Regulatory Potential of SNP Markers in the Genes of DNA Repair Systems

封面

如何引用文章

全文:

开放存取 开放存取
受限制的访问 ##reader.subscriptionAccessGranted##
受限制的访问 订阅存取

详细

In non-coding regions of the genome, the widest range of SNP markers associated with human diseases and petrogenetically significant features were identified. This raised the critical question of identifying the mechanisms that explain these associations. Previously, we identified a number of associations of polymorphic variants of genes encoding DNA repair proteins with multifactorial diseases. To clarify the possible mechanisms underlying established associations, we carried out a detailed annotation of the regulatory potential of the studied markers using a number of on-line resources (GTXPortal, VannoPortal, Ensemble, RegulomeDB, Polympact, UCSC, GnomAD, ENCODE, GeneHancer, EpiMap Epigenomics 2021, HaploReg, GWAS4D, JASPAR, ORegAnno, DisGeNet, OMIM). The article characterizes the regulatory potential of polymorphic variants rs560191 (in the TP53BP1 gene), rs1805800 and rs709816 (in the NBN gene), rs473297 (MRE11), rs189037 and rs1801516 (ATM), rs1799977 (MLH1), rs1805321 (PMS2), rs20579 (LIG1). Both the general characteristics of the studied markers and information on their influence on the expression of “own” and co-regulated genes, on changes in binding affinity of transcription factors are given. Known data on both adaptogenic and pathogenicity potential of these SNPs and on histone modifications co-localized with them are presented. The potential involvement in regulatory function of not only genes that contain SNPs studied but also nearby genes may explain the association of the markers with diseases and their clinical phenotypes.

作者简介

N. Babushkina

Research Institute of Medical Genetics, Tomsk National Research Medical Center, Russian Academy of Sciences

编辑信件的主要联系方式.
Email: nad.babushkina@medgenetics.ru
Russia, 634050, Tomsk

A. Kucher

Research Institute of Medical Genetics, Tomsk National Research Medical Center, Russian Academy of Sciences

Email: nad.babushkina@medgenetics.ru
Russia, 634050, Tomsk

参考

  1. Zhang F., Lupski J.R. (2015) Non-coding genetic variants in human disease. Hum. Mol. Genet. 24(R1), R102‒R110. https://doi.org/10.1093/hmg/ddv259
  2. Бабушкина Н.П., Постригань А.Е., Кучер А.Н. (2021) Вовлеченность генов белков BRСA1-ассоциированного комплекса наблюдения за геномом (BASC) в развитие многофакторной патологии. Молекуляр. биология. 55(2), 318–337. https://doi.org/10.31857/S0026898421020038
  3. Бабушкина Н.П., Постригань А.Е., Кучер А.Н. (2018) Вовлеченность генов систем репарации ДНК в развитие сердечно-сосудистой патологии. Сб.: Молекулярно-биологические технологии в медицинской практике. Ред. А.Б. Масленников. Новосибирск: Академиздат, с. 48‒62.
  4. Бабушкина Н.П., Постригань А.Е., Хитринская Е.Ю., Кучер А.Н. (2019) Средовые эффекты на ассоциации генов белков систем репарации ДНК с бронхиальной астмой. VII Съезд Вавиловского общества генетиков и селекционеров (ВОГиС) (2019), Санкт-Петербург, Россия. Сборник тезисов, с. 788.
  5. Бабушкина Н.П., Постригань А.Е., Хитринская Е.Ю., Кучер А.Н. (2019) Вовлеченность полиморфных вариантов генов систем репарации ДНК в развитие многофакторных заболеваний. Сб.: Генетика человека и патология: актуальные проблемы клинической и молекулярной цитогенетики. Ред. В.А. Степанов. Томск: Литературное бюро, с. 5–6.
  6. Бабушкина Н.П., Постригань А.Е., Кучер А.Н. (2020) Гены белков репарации ДНК и продолжительности жизни. Медицинская генетика. 19(5), 99–100. https://doi.org/10.25557/2073-7998.2020.05.99-100
  7. Бабушкина Н.П., Постригань А.Е., Кучер А.Н., Кужелева Е.А., Гарганеева А.А. (2020) Ассоциации полиморфизма генов систем репарации ДНК с показателями липидного обмена. Кардиология 2020 – новые вызовы и новые решения, Казань. Сборник тезисов, с. 811.
  8. Постригань А.Е., Бабушкина Н.П., Кучер А.Н. (2020) Вовлеченность полиморфизма гена NBN в формирование предрасположенности к дистропным заболеваниям. Медицинская генетика. 19(8), 98–99. https://doi.org/10.25557/2073-7998.2020.08.98-99
  9. Peakall R., Smouse P.E. (2012) GenAlEx 6: genetic analysis in Excel. Population genetic software for teaching and research ‒ an update. Bioinformatics. 28(19), 2537‒2539. https://doi.org/10.1093/bioinformatics/bts460
  10. Taverna S.D., Li H., Ruthenburg A.J., Allis C.D., Patel D.J. (2007) How chromatin-binding modules interpret histone modifications: lessons from professional pocket pickers. Nat. Struct. Mol. Biol. 14(11), 1025‒1040. https://doi.org/10.1038/nsmb1338
  11. Hoon D.S.B., Rahimzadeh N., Bustos M.A. (2021) EpiMap: fine-tuning integrative epigenomics maps to understand complex human regulatory genomic circuitry. Signal. Transduct. Target Ther. 6(1), 179. https://doi.org/10.1038/s41392-021-00620-5
  12. Fu Y., Sinha M., Peterson C.L., Weng Z. (2008) The insulator binding protein CTCF positions 20 nucleosomes around its binding sites across the human genome. PLoS Genet. 4(7), e1000138. https://doi.org/10.1371/journal.pgen.1000138
  13. Rubio E.D., Reiss D.J., Welcsh P.L., Disteche C.M., Filippova G.N., Baliga N.S., Aebersold R., Ranish J.A., Krumm A. (2008) CTCF physically links cohesin to chromatin. Proc. Natl. Acad. Sci. USA. 105(24), 8309‒8314. https://doi.org/10.1073/pnas.0801273105
  14. Mishiro T., Ishihara K., Hino S., Tsutsumi S., Aburatani H., Shirahige K., Kinoshita Y., Nakao M. (2009) Architectural roles of multiple chromatin insulators at the human apolipoprotein gene cluster. EMBO J. 28(9), 1234‒1245. https://doi.org/10.1038/emboj.2009.81
  15. Shoaib M., Chen Q., Shi X., Nair N., Prasanna C., Yang R., Walter D., Frederiksen K.S., Einarsson H., Svensson J.P., Liu C.F., Ekwall K., Lerdrup M., Nordenskiöld L., Sørensen C.S. (2021) Histone H4 lysine 20 mono-methylation directly facilitates chromatin openness and promotes transcription of housekeeping genes. Nat. Commun. 12(1), 4800. https://doi.org/10.1038/s41467-021-25051-2
  16. Hansen K.H., Bracken A.P., Pasini D., Dietrich N., Gehani S.S., Monrad A., Rappsilber J., Lerdrup M., Helin K. (2008) A model for transmission of the H3K27me3 epigenetic mark. Nat. Cell Biol. 10(11), 1291‒1300. https://doi.org/10.1038/ncb1787
  17. Vandamme J., Sidoli S., Mariani L., Friis C., Christensen J., Helin K., Jensen O.N., Salcini A.E. (2015) H3K23me2 is a new heterochromatic mark in Caenorhabditis elegans. Nucleic Acids Res. 43(20), 9694‒9710. https://doi.org/10.1093/nar/gkv1063
  18. Yang W., Bai Y., Xiong Y., Zhang J., Chen S., Zheng X., Meng X., Li L., Wang J., Xu C., Yan C., Wang L., Chang C.C., Chang T.Y., Zhang T., Zhou P., Song B.L., Liu W., Sun S.C., Liu X., Li B.L., Xu C. (2016) Potentiating the antitumour response of CD8+ T cells by modulating cholesterol metabolism. Nature. 531(7596), 651‒655. https://doi.org/10.1038/nature17412
  19. Fornes O., Castro-Mondragon J.A., Khan A., van der Lee R., Zhang X., Richmond P.A., Modi B.P., Correard S., Gheorghe M., Baranasic D., Santana-Garcia W., Tan G., Cheneby J., Ballester B., Parcy F., Sandelin A., Lenhard B., Wasserman W.W., Mathelier A. (2020) JASPAR 2020: update of the open-access database of transcription factor binding profiles. Nucleic A-cids Res. 48(D1), D87‒D92. https://doi.org/10.1093/nar/gkz1001
  20. Lesurf R., Cotto K.C., Wang G., Griffith M., Kasaian K., Jones S.J., Montgomery S.B., Griffith O.L.; Open Regulatory Annotation Consortium. (2016) ORegAnno 3.0: a community-driven resource for curated regulatory annotation. Nucleic Acids Res. 44(D1), D126‒D132. https://doi.org/10.1093/nar/gkv1203
  21. Kazachenka A., Bertozzi T.M., Sjoberg-Herrera M.K., Walker N., Gardner J., Gunning R., Pahita E., Adams S., Adams D., Ferguson-Smith A.C. (2018) Identification, characterization, and heritability of murine metastable epialleles: implications for non-genetic inheritance. Cell. 175(5), 1259‒1271.e13. https://doi.org/10.1016/j.cell.2018.09.043
  22. Li M.J., Wang L.Y., Xia Z., Sham P.C., Wang J. (2013) GWAS3D: detecting human regulatory variants by integrative analysis of genome-wide associations, chromosome interactions and histone modifications. Nucleic Acids Res. 41(Web Server issue), W150‒W158. https://doi.org/10.1093/nar/gkt456
  23. Huang D., Yi X., Zhang S., Zheng Z., Wang P., Xuan C., Sham P.C., Wang J., Li M.J. (2018) GWAS4D: multidimensional analysis of context-specific regulatory variant for human complex diseases and traits. Nucleic Acids Res. 46(W1), W114‒W120. https://doi.org/10.1093/nar/gky407
  24. Huang D., Zhou Y., Yi X., Fan X., Wang J., Yao H., Sham P.C., Hao J., Chen K., Li M.J. (2022) VannoPortal: multiscale functional annotation of human genetic variants for interrogating molecular mechanism of traits and diseases. Nucleic Acids Res. 50(D1), D1408‒D1416. https://doi.org/10.1093/nar/gkab853
  25. Lee R., Kang M.K., Kim Y.J., Yang B., Shim H., Kim S., Kim K., Yang C.M., Min B.G., Jung W.J., Lee E.C., Joo J.S., Park G., Cho W.K., Kim H.P. (2022) CTCF-mediated chromatin looping provides a topological framework for the formation of phase-separated transcriptional condensates. Nucleic Acids Res. 50(1), 207‒226. https://doi.org/10.1093/nar/gkab1242
  26. Putt W., Palmen J., Nicaud V., Tregouet D.A., Tahri-Daizadeh N., Flavell D.M., Humphries S.E., Talmud P.J.; EARSII group. (2004) Variation in USF1 shows haplotype effects, gene : gene and gene : environment associations with glucose and lipid parameters in the European Atherosclerosis Research Study II. Hum. Mol. Genet. 13(15), 1587‒1597. https://doi.org/10.1093/hmg/ddh168
  27. Laurila P.P., Naukkarinen J., Kristiansson K., Ripatti S., Kauttu T., Silander K., Salomaa V., Perola M., Karhunen P.J., Barter P.J., Ehnholm C., Peltonen L. (2010) Genetic association and interaction analysis of USF1 and APOA5 on lipid levels and atherosclerosis. Arterioscler. Thromb. Vasc. Biol. 30(2), 346‒352. https://doi.org/10.1161/ATVBAHA.109.188912
  28. Taghizadeh E., Mirzaei F., Jalilian N., Ghayour Mobarhan M., Ferns G.A., Pasdar A. (2020) A novel mutation in USF1 gene is associated with familial combined hyperlipidemia. IUBMB Life. 72(4), 616‒623. https://doi.org/10.1002/iub.2186
  29. Pollard K.S., Hubisz M.J., Rosenbloom K.R., Siepel A. (2010) Detection of nonneutral substitution rates on mammalian phylogenies. Genome Res. 20(1), 110–121. https://doi.org/10.1101/gr.097857.109
  30. Caron B., Luo Y., Rausell A. (2019) NCBoost classifies pathogenic non-coding variants in Mendelian diseases through supervised learning on purifying selection signals in humans. Genome Biol. 20(1), 32. https://doi.org/10.1186/s13059-019-1634-2
  31. Siepel A. (2005) Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes. Genome Res. 15(8), 1034‒1035. https://doi.org/10.1101/gr.3715005
  32. Hubisz M.J., Pollard K.S., Siepel A. (2011) PHAST and RPHAST: phylogenetic analysis with space/time models. Brief. Bioinform. 12(1), 41–51. https://doi.org/10.1093/bib/bbq072
  33. Zerbino D.R., Achuthan P., Akanni W., Amode M.R., Barrell D., Bhai J., Billis K., Cummins C., Gall A., Giron C.G., Gil L., Gordon L., Haggerty L., Haskell E., Hourlier T., Izuogu O.G., Janacek S.H., Juettemann T., To J.K., Laird M.R., Lavidas I., Liu Z., Loveland J.E., Maurel T., McLaren W., Moore B., Mudge J., Murphy D.N., Newman V., Nuhn M., Ogeh D., Ong C.K., Parker A., Patricio M., Riat H.S., Schuilenburg H., Sheppard D., Sparrow H., Taylor K., Thormann A., Vullo A., Walts B., Zadissa A., Frankish A., Hunt S.E., Kostadima M., Langridge N., Martin F.J., Muffato M., Perry E., Ruffier M., Staines D.M., Trevanion S.J., Aken B.L., Cunningham F., Yates A., Flicek P. (2018) Ensembl 2018. Nucleic Acids Res. 46(D1), D754‒D761. https://doi.org/10.1093/nar/gkx1098
  34. Gulko B., Hubisz M.J., Gronau I., Siepel A. (2015) A method for calculating probabilities of fitness consequences for point mutations across the human genome. Nat. Genet. 47(3), 276‒283. https://doi.org/10.1038/ng.3196
  35. Freund M.K., Burch K.S., Shi H., Mancuso N., Kichaev G., Garske K.M., Pan D.Z., Miao Z., Mohlke K.L., Laakso M., Pajukanta P., Pasaniuc B., Arboleda V.A. (2018) Phenotype-specific enrichment of Mendelian disorder genes near GWAS regions across 62 complex traits. Am. J. Hum. Genet. 103, 535‒552. https://doi.org/10.1016/j.ajhg.2018.08.017
  36. Spataro N., Rodrıguez J. A., Navarro A., Bosch E. (2017) Properties of human disease genes and the role of genes linked to Mendelian disorders in complex disease aetiology. Hum. Mol. Genet. 26, 489–500. https://doi.org/10.1093/hmg/ddw405
  37. Zhang S., He Y., Liu H., Zhai H., Huang D., Yi X., Dong X., Wang Z., Zhao K., Zhou Y., Wang J., Yao H., Xu H., Yang Z., Sham P.C., Chen K., Li M.J. (2019) regBase: whole genome base-wise aggregation and functional prediction for human non-coding regulatory variants. Nucleic Acids Res. 47(21), e134. https://doi.org/10.1093/nar/gkz774
  38. Plotz G., Raedle J., Spina A., Welsch C., Stallmach A., Zeuzem S., Schmidt C. (2008) Evaluation of the MLH1 I219V alteration in DNA mismatch repair activity and ulcerative colitis. Inflamm. Bowel Dis. 14(5), 605‒611. https://doi.org/10.1002/ibd.20358
  39. Vietri M.T., Riegler G., De Paola M., Simeone S., Boggia M., Improta A., Parisi M., Molinari A.M., Cioffi M. (2009) I219V polymorphism in hMLH1 gene in patients affected with ulcerative colitis. Genet. Test. Mol. Biomarkers. 13(2), 193‒197. https://doi.org/10.1089/gtmb.2008.0088
  40. Li S., Zhang L., Chen T., Tian B., Deng X., Zhao Z., Yuan P., Dong B., Zhang Y., Mo X. (2011) Functional polymorphism rs189037 in the promoter region of ATM gene is associated with angiographically characterized coronary stenosis. Atherosclerosis. 219(2), 694‒697. https://doi.org/10.1016/j.atherosclerosis.2011.08.040
  41. Li Z., Yu J., Zhang T., Li H., Ni Y. (2013) rs189037, a functional variant in ATM gene promoter, is associated with idiopathic nonobstructive azoospermia. Fertil. Steril. 100(6), 1536‒1541.e1. https://doi.org/10.1016/j.fertnstert.2013.07.1995
  42. Ding X., Yue J.R., Yang M., Hao Q.K., Xiao H.Y., Chen T., Gao L.Y., Dong B.R. (2015) Association between the rs189037 single nucleotide polymorphism in the ATM gene promoter and cognitive impairment. Genet. Mol. Res. 14(2), 4584‒4592. https://doi.org/10.4238/2015.May.4.17
  43. Ding X., He Y., Hao Q., Chen S., Yang M., Leng S.X., Yue J., Dong B. (2018) The association of single nucleotide polymorphism rs189037C>T in ATM gene with coronary artery disease in Chinese Han populations: a case control study. Medicine (Baltimore). 97(4), e9747. https://doi.org/10.1097/MD.0000000000009747

补充文件

附件文件
动作
1. JATS XML
2.

下载 (29KB)
3.

下载 (162KB)
4.

下载 (1MB)
5.

下载 (246KB)
6.

下载 (540KB)
7.

下载 (69KB)
8.

下载 (152KB)
9.

下载 (106KB)
10.

下载 (68KB)

版权所有 © Н.П. Бабушкина, А.Н. Кучер, 2023

##common.cookie##