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Evolution of Synonymous Codon Usage Bias in West African and Central African Strains of Monkeypox Virus

Authors :
Sudeesh Karumathil
Nimal T Raveendran
Doss Ganesh
Sampath Kumar NS
Rahul R Nair
Vijaya R Dirisala
Source :
Evolutionary Bioinformatics, Vol 14 (2018)
Publication Year :
2018
Publisher :
SAGE Publishing, 2018.

Abstract

The evolution of bias in synonymous codon usage in chosen monkeypox viral genomes and the factors influencing its diversification have not been reported so far. In this study, various trends associated with synonymous codon usage in chosen monkeypox viral genomes were investigated, and the results are reported. Identification of factors that influence codon usage in chosen monkeypox viral genomes was done using various codon usage indices, such as the relative synonymous codon usage, the effective number of codons, and the codon adaptation index. The Spearman rank correlation analysis and a correspondence analysis were used for correlating various factors with codon usage. The results revealed that mutational pressure due to compositional constraints, gene expression level, and selection at the codon level for utilization of putative optimal codons are major factors influencing synonymous codon usage bias in monkeypox viral genomes. A cluster analysis of relative synonymous codon usage values revealed a grouping of more virulent strains as one major cluster (Central African strains) and a grouping of less virulent strains (West African strains) as another major cluster, indicating a relationship between virulence and synonymous codon usage bias. This study concluded that a balance between the mutational pressure acting at the base composition level and the selection pressure acting at the amino acid level frames synonymous codon usage bias in the chosen monkeypox viruses. The natural selection from the host does not seem to have influenced the synonymous codon usage bias in the analyzed monkeypox viral genomes.

Subjects

Subjects :
Evolution
QH359-425

Details

Language :
English
ISSN :
11769343 and 48704660
Volume :
14
Database :
Directory of Open Access Journals
Journal :
Evolutionary Bioinformatics
Publication Type :
Academic Journal
Accession number :
edsdoj.736e48704660438caf988fcb98fb7361
Document Type :
article
Full Text :
https://doi.org/10.1177/1176934318761368