Epidemiological comparisons of codon usage patterns among HIV-1 isolates from Asia, Europe, Africa and the Americas

Abstract

To investigate the genomic properties of HIV-1, we collected 3,081 sequences from the HIV Sequence Database. The sequences were categorized according to sampling region, country, year, subtype, gene name, and sequence and were saved in a database constructed for this study. The relative synonymous codon usage (RSCU) values of matrix, capsid, and gp120 and gp41 genes were calculated using correspondence analysis. The synonymous codon usage patterns based on the geographical regions of African countries showed broad distributions; when all the other regions, including Asia, Europe, and the Americas, were taken into account, the Asian countries tended to be divided into two groups. The sequences were clustered into nine non-CRF subtypes. Among these, subtype C showed the most distinct codon usage pattern. To determine why the codon usage patterns in Asian countries were divided into two groups for four target genes, the sequences of the isolates from the Asian countries were analyzed. As a result, the synonymous codon usage patterns among Asian countries were divided into two groups, the southern Asian countries and the other Asian countries, with subtype 01_AE being the most dominant subtype in southern Asia. In summary, the synonymous codon usage patterns among the individual HIV-1 subtypes reflect genetic variations, and this bioinformatics technique may be useful in conjunction with phylogenetic methods for predicting the evolutionary patterns of pandemic viruses.

Mutation pressure shapes codon usage in the GC-Rich genome of foot-and-mouth disease virus

“…Up to now, it is unclear how FMDV serotypes might affect codon choice in FMD viruses and we used RSCU [42], ENC [32], COA [43,44] and GC 3S , to measure the synonymous codon usage bias in order to minimize the effects of serotypes on codon bias, which have been successfully used to analyze the variation of codon usage among different viruses species [11,13,14,22,45,46]. The analysis revealed that codon usage bias is low in most cases.…”

Differential Trends in the Codon Usage Patterns in HIV-1 Genes

“…Being a rapidly evolving pathogen, codon usage pattern similar to host may help HIV-1 to attain higher gene expression, development of drug resistance, and immune evasion at the same time resulting in mutational robustness and translational selection [8] , [13] . Most evolutionary studies on codon usage of HIV-1 have focused on either the specific codons under selection or compared the codon usage pattern of structural genes in different geographical locations [32] – [35] , [51] . Our population level studies of the “Relative neutrality plot” ( Figure 2A ) and “Effective number of codons” ( Figure 2B ) of all genes of HIV-1 indicate that genetic compositional constraints may not be the primary reason for the observed codon usage bias in HIV-1 genes, and translational selection may underlie this feature.…”

“…At the population level also, various studies have demonstrated similar selection of functionally important sites in different HIV-1 subtypes, arguing for presence of positive selection [33], [34]. Contrary to these studies, genetic/mutational drift has also been shown to drive evolution of HIV-1 in inter-host transmission, as immune selection changes with change in individual host [17], [35]. Given these opposing results, a clear understanding of the mechanisms leading to host-specific adaptation of the virus, both within a particular individual and at the population level, can provide plausible targets for drug therapy and help to develop effective vaccines.…”

Comparative study of synonymous codon usage variations between the nucleocapsid and spike genes of coronavirus, and C-type lectin domain genes of human and mouse

“…Codon usage bias has been studied in various organisms ranging from virus to eukaryote, and optimized codon usages in the target viral genes also have been made to improve the efficacy of DNA vaccines development ( Ramakrishna et al, 2004 ; Shackelton et al, 2006 ; van Hemert et al, 2007 ; Wang et al, 2006a , 2006b ). Based on our previous studies, synonymous codon usage itself among RNA viruses such as influenza A viruses and HIV-1s revealed specific bias on the basis of each region, subtype, host or occurring-year group, suggesting that there might be some correlations between the codon usage patterns and viral variations in the codon basis ( Ahn and Son, 2006 , 2007 ; Ahn et al, 2006 ).…”

“…They suggested that the main reason for these differences might be due to the differences in the viral replication and repairing mechanisms, such as cellular or viral replicative machinery. In our previous study, synonymous codon usage patterns among RNA viruses such as influenza A viruses and HIV-1s were divided into each region, subtype, host or occurring-year group, with an expectation that there might be some correlations between the nucleotide patterns and the direction of viral variations on the codon basis ( Ahn and Son, 2006 , 2007 ; Ahn et al, 2006 ). Furthermore, van Hemert et al ( 2007 ) reported that the recent evolution of astroviruses was associated with a switch in nucleotide composition and codon usage among non-human mammalian versus human/avian astroviruses.…”