An In-Silico Approach for the Prediction of miRNAs in Merkel Cell Polyoma Virus and its Target Genes

Gohar Rahman, Bilal Ahmad Mian, Najib Ullah, Huzaifa Khan, Shaker Khan


Background: For last five years, as technological advancement occurs, novel kinds of human generation viruses’ discovery have been increased. A rare human cancer associated virus Merkel’s Cell polyomavirus (MCPyV or MCV) got remarkable attraction among the newly discovered viruses. As a common human virus MCPyV infection frequently found in skin and also occurs at other anatomical sites. Methods: In this study, the in-silico screening of miRNAs from MCPyV was done, as the computational screening procedures are functionally vital, efficient and inexpensive for the said purpose. Results: Primarily 52 sequences, possessing possible hairpin-like structures, were extracted from MCPyV genome by searching through VMir software using various filters. 17 nominees were confirmed with real pre-miRNA like hairpin organizations by iMiRNA-SSF program. Further seven nominees were excluded by free energy measurement and other parameters. 10 mature miRNAs were affirmed in 10 impending candidates for pre-miRNAs by MatureBayes web server v1.0, among these 10 candidates 2 were reported already by earlier studies. The homologous miRNA for these candidates were searched in mirBase. To find the target gene and its relevant diseases the best homologous miRNAs were then searched in Target Scan. Among all miRNAs Cancer was found to be common. Conclusion: These findings open new avenues for researchers to explore the role of these novel miRNAs in viral pathogenesis as well as in developing new antiviral therapy. 

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