RNA interference (RNAi) is a powerful gene knockdown technique used for study gene function. It also potentially provides effective agents for inhibiting infectious and genetic diseases. Most of RNAi studies employ a single siRNA designing program and then require large-scale screening experiments to identify functional siRNAs. In this study, we demonstrate that an assembly of results generated from different siRNA designing programs could provide clusters of predicting sites that aided selection of potent siRNAs. Based on the clusters, three siRNA target sites were selected on a conserved RNA region of hepatitis B virus (HBV), known as HBV post-transcriptional regulatory element (HBV PRE) at nucleotide positions 1317-1337, 1357-1377 and 1644-1664. All three chosen siRNAs driven by H1 promoter were highly effective and could drastically decrease expression of HBV transcripts (core, surface and X) and surface protein without induction of interferon response and cell cytotoxicity in liver cancer cell line (HepG2). Based on prediction of secondary structures, the silencing effects of siRNAs were less effective against a loop sequence of the mRNA target with hairpin structure. In summary, we demonstrate an effectual approach for identification of functional siRNAs. Moreover, highly potent siRNAs identified here may serve as novel agents for development of nucleic acid-based HBV therapy.
Keywords: Effective siRNAs; HBV PRE; Hepatitis B virus; RNA interference; siRNA predicting program.
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