Data Analysis of Single Nucleotide Polymorphism in Human <i>AGT</i> Gene Using Computational Approach

Mohammed Youssif Mohammed; Afra Mohamed Al Bkrye; Hind Abdelaziz Elnasri; Mona Abdelrahman Mohamed Khaier

doi:doi:10.11648/j.ijgg.20200802.14

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Data Analysis of Single Nucleotide Polymorphism in Human AGT Gene Using Computational Approach

Mohammed Youssif Mohammed, Afra Mohamed Al Bkrye, Hind Abdelaziz Elnasri, Mona Abdelrahman Mohamed Khaier

Published in International Journal of Genetics and Genomics (Volume 8, Issue 2)

Received: 10 January 2020 Accepted: 27 January 2020 Published: 7 April 2020

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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.

Published in	International Journal of Genetics and Genomics (Volume 8, Issue 2)
DOI	10.11648/j.ijgg.20200802.14
Page(s)	78-84
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2020. Published by Science Publishing Group

Keywords

AGT Gene, Hypertension, I-mutant, SIFT, SNP & Go and PHD, Polyphen-2, Provean and Project Hope, SNP

References

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[3]	Engeli, S., Sharma, A. The renin-angiotensin system and natriuretic peptides in obesity-associated hypertension. J Mol Med 79, 21–29 (2001).
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[5]	Dodoo SN, Benjamin IJ. Genomic Approaches to Hypertension. Cardiol Clin. 2017 May; 35 (2): 185-196. doi: 10.1016/j.ccl.2016.12.001. Review.
[6]	Gkaliagkousi E, Douma S, Zamboulis C, Ferro A. Nitric oxide dysfunction in vascular endothelium and platelets: role in essential hypertension. J Hypertens. 2009 Dec; 27 (12): 2310-20. doi: 10.1097/HJH.0b013e328330e89a. Review.
[7]	Gribouval O, Gonzales M, Neuhaus T, Aziza J, Bieth E, Laurent N, Bouton JM, Feuillet F, Makni S, Ben Amar H, Laube G, Delezoide AL, Bouvier R, Dijoud F, Ollagnon-Roman E, Roume J, Joubert M, Antignac C, Gubler MC. Mutations in genes in the renin-angiotensin system are associated with autosomal recessive renal tubular dysgenesis. Nat Genet. 2005 Sep; 37 (9): 964-8. Epub 2005 Aug 14.
[8]	Gubler MC, Antignac C. Renin-angiotensin system in kidney development: renal tubular dysgenesis. Kidney Int. 2010 Mar; 77 (5): 400-6. doi: 10.1038/ki.2009.423. Epub 2009 Nov 18. Review.
[9]	gunda Padma, et al Risk conferred by tagged SNPs of AGT gene in causing susceptibility to essential hypertension, 2014, DOI: 10.3109/10641963.2014.881845.
[10]	Hu J, Ng PC. Predicting the effects of frame shifting indels Genome Biol. 2012; vol. 13 pg. R9.
[11]	Khalid Zuberi, Max Franz, Harold Rodriguez, Jason Montojo, Christian Tannus Lopes, Gary D. Bader Quaid Morr. GeneMANIA Prediction Server 2013 Update. Nucleic Acids Research. 2013; 41, Issue W1, 1 J W115–W122.
[12]	mohamed al nagi et al Association of the angiotensinogen gene polymorphism with atherosclerosis and its risk traits in the Saudi population, 2013, Published online 2013 Mar 11. doi: 10.1186/1471-2261-13-17.
[13]	pulakes purkait, Association of angiotensinogen gene SNPs and haplotypes with risk of hypertension in eastern Indian population, 2017, Published online 2017 Mar 29. doi: 10.1186/s40885-017-0069-x.
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[15]	Wolf G. Angiotensin II and tubular development. Nephrol Dial Transplant. 2002; 17 Suppl 9: 48-51.

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APA Style

Mohammed Youssif Mohammed, Afra Mohamed Al Bkrye, Hind Abdelaziz Elnasri, Mona Abdelrahman Mohamed Khaier. (2020). Data Analysis of Single Nucleotide Polymorphism in Human AGT Gene Using Computational Approach. International Journal of Genetics and Genomics, 8(2), 78-84. https://doi.org/10.11648/j.ijgg.20200802.14

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ACS Style

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. Int. J. Genet. Genomics 2020, 8(2), 78-84. doi: 10.11648/j.ijgg.20200802.14

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AMA Style

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. Int J Genet Genomics. 2020;8(2):78-84. doi: 10.11648/j.ijgg.20200802.14

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@article{10.11648/j.ijgg.20200802.14,
  author = {Mohammed Youssif Mohammed and Afra Mohamed Al Bkrye and Hind Abdelaziz Elnasri and Mona Abdelrahman Mohamed Khaier},
  title = {Data Analysis of Single Nucleotide Polymorphism in Human AGT Gene Using Computational Approach},
  journal = {International Journal of Genetics and Genomics},
  volume = {8},
  number = {2},
  pages = {78-84},
  doi = {10.11648/j.ijgg.20200802.14},
  url = {https://doi.org/10.11648/j.ijgg.20200802.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijgg.20200802.14},
  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.},
 year = {2020}
}

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TY - JOUR
T1 - Data Analysis of Single Nucleotide Polymorphism in Human AGT Gene Using Computational Approach
AU - Mohammed Youssif Mohammed
AU - Afra Mohamed Al Bkrye
AU - Hind Abdelaziz Elnasri
AU - Mona Abdelrahman Mohamed Khaier
Y1 - 2020/04/07
PY - 2020
N1 - https://doi.org/10.11648/j.ijgg.20200802.14
DO - 10.11648/j.ijgg.20200802.14
T2 - International Journal of Genetics and Genomics
JF - International Journal of Genetics and Genomics
JO - International Journal of Genetics and Genomics
SP - 78
EP - 84
PB - Science Publishing Group
SN - 2376-7359
UR - https://doi.org/10.11648/j.ijgg.20200802.14
AB - 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.
VL - 8
IS - 2
ER -

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Author Information

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

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APA Style

Mohammed Youssif Mohammed, Afra Mohamed Al Bkrye, Hind Abdelaziz Elnasri, Mona Abdelrahman Mohamed Khaier. (2020). Data Analysis of Single Nucleotide Polymorphism in Human AGT Gene Using Computational Approach. International Journal of Genetics and Genomics, 8(2), 78-84. https://doi.org/10.11648/j.ijgg.20200802.14

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ACS Style

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. Int. J. Genet. Genomics 2020, 8(2), 78-84. doi: 10.11648/j.ijgg.20200802.14

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AMA Style

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. Int J Genet Genomics. 2020;8(2):78-84. doi: 10.11648/j.ijgg.20200802.14

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@article{10.11648/j.ijgg.20200802.14,
  author = {Mohammed Youssif Mohammed and Afra Mohamed Al Bkrye and Hind Abdelaziz Elnasri and Mona Abdelrahman Mohamed Khaier},
  title = {Data Analysis of Single Nucleotide Polymorphism in Human AGT Gene Using Computational Approach},
  journal = {International Journal of Genetics and Genomics},
  volume = {8},
  number = {2},
  pages = {78-84},
  doi = {10.11648/j.ijgg.20200802.14},
  url = {https://doi.org/10.11648/j.ijgg.20200802.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijgg.20200802.14},
  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.},
 year = {2020}
}

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