Abstract
BackgroundRNA interference (RNAi) is commonly applied in genome-scale gene functional screens. However, a one-on-one RNAi analysis that targets each gene is cost-ineffective and laborious. Previous studies have indicated that siRNAs can also affect RNAs that are near-perfectly complementary, and this phenomenon has been termed an off-target effect. This phenomenon implies that it is possible to silence several genes simultaneously with a carefully designed siRNA.ResultsWe propose a strategy that is combined with a heuristic algorithm to design suitable siRNAs that can target multiple genes and a group testing method that would reduce the number of required RNAi experiments in a large-scale RNAi analysis. To verify the efficacy of our strategy, we used the Orchid expressed sequence tag data as a case study to screen the putative transcription factors that are involved in plant disease responses. According to our computation, 94 qualified siRNAs were sufficient to examine all of the predicated 229 transcription factors. In addition, among the 94 computer-designed siRNAs, an siRNA that targets both TF15 (a previously identified transcription factor that is involved in the plant disease-response pathway) and TF21 was introduced into orchids. The experimental results showed that this siRNA can simultaneously silence TF15 and TF21, and application of our strategy successfully confirmed that TF15 is involved in plant defense responses. Interestingly, our second-round analysis, which used an siRNA specific to TF21, indicated that TF21 is a previously unidentified transcription factor that is related to plant defense responses.ConclusionsOur computational results showed that it is possible to screen all genes with fewer experiments than would be required for the traditional one-on-one RNAi screening. We also verified that our strategy is capable of identifying genes that are involved in a specific phenotype.
Highlights
RNA interference (RNAi) is commonly applied in genome-scale gene functional screens
Even when one-on-one RNAi experiments are feasible in model organisms, it is still laborious and costly because more than ten thousand coding and non-coding genes are typically found in an organism
Our strategy utilizes a heuristic algorithm to design siRNAs that have multiple target genes and uses group testing methods [33] to minimize the RNAi analysis for identifying genes that are involved in a specific phenotype
Summary
RNA interference (RNAi) is commonly applied in genome-scale gene functional screens. a one-on-one RNAi analysis that targets each gene is cost-ineffective and laborious. Previous studies have indicated that siRNAs can affect RNAs that are near-perfectly complementary, and this phenomenon has been termed an off-target effect This phenomenon implies that it is possible to silence several genes simultaneously with a carefully designed siRNA. The primary goals of these applications are usually related to the screening of a single gene or multiple genes that convey(s) a specific phenotype In these applications, each dsRNA is designed to target one specific gene and to facilitate the observation of the resulting phenotype change. Each dsRNA is designed to target one specific gene and to facilitate the observation of the resulting phenotype change This one-on-one approach works very well for model organisms, because whole genome RNAi libraries are available for these model organisms [21,22,23]. Using a vector carrying multiple shRNAs/multi-miRNA hairpins can be applied to silence multiple genes simultaneously (“combinatorial RNAi”) [26,27] and can reduce the required experiments for highthroughput analysis, these approaches still need to design and synthesize as many siRNAs as the number of target gene sets
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