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Genome composition and genetic characterization of SARS-CoV-2.

ABSTRACT: SARS-CoV-2 is a type of Betacoronaviruses responsible for COVID-19 pandemic disease, with more than 1.745 million fatalities globally as of December-2020. Genetically, it is considered the second largest genome of all RNA viruses with a 5' cap and 3' poly-A tail. Phylogenetic analyses of coronaviruses reveal that SARS-CoV-2 is genetically closely related to the Bat-SARS Like-Corona virus (Bat-SL-Cov) with 96% whole-genome identity. SARS-CoV-2 genome consists of 15 ORFs coded into 29 proteins. At the 5' terminal of the genome, we have ORF1ab and ORF1a, which encode the 1ab and 1a polypeptides that are proteolytically cleaved into 16 different nonstructural proteins (NSPs). The 3' terminal of the genome represents four structural (spike, envelope, matrix, and nucleocapsid) and nine accessory (3a, 3b, 6, 7a, 7b, 8b, 9a, 9b, and orf10) proteins. As the number of COVID-19 patients increases dramatically worldwide, there is an urgent need to find a quick and sensitive diagnostic tool for controlling the outbreak of SARS-CoV-2 in the community. Today, molecular testing methods utilizing viral genetic material (e.g., PCR) represent the crucial diagnostic tool for the SARS-CoV-2 virus despite its low sensitivity in the early stage of viral infection. This review summarizes the genome composition and genetic characterization of the SARS-CoV-2.

SUBMITTER: Al-Qaaneh AM

PROVIDER: S-EPMC7834485 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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Genome composition and genetic characterization of SARS-CoV-2.

Al-Qaaneh Ayman M AM Alshammari Thamer T Aldahhan Razan R Aldossary Hanan H Alkhalifah Zahra Abduljaleel ZA Borgio J Francis JF

Saudi journal of biological sciences 20210106 3

SARS-CoV-2 is a type of Betacoronaviruses responsible for COVID-19 pandemic disease, with more than 1.745 million fatalities globally as of December-2020. Genetically, it is considered the second largest genome of all RNA viruses with a 5' cap and 3' poly-A tail. Phylogenetic analyses of coronaviruses reveal that SARS-CoV-2 is genetically closely related to the Bat-SARS Like-Corona virus (Bat-SL-Cov) with 96% whole-genome identity. SARS-CoV-2 genome consists of 15 ORFs coded into 29 proteins. At ...[more]

PMID: 33519278

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Project description:Background: The ongoing COVID-19 pandemic is a global health crisis caused by the spread of SARS-CoV-2. Establishing links between known cases is crucial for the containment of COVID-19. In the healthcare setting, the ability to rapidly identify potential healthcare-associated COVID-19 clusters is critical for healthcare worker and patient safety. Increasing sequencing technology accessibility has allowed routine clinical diagnostic laboratories to sequence SARS-CoV-2 in clinical samples. However, these laboratories often lack specialized informatics skills required for sequence analysis. Therefore, an on-site, intuitive sequence analysis tool that enables clinical laboratory users to analyze multiple genomes and derive clinically relevant information within an actionable timeframe is needed. Results: We propose CalmBelt, an integrated framework for on-site whole genome characterization and outbreak tracking. Nanopore sequencing technology enables on-site sequencing and construction of draft genomes for multiple SARS-CoV-2 samples within 12 h. CalmBelt's interactive interface allows users to analyse multiple SARS-CoV-2 genomes by utilizing whole genome information, collection date, and additional information such as predefined potential clusters from epidemiological investigations. CalmBelt also integrates established SARS-CoV-2 nomenclature assignments, GISAID clades and PANGO lineages, allowing users to visualize relatedness between samples together with the nomenclatures. We demonstrated multiple use cases including investigation of potential hospital transmission, mining transmission patterns in a large outbreak, and monitoring possible diagnostic-escape. Conclusions: This paper presents an on-site rapid framework for SARS-CoV-2 whole genome characterization. CalmBelt interactive web application allows non-technical users, such as routine clinical laboratory users in hospitals to determine SARS-CoV-2 variants of concern, as well as investigate the presence of potential transmission clusters. The framework is designed to be compatible with routine usage in clinical laboratories as it only requires readily available sample data, and generates information that impacts immediate infection control mitigations.

Dataset Information

Genome composition and genetic characterization of SARS-CoV-2.

Publications

Genome composition and genetic characterization of SARS-CoV-2.

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