A Computational Approach of Rice (Oryza Sativa) Plant miRNA Target Prediction against Tungro Virus

Abstract

Viruses attack plants many times, as they are exposed to open environment. Rice tungro disease is one of the destructive diseases of rice in south and south-east Asia which causes on average about 2% losses in rice production in India. During evolution, plants have its own mechanism to withstand against viral epidemics. Current research findings show that microRNA (miRNA) plays vital role in plant defence against virus. miRNA are single stranded Ribonucleic acid (RNA) molecules of around 22 nucleotides long non-coding RNA. These small RNA regulates post-transcriptional expression by directly cleaving targeted (Messenger RNA) mRNAs. As viruses exploit the plants nucleic acids as the first infection strategy, miRNA approach can act as best defence system against viruses. In this paper, computational approach have been proposed to explore the possibility of endogenous rice plant miRNAs having role in antiviral defence by targeting the mRNA of different genes of rice plant infecting tungro viruses of both Rice Tungro Spherical Virus (RTSV) and Rice Tungro Baciliform Virus (RTBV). From miRBase database 581 numbers of miRNA sequences have been selected and target against rice tungro viruses genes like coat proteins, poly-protein of RTSV and ORF1, ORF2, ORF3, P12, P24, P46 and P194 of RTBV considered for simulation. The miRNAs targeted in our approach has been validated by comparing with the web based sever psRNATarget. The results are highly supported that rice miRNAs can be able to resist against tungro viruses which is helpful to elucidate new biotechnological manipulation for rice production.