siRNA脱靶效应研究进展

RNA干扰过程中,siRNA和mRNA特异结合能够使得靶基因沉默。但研究证实,siRNA可能与非靶基因结合而导致非靶基因沉默,这种现象称为siRNA脱靶效应。多种真核生物中的RNA干扰实验证实了脱靶效应的存在。对脱靶机制的研究发现脱靶可能与模体匹配、结构和长dsRNA等有关,很多新方法被提出来预测脱靶概率和检测脱靶基因。通过利用siRNApool、化学修饰和生物信息学方法能够尽可能地降低脱靶效应,提高RNAi实验的质量。对脱靶效应方面的研究进行了总结论述。     

Whole-Genome Thermodynamic Analysis Reduces siRNA Off-Target Effects

Small interfering RNAs (siRNAs) are important tools for knocking down targeted genes, and have been widely applied to biological and biomedical research. To design siRNAs, two important aspects must be considered: the potency in knocking down target genes and the off-target effect on any nontarget genes. Although many studies have produced useful tools to design potent siRNAs, off-target prevention has mostly been delegated to sequence-level alignment tools such as BLAST. We hypothesize that whole-genome thermodynamic analysis can identify potential off-targets with higher precision and help us avoid siRNAs that may have strong off-target effects. To validate this hypothesis, two siRNA sets were designed to target three human genes IDH1, ITPR2 and TRIM28. They were selected from the output of two popular siRNA design tools, siDirect and siDesign. Both siRNA design tools have incorporated sequence-level screening to avoid off-targets, thus their output is believed to be optimal. However, one of the sets we tested has off-target genes predicted by Picky, a whole-genome thermodynamic analysis tool. Picky can identify off-target genes that may hybridize to a siRNA within a user-specified melting temperature range. Our experiments validated that some off-target genes predicted by Picky can indeed be inhibited by siRNAs. Similar experiments were performed using commercially available siRNAs and a few off-target genes were also found to be inhibited as predicted by Picky. In summary, we demonstrate that whole-genome thermodynamic analysis can identify off-target genes that are missed in sequence-level screening. Because Picky prediction is deterministic according to thermodynamics, if a siRNA candidate has no Picky predicted off-targets, it is unlikely to cause off-target effects. Therefore, we recommend including Picky as an additional screening step in siRNA design.     

siSPOTR: a tool for designing highly specific and potent siRNAs for human and mouse

RNA interference (RNAi) serves as a powerful and widely used gene silencing tool for basic biological research and is being developed as a therapeutic avenue to suppress disease-causing genes. However, the specificity and safety of RNAi strategies remains under scrutiny because small inhibitory RNAs (siRNAs) induce off-target silencing. Currently, the tools available for designing siRNAs are biased toward efficacy as opposed to specificity. Prior work from our laboratory and others’ supports the potential to design highly specific siRNAs by limiting the promiscuity of their seed sequences (positions 2–8 of the small RNA), the primary determinant of off-targeting. Here, a bioinformatic approach to predict off-targeting potentials was established using publically available siRNA data from more than 50 microarray experiments. With this, we developed a specificity-focused siRNA design algorithm and accompanying online tool which, upon validation, identifies candidate sequences with minimal off-targeting potentials and potent silencing capacities. This tool offers researchers unique functionality and output compared with currently available siRNA design programs. Furthermore, this approach can greatly improve genome-wide RNAi libraries and, most notably, provides the only broadly applicable means to limit off-targeting from RNAi expression vectors.     

Forward and robust selection of the most potent and noncellular toxic siRNAs from RNAi libraries

Use of highly potent small interfering RNAs (siRNAs) can substantially reduce dose-dependent cytotoxic and off-target effects. We developed a genetic forward approach by fusing the cytosine deaminase gene with targets for the robust identification of highly potent siRNAs from RNA interference (RNAi) libraries that were directly delivered into cells via bacterial invasion. We demonstrated that two simple drug selection cycles performed conveniently in a single container predominately enriched two siRNAs targeting the MVP gene (siMVP) and one siRNA targeting the egfp gene (siEGFP) in surviving cells and these proved to be the most effective siRNAs reported. Furthermore, the potent siRNAs isolated from the surviving cells possessed noncellular toxic characteristics. Interestingly, the length of highly potent siMVPs identified could be as short as 16-mer, and increasing the length of their native sequences dramatically reduced RNAi potency. These results suggest that the current approach can robustly discover the most potent and nontoxic siRNAs in the surviving cells, and thus has great potential in facilitating RNAi applications by minimizing the dose-dependent and sequence nonspecific side effects of siRNAs.     

RNAi Experiments in D. melanogaster: Solutions to the Overlooked Problem of Off-Targets Shared by Independent dsRNAs

Background

RNAi technology is widely used to downregulate specific gene products. Investigating the phenotype induced by downregulation of gene products provides essential information about the function of the specific gene of interest. When RNAi is applied in Drosophila melanogaster or Caenorhabditis elegans, often large dsRNAs are used. One of the drawbacks of RNAi technology is that unwanted gene products with sequence similarity to the gene of interest can be down regulated too. To verify the outcome of an RNAi experiment and to avoid these unwanted off-target effects, an additional non-overlapping dsRNA can be used to down-regulate the same gene. However it has never been tested whether this approach is sufficient to reduce the risk of off-targets.

Methodology

We created a novel tool to analyse the occurance of off-target effects in Drosophila and we analyzed 99 randomly chosen genes.

Principal Findings

Here we show that nearly all genes contain non-overlapping internal sequences that do show overlap in a common off-target gene.

Conclusion

Based on our in silico findings, off-target effects should not be ignored and our presented on-line tool enables the identification of two RNA interference constructs, free of overlapping off-targets, from any gene of interest.     

Off-target effects by siRNA can induce toxic phenotype

Although recent microarray studies have provided evidence of RNA interference (RNAi)-mediated off-target gene modulation, little is known about whether these changes induce observable phenotypic outcomes. Here we show that a fraction of randomly selected small inhibitory RNAs (siRNAs) can induce changes in cell viability in a target-independent fashion. The observed toxicity requires an intact RNAi pathway and can be eliminated by the addition of chemical modifications that reduce off-target effects. Furthermore, an analysis of toxic and nontoxic duplexes identifies a strong correlation between the toxicity and the presence of a 4-base-pair motif (UGGC) in the RISC-entering strand of toxic siRNA. This article provides further evidence of siRNA-induced off-target effects generating a measurable phenotype and also provides an example of how such undesirable phenotypes can be mitigated by addition of chemical modifications to the siRNA.     

Common seed analysis to identify off-target effects in siRNA screens

Genome-scale small interfering RNA (siRNA) screens have become an increasingly popular approach to new target identification and pathway elucidation. However, the large data sets generated from siRNA screens have demonstrated high false-positive rates and the requirement for extensive experimental triage to distinguish true hits. A number of groups have independently reported the presence of siRNAs with identical seed sequences among their top screening hits. Based on these observations, we have developed a comprehensive technique for detecting and visualizing seed-based off-target effects in siRNA screening data. This is accomplished by analyzing the behavior of siRNAs that share identical seed sequences, which we refer to as common seed analysis (CSA). By applying these techniques to primary screening data of the Wnt pathway, we identify 158 distinct seed sequences that have a statistically significant effect on the assay. The promiscuous seed sequences identified in this manner can then be discounted in the analysis of follow-up experiments using single siRNAs. The ability to detect off-target effects when sufficient numbers of siRNAs share a common seed has significant implications for the design of siRNA screening experiments, data analysis, hit selection, and library design.     

Properties of short double-stranded RNAs carrying randomized base pairs: toward better controls for RNAi experiments

Short interfering RNAs (siRNAs) are mediators of RNA interference (RNAi), a commonly used technique for selective down-regulation of target gene expression. Using an equimolar mixture of A, G, C, and U phosphoramidites during solid-phase synthesis, we introduced degenerate positions into RNA guide and passenger strands so that, when annealed, a large pool of distinct siRNA duplexes with randomized base pairs at defined sites was created. We assessed the randomization efficiency by deep sequencing one of the RNAs. All possible individual sequences were present in the pool with generally an excellent distribution of bases. Melting temperature analyses suggested that pools of randomized guide and passenger strands RNAs with up to eight degenerate positions annealed so that mismatched base-pairing was minimized. Transfections of randomized siRNAs (rnd-siRNAs) into cells led to inhibition of luciferase reporters by a miRNA-like mechanism when the seed regions of rnd-siRNA guide strands were devoid of degenerate positions. Furthermore, the mRNA levels of a select set of genes associated with siRNA off-target effects were measured and indicated that rnd-siRNAs with degenerate positions in the seed likely show typical non-sequence-specific effects, but not miRNA-like off-target effects. In the wake of recent reports showing the preponderance of miRNA-like off-target effects of siRNAs, our findings are of value for the design of a novel class of easily prepared and universally applicable negative siRNA controls.     

In Silico Target-Specific siRNA Design Based on Domain Transfer in Heterogeneous Data

RNA interference via exogenous small interference RNAs (siRNA) is a powerful tool in gene function study and disease treatment. Designing efficient and specific siRNA on target gene remains the key issue in RNAi. Although various in silico models have been proposed for rational siRNA design, most of them focus on the efficiencies of selected siRNAs, while limited effort has been made to improve their specificities targeted on specific mRNAs, which is related to reducing off-target effects (OTEs) in RNAi. In our study, we propose for the first time that the enhancement of target specificity of siRNA design can be achieved computationally by domain transfer in heterogeneous data sources from different siRNA targets. A transfer learning based method i.e., heterogeneous regression (HEGS) is presented for target-specific siRNA efficacy modeling and feature selection. Based on the model, (1) the target regression model can be built by extracting information from related data in other targets/experiments, thus increasing the target specificity in siRNA design with the help of information from siRNAs binding to other homologous genes, and (2) the potential features correlated to the current siRNA design can be identified even when there is lack of experimental validated siRNA affinity data on this target. In summary, our findings present useful instructions for a better target-specific siRNA design, with potential applications in genome-wide high-throughput screening of effective siRNA, and will provide further insights on the mechanism of RNAi.