An accurate and interpretable model for siRNA efficacy prediction

Background  

The use of exogenous small interfering RNAs (siRNAs) for gene silencing has quickly become a widespread molecular tool providing a powerful means for gene functional study and new drug target identification. Although considerable progress has been made recently in understanding how the RNAi pathway mediates gene silencing, the design of potent siRNAs remains challenging.     

A plasmid-based system for expressing small interfering RNA libraries in mammalian cells

Background  

RNA interference (RNAi) is an evolutionarily conserved process that functions to inhibit gene expression. The use of RNAi in mammals as a tool to study gene function has rapidly developed in the last couple of years since the discovery that the function-inhibiting units of RNAi are short 21–25 nt double-stranded RNAs (siRNAs) derived from their longer template. The use of siRNAs allows for gene-specific knock-down without induction of the non-specific interferon response in mammalian cells. Multiple systems have been developed to introduce siRNAs into mammals. One of the most appealing of these techniques is the use of vectors containing polymerase III promoters to drive expression of hairpin siRNAs. However, there are multiple limitations to using hairpin siRNA vectors including the observation that some are unstable in bacteria and are difficult to sequence.     

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.     

Designing of highly effective complementary and mismatch siRNAs for silencing a gene

In past, numerous methods have been developed for predicting efficacy of short interfering RNA (siRNA). However these methods have been developed for predicting efficacy of fully complementary siRNA against a gene. Best of author's knowledge no method has been developed for predicting efficacy of mismatch siRNA against a gene. In this study, a systematic attempt has been made to identify highly effective complementary as well as mismatch siRNAs for silencing a gene.Support vector machine (SVM) based models have been developed for predicting efficacy of siRNAs using composition, binary and hybrid pattern siRNAs. We achieved maximum correlation 0.67 between predicted and actual efficacy of siRNAs using hybrid model. All models were trained and tested on a dataset of 2182 siRNAs and performance was evaluated using five-fold cross validation techniques. The performance of our method desiRm is comparable to other well-known methods. In this study, first time attempt has been made to design mutant siRNAs (mismatch siRNAs). In this approach we mutated a given siRNA on all possible sites/positions with all possible nucleotides. Efficacy of each mutated siRNA is predicted using our method desiRm. It is well known from literature that mismatches between siRNA and target affects the silencing efficacy. Thus we have incorporated the rules derived from base mismatches experimental data to find out over all efficacy of mutated or mismatch siRNAs. Finally we developed a webserver, desiRm (http://www.imtech.res.in/raghava/desirm/) for designing highly effective siRNA for silencing a gene. This tool will be helpful to design siRNA to degrade disease isoform of heterozygous single nucleotide polymorphism gene without depleting the wild type protein.     

Identification of sequence features that predict competition potency of siRNAs

Small interfering RNAs (siRNAs) specifically knock-down target mRNAs via RNA interference (RNAi) mechanism. During this process, introduction of excess amount of exogenous siRNAs could lead to the saturation of cellular RNAi machinery. One consequence of RNAi machinery saturation is the competition between two simultaneously introduced siRNAs, during which one siRNA loses gene silencing activity. Although competition phenomena have been well characterized, the molecular and sequence features of siRNAs that specify the competition potency remain poorly understood. Here, for the first time, we performed a large-scale siRNA competition potency analysis by measuring the competition potency of 56 different siRNAs and ranking them based on their competition potency. We have also established an algorithm to predict the competition potency of siRNAs based upon the conserved sequence features of strong and weak competitor siRNAs. The present study supports our hypothesis that the competition potency of siRNAs is specified by the 5′-half antisense sequence and provides a useful guideline to design siRNAs with minimal RNAi machinery saturation.     

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.     

A study on the fundamental factors determining the efficacy of siRNAs with high C/G contents

Although there are many reports about the efficacy of siRNAs, it is not clear whether those siRNAs with high C/G contents can be used to silence their target mRNAs efficiently. In this study, we investigated the structure and function of a group of siRNAs with high C/G contents. The results showed that single siRNAs against the Calpain, Otoferlin and Her2 mRNAs could induce different silencing effects on their targets, suggesting that the accessibility to target sequences influences the efficacy of siRNA. Unexpectedly, a single siRNA could target its cognate sequence in the 3’UTR of EEF1D or the 5’UTR of hTRF2 or CDC6. Their interaction induced different modes of gene silencing. Furthermore, the introduction of mutations into the 3’ end of the passenger strand showed that the position and number of mutated nucleotides could exert some influence on the efficacy of siRNA. However, these mutations did not completely block the passenger strand from exerting its RNAi effect. Interestingly, our findings also indicated that the target mRNA might play essential roles in maintaining or discarding the guide strand in RISCs. Thus, the conclusion could be drawn that favorable siRNA sequences, accessible target structures and the fast cleavage mode are necessary and sufficient prerequisites for efficient RNAi.     

The impact of target site accessibility on the design of effective siRNAs

Small-interfering RNAs (siRNAs) assemble into RISC, the RNA-induced silencing complex, which cleaves complementary mRNAs. Despite their fluctuating efficacy, siRNAs are widely used to assess gene function. Although this limitation could be ascribed, in part, to variations in the assembly and activation of RISC, downstream events in the RNA interference (RNAi) pathway, such as target site accessibility, have so far not been investigated extensively. In this study we present a comprehensive analysis of target RNA structure effects on RNAi by computing the accessibility of the target site for interaction with the siRNA. Based on our observations, we developed a novel siRNA design tool, RNAxs, by combining known siRNA functionality criteria with target site accessibility. We calibrated our method on two data sets comprising 573 siRNAs for 38 genes, and tested it on an independent set of 360 siRNAs targeting four additional genes. Overall, RNAxs proves to be a robust siRNA selection tool that substantially improves the prediction of highly efficient siRNAs.     

Variations of the 3' protruding ends in synthetic short interfering RNA (siRNA) tested by microinjection in Drosophila embryos

Short interfering RNAs (siRNAs) are the processing product originating from long double-stranded RNAs (dsRNAs) that are cleaved by the RNase III-like ribonuclease Dicer. As siRNAs mediate cleavage of specific single-stranded target RNAs, they are essential intermediates of RNA interference (RNAi). When applied in synthetic form, siRNAs likewise can induce the silencing process in the absence of long dsRNAs. Here, we tested variations of a conventional synthetic siRNA that had been used successfully to silence the Drosophila notch gene. The variants had two 3 ' -terminal deoxynucleotides in their protruding single-stranded ends. In one case, the deoxynulceotides would match to the notch mRNA, whereas the other variant had nonmatching deoxy-T residues, representing a widely used siRNA design. siRNAs with different combinations of sense and antisense strands were injected into Drosophila embryos at two different concentrations. We found that the all-ribonucleotide siRNA gave the best inhibition of notch expression. The combination of two modified strands with 3 ' -terminal deoxynucleotides was effective, but if combined with a sense or antisense ribostrand, the efficacy dropped. The siRNAs with nonmatching 3 ' -terminal TT residues showed a reduced silencing potential, which became evident at low concentration. An siRNA with a nonmatching 3 ' -terminal ribonucleotide in the antisense strand retained most of its silencing potential in accordance with the hypothesis that primer extension for generation of ssRNA from single-stranded mRNA does not operate in Drosophila.     

Focusing on RISC assembly in mammalian cells

RISC (RNA-induced silencing complex) is a central protein complex in RNAi, into which a siRNA strand is assembled to become effective in gene silencing. By using an in vitro RNAi reaction based on Drosophila embryo extract, an asymmetric model was recently proposed for RISC assembly of siRNA strands, suggesting that the strand that is more loosely paired at its 5′ end is selectively assembled into RISC and results in target gene silencing. However, in the present study, we were unable to establish such a correlation in cell-based RNAi assays, as well as in large-scale RNAi data analyses. This suggests that the thermodynamic stability of siRNA is not a major determinant of gene silencing in mammalian cells. Further studies on fork siRNAs showed that mismatch at the 5′ end of the siRNA sense strand decreased RISC assembly of the antisense strand, but surprisingly did not increase RISC assembly of the sense strand. More interestingly, measurements of melting temperature showed that the terminal stability of fork siRNAs correlated with the positions of the mismatches, but not gene silencing efficacy. In summary, our data demonstrate that there is no definite correlation between siRNA stability and gene silencing in mammalian cells, which suggests that instead of thermodynamic stability, other features of the siRNA duplex contribute to RISC assembly in RNAi.     

Potent RNAi by short RNA triggers

RNA interference (RNAi) is a gene-silencing mechanism by which a ribonucleoprotein complex, the RNA-induced silencing complex (RISC) and a double-stranded (ds) short-interfering RNA (siRNA), targets a complementary mRNA for site-specific cleavage and subsequent degradation. While longer dsRNA are endogenously processed into 21- to 24-nucleotide (nt) siRNAs or miRNAs to induce gene silencing, RNAi studies in human cells typically use synthetic 19- to 20-nt siRNA duplexes with 2-nt overhangs at the 3′-end of both strands. Here, we report that systematic synthesis and analysis of siRNAs with deletions at the passenger and/or guide strand revealed a short RNAi trigger, 16-nt siRNA, which induces potent RNAi in human cells. Our results indicate that the minimal requirement for dsRNA to trigger RNAi is an ~42 Å A-form helix with ~1.5 helical turns. The 16-nt siRNA more effectively knocked down mRNA and protein levels than 19-nt siRNA when targeting the endogenous CDK9 gene, suggesting that 16-nt siRNA is a more potent RNAi trigger. In vitro kinetic analysis of RNA-induced silencing complex (RISC) programmed in HeLa cells indicates that 16-nt siRNA has a higher RISC-loading capacity than 19-nt siRNA. These results suggest that RISC assembly and activation during RNAi does not necessarily require a 19-nt duplex siRNA and that 16-nt duplexes can be designed as more potent triggers to induce RNAi.