Department of Computer Science, National Tsing Hua University, Hsinchu, Taiwan.
BMC Genomics. 2012 Sep 18;13:491. doi: 10.1186/1471-2164-13-491.
RNA 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.
We 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.
Our 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.
RNA 干扰（RNAi）常用于全基因组规模的基因功能筛选。然而，针对每个基因的一对一 RNAi 分析既昂贵又费力。先前的研究表明，siRNA 也可以影响与其近乎完全互补的 RNA，这种现象被称为脱靶效应。这种现象意味着可以用精心设计的 siRNA 同时沉默几个基因。
我们提出了一种策略，该策略结合启发式算法设计合适的 siRNA，可以靶向多个基因，以及一种群体测试方法，可以减少大规模 RNAi 分析中所需的 RNAi 实验数量。为了验证我们策略的有效性，我们使用兰花表达序列标签数据作为案例研究，筛选参与植物疾病反应的假定转录因子。根据我们的计算，94 个合格的 siRNA 足以检查所有预测的 229 个转录因子。此外，在 94 个计算机设计的 siRNA 中，引入了一个针对 TF15（先前鉴定的参与植物疾病反应途径的转录因子）和 TF21 的 siRNA。实验结果表明，该 siRNA 可以同时沉默 TF15 和 TF21，并且我们的策略成功地证实了 TF15 参与植物防御反应。有趣的是，我们使用针对 TF21 的特异性 siRNA 进行的第二轮分析表明，TF21 是一个先前未被识别的与植物防御反应相关的转录因子。
我们的计算结果表明，使用较少的实验就可以筛选出所有的基因，而不需要进行传统的一对一 RNAi 筛选。我们还验证了我们的策略能够识别参与特定表型的基因。
