Home > Free Essays > Sciences > Genetics > SNP Genetic Epidemiology
Cite this

SNP Genetic Epidemiology Essay


Doss, C., & Rajith, B. B. (2012). Computational Refinement of Functional Single Nucleotide Polymorphisms Associated with ATM Gene. Plos ONE, 7(4), 1-11. doi:10.1371/journal.pone.0034573

Single Nucleotide Polymorphisms (SNPs) refers to a genetic distinction occurring in humans. A unit SNP is a depiction of dissimilarity in one DNA building block (nucleotide). Every DNA contains SNPs in the ratio of 1:300 in every nucleotide contained in the body of humans. Usually, variation occurs between genes making it possible for researchers to identify genes responsible for diseases.

SNPs play a fundamental role in researching human health through utilization of genetic differences (Doss & Rajith, 2012). It is evident that SNPs can be useful in determining various responses of drugs to persons, and the presence of certain risks that concern environmental exposure.

The study aims at refining and separating SNPs that relate to ATM gene. ATM gene exists due to activation by DNA strands breaks. It is responsible for the presence of various proteins that culminate to DNA damage and apoptosis. The aim of computational refinement was to identify SNPs and the result of substituting amino acids in the ATM gene (Doss & Rajith, 2012). The genetic variations could be useful in determining diverse forms of cancer. The study concentrates on the functional effects of SNPs occurring in the coding area.

The SNPs found in this part can transform a lone amino acid present in a protein molecule. The SNPs found in non coding areas are significant in impacting gene splicing plus non coding RNA (4). The study aims at analyzing any deleterious possibilities of SNPs in relation to the ATM gene.

This was possible via use of dissimilar computation methods in order to arrive to better results. The study develops knowledge of computational methods of research, hence revealing both functional plus non functional variants occurring in coding and non coding areas (Doss & Rajith, 2012).

The article uses SNPs to create an understanding of disease in molecular perspective. This is possible because of the characteristics evident in SNPs in creating, damaging or altering coding sites (Doss & Rajith, 2012). The article uses SNPs in the determination of areas of genes that are vulnerable to disease attack.

The use of SNPs in determining phenotypic variations is evident in the article. The non functional SNPs are likely to trigger cellular changes thus leading to undesired disturbances and vulnerability of acquiring cancer. In the attempt to reveal the relationship between genetic mutation and phenotypic distinctions, the article employed SNP screening by utilizing distinct algorithms such as SIFT plus UTRScan (Reiner, Lettre, Nalls, Ganesh, Mathias, Austin & Kubo, 2011).

These methods of the study were significant in revealing SNPs via scores plus annotations. The method was not suitable for determining deleterious SNPs in the ATM gene and the results to the working of proteins due to certain limitations. The article uses SNPs in a suitable manner by employing a system that performs integration of scores from the in silico perspectives. This enabled identification of disease causing mutation occurring in unique regions.

The article utilizes Bayersian method to perform the analysis that yielded the results of SNPs in Translation modification (PTM) of proteins. There is evidence of the importance of protein acetylation in the working of cells where they affect ATM gene functioning (Doss & Rajith, 2012).

The article utilizes fundamental tools that incorporate both sequence plus structure in order to ensure reliability of end results. Through this criterion, it is possible to forecast the action of non functional SNPs where various algorithms are in use.

In order to attain accurate results, the ranking system enabled determination of protein function by utilizing SNPs. The ranking was possible through the use of scores from distinct systems (Doss & Rajith, 2012). In order to reveal the sites for PTM, certain methods, for example, recognition of physical plus chemical properties were evident in the article.

The statistical analysis performed to determine the functional effects SNPs in ATM provided significant findings on SNPs and ATM genes relationships. Refining the SNPs was vital in determining the variation of DNA and thus revealed the existence of disease. The frequent occurrence of SNPs is vital in conducting studies whose purpose is to indicate vulnerability for disease attack (Reiner, et al., 2011).

Results on the forecast of deleterious effects of non identical SNPs in the coding area indicated 25, 69 and 67 percent to be deleterious. In this prediction, about 168 non synonymous SNPs were in use with the incorporation of SIFT and POLYPHEN phenomenon. Examination of functional SNPs occurring in the regulatory area offered a comparison of the practical elements and functional significance in line with each sequence (Doss & Rajith, 2012).

In the process of determining the impact of SNPs on the working of proteins, it was evident that, for every 168 SNPs, there were 36 non synonymous SNPs which appeared to destroy splicing. Analysis of functional effects of nsSNPs on protein indicated accuracy while using POLYPHEN and SIFTS methods (Doss & Rajith, 2012).

References

Doss, C., & Rajith, B. B. (2012). Computational Refinement of Functional Single Nucleotide Polymorphisms Associated with ATM Gene. Plos ONE, 7(4), 1-11. doi:10.1371/journal.pone.0034573

Reiner, A. P., Lettre, G., Nalls, M. A., Ganesh, S. K., Mathias, R., Austin, M. A., & … Kubo, M. (2011). Genome-Wide Association Study of White Blood Cell Count in 16,388 African Americans: the Continental Origins and Genetic Epidemiology Network (COGENT). Plos Genetics, 7(6), 1-14. doi:10.1371/journal.pgen.1002108

This essay on SNP Genetic Epidemiology was written and submitted by your fellow student. You are free to use it for research and reference purposes in order to write your own paper; however, you must cite it accordingly.

Need a custom Essay sample written from scratch by
professional specifically for you?

Writer online avatar
Writer online avatar
Writer online avatar
Writer online avatar
Writer online avatar
Writer online avatar
Writer online avatar
Writer online avatar
Writer online avatar
Writer online avatar
Writer online avatar
Writer online avatar

301 certified writers online

GET WRITING HELP
Cite This paper

Select a citation style:

Reference

IvyPanda. (2018, November 20). SNP Genetic Epidemiology. Retrieved from https://ivypanda.com/essays/snp-genetic-epidemiology/

Work Cited

"SNP Genetic Epidemiology." IvyPanda, 20 Nov. 2018, ivypanda.com/essays/snp-genetic-epidemiology/.

1. IvyPanda. "SNP Genetic Epidemiology." November 20, 2018. https://ivypanda.com/essays/snp-genetic-epidemiology/.


Bibliography


IvyPanda. "SNP Genetic Epidemiology." November 20, 2018. https://ivypanda.com/essays/snp-genetic-epidemiology/.

References

IvyPanda. 2018. "SNP Genetic Epidemiology." November 20, 2018. https://ivypanda.com/essays/snp-genetic-epidemiology/.

References

IvyPanda. (2018) 'SNP Genetic Epidemiology'. 20 November.

Related papers