Analysis of Codon Usage and Nucleotide Bias in Middle East Respiratory Syndrome Coronavirus Genes

Author:

Hussain Snawar1ORCID,Shinu Pottathil1,Islam Mohammed Monirul1,Chohan Muhammad Shahzad1,Rasool Sahibzada Tasleem1

Affiliation:

1. Department of Biomedical Science, College of Clinical Pharmacy, King Faisal University, Al-Ahsa, Kingdom of Saudi Arabia

Abstract

The Middle East Respiratory Syndrome (MERS) is an emerging disease caused by a recently identified human coronavirus (CoV). Over 2494 laboratory-confirmed cases and 858 MERS-related deaths have been reported from 27 countries. MERS-CoV has been associated with a high case fatality rate, especially in patients with pre-existing conditions. Despite the fatal nature of MERS-CoV infection, a comprehensive study to explore its evolution and adaptation in different hosts is lacking. We performed codon usage analyses on 4751 MERS-CoV genes and determined underlying forces that affect the codon usage bias in the MERS-CoV genome. The current analyses revealed a low but highly conserved, gene-specific codon usage bias in the MERS-CoV genome. The codon usage bias is mainly shaped by natural selection, while mutational pressure emerged as a minor factor affecting codon usage in some genes. Other contributory factors included CpG dinucleotide bias, physical and chemical properties of encoded proteins and gene length. Results reported in this study provide considerable insights into the molecular evaluation of MERS-CoV and could serve as a theoretical basis for optimizing MERS-CoV gene expression to study the functional relevance of various MERS-CoV proteins. Alternatively, an attenuated vaccine strain containing hundreds of silent mutations could be engineered. Codon de-optimization will not affect the amino acid sequence or antigenicity of a vaccine strain, but the sheer number of mutations would make viral reversion to a virulent phenotype extremely unlikely.

Funder

deanship of scientific research, king faisal university

Publisher

SAGE Publications

Subject

Computer Science Applications,Genetics,Ecology, Evolution, Behavior and Systematics

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