On the art of identifying effective and specific siRNAs

Howard Hughes Medical Institute, Laboratory of RNA Molecular Biology, The Rockefeller University, 1230 York Avenue, Box 186, New York, New York 10021, USA.
Nature Methods (Impact Factor: 32.07). 10/2006; 3(9):670-6. DOI: 10.1038/nmeth911
Source: PubMed


Small interfering RNAs (siRNAs) have been widely exploited for sequence-specific gene knockdown, predominantly to investigate gene function in cultured vertebrate cells, and also hold promise as therapeutic agents. Because not all siRNAs that are cognate to a given target mRNA are equally effective, computational tools have been developed based on experimental data to increase the likelihood of selecting effective siRNAs. Furthermore, because target-complementary siRNAs can also target other mRNAs containing sequence segments that are partially complementary to the siRNA, most computational tools include ways to reduce potential off-target effects in the siRNA selection process. Though these methods facilitate selection of functional siRNAs, they do not yet alleviate the need for experimental validation. This perspective provides a practical guide based on current wisdom for selecting siRNAs.

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Available from: Yi Pei, Jan 06, 2015
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    • "The results of these studies have shown that a high GC content may be a negative determinant of the functionality of a siRNA as it may inhibit the dissociation of the duplex impairing RISC loading. On the other hand, low GC content is associated with a decrease in potency, presumably due to decreased target affinity and specificity (Pei and Tuschl, 2006). Recent studies have shown that siRNA sequences with a GC content in the range of 25-55 % have an increased potency (Liu et al., 2012). "
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    • "This is just like finding a needle in husk . In silico approach by bioinformatics software and algorithms are available to predict effective siRNA based on common features with limitations over in vitro approach ( Pei & Tuschl , 2006 ; Reynolds et al . , 2004 ) . "
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    • "The success of RNAi experiments critically depends on the expression levels of shRNAs or siRNAs, respectively. Too low expression levels may result in difficult-to-interpret hypomorphic phenotypes, while too high levels can interfere with the processing of endogenous small non coding RNAs, such as miRNAs [31], and increase the chance of off-target effects. Off-target effects are caused by sufficient similarities between the siRNA sequences (of both the sense and antisense strand) and cellular mRNAs other than the target molecule [31], [32]. "
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