Skip to main content
Log in

Genetic Polymorphism of Experimentally Produced Forms of Arterial Hypertension

  • ANIMAL GENETICS
  • Published:
Russian Journal of Genetics Aims and scope Submit manuscript

Abstract

The paper analyzes the distribution of polymorphic loci in rats of different hypertensive strains. When analyzing the transcribed loci of ISIAH rats and the corresponding loci of 11 other hypertensive strains/substrains of rats, the maximum frequency of occurrence of identical SNPs in different strains was 0.58 (i.e., in 7 of 12 hypertensive strains/substrains). The analysis of the genomic sequences of 11 hypertensive strains/substrains of rats, which model different forms of arterial hypertension, also did not reveal a single SNP common to all 11 hypertensive strains/substrains of rats taken in the analysis. Analysis of experimental data suggests that hypertension is a genetically heterogeneous disease.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1.
Fig. 2.

Similar content being viewed by others

REFERENCES

  1. Ellinor, P.T., Lunetta, K.L., Glazer, N.L., et al., Common variants in KCNN3 are associated with lone atrial fibrillation, Nat. Genet., 2010, vol. 42, no. 3, pp. 240—244. https://doi.org/10.1038/ng.537

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Low, S.K., Takahashi, A., Mushiroda, T., Kubo, M., Genome-wide association study: a useful tool to identify common genetic variants associated with drug toxicity and efficacy in cancer pharmacogenomics, Clin. Cancer Res., 2014, vol. 20, no. 10, pp. 2541—2552. https://doi.org/10.1158/1078-0432.CCR-13-2755

    Article  CAS  PubMed  Google Scholar 

  3. Kingsmore, S.F., Lindquist, I.E., Mudge, J., et al., Genome-wide association studies: progress and potential for drug discovery and development, Nat. Rev. Drug Discovery, 2008, vol. 7, no. 3, pp. 221–230. https://doi.org/10.1038/nrd2519

    Article  CAS  PubMed  Google Scholar 

  4. Rapp, J.P., Genetic analysis of inherited hypertension in the rat, Physiol. Rev., 2000, vol. 80, no. 1, pp. 135—172. https://doi.org/10.1152/physrev.2000.80.1.135

    Article  CAS  PubMed  Google Scholar 

  5. Ershov, N.I., Markel, A.L., and Redina, O.E., Strain-specific single-nucleotide polymorphisms in hypertensive ISIAH rats, Biochemistry (Moscow), 2017, vol. 82, no. 2, pp. 224—235. https://doi.org/10.1134/S0006297917020146

    Article  CAS  PubMed  Google Scholar 

  6. Kim, D., Pertea, G., Trapnell, C., et al., TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions, Genome Biol., 2013, vol. 14, no. 4, p. R36. https://doi.org/10.1186/gb-2013-14-4-r36

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. McKenna, A., Hanna, M., Banks, E., et al., The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data, Genome Res., 2010, vol. 20, no. 9, pp. 1297—1303. https://doi.org/10.1101/gr.107524.110

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Hermsen, R., de Ligt, J., Spee, W., et al., Genomic landscape of rat strain and substrain variation, BMC Genomics, 2015, vol. 16, no. 357. https://doi.org/10.1186/s12864-015-1594-1

  9. Kumar, P., Henikoff, S., and Ng, P.C., Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm, Nat. Protoc., 2009, vol. 4, no. 7, pp. 1073—1081. https://doi.org/10.1038/nprot.2009.86

    Article  CAS  PubMed  Google Scholar 

  10. Zheng, X., Levine, D., Shen, J., et al., A high-performance computing toolset for relatedness and principal component analysis of SNP data, Bioinformatics, 2012, vol. 28, no. 24, pp. 3326—3328. https://doi.org/10.1093/bioinformatics/bts606

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Sarikonda, K.V., Watson, R.E., Opara, O.C., and Dipette, D.J., Experimental animal models of hypertension, J. Am. Soc. Hypertens., 2009, vol. 3, no. 3, pp. 158—165. https://doi.org/10.1016/j.jash.2009.02.003

    Article  PubMed  Google Scholar 

  12. Bader, M., Rat models of cardiovascular diseases, Methods Mol. Biol., 2010, vol. 597, pp. 403—414. https://doi.org/10.1007/978-1-60327-389-3_27

    Article  PubMed  Google Scholar 

  13. Cardenas-Rodriguez, M., Osborn, D.P., Irigoin, F., et al., Characterization of CCDC28B reveals its role in ciliogenesis and provides insight to understand its modifier effect on Bardet—Biedl syndrome, Hum. Genet., 2013, vol. 132, no. 1, pp. 91—105. https://doi.org/10.1007/s00439-012-1228-5

    Article  CAS  PubMed  Google Scholar 

  14. Elbedour, K., Zucker, N., Zalzstein, E., et al., Cardiac abnormalities in the Bardet—Biedl syndrome: echocardiographic studies of 22 patients, Am. J. Med. Genet., 1994, vol. 52, no. 2, pp. 164—169. https://doi.org/10.1002/ajmg.1320520208

    Article  CAS  PubMed  Google Scholar 

  15. Croft, J.B. and Swift, M. Obesity, hypertension, and renal disease in relatives of Bardet—Biedl syndrome sibs, Am. J. Med. Genet., 1990, vol. 36, no. 1, pp. 37—42. https://doi.org/10.1002/ajmg.1320360109

    Article  CAS  PubMed  Google Scholar 

  16. Rahmouni, K., Fath, M.A., Seo, S., et al., Leptin resistance contributes to obesity and hypertension in mouse models of Bardet—Biedl syndrome, J. Clin. Invest., 2008, vol. 118, no. 4, pp. 1458—1467. https://doi.org/10.1172/JCI32357

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Oparil, S. and Schmieder, R.E., New approaches in the treatment of hypertension, Circ. Res., 2015, vol. 116, no. 6, pp. 1074—1095. https://doi.org/10.1161/CIRCRESAHA.116.303603

    Article  CAS  PubMed  Google Scholar 

  18. Benjamin, E.J., Blaha, M.J., Chiuve, S.E., et al., Heart disease and stroke statistics—2017 Update: a report from the American Heart Association, Circulation, 2017, vol. 135, no. 10, pp. e146—e603. https://doi.org/10.1161/CIR.0000000000000485

    Article  PubMed  PubMed Central  Google Scholar 

  19. Mann, S.J., Neurogenic essential hypertension revisited: the case for increased clinical and research attention, Am. J. Hypertens., 2003, vol. 16, no. 10, pp. 881—888.

    Article  PubMed  Google Scholar 

  20. Jazwinska, E.C., Exploiting human genetic variation in drug discovery and development, Drug Discovery Today, 2001, vol. 6, no. 4, pp. 198—205. https://doi.org/10.1016/S1359-6446(00)01642-1

    Article  PubMed  Google Scholar 

Download references

Funding

This work was supported by budget projects 0324-2019-0041 and 0324-2019-0042. The studies were carried out using the equipment of the Center for Genetic Resources of Laboratory Animals at the Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, supported by the Russian Ministry of Education and Science (unique project identifier RFMEFI62117X0015). Computational analysis of the data was carried out using the resources of the Siberian Supercomputer Center of the Institute of Computational Mathematics and Mathematical Geophysics, Siberian Branch, Russian Academy of Sciences.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to O. E. Redina.

Ethics declarations

The authors declare that they have no conflict of interest. This article does not contain any studies involving animals or human participants performed by any of the authors.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Redina, O.E., Devyatkin, V.A., Ershov, N.I. et al. Genetic Polymorphism of Experimentally Produced Forms of Arterial Hypertension. Russ J Genet 56, 213–225 (2020). https://doi.org/10.1134/S1022795420020106

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S1022795420020106

Keywords:

Navigation