Abstract
AbstractRNAi has become an important tool to silence gene expression in a variety of organisms, in particular when classical genetic methods are missing. However, application of this method in functional studies has raised new challenges in the design of RNAi reagents in order to minimize false positive and false negative results. Since the performance of reagents can be rarely validated on a genome-wide scale, improved computational methods are required that consider experimentally derived design parameters. Here, we describe computational methods for the design of RNAi reagents for invertebrate model organisms and human disease vectors, such as Anopheles. We describe procedures on how to design short and long double-stranded RNAs for single genes, and evaluate their predicted specificity and efficiency. Using a bioinformatics pipeline we also describe how to design a genome-wide RNAi library for Anopheles gambiae.
Highlights
RNA interference (RNAi) screens have become an important tool for the identification and characterization of gene function on a large-scale
RNAi is a post-transcriptional gene silencing mechanism conserved from plants to mammals and relies on the delivery of exogenous short double-stranded RNAs that trigger the degradation of homologous mRNAs in cells [3, 4]
The crucial observation that each RNA-induced silencing complex (RISC) complex contains only one of the two strands of an short-interfering RNA (siRNA) duplex [14], and that only the antisense strand of an siRNA can direct the cleavage of the sense mRNA target has provided important insights into the biochemical mechanism of RNAi-mediated gene silencing [15,16,17,18,19,20]
Summary
RNAi has become an important tool to silence gene expression in a variety of organisms, in particular when classical genetic methods are missing. Application of this method in functional studies has raised new challenges in the design RNAi reagents in order to minimize false positive and false negative results. Since the performance of reagents can be rarely validated on a genome-wide scale, improved computational methods are required that consider experimentally derived design parameters. We describe computational methods for the design of RNAi reagents for invertebrate model organisms and human disease vectors, such as Anopheles. Using a bioinformatics pipeline we describe how to design a genome-wide RNAi library for Anopheles gambiae
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