Abstract
Among the members of single-stranded and double-stranded DNA and RNA viruses, those belonging to the family of plant genomes, cause various diseases in cereals and other economically important plants and also considered asa major constraint in agricultural production across the globe. These viruses are counter acted by plant defence mechanism through RNAi. There have been increasing interests in the use of siRNA as a tool for conferring resistance against plant-infecting viruses by silencing the target genes in a sequence specific manner. In this study, highly cited bioinformatics tools viz., siRNA Target Finder, Genscript, siDESIGNCenter, siRNA-wizard and siRNA Selection Server, combined with different algorithms namely Tuschl, Reynolds, Ui-Tei and their combinations were used to screen and design putative siRNAs against the genes of five different plant viruses. BLAST was performed to confirm that the designed siRNAs do not have any homology to other plants. In the present study, 18 most promising siRNAs were identified computationally based on GC%, thermodynamic properties and secondary structures having high potential of targeted gene silencing and will be useful for chemical synthesis. This study also reveals that above 70% efficient siRNAs were obtained with bioinformatics tools using machine learning techniques.
