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RNA interference (RNAi) is an evolutionarily conserved mechanism of gene silencing induced by double-stranded RNAs (dsRNAs). Among the widely used dsRNAs, small interfering RNAs (siRNAs) and short hairpin RNAs have evolved as extremely powerful and the most popular gene silencing reagents. The key challenge to achieving efficient gene silencing especially for the purpose of therapeutics is mainly dependent on the effectiveness and specificity of the selected RNAi-targeted sequences. Practically, only a small number of dsRNAs are capable of inducing highly effective and sequence-specific gene silencing via RNAi mechanism. In addition, the efficiency of gene silencing induced by dsRNAs can only be experimentally examined based on inhibition of the target gene expression. Therefore, it is essential to develop a fully robust and comparative validation system for measuring the efficacy of designed dsRNAs. In this chapter, we focus our discussion on a reliable and quantitative reporter-based siRNA validation system that has been previously established in our laboratory. The system consists of a short synthetic DNA fragment containing an RNAi-targeted sequence of interest and two expression vectors for targeting reporter and triggering siRNA expressions. The efficiency of siRNAs is determined by their abilities to inhibit expression of the targeting reporters with easily quantified readouts including enhanced green fluorescence protein and firefly luciferase. Since only a readily available short synthetic DNA fragment is needed for constructing this reliable and efficient reporter-based siRNA validation system, this system not only provides a powerful strategy for screening highly effective RNAi-targeted sequences from mammalian genes but also implicates the use of RNAi-based dsRNA reagents for reverse functional genomics and molecular therapeutics.

methods in molecular biology

Construction of Simple and Efficient siRNA Validation Systems for Screening and Identification of Effective RNAi-Targeted Sequences from Mammalian Genes