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Genes can be silenced with short-interfering RNA molecules (siRNA). siRNAs are widely used to identify gene functions and have high potential for therapeutic treatments. It is critical that the siRNA specifically targets the expression of the gene of interest but has no off-target effects on other genes. Although siRNAs were initially considered to be exclusively active on mature mRNAs in the cytoplasm, additional studies have shown that siRNAs are present in the nucleus as well, suggesting that pre-mRNA sequences containing introns and other untranslated regions can also be targeted. In this study, we investigated the extent to which off-targets may occur in Drosophila melanogaster by looking at mature mRNA sequences and pre-mature RNA sequences separately. First, an in silico approach revealed that, based on sequence similarity, numerous off-targets are predicted to occur in RNAi experiments. Second, existing microarray data were used to investigate a possible effect of the predicted off-targets based on analysis of in vitro data. We found that the occurrence of off-targets in both mature and pre-mature RNA sequences in RNAi experiments can be extensive and significant. Possibilities are discussed how to minimize off-target effects.

Background: RNAi technology is widely used to downregulate specific gene products. Investigating the phenotype induced by downregulation of gene products provides essential information about the function of the specific gene of interest. When RNAi is applied in Drosophila melanogaster or Caenorhabditis elegans, often large dsRNAs are used. One of the drawbacks of RNAi technology is that unwanted gene products with sequence similarity to the gene of interest can be down regulated too. To verify the outcome of an RNAi experiment and to avoid these unwanted off-target effects, an additional non-overlapping dsRNA can be used to down-regulate the same gene. However it has never been tested whether this approach is sufficient to reduce the risk of off-targets.Methodology: We created a novel tool to analyse the occurance of off-target effects in Drosophila and we analyzed 99 randomly chosen genes.Principal Findings: Here we show that nearly all genes contain non-overlapping internal sequences that do show overlap in a common off-target gene.Conclusion: Based on our in silico findings, off-target effects should not be ignored and our presented on-line tool enables the identification of two RNA interference constructs, free of overlapping off-targets, from any gene of interest.

The study of human microRNAs is seriously hampered by the lack of proper tools allowing genome-wide identification of miRNA targets. We performed Ribonucleoprotein ImmunoPrecipitation-gene Chip (RIP-Chip) using antibodies against wild-type human Ago2 in untreated Hodgkin lymphoma (HL) cell lines. Ten to thirty percent of the gene transcripts from the genome were enriched in the Ago2-IP fraction of untreated cells, representing the HL miRNA-targetome. In silico analysis indicated that similar to 40% of these gene transcripts represent targets of the abundantly co-expressed miRNAs. To identify targets of miR-17/20/93/106, RIP-Chip with anti-miR-17/20/93/106 treated cells was performed and 1189 gene transcripts were identified. These genes were analyzed for miR-17/20/93/106 target sites in the 5'-UTRs, coding regions and 3'-UTRs. Fifty-one percent of them had miR-17/20/93/106 target sites in the 3'-UTR while 19% of them were predicted miR-17/20/93/106 targets by TargetScan. Luciferase reporter assay confirmed targeting of miR-17/20/93/106 to the 3'-UTRs of 8 out of 10 genes. In conclusion, we report a method which can establish the miRNA-targetome in untreated human cells and identify miRNA specific targets in a high throughput manner. This approach is applicable to identify miRNA targets in any human tissue sample or purified cell population in an unbiased and physiologically relevant manner.