COMPUTATIONAL PREDICTION OF NOVEL HUMAN MIRNA TARGET SITES IN VIRAL GENOMES

MicroRNAs (miRNAs) are a class of small non-coding RNAs that play a large role inpost-transcriptional processes. MiRNAs bind to the 3’ Untranslated region (3’UTR) of a sequence. Once bound the miRNA proceeds to cause degradation or repression of a messenger RNA (mRNA). In recent years the study of miRNAs has increased the pool of understanding for cancer research and personalized treatments for a multitude of diseases. Recent studies have suggested that miRNAs play a role in viral infection and proliferation. However, many known viral targets of these miRNAs aren’t known. Therefore, this study takes a computational approach to attempt to find a preliminary method of finding miRNA target sites in viral genomes. The use of different bioinformatic programs with different algorithms provided insight into what is already known about viral infections and the use of host cellular mechanisms while also providing questions for the future. Results show that the use of RNAhybrid in tandem with BLAST is a sufficient preliminary way to characterize potential target sites in viral genomes.