Entropy and codon bias in HIV-1

Abstract

For the heterologous gene expression systems, the codon bias has to be optimized according to the host for efficient expression. Although DNA viruses show a correlation on codon bias with their hosts, HIV genes show low correlation for both nucleotide composition and codon usage bias with its human host which limits the efficient expression of HIV genes. Despite this variation, HIV is efficient at infecting hosts and multiplying in large number. In this study, first, the degree of codon adaptation is calculated as codon adaptation index (CAI) and compared with the expected threshold value (eCAI) determined from the sequences with the same nucleotide composition as that of the HIV-1 genome. Then, information theoretic analysis of nine genes of HIV-1 based on codon statistics of the HIV-1 genome, individual genes and codon usage of human genes is done. Comparison of codon adaptation indices with their respective threshold values shows that the CAI lies very close to the threshold values. Despite not being well adapted to the codon usage bias of human hosts, it was found that the Shannon entropies of the nine genes based on overall codon statistics of HIV-1 genome are very similar to the entropies calculated from codon usage of human genes. Similarly, for the HIV-1 genome sequence analyzed, the codon statistics of the third reading frame has the highest bias representing minimum entropy and hence the maximum information.