ABSTRACT
In recent years, RNAi has developed into a leading technique to assess gene function in eukaryotic cells (Mello and Conte, 2004). RNAi (also called posttranscriptional gene silencing) is a process in which a dsRNA triggers the degradation of a homologous mRNA. A long dsRNA is cleaved by the dsRNA processing enzyme Dicer into small 21-23mers, referred to as siRNA, which are incorporated into the RISC and unwound. When loaded with a singlestrand siRNA, RISC* binds to a complementary sequence on an mRNA molecule and cleaves it between nucleotides 10 and 11 relative to the siRNA (Elbashir et al., 2001b; Yuan et al., 2005). This initiates the degradation of the target mRNA and, therefore, inhibits further gene expression. Mammalian cells have a cellular defense mechanism that, in the presence of dsRNAs (longer than 30 base pairs), provokes a global unspecific repression of gene expression (Sledz and Williams, 2004; Stark et al., 1998). The discovery that small 21mer siRNA, in contrast to longer dsRNA, elicits a very limited unspecific response (Elbashir et al., 2001a) allowed the use of the technology as a tool to assess gene function in mammalian cells. Because of its efficiency and high specificity, RNAi has revolutionized genomics and drug discovery. It has become the technique of choice to perform reverse genetics in organisms where previously genetic manipulation was difficult if not impossible. RNAi is easily scalable to study all genome functions and has proven useful for many applications, including functional annotation of genome data and in vivo target validation. Finally, therapeutic applications of RNAi are currently being studied intensively because of their potential for the development of gene-specific medicine (Huppi et al., 2005; Mittal, 2004). To allow the successful delivery of the RNA duplexes into mammalian cell lines, different strategies have been developed over the last few years, including chemical synthesis (Elbashir et al., 2002), in vitro transcription (Donze and Picard, 2002), or vector-based delivery (Miyagishi et al., 2004).
