• Neema Tufchi Graphic Era University
  • Kumud Pant Graphic Era University
  • Bhasker Pant Graphic Era University
  • Syed Mohsin Waheed Graphic Era University


MicroRNAs, Japanese encephalitis virus, Secondary structure prediction, MiPred, Genscan, Mirbase, RNApred, RNAfold, Mfold and minimum free energy


Objective: MicroRNAs are endogenous, small, single stranded, non coding RNAs having 19-25 nucleotides. These miRNAs are complementary to their target messenger RNAs that bind principally to its 3' un translated regions (3' UTRs). Small RNAs play crucial roles in the regulation of gene expression in many eukaryotes; therefore it is important to predict potential viral miRNAs which might be involved in an establishment of Japanese Encephalitis virus (JEV) disease. Different computational approaches and methods were used for predicting viral microRNAs from the JEV genome in this work.

Methods: In the present study, the use of genome-wide computational approach has been demonstrated to predict miRNAs and their target(s) in JEV genome. Two freely accessible softwares, MiPred and Genscan were used to predict the secondary structures of the potential miRNAs.

Results: In all, 36 miRNAs were predicted and characterized by conducting genome-wide homology search against all the reported miRNAs. These miRNAs were further validated by performing phylogenetic analyses and using statistical tools.Further, attempt was made to predict the 3′ untranslated regions of mRNAs from whole genome of JEV which may prove helpful in finding putative targets of these miRNAs.

Conclusion: This is the first study to identify and validate miRNAs in JEV which is an important step in identifying putative JEV miRNAs that utilize host cell machinery, and may play a crucial role in neuroinflammation and silencing of host genes, thus demonstrating the role of viral miRNAs in establishing viral pathogenesis.



Download data is not yet available.


Reference. Available from: MicroRNA.

Singh J, Nagaraju J. In silico prediction and characterization of micro RNAs from red flour beetle (Tribolium castaneum). Insect Mol Biol 2008;17:427-36.

Kamarajan BP, Sridhar J, Subramanian S. In silico prediction of MicroRNAs in plant mitochondria. Int J BIOautom 2012;16:251-62.

M Zhou, Q Wang, J Sun, X Li, L Xu, H Yang, et al. In silico detection and characteristics of novel microRNA genes in the Equuscaballus genome using an integrated ab initio and comparative genomic approach. Genomics 2009;94:125–31.

Lau NC, Lim NP, Weinstein EG, Bartel DP. An Abundant class of tiny RNAs with probable regulatory roles in Caenorhabditiselegans. Sci 2001;26:858-62.

Kalaria R, Patel N. In silico candidates miRNA prediction from genome Dictyosteliumdiscoideum. Int J Pharm Biol Res 2012;3:41-50.

Yue D, Meng J, Lu M, Chen C, Guo M, Huang Y. Understanding microRNA regulation: a computational perspective. Signal Processing Magazine IEEE 2012;29:77–88.

Reference. Available from wiki/ Japanese_encephalitis.

Reference. Available from: niv/JAPANESE%20ENCEPHALITIS.pdf.

Reference. Available from: /factsheets/fs386/en/.

Thounaojam CM, Kundu K, Kaushik DK, Basu A. MicroRNA-29b modulates Japanese encephalitis virus-induced microglia activation by targeting tumor necrosis factor alpha-induced protein 3. J Neurochem 2014;129:143-54.

Wu Z, Xue Y, Wang B, Du J, Jin Q, Broad-spectrum antiviral activity of RNA interference against four genotypes of japanese encephalitis virus based on single MicroRNA polycistrons. PLoS ONE 2011;6:e26304.

Thounaojam CM, Kundu K, Kaushik DK, Swaroop S, Mahadevan A, Shankar SK, et al. MicroRNA 155 regulates japanese encephalitis virus-induced inflammatory response by targeting src homology 2-containing inositol phosphatase 1. J Virol 2014;88:4798-10.

Sharma N, Verma R, Kumawat KL, Basu A, Singh SK. miR-146a suppresses cellular immune response during Japanese encephalitis virus JaOArS982 strain infection in human microglial cells. J Neuroinflammation 2015;12:30.

Reference. Available from: National_Center_for_Biotechnology_Information.

Kozomara A, Griffiths-Jones S. miRBase: annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Res 2014;42:D68-73.

Reference. Available from:

Reference. Available from: applications/mfold/rna/form1.cgi.

Zuker M. On finding all suboptimal foldings of an RNA molecule. Sci 1989;244:48–52.

Zuker M. Mfold web server for nucleic acid folding and hybridization prediction. Nucleic Acids Res 2003;31:3406-15.

Jiang P, Wu H, Wang W, Ma W, Sun X, Lu Z. MiPred: classification of real and pseudo microRNA precursors using random forest prediction model with combined features. Nucleic Acids Res 2007;35:W339–44.

Reference. Available from: GENSCAN

Reference. Available from: crt/GENSCAN/index.xml.

Burge C, Samuel K. Prediction of complete gene structures in human genomic DNA. J Mol Biol 1997;268:78-94.

Brennecke J, Hipfner DR, Stark A, Russell RB, Cohen SM. Bantam encodes a developmentally regulated microRNA that controls cell proliferation and regulates the proapoptotic gene hid in Drosophila. Cell 2003;113:25–36.

Lin SY, Johnson SM, Abraham M, Vella MC, Pasquinelli A, Gamberi C. The C elegans hunchback homolog, hbl-1, controls temporal patterning and is a probable microRNA target. Dev Cell 2003;4:639–50.

Rhoades MW, Reinhart BJ, Lim LP, Burge CB, Bartel B, Bartel DP. Prediction of plant microRNA targets. Cell 2002;110:513–20.

Lytle JR, Yario TA, Steitz JA. Target mRNAs are repressed as efficiently by microRNA-binding sites in the 5′ UTR as in the 3′ UTR. Proc Natl Acad Sci 2007;104:9667–72.

Jones-Rhoades MW, Bartel DP. Computational identification of plant microRNAs and their targets, including a stress-induced miRNA. Mol Cell 2004;14:787–99.

Bartel B, Bartel DP. MicroRNAs: at the root of plant development. Plant Physiol 2003;132:709–17.

Rajewsky N. MicroNA target predictions in animals. Nat Genet 2006;38:S8–13.

Vella MC, Choi EY, Lin SY, Reinert K, Slack FJ. The C. elegans microRNA let-7 binds to imperfect let-7 complementary sites from the lin-41 3’UTR. Genes Dev 2004;18:132–7.



How to Cite

Tufchi, N., K. Pant, B. Pant, and S. M. Waheed. “IN SILICO PREDICTION AND VALIDATION OF MICRORNAS FROM JAPANESE ENCEPHALITIS VIRUS (JEV)”. International Journal of Pharmacy and Pharmaceutical Sciences, vol. 7, no. 6, June 2015, pp. 333-6,



Original Article(s)