Entropy and codon bias in HIV-1

BioRxiv : the Preprint Server for Biology
Aakash Pandey

Abstract

HIV is rapidly evolving virus with high mutation rate. For heterologous gene expression system, the codon bias has to be optimized according to the host for efficient expression. Although DNA viruses show some correlation on codon bias with their hosts, HIV genes show very 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 in infecting hosts and multiplying in large number. In this study, I have performed information theoretic analysis of nine genes of HIV-1 based on codon statistics of the whole HIV genome, individual genes and codon usage of human genes. For the HIV-1 whole genome sequence analyzed, it has been observed that the codon statistics of the third reading frame has the highest bias representing minimum entropy and hence maximum information. Similarly, despite being poorly adapted to the codon usage bias of human hosts, I have found that the Shannon entropies of nine genes based on overall codon statistics of HIV-1 genome are very similar to the entropies calculated from codon usage of human genes probably suggesting co-evolution of HIV-1 along with human genes.

Related Concepts

Codon (Nucleotide Sequence)
DNA
Gene Expression
Genes
Genome
HIV
HIV Infections
Nucleotides
Virus
Human gene

Related Feeds

BioRxiv & MedRxiv Preprints

BioRxiv and MedRxiv are the preprint servers for biology and health sciences respectively, operated by Cold Spring Harbor Laboratory. Here are the latest preprint articles (which are not peer-reviewed) from BioRxiv and MedRxiv.