A computational analysis of molecular evolution for virulence genes of zoonotic novel coronavirus (COVID-19).
Comput Biol Chem
; 93: 107532, 2021 Aug.
Article
in English
| MEDLINE | ID: covidwho-1275230
ABSTRACT
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.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Virulence
/
Spike Glycoprotein, Coronavirus
/
Coronavirus RNA-Dependent RNA Polymerase
/
Coronavirus Nucleocapsid Proteins
/
SARS-CoV-2
/
Hemagglutinins
Type of study:
Diagnostic study
Language:
English
Journal:
Comput Biol Chem
Journal subject:
Biology
/
Medical Informatics
/
Chemistry
Year:
2021
Document Type:
Article
Affiliation country:
J.compbiolchem.2021.107532
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