Computational Prediction Of Micro-RNAs In Hepatitis B Virus Genome

MicroRNAs (miRNAs) are 19—25 nucleotides long, single-stranded, endogenous non-coding RNA molecules that play crucial roles in the post-transcriptional regulation of gene expression by targeting messenger RNAs for cleavage or translational repression. Genomes of various organisms ranging from higher animals and plants to viruses transcribe miRNAs. Recent studies show that both virus and host encode miRNAs that can give benefit either to virus or to host, depending upon the specific interactions. Hepatitis B Virus (HBV) is involved in acute and chronic diseases of liver and can bring about hepatitis, liver cirrhosis and hepatocellular carcinoma (HCC). In this study, we analyzed HBV (genotype D) for miRNAs, computationally, since computational methods serve vigorous, better, and affordable tools for microRNAs identification. Initial searches through VMir software extracted 57 sequences with potential hairpin-like structures from HBV genome. MiPred program confirmed 10 candidates as real pre-miRNA like hairpin structures. Measurements of free energy and other parameters further excluded three candidates. Finally, MatureBayes web server v1.0 confirmed 12 mature miRNAs in 6 potential pre-miRNA candidates in HBV genome, including one which has been identified in earlier studies. These findings open new avenues for researchers to explore the role of these novel miRNAs in viral pathogenesis as well as in developing novel antiviral therapies.