deng Y, Huang H, Shi J, Jin H. Identification of Candidate Genes in Breast Cancer Induced by Estrogen Plus Progestogens Using Bioinformatic Analysis. Int J Mol Sci 2022; 23:ijms231911892. [PMID: 36233194 PMCID: PMC9569986 DOI: 10.3390/ijms231911892] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 09/28/2022] [Accepted: 10/04/2022] [Indexed: 11/16/2022] Open
Abstract
Menopausal hormone therapy (MHT) was widely used to treat menopause-related symptoms in menopausal women. However, MHT therapies were controversial with the increased risk of breast cancer because of different estrogen and progestogen combinations, and the molecular basis behind this phenomenon is currently not understood. To address this issue, we identified differentially expressed genes (DEGs) between the estrogen plus progestogens treatment (EPT) and estrogen treatment (ET) using the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) data. As a result, a total of 96 upregulated DEGs were first identified. Seven DEGs related to the cell cycle (CCNE2, CDCA5, RAD51, TCF19, KNTC1, MCM10, and NEIL3) were validated by RT-qPCR. Specifically, these seven DEGs were increased in EPT compared to ET (p < 0.05) and had higher expression levels in breast cancer than adjacent normal tissues (p < 0.05). Next, we found that estrogen receptor (ER)-positive breast cancer patients with a higher CNNE2 expression have a shorter overall survival time (p < 0.05), while this effect was not observed in the other six DEGs (p > 0.05). Interestingly, the molecular docking results showed that CCNE2 might bind to 17β-estradiol (−6.791 kcal/mol), progesterone (−6.847 kcal/mol), and medroxyprogesterone acetate (−6.314 kcal/mol) with a relatively strong binding affinity, respectively. Importantly, CNNE2 protein level could be upregulated with EPT and attenuated by estrogen receptor antagonist, acolbifene and had interactions with cancer driver genes (AKT1 and KRAS) and high mutation frequency gene (TP53 and PTEN) in breast cancer patients. In conclusion, the current study showed that CCNE2, CDCA5, RAD51, TCF19, KNTC1, MCM10, and NEIL3 might contribute to EPT-related tumorigenesis in breast cancer, with CCNE2 might be a sensitive risk indicator of breast cancer risk in women using MHT.
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Affiliation(s)
- Yu Deng
- Department of Obstetrics and Gynecology, Peking University First Hospital, No. 8 Xishiku Street, Beijing 100034, China
| | - He Huang
- Department of Obstetrics and Gynecology, Peking University First Hospital, No. 8 Xishiku Street, Beijing 100034, China
| | - Jiangcheng Shi
- School of Life Sciences, Tiangong University, Tianjin 300387, China
| | - Hongyan Jin
- Department of Obstetrics and Gynecology, Peking University First Hospital, No. 8 Xishiku Street, Beijing 100034, China
- Correspondence:
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Boytsov A, Abramov S, Aiusheeva AZ, Kasianova A, Baulin E, Kuznetsov I, Aulchenko Y, Kolmykov S, Yevshin I, Kolpakov F, Vorontsov I, Makeev V, Kulakovskiy I. ANANASTRA: annotation and enrichment analysis of allele-specific transcription factor binding at SNPs. Nucleic Acids Res 2022; 50:W51-W56. [PMID: 35446421 PMCID: PMC9252736 DOI: 10.1093/nar/gkac262] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 03/15/2022] [Accepted: 04/04/2022] [Indexed: 11/12/2022] Open
Abstract
We present ANANASTRA, https://ananastra.autosome.org, a web server for the identification and annotation of regulatory single-nucleotide polymorphisms (SNPs) with allele-specific binding events. ANANASTRA accepts a list of dbSNP IDs or a VCF file and reports allele-specific binding (ASB) sites of particular transcription factors or in specific cell types, highlighting those with ASBs significantly enriched at SNPs in the query list. ANANASTRA is built on top of a systematic analysis of allelic imbalance in ChIP-Seq experiments and performs the ASB enrichment test against background sets of SNPs found in the same source experiments as ASB sites but not displaying significant allelic imbalance. We illustrate ANANASTRA usage with selected case studies and expect that ANANASTRA will help to conduct the follow-up of GWAS in terms of establishing functional hypotheses and designing experimental verification.
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Affiliation(s)
- Alexandr Boytsov
- Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, 119991, Russia
- Moscow Institute of Physics and Technology, Dolgoprudny, 141701, Russia
- Laboratory of Regulatory Genomics, Institute of Fundamental Medicine and Biology, Kazan Federal University, Kazan, 420008, Russia
| | - Sergey Abramov
- Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, 119991, Russia
- Moscow Institute of Physics and Technology, Dolgoprudny, 141701, Russia
- Laboratory of Regulatory Genomics, Institute of Fundamental Medicine and Biology, Kazan Federal University, Kazan, 420008, Russia
| | - Ariuna Z Aiusheeva
- Institute of Protein Research, Russian Academy of Sciences, Pushchino, 142290, Russia
| | - Alexandra M Kasianova
- Institute of Protein Research, Russian Academy of Sciences, Pushchino, 142290, Russia
- Southern Federal University, Rostov-on-Don, 344006, Russia
| | - Eugene Baulin
- Moscow Institute of Physics and Technology, Dolgoprudny, 141701, Russia
- Institute of Mathematical Problems of Biology RAS - the Branch of Keldysh Institute of Applied Mathematics of Russian Academy of Sciences, Pushchino, 142290, Russia
| | - Ivan A Kuznetsov
- Skolkovo Institute of Science and Technology, Moscow, 121205, Russia
| | - Yurii S Aulchenko
- Institute of Cytology and Genetics SB RAS, Novosibirsk, 630090, Russia
- PolyKnomics BV, ’s-Hertogenbosch, 5237 PA, Netherlands
| | - Semyon Kolmykov
- Sirius University of Science and Technology, Sochi, 354340, Russia
- Biosoft.Ru LLC, Novosibirsk, 630090, Russia
| | - Ivan Yevshin
- Sirius University of Science and Technology, Sochi, 354340, Russia
- Biosoft.Ru LLC, Novosibirsk, 630090, Russia
| | - Fedor Kolpakov
- Sirius University of Science and Technology, Sochi, 354340, Russia
- Federal Research Center for Information and Computational Technologies, Novosibirsk, 630090, Russia
| | - Ilya E Vorontsov
- Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, 119991, Russia
- Institute of Protein Research, Russian Academy of Sciences, Pushchino, 142290, Russia
| | - Vsevolod J Makeev
- Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, 119991, Russia
- Moscow Institute of Physics and Technology, Dolgoprudny, 141701, Russia
- Laboratory of Regulatory Genomics, Institute of Fundamental Medicine and Biology, Kazan Federal University, Kazan, 420008, Russia
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, 119991, Russia
| | - Ivan V Kulakovskiy
- Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, 119991, Russia
- Laboratory of Regulatory Genomics, Institute of Fundamental Medicine and Biology, Kazan Federal University, Kazan, 420008, Russia
- Institute of Protein Research, Russian Academy of Sciences, Pushchino, 142290, Russia
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