Comprehensive examination on codon usage bias pattern of the Bovine Ephemeral fever virus.

Bovine ephemeral fever virus (BEFV) PR2 codon usage bias eNC neutrality plot phylogenetic tree recombination detection

Journal

Journal of biomolecular structure & dynamics
ISSN: 1538-0254
Titre abrégé: J Biomol Struct Dyn
Pays: England
ID NLM: 8404176

Informations de publication

Date de publication:
13 Sep 2023
Historique:
medline: 14 9 2023
pubmed: 14 9 2023
entrez: 14 9 2023
Statut: aheadofprint

Résumé

Bovine Ephemeral Fever Virus (BEFV) is a non-contagious virus that commonly infects cattle and water buffalo, reduces milk productivity, decreases the quality of beef, and causes an adverse economic impact on the global livestock industry. However, the evolution of BEFV is unclear, and uncertainty exists regarding its global geodynamics. Consequently, this study aims to comprehend the pattern of viral evolution and gene expression in the BEFV genes G, M, N, and P, including synonymous codons. Additionally, we performed recombination analyses, which exclusively detected recombination signals in the G- and P-genes. Subsequently, a phylogenetic tree was constructed to validate and support these findings. The codon usage bias results showed that the BEFV-selected genes were influenced by both natural and mutation pressure. Furthermore, nucleotide A is more abundant in all the selected genes. The eNC values, ranging from 42.99 to 47.10, revealed the presence of moderate codon usage bias, where gene P exhibited the highest and gene G had the lowest codon usage bias. The neutrality and PR-2 plots, specified codon usage patterns of the genes, are also being shaped by strong selectional pressure. This comprehensive analysis of BEFV genes (G, M, N, and P) sheds light on the molecular evolutionary patterns, co-adaptation, and different genes expression in diverse regions, facilitating the development of preventative programs and insights into viral pathogenesis and vaccine design.Communicated by Ramaswamy H. Sarma.

Identifiants

pubmed: 37705249
doi: 10.1080/07391102.2023.2258220
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1-11

Auteurs

Swati Rani (S)

Disease Informatics, Spatial Epidemiology Lab, ICAR - National Institute of Veterinary Epidemiology and Disease Informatics, Bengaluru, India.

M N Mamathashree (MN)

Disease Informatics, Spatial Epidemiology Lab, ICAR - National Institute of Veterinary Epidemiology and Disease Informatics, Bengaluru, India.

Uma Bharthi I (U)

Disease Informatics, Spatial Epidemiology Lab, ICAR - National Institute of Veterinary Epidemiology and Disease Informatics, Bengaluru, India.

S S Patil (SS)

Disease Informatics, Spatial Epidemiology Lab, ICAR - National Institute of Veterinary Epidemiology and Disease Informatics, Bengaluru, India.

P Krishnamoorthy (P)

Disease Informatics, Spatial Epidemiology Lab, ICAR - National Institute of Veterinary Epidemiology and Disease Informatics, Bengaluru, India.

Mohammad Shueb (M)

Department of Biotechnology and Bioinformatics, JSS Academy of Higher Education and Research, Mysuru, India.

Rajan Kumar Pandey (RK)

Department of Medical Biochemistry and Biophysics, Karolinska Institute, Solna, Sweden.

K P Suresh (KP)

Disease Informatics, Spatial Epidemiology Lab, ICAR - National Institute of Veterinary Epidemiology and Disease Informatics, Bengaluru, India.

Classifications MeSH