Analysis of preferred codon usage in the coronavirus N genes and their implications for genome evolution and vaccine design

•The nucleotide variations among the N genes of 13 different coronaviruses (CoVs) were interpreted.•Overall, 18 amino acids observed with varying preferred codons.•The effective number of codon values ranged from 40.43 to 53.85, revealing a slight codon bias.•A highly significant correlation between GC3s and ENc values was observed in porcine epidemic diarrhea CoV, followed by Middle East respiratory syndrome CoV. [Display omitted] The nucleocapsid (N) protein of a coronavirus plays a crucial role in virus assembly and in its RNA transcription. It is important to characterize a virus at the nucleotide level to discover the virus’s genomic sequence variations and similarities relative to other viruses that could have an impact on the functions of its genes and proteins. This entails a comprehensive and comparative analysis of the viral genomes of interest for preferred nucleotides, codon bias, nucleotide changes at the 3rd position (NT3s), synonymous codon usage and relative synonymous codon usage. In this study, the variations in the N proteins among 13 different coronaviruses (CoVs) were analysed at the nucleotide and amino acid levels in an attempt to reveal how these viruses adapt to their hosts relative to their preferred codon usage in the N genes. The results revealed that, overall, eighteen amino acids had different preferred codons and eight of these were over-biased. The N genes had a higher AT% over GC% and the values of their effective number of codons ranged from 40.43 to 53.85, indicating a slight codon bias. Neutrality plots and correlation analyses showed a very high level of GC3s/GC correlation in porcine epidemic diarrhea CoV (pedCoV), followed by Middle East respiratory syndrome-CoV (MERS CoV), porcine delta CoV (dCoV), bat CoV (bCoV) and feline CoV (fCoV) with r values 0.81, 0.68, -0.47, 0.98 and 0.58, respectively. These data implied a high rate of evolution of the CoV genomes and a strong influence of mutation on evolutionary selection in the CoV N genes. This type of genetic analysis would be useful for evaluating a virus’s host adaptation, evolution and is thus of value to vaccine design strategies.