Choosing siRNA, shRNA, and miRNA for Gene Silencing

RNAi refers to dsRNA-induced gene silencing, a cellular process that degrades RNA homologous to one strand of the dsRNA [1, 2]. The intermediates of long dsRNA-initiated RNAi are double-stranded small interfering RNAs (siRNA), typically 21-23 nucleotide (nt) long. The siRNAs, when introduced into cells, can be used to silence genes in mammalian systems where long dsRNAs prompt protein kinase R (PKR), RNase L, and interferon activities that result in non-specific RNA degradation and general shutdown of protein synthesis [3]. siRNAs can either be chemically synthesized then directly transfected into cells or can be generated inside the cell by introducing vectors that express short-hairpin RNA (shRNA) precursors of siRNAs. The process of shRNA into functional siRNA involves cellular RNAi machinery that naturally process genome encoded microRNAs (miRNA) that are responsible for cellular regulation of gene expression by modulating mRNA stability, translation, and chromatin structures [4].

Chemically synthesized siRNA is the simplest format for RNAi. One of the biggest hurdles for achieving effective RNAi with siRNA is that many cells are difficult to transfect. An RNAi experiment is typically considered successful when the target gene expression is reduced by >70%, a threshold not reachable by many types of cells due to their low transfection efficiency. Another drawback of using synthetic siRNA is the limited duration of post-transfection effects, typically with gene silencing activities peaking around 24 hours, and diminishing within 48 hours [5]. Chemical synthesis of siRNA, which is a service Allele Biotech and Orbigen (now merged under the Allele brand) pioneered and still provides, is expensive on a per transfection basis relative to DNA vector based reagents.

shRNA can be introduced by DNA plasmid, linear template, or packaged retroviral/lentiviral vectors. Using any form of DNA construct, except the PCR template format such as Allele’s LineSilence platform, requires creating DNA constructs and sequence verification; a taxing work load if multiple genes need to be studied. However, once the constructs are made, they can be reproduced easily and inexpensively. It is difficult to directly compare the effectiveness of siRNA versus shRNA on a per molecule basis because RNA polymerase III (Pol III) promoters such as U6 or H1 commonly used to express shRNAs can make thousands of copies of shRNA from a single DNA template. However when both siRNA and shRNA are produced the same way, e.g. synthesized chemically, shRNA is reported to be somewhat more effective [6, 7]. For the goals of this research, the most important advantage using shRNA can provide over siRNA is that it can be carried on a lentiviral vector and introduced into a wide variety of cells.

Similar to the comparison between siRNA versus shRNA, it is also difficult to rank the efficiency of shRNA versus miRNA from published data, partly due to different results from different experimental systems. There have been several reports that showed shRNA can cause significant cell toxicity, especially in vivo such as after injection into mouse brain. It was originally reasoned that highly efficient expression from Pol III promoters might overwhelm the cellular machinery that is needed to execute endogenous RNAi functions such as transporting miRNA from the nucleus to the cytoplasm. It was later found out that even using Pol III promoter to create miRNA could still mitigate the toxic effects of shRNA [8]. Since shRNA and miRNA are processed by endonuclease Dicer before being incorporated into RNA induced silencing complex (RISC), the exact identity of siRNAs produced from a given shRNA or miRNA targeting the same region on the mRNA are not known in most of the earlier studies. By designing shRNA and miRNA to give exactly the same processed siRNAs, Boudreau et al. showed that shRNA is actually more potent than miRNA in various systems [9].

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1. Fire, A., S. Xu, M.K. Montgomery, S.A. Kostas, S.E. Driver, and C.C. Mello, Potent and specific genetic interference by double-stranded RNA in Caenorhabditis elegans. Nature, 1998. 391(6669): p. 806-11.
2. Hannon, G.J., RNA interference. Nature, 2002. 418(6894): p. 244-51.
3. McManus, M.T. and P.A. Sharp, Gene silencing in mammals by small interfering RNAs. Nat Rev Genet, 2002. 3(10): p. 737-47.
4. Hutvagner, G. and P.D. Zamore, A microRNA in a multiple-turnover RNAi enzyme complex. Science, 2002. 297(5589): p. 2056-60.
5. Rao, D.D., J.S. Vorhies, N. Senzer, and J. Nemunaitis, siRNA vs. shRNA: similarities and differences. Adv Drug Deliv Rev, 2009. 61(9): p. 746-59.
6. Vlassov, A.V., B. Korba, K. Farrar, S. Mukerjee, A.A. Seyhan, H. Ilves, R.L. Kaspar, D. Leake, S.A. Kazakov, and B.H. Johnston, shRNAs targeting hepatitis C: effects of sequence and structural features, and comparision with siRNA. Oligonucleotides, 2007. 17(2): p. 223-36.
7. Siolas, D., C. Lerner, J. Burchard, W. Ge, P.S. Linsley, P.J. Paddison, G.J. Hannon, and M.A. Cleary, Synthetic shRNAs as potent RNAi triggers. Nat Biotechnol, 2005. 23(2): p. 227-31.
8. McBride, J.L., R.L. Boudreau, S.Q. Harper, P.D. Staber, A.M. Monteys, I. Martins, B.L. Gilmore, H. Burstein, R.W. Peluso, B. Polisky, B.J. Carter, and B.L. Davidson, Artificial miRNAs mitigate shRNA-mediated toxicity in the brain: implications for the therapeutic development of RNAi. Proc Natl Acad Sci U S A, 2008. 105(15): p. 5868-73.
9. Boudreau, R.L., A.M. Monteys, and B.L. Davidson, Minimizing variables among hairpin-based RNAi vectors reveals the potency of shRNAs. Rna, 2008. 14(9): p. 1834-44.

Tags: alpaca antibodies, camelid antibody, gene knockdown, gene silencing, GFP-Trap, lentivirus packaging, miRNA, nanobodies, packaging systems, RFP-Trap, RNAi, shRNA, shRNA packaging, siRNA, VHH, virus packaging service

RNAi Design, Validation and Target Screening

Since Tuschl et al. published the first empirical guidelines on how to design effective siRNA [1], the most significant advancement (based on the understanding of biochemical mechanisms of RNAi such as how RISC is assembled) is the recognition of asymmetric thermostability of the 5’ end of the antisense strand (AS) relative to that of the sense strand (SS) [2, 3]. siRNAs with an A/T-rich AS 5’ end can be more easily integrated into RISC. By biasing against the sense strand for RISC loading, the off-target effects due to the presence of the SS (as one of the sources of off-targets effects) can also be minimized. In recent years datasets of increased number of siRNAs and shRNAs became available and statistical analysis suggested additional rules for RNAi design. These newer rules in general define the siRNA prediction parameters in more detail, for instance, the number of bases of the 5’ ends that should be included when calculating asymmetric thermostability, base preferences at each particular position, and the identity of the 2 nt 3’ overhang [4, 5]. Computer programs and websites are developed based on these features also resulting from NIH funded research through universities and organizations. Among the well-known ones, Design of SIRna (DSIR at biodev.extra.cea.fr/DSIR/DSIR.html) and the shRNA search program at the Broad Institute (broadinstitute.org/genome_bio/trc/publicSearchForHairpinsForm.php) are freely available.

Several companies such as Open Biosystems, System Biosciences, Dharmacon/ThermoFisher, Sigma-Aldrich, Invitrogen/LifeTech, provide premade RNAi reagents against various numbers of human and rodent genes. Although some product lines from these suppliers are labeled as validated RNAi reagents, apparently only one reveals clone sequences and only a few hundred among the claimed 4,500 shRNA clones. It is not possible to find what shRNAs are used against any target gene from most companies even though many of them claim to have a few hundred pre-validated constructs. Some of them may provide additional information upon purchase.

Even with the recent advancement of RNAi design technologies, prediction of effective RNAi is still far from accurate. Depending on the datasets used to score the success rates of the programs at DSIR, Broad or any other software, the general consensus is that about 50% of predicted RNAi target sequences will be effective, resulting in better than 70% gene knockdown. Allele Biotech uses a software that was trained with known RNAi results to predict siRNA target candidates on a given mRNA, and then applies an additional set of rules to pick the most promising candidates. Off-target effects caused by partial-matching between AS strand and untended targets are reduced by searching the chosen site against the NCBI gene base. The basic rules Allele Biotech uses include most currently known ones and are similar to what are listed by The RNAi Consortium (TRC) program at the Broad Institute.

Criteria for RNAi design:
(1) Overall GC content is between 30-55%
(2) The 4 bases at the 5’ of AS is more AT-rich than those of the SS
(3) The first base of AS and SS 5’ is preferably A/T and G/C, respectively
(4) “U” is preferred at the 10th position of the antisense from the 5’ end
(5) “C” is to be avoided as the last base of an overhang
(6) Avoid 4-nt mono-nucleotide regions
(7) Avoid 6-nt GC-rich regions
(8) If possible, do not include those with apparent secondary structures

These selected rules are based on a number of publications (for example, [4-6]), but it is impossible to include all known rules, many of which conflict with each other. In case of conflicting rules we rely more on recent discoveries and our own experience from providing RNAi service during the past 8 years.

Allele Biotech provides RNAi validation and screening services to customers using synthetic siRNA, linear DNA cassettes with engineered Pol III promoter, and shRNA expressing lentiviral vectors in high throughput formats. In a unique design, all RNAi target candidate sequences of a gene transcript are fused consecutively to a bright green fluorescent protein, mWasabi, on a lentiviral vector. Instead of analyzing gene silencing by QPCR, the initial selection of effective RNAi can be performed by measuring fluorescence.

RNAi screening has been conducted to identify correlations between gene functions and cellular phenotypes such as synthetic lethality among DNA damage signaling and repair pathway factors. Successfully performing high throughput screenings requires capabilities of efficient RNAi design, viral packaging, fluorescent proteins, and advanced cell culture and analysis techniques. In addition to these capabilities, Allele’s RNAi services are provided with access to commercial use of Allele’s own patents on Pol III promoter driven shRNA expression, and licensed patents on lentiviral vector, packaging, and fluorescent proteins.

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RNAi validation/screening service.

1. Tuschl, T., P.D. Zamore, R. Lehmann, D.P. Bartel, and P.A. Sharp, Targeted mRNA degradation by double-stranded RNA in vitro. Genes Dev, 1999. 13(24): p. 3191-7.
2. Khvorova, A., A. Reynolds, and S.D. Jayasena, Functional siRNAs and miRNAs exhibit strand bias. Cell, 2003. 115(2): p. 209-16.
3. Schwarz, D.S., G. Hutvagner, T. Du, Z. Xu, N. Aronin, and P.D. Zamore, Asymmetry in the assembly of the RNAi enzyme complex. Cell, 2003. 115(2): p. 199-208.
4. Vert, J.P., N. Foveau, C. Lajaunie, and Y. Vandenbrouck, An accurate and interpretable model for siRNA efficacy prediction. BMC Bioinformatics, 2006. 7: p. 520.
5. Zhou, H. and X. Zeng, Energy profile and secondary structure impact shRNA efficacy. BMC Genomics, 2009. 10 Suppl 1: p. S9.
6. Ui-Tei, K., Y. Naito, F. Takahashi, T. Haraguchi, H. Ohki-Hamazaki, A. Juni, R. Ueda, and K. Saigo, Guidelines for the selection of highly effective siRNA sequences for mammalian and chick RNA interference. Nucleic Acids Res, 2004. 32(3): p. 936-48.

Tags: cell based assays, DNA damage repair, gene knockdown, gene silencing, lentiviral vector, Pol III promoter, RNAi, RNAi design, RNAi screening, RNAi service, RNAi targets, shRNA, siRNA, Synthetic lethal