Analysis of compositional bias and codon usage pattern of the coding sequence in Banna virus genome

Area of Science:

• Virology
• Molecular Biology
• Bioinformatics

Background:

• Bovine alphaherpesvirus 1 (BAV) is a significant pathogen causing viral encephalitis in cattle.
• Understanding BAV gene composition and codon usage is crucial for developing effective disease control strategies.

Purpose of the Study:

• To analyze the nucleotide composition and codon usage patterns of 115 BAV genes.
• To investigate the factors influencing codon bias, including natural selection and neutral mutation.
• To provide a theoretical foundation for BAV disease management.

Main Methods:

• Utilized bioinformatics tools: DNA Star, CUSP of EMBOSS, Codon W, and IBM SPSS Statistics.
• Analyzed nucleotide composition, codon usage bias (Effective Number of Codons - ENC), and correlation analyses.
• Examined gene function and host interactions in relation to codon usage patterns.

Main Results:

• BAV genes exhibit a preference for AU over CG composition, with A, U, G, C order prevalent.
• A weak codon bias was observed across most genes, with VP9 showing the highest bias.
• Codon usage patterns varied among genes, correlating with composition, function (e.g., VP9 spike protein, VP1-4 capsid proteins), and host interactions.
• Analysis indicated that both natural selection and neutral mutation influence BAV codon usage patterns to varying degrees.

Conclusions:

• The nucleotide composition and codon usage patterns of BAV genes are shaped by a combination of evolutionary forces.
• Understanding these patterns offers insights into BAV gene expression and regulation.
• Compositional and codon bias analyses provide a valuable theoretical basis for developing strategies to control BAV-associated diseases.