DNA Sequencing Essay Example

Introduction

DNA sequencing is a common practice in the health industry which is used in medical research. Advances in DNA sequencing methods have greatly aided discoveries that have revolutionised modern medical practices (Metzker, 2010). Some of the tools used in DNA sequencing include the Sanger Data Sequencing method and the Next Generation Sequencing (NGS) method (Augusto et al., 2013). The following report will explain which data sequencing method, between Sanger and NGS, is more reliable than the other.

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The NGS technologies are more reliable than Sanger sequencing since they have a higher sequencing volume (Kilian, 2012). NGS technologies can sequence millions of fragments at once while the Sanger method only sequences one DNA fragment at a time (Bekel, 2009).

The advantage of the NGS technology is that by sequencing several genes at a time, it enables researchers to detect even the slightest variations between genomes. The only disadvantage of the NGS method is that it increases the risk of errors (Varshney, 2009). While sequencing a large volume of DNA, there is a greater chance that the researcher might make a mistake (Gounder et al., 2017; Haddad, 2018). Hence, researchers are working to look for methods and programs that can be used to analyse DNA sequencing following the use of NGS technologies (Varshney, 2009).

Benefits of public databases

Technologies such as NGS have greatly enhanced the ability of researchers to conduct DNA sequencing. However, the researchers do not have the capacity to analyse the data they get from DNA sequencing (BauerMehren, 2009). Public databases such as the Exome Aggregation Consortium have therefore been created to help address these obstacle facing the researchers. Such databases contain information such as the gene sequence, different variants of the gene as well as presumed pathogenic mutations (BauerMehren, 2009). Therefore, the databases are beneficial in the identification of pathogenic mutations since they help researchers avoid unnecessary testing (Litman, 2017). Such databases are updated regularly hence a researcher can easily search for pathogenic mutations in the database (BauerMehren, 2009).

References

Augusto, F., Hantao, L. W., Mogollon, N. G., & Braga, S. C. (2013). New materials and trends in sorbents for solid-phase extraction. TrAC Trends in Analytical Chemistry, 43, 14-23.

BauerMehren, A., Furlong, L. I., & Sanz, F. (2009). Pathway databases and tools for their exploitation: benefits, current limitations and challenges. Molecular systems biology, 5(1), 290.

Bekel, T., Henckel, K., Kuster, H., Meyer, F., Runte, V. M., Neuweger, H., ... & Stoye, J. (2009). The Sequence Analysis and Management System-SAMS-2.0: data management and sequence analysis adapted to changing requirements from traditional sanger sequencing to ultrafast sequencing technologies. Journal of biotechnology, 140(1-2), 3-12.

Gounder, M. M., Ali, S. M., Robinson, V., Bailey, M., Ferraro, R., Patel, N. M., & Keohan, M. L. (2017). Impact of next-generation sequencing (NGS) on diagnostic and therapeutic options in soft-tissue and bone sarcoma.

Haddad, F. S. (2018). Next generation sequencing: is this the moment?.Kilian, B., & Graner, A. (2012). NGS technologies for analyzing germplasm diversity in genebanks. Briefings in functional genomics, 11(1), 38-50.

Litman, T. (2017). Evaluating public transit benefits and costs: Best practices guidebook.

Metzker, M. L. (2010). Sequencing technologies-the next generation. Nature reviews genetics, 11(1), 31.

Varshney, R. K., Nayak, S. N., May, G. D., & Jackson, S. A. (2009). Next-generation sequencing technologies and their implications for crop genetics and breeding. Trends in biotechnology, 27(9), 522-530.