QIAGEN Inc.
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Valencia, CA, 91355-1018
Website: http://www.qiagen.com
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Applying RNAi Technology — Opportunities And Pitfalls
by Elizabeth Scanlan and Eric Lader
Figure 1. HP OnGuard siRNA Design includes several bioinformatic steps for avoidance of off-target effects. Click to enlarge. |
The revolution that the discovery of RNA interference (RNAi) has brought to the fields of functional genomics and drug research was marked last year when its discoverers Andrew Z. Fire and Craig C. Mello were awarded the Nobel Prize in Physiology or Medicine. RNAi enables targeted gene knockdown by the introduction into cells of chemically synthesized, double-stranded RNA duplexes of 21-27 bases (short interfering RNA or siRNA). It has been used as an experimental tool for multiple applications, including identification of therapeutic targets and analysis of regulatory pathways, in organisms as diverse as C. elegans and human.
RNAi can be applied to biological questions in low- or high-throughput experimental systems. Low-throughput experiments involve knockdown of a single gene or a small group of genes. These experiments are commonly performed to elucidate or confirm the role of a gene in a pathway or phenotype of interest. In high-throughput analyses, large sets of siRNAs targeting from a few dozen genes to the whole transcriptome are used in RNAi screens. In these screens, transfection of siRNA into cultured cells is followed by an appropriate biochemical, functional, or phenotypic assay, from 12 to 72 hours after transfection. These assays range from simple live/dead assays to those that measure a wide variety of phenotypes, including cell proliferation, apoptosis, morphology, signaling pathways, and subcellular protein localization.
To ensure RNAi experiments are efficient and provide reproducible, biologically relevant results, various factors must be considered and carefully controlled. These include aspects of siRNA design such as bioinformatic controls to minimize off-target effects, optimization of siRNA delivery to maximize knockdown and minimize cytotoxicity, experimental set up to minimize sample-to-sample variability, and proper assay design, including the use of appropriate positive and negative assay controls.
Here we describe the methods used at QIAGEN Inc. (Valencia, CA) to optimize each step of the experimental process, and to thus ensure reliable results.
Optimizing siRNA potency
Figure 2. HeLa cells were reverse transfected in a 384-well plate with a range of concentrations of siRNA targeted against lamin A/C using HiPerFect Transfection Reagent from QIAGEN or Reagent L from another supplier. After 48 hours, gene silencing was assessed by quantitative, real-time RT-PCR. Click to enlarge. |
siRNA design significantly impacts the outcome of an RNA experiment. In addition to influencing the extent of target gene knockdown, siRNA design can also influence the level of off-target effects. An optimally designed siRNA will result in high levels of knockdown when transfected at low concentrations. HP OnGuard siRNA Design is used for siRNA design at QIAGEN (see figure 1). HP OnGuard siRNA Design uses a neural network for siRNA selection.(1) The neural network has been trained using data from thousands of RNAi experiments, ensuring the selection of highly potent siRNAs.
Avoiding off-target effects
Off-target effects are any detectable effects which arise as a result of unintended actions of siRNA or the siRNA transfection process. It is important to avoid off-target effects as they result in unreliable data that could be misinterpreted. One type of off-target effect occurs when siRNAs with partial complementarity to unintended gene targets alter their expression, producing a biological effect that shows up as a 'hit' in an assay. During the HP OnGuard siRNA Design process, potential siRNA designs are evaluated for partial homology to other mRNAs in the transcriptome using an up-to-date, nonredundant sequence database and a proprietary homology analysis tool which is optimized for searches of small regions of complementarity. A 3' UTR/seed region analysis is also performed during this stage of the design process. The seed region comprises 6 nucleotides in positions 2-7 of the antisense siRNA strand of the siRNA duplex. Several studies have shown that off-target effects may be caused by perfect matches of the seed region of the siRNA antisense strand with the 3' untranslated region of unintended mRNA targets combined with limited homology elsewhere in the 21-base target sequence.(2, 3, 4) Partial matches of this particular configuration are more likely to contribute to downregulation of unintended targets due to the siRNA mimicking the action of an miRNA. siRNA designs which show the smallest number of potentially unfavorable matches are selected.
To avoid the possibility of siRNAs inducing an interferon response, siRNAs are also screened for sequence motifs reported to result in such responses in some situations.(5, 6)
siRNA delivery
Efficient delivery of siRNA into cells is critical for the success of RNAi experiments. The transfection method used should effectively deliver low siRNA amounts in a highly biologically accessible formulation, as research has suggested that transfection using low siRNA concentrations is important for the avoidance of off-target effects.(7, 8) It is also important that the transfection reagent or method used is minimally cytotoxic. At QIAGEN, the transfection reagent used for RNAi experiments combines the properties of low cytotoxicity and high transfection efficiency, allowing in some cases successful transfection of as little as 100 pM siRNA (see figure 2 and www.qiagen.com/goto/HiPerFect ).
Redundancy experiments and controls
Figure 3. Multiple negative control siRNAs (Control 1- Control 10) were transfected in triplicate into MCF-7 cells. After incubation, cRNA was prepared and hybridized to Affymetrix human U133 GeneChip arrays. Regulated genes were identified as genes that showed at least a 1.5-fold change in expression compared to untransfected cells. AllStars Negative Control siRNA (indicated with arrow) resulted in the lowest number of regulated genes. In contrast, other control siRNAs resulted in higher numbers of regulated genes from important cellular pathways. Click to enlarge. |
As it is impossible to completely eliminate the risk of off-target effects, it is critical to design RNAi experiments so that spurious results can quickly be discounted.
In recent commentary articles, redundancy experiments have been recommended for this purpose. Redundancy experiments use multiple different silencing reagents, for example, several siRNAs targeting different areas of the same mRNA. The probability of several siRNAs that target different sequences of the same gene causing the same phenotype through off-target interaction with another gene is very low. This makes use of redundancy an easily applied and convincing way to show siRNA specificity and the validity of the relationship between target gene knockdown and resulting phenotype.(9, 10)
While redundancy tackles the problem of sequence-specific off-target effects, it is also important to control for sequence-independent off-target effects. Nonsilencing siRNAs which do not target any genes in the genome under study are the best controls for this purpose. However, it is important to ensure that the nonsilencing siRNA does not itself elicit a sequence-dependent off-target effect. The control siRNA should be validated to ensure that it reflects baseline gene expression and cellular phenotype.(9, 10)
To address the challenge of selecting a 'clean' nonsilencing siRNA, scientists at QIAGEN extensively tested multiple nonsilencing siRNAs and selected AllStars Negative Control siRNA as the siRNA which caused minimal nonspecific effects (see figure 3). Tests performed included genomewide expression profiling using Affymetrix GeneChip arrays (Affyemtrix, Inc., Santa Clara, CA) and a thorough phenotypic analysis. For more information and data for RNAi controls, visit www.qiagen.com/AllStars.
In addition to the nonsilencing control, a positive control siRNA should be routinely transfected in every experiment to ensure optimal conditions are maintained. An ideal positive control is an siRNA which is known to provide high knockdown of a target gene that produces the desired phenotype or assay result. Such an siRNA can be used to test the transfection system and assay to ensure that no faults occur in the experimental setup. The use of a positive control reduces the risk of false negative results arising from problems with siRNA delivery and subsequent assays.
About the authors
Elizabeth Scanlan is Technical and Marketing Writer for RNAi at QIAGEN. She carried out her Ph.D. in the Genetics Department of Trinity College Dublin, Ireland and also holds an M.Sc. in Molecular Genetics from the University of Leicester, UK. Eric Lader is Associate Director for RNAi at QIAGEN. He holds a Ph.D. in Developmental Genetics from Cornell Medical College and has carried out postdoctoral research in the molecular biology of differentiation and development at the NIH and the University of Texas. For the last 10 years, he has worked in technology development in the biotechnology sector.
Further information about RNAi solutions and the topics covered in this article is available at www.qiagen.com/siRNA.
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2. Farh, K.K. et al. The widespread impact of mammalian MicroRNAs on mRNA repression and evolution. Science 310:1817 (2005).
3. Lin, X. et al. siRNA-mediated off-target gene silencing triggered by a 7 nt complementation. Nucleic Acids Res. 33:4527 (2005).
4. Jackson, A.L. et al. Widespread siRNA ''off-target'' transcript silencing mediated by seed region sequence complementarity. RNA 12:1179 (2006).
5. Judge, A.D. et al. Sequence-dependent stimulation of the mammalian innate immune response by synthetic siRNA. Nat Biotechnol. 23:457 (2005).
6. Hornung, V. et al. Sequence-specific potent induction of IFN-alpha by short interfering RNA in plasmacytoid dendritic cells through TLR7. Nat Med. 11:263 (2005).
7. Semizarov, D. et al. Specificity of short-interfering RNA determined through gene expression signatures. Proc. Natl. Acad. Sci. USA 100:6347 (2003).
8. Persengiev, S.P., Zhu, X., and Green, M.R. Nonspecific, concentration-dependent stimulation and repression of mammalian gene expression by small interfering RNAs (siRNAs). RNA 10:12 (2004).
9. Echeverri, C.J. et al. Minimizing the risk of reporting false positives in large-scale RNAi screens. Nat. Methods. 3:777 (2006).
10. Echeverri, C.J. and Perrimon, N. High-throughput RNAi screening in cultured cells: a user's guide. Nature Reviews Genetics 7:373 (2006).
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