Volume 8, Issue 2, June 2020, Page: 78-84
Data Analysis of Single Nucleotide Polymorphism in Human AGT Gene Using Computational Approach
Mohammed Youssif Mohammed, Department of Molecular Biology and Bioinformatics, College of Veterinary Medicine, University of Bahri, Khartoum, Sudan
Afra Mohamed Al Bkrye, Department of Molecular Biology and Bioinformatics, College of Veterinary Medicine, University of Bahri, Khartoum, Sudan
Hind Abdelaziz Elnasri, Department of Molecular Biology and Bioinformatics, College of Veterinary Medicine, University of Bahri, Khartoum, Sudan
Mona Abdelrahman Mohamed Khaier, Department of Molecular Biology and Bioinformatics, College of Veterinary Medicine, University of Bahri, Khartoum, Sudan
Received: Jan. 10, 2020;       Accepted: Jan. 27, 2020;       Published: Apr. 7, 2020
DOI: 10.11648/j.ijgg.20200802.14      View  372      Downloads  151
Abstract
Background: The AGT gene is gene responsible for regulation of protein called angiotensinogen which regulates blood pressure and balances fluids in the body. Hypertension happens due to many causes one of this is the defect in AGT gene. Hypertension usually has no symptoms. However, it is a major risk factor for heart diseases, stroke, kidney failure, and eye problems. Objectives: in this study we use software to analyze the gene using different software and represented statistically and to detect the SNPs that can cause the disease. Material and Method: In this analysis using many software tools that can analyze the nsSNPs retrieved from NCBI website. These software include SIFT, I-mutant, Polyphen-2, PHD SNP and SNP& Go, Projecthop and GeneMANIA. Results: The study showed that from 172 nsSNPs only 46 nsSNPs were deleterious while 126 were tolerated using SIFT. Two were benign, 11 were possibly damaging and 33 were probably damaging by Polyphen-2. Using Provean, 19 nsSNPs were neutral and 27 were deleterious. For PHD-SNP software 20 nsSNPs were disease related and 18 were neutral. Also SNPs were checked using SNP & Go software that showed 32 neutral nsSNPs and 14 nsSNPs were disease associated variants. Using I-Mutant software 13 nsSNPs increase the stability of the protein and 33 decrease the protein stability. Conclusions: In conclusion, extensive functional and structural analyses are carried out to predict potentially damaging and deleterious nsSNPs of AGT gene using bioinformatics and computational methods. In the study, 14 high confidence damaging nsSNPs are identified from 172 nsSNPs. Although bioinformatics tools have their limitations, the results from the present study may be convenient in future for further population based research activities and towards development of accuracy medicines.
Keywords
AGT Gene, Hypertension, I-mutant, SIFT, SNP & Go and PHD, Polyphen-2, Provean and Project Hope, SNP
To cite this article
Mohammed Youssif Mohammed, Afra Mohamed Al Bkrye, Hind Abdelaziz Elnasri, Mona Abdelrahman Mohamed Khaier, Data Analysis of Single Nucleotide Polymorphism in Human AGT Gene Using Computational Approach, International Journal of Genetics and Genomics. Vol. 8, No. 2, 2020, pp. 78-84. doi: 10.11648/j.ijgg.20200802.14
Copyright
Copyright © 2020 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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