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Current Bioinformatics

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ISSN (Print): 1574-8936
ISSN (Online): 2212-392X

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Systematic Review Article

Genomic Characterization of Emerging SARS-CoV-2: A Systematic Review

Author(s): Shikha Sharma*, Rinkle Rani and Nidhi Kalra

Volume 18, Issue 5, 2023

Published on: 17 April, 2023

Page: [375 - 408] Pages: 34

DOI: 10.2174/1574893618666230228115423

Price: $65

Abstract

Introduction: Severe Acute Respiratory Syndrome Coronavirus – 2, SARS-CoV-2, is a wellknown virus for its fatal infectivity and widespread impact on the health of the worldwide population. Genome sequencing is critical in understanding the virus’s behavior, origin, and genetic variants. This article conducts an extensive literature review on the SARS-CoV-2 genome, including its Genome Structure, Genome Analysis, Evolution, Mutation, and, Genome Computation. It highlights the summary of clinical and evolutionary research along with the applicability of computational methods in the areas. It lucidly presents the structural detail and mutation analysis of SARS-CoV-2 without overwhelming the readers with difficult terms. In the pandemic, machine learning and deep learning emerged as a paradigm change, that when combined with genome analysis, enabled more precise identification and prognosis of the virus's impact. Molecular detailing is crucial in extracting features from the SARS-CoV-2 genome before computation models are applied.

Methods: Further, in this systematic study we investigate the usage of Machine Learning and Deep Learning models mapped to SARS-CoV-2 genome samples to see their applicability in virus detection and disease severity prediction. We searched research articles from various reputed journals explaining the structure, evolution, mutations, and computational methods published until June 2022.

Results: The paper summarizes significant trends in the research of SARS-COV-2 genomes. Furthermore, this research also identifies the limitations and research gaps that yet have to be explored more and indicates future directions.

Impact Statement: There are few review articles on the SARS-CoV-2 genome; these reviews target various aspects of the SARS-COV2 genome individually. This article considers all the aspects simultaneously and provides in-depth knowledge about the SARS-CoV-2 genome.

Conclusion: This article provides a detailed description about the type of samples, volumes of selection, processes, and tools used by various researchers in their studies. Further, the computational techniques applied to the SARS-COV2 genome are also discussed and analysed thoroughly.

Keywords: COVID-19, 2019-nCoV evolution, SARS-CoV-2 structure, virus-host interactions, SARS-CoV-2 mutations, learning models.

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