Marshall Wallace F
Department of Biochemistry and Biophysics, Integrative Program in Quantitative Biology, University of California San Francisco, San Francisco, California, United States of America.
PLoS Comput Biol. 2008 Sep 19;4(9):e1000183. doi: 10.1371/journal.pcbi.1000183.
An important application of the RNA interference (RNAi) pathway is its use as a small RNA-based regulatory system commonly exploited to suppress expression of target genes to test their function in vivo. In several published experiments, RNAi has been used to inactivate components of the RNAi pathway itself, a procedure termed recursive RNAi in this report. The theoretical basis of recursive RNAi is unclear since the procedure could potentially be self-defeating, and in practice the effectiveness of recursive RNAi in published experiments is highly variable. A mathematical model for recursive RNAi was developed and used to investigate the range of conditions under which the procedure should be effective. The model predicts that the effectiveness of recursive RNAi is strongly dependent on the efficacy of RNAi at knocking down target gene expression. This efficacy is known to vary highly between different cell types, and comparison of the model predictions to published experimental data suggests that variation in RNAi efficacy may be the main cause of discrepancies between published recursive RNAi experiments in different organisms. The model suggests potential ways to optimize the effectiveness of recursive RNAi both for screening of RNAi components as well as for improved temporal control of gene expression in switch off-switch on experiments.
RNA干扰(RNAi)途径的一个重要应用是作为一种基于小RNA的调控系统,通常用于抑制靶基因的表达,以在体内测试其功能。在一些已发表的实验中,RNAi已被用于使RNAi途径本身的成分失活,本报告中将此过程称为递归RNAi。递归RNAi的理论基础尚不清楚,因为该过程可能会适得其反,而且在实际操作中,已发表实验中递归RNAi的有效性差异很大。我们开发了一个递归RNAi的数学模型,并用于研究该过程应该有效的条件范围。该模型预测,递归RNAi的有效性强烈依赖于RNAi敲低靶基因表达的效力。已知这种效力在不同细胞类型之间差异很大,将模型预测与已发表的实验数据进行比较表明,RNAi效力的差异可能是不同生物体中已发表的递归RNAi实验之间差异的主要原因。该模型提出了一些潜在方法,可优化递归RNAi的有效性,用于筛选RNAi成分以及在关闭-开启实验中改善基因表达的时间控制。