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A computational analysis of molecular evolution for virulence genes of zoonotic novel coronavirus (COVID-19)

Zoonotic Novel coronavirus disease 2019 (COVID-19) is highly pathogenic and transmissible considered as emerging pandemic disease. The virus belongs from a large virus Coronaviridae family affect respiratory tract of animal and human likely originated from bat and homology to SARA-CoV and MERS-CoV....

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Detalles Bibliográficos
Autores principales: Kumari, Priya, Poddar, Raju
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8213524/
https://www.ncbi.nlm.nih.gov/pubmed/34171504
http://dx.doi.org/10.1016/j.compbiolchem.2021.107532
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author Kumari, Priya
Poddar, Raju
author_facet Kumari, Priya
Poddar, Raju
author_sort Kumari, Priya
collection PubMed
description Zoonotic Novel coronavirus disease 2019 (COVID-19) is highly pathogenic and transmissible considered as emerging pandemic disease. The virus belongs from a large virus Coronaviridae family affect respiratory tract of animal and human likely originated from bat and homology to SARA-CoV and MERS-CoV. The virus consists of single-stranded positive genomic RNA coated by nucleocapsid protein. The rate of mutation in any virulence gene may influence the phenomenon of host radiation. We have studied the molecular evolution of selected virulence genes (HA, N, RdRP and S) of novel COVID-19. We used a site-specific comparison of synonymous (silent) and non-synonymous (amino acid altering) nucleotide substitutions. Maximum Likelihood genealogies based on differential gamma distribution rates were used for the analysis of null and alternate hypothesis. The null hypothesis was found more suitable for the analysis using Likelihood Ratio Test (LRT) method, confirming higher rate of substitution. The analysis revealed that RdRP gene had the fastest rate evolution followed by HA gene. We have also reported the new motifs for different virulence genes, which are further useful to design new detection and diagnosis kit for COVID -19.
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spelling pubmed-82135242021-06-21 A computational analysis of molecular evolution for virulence genes of zoonotic novel coronavirus (COVID-19) Kumari, Priya Poddar, Raju Comput Biol Chem Article Zoonotic Novel coronavirus disease 2019 (COVID-19) is highly pathogenic and transmissible considered as emerging pandemic disease. The virus belongs from a large virus Coronaviridae family affect respiratory tract of animal and human likely originated from bat and homology to SARA-CoV and MERS-CoV. The virus consists of single-stranded positive genomic RNA coated by nucleocapsid protein. The rate of mutation in any virulence gene may influence the phenomenon of host radiation. We have studied the molecular evolution of selected virulence genes (HA, N, RdRP and S) of novel COVID-19. We used a site-specific comparison of synonymous (silent) and non-synonymous (amino acid altering) nucleotide substitutions. Maximum Likelihood genealogies based on differential gamma distribution rates were used for the analysis of null and alternate hypothesis. The null hypothesis was found more suitable for the analysis using Likelihood Ratio Test (LRT) method, confirming higher rate of substitution. The analysis revealed that RdRP gene had the fastest rate evolution followed by HA gene. We have also reported the new motifs for different virulence genes, which are further useful to design new detection and diagnosis kit for COVID -19. Elsevier Ltd. 2021-08 2021-06-19 /pmc/articles/PMC8213524/ /pubmed/34171504 http://dx.doi.org/10.1016/j.compbiolchem.2021.107532 Text en © 2021 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Kumari, Priya
Poddar, Raju
A computational analysis of molecular evolution for virulence genes of zoonotic novel coronavirus (COVID-19)
title A computational analysis of molecular evolution for virulence genes of zoonotic novel coronavirus (COVID-19)
title_full A computational analysis of molecular evolution for virulence genes of zoonotic novel coronavirus (COVID-19)
title_fullStr A computational analysis of molecular evolution for virulence genes of zoonotic novel coronavirus (COVID-19)
title_full_unstemmed A computational analysis of molecular evolution for virulence genes of zoonotic novel coronavirus (COVID-19)
title_short A computational analysis of molecular evolution for virulence genes of zoonotic novel coronavirus (COVID-19)
title_sort computational analysis of molecular evolution for virulence genes of zoonotic novel coronavirus (covid-19)
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8213524/
https://www.ncbi.nlm.nih.gov/pubmed/34171504
http://dx.doi.org/10.1016/j.compbiolchem.2021.107532
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