Target Identification & Validation, RNA interference



New targets for drug discovery have been classically identified by various methods such as analysing family pedigrees for inherited diseases or pathological alterations in diseased tissue samples. Protein, mRNA or genetic alterations have been detected by molecular methods. Various perturbation methods (Fig. 1) have been developed to induce and characterise alterations. Deletion or mutation of genes has been used to understand their function, as well as inhibiting their correlating mRNAs or proteins by antisense molecules or antibodies. Pharmacologically active chemical compounds can be used to fish for binding target proteins which might help to understand its mode of action, or use it selectively to interfere with its target protein to induce and analyse the phenotype. However, final validation of a target and a correlating perturbating molecule can only be achieved in a clinical setting by curing a diseased patient.


Perturbation methods for target ID

Fig. 1.


Fig. 1. Analysis and perturbation methods for target identification and early validation (1-3).




Currently, one of the most important target identification and validation tools is RNA interference. RNA interference (RNAi) has been discovered in the worm and model organism Caenorhabditis elegans by Andrew Fire and Craig Mellow in 1998 (4), and subsequently reduced to a tool that works also in mammalian cell cultures including cells of human origin (5). Exploiting an endogenous mechanism, mRNA of a gene of interest can be depleted in whole organisms, organs/tissues or individual cells, and the induced phenotype can be described. Such perturbations are performed nowadays at large scale for example by screening whole genomes while analysing one or multiple parameters at once to describe systematically the effect(s) of each gene’s depletion.




Various technologies have been developed to induce RNA interference in mammalian cells. Most prominent and widely used are chemically synthesised short interfering RNAs (siRNA). However, alternative methods such as expressing short hairpin RNAs (shRNA) from viral vectors or esiRNAs are further valuable tools (Fig. 2). All of them have certain advantages and disadvantages, and depending preference and requirements one might serve best the individual need. 


RNAi technologies in mammalian cells

Fig. 2.


Fig. 2. Some technologies applied to induce RNA interference in mammalian cells. (6)




Major challenges in applying RNA interference are off-target effects and delivery. Unfortunately, although in principle a sequence-specific mechanism, off-target effects are widely observed in practice and explained by various mechanisms. Many strategies have been explored to control, or at least reduce, this problem. Already early on, basic standards for good practice in RNAi experiments were defined and published (Fig. 3; ref. 7-10). Certain design algorithms are applied for example to avoid known motifs that trigger off-target effects. siRNAs can be chemically modified to reduce the likelihood for off target effects, or libraries are expanded significantly to have more non-overlapping effector molecules at hand per gene, such as the TRC library that offers 5-10 shRNAs per target.


Guidelines on RNA interference

Fig. 3.


Fig. 3. Guidelines elaborated at the Nature HORIZON meeting on RNA by leaders in the field and published as an editorial in Nature Cell Biology in 2003 (6, 7).





Good negative control siRNAs/shRNAs have been described (5, 11-13). However, for any assay a set of negative control siRNAs/shRNAs (Fig.4) should be tested to be sure to work with one or more controls that are really ‘negative’ in the desired assay.


negative control siRNAs

Fig. 4.

Fig. 4. Negative control siRNAs. (Krausz et al., TDS, Max Planck Institute for Molecular Cell Biology and Genetics, Dresden, Germany.





Another challenge is efficient delivery of RNAi molecules. For this, positive control siRNAs/shRNAs are valuable that target a quantifiable reporter, an endogenous gene whose efficient depletion induces a strong effect or phenotype, or any other marker that could not only report on successful delivery, but also on the performance of the assay. A wide toolbox is available. In principle, target mRNA depletion could be quantified by qRT-PCR. However, genes involved in apoptosis or cell cycling, and here in particularly those that induce mitotic arrest, are very attractive to derive more conveniently information if sufficient siRNA molecules are delivered to induce a certain phenotype. Targets such as KIF11 (Eg5), PLK1 or TRX2 and correlating siRNA sequences to deplete have been described (12, 13). Efficient depletion can be easily observed and/or quantified. (Fig. 5)


targets to demonstrate siRNA delivery

Fig. 5.

Fig. 5. Some examples of targets that could be addressed by RNAi molecules to demonstrated efficient delivery. Upon successful delivery of the Eg5 siRNA (12), HeLa cells arrested in mitosis, and rounded-up cells can be easily counted, as depicted on the right image. If incubation is prolonged, cells undergo apoptosis. After a few days, transfected cells disappear. (6, adapted from 14)





Delivery of siRNAs into mammalian cells is addressed by many methods. Classical transfection reagents based on liposomes or electroporation, but also many more technologies are applied. Also for viral vectors, delivery efficiency might be important to assess. For systematically searching optimal conditions, experiments in 96-well microtiter plates are recommended (15, 16).


siRNA delivery optimisation

Fig. 6.

Fig. 6. Good practice in elaborating optimal delivery conditions should always cover a positive and a negative control to consider various aspects in parallel. (6).








(1) Krausz, E.: Cell-Based Assays for Target Identification and Validation. On-line Course ‘Cell-Based Assays for Drug Discovery’, Module 5, The Society for Biomolecular Science, October 28, 2008.


(2) Lindsay, M.A.: Target Discovery. Nat Rev Drug Discov 2003, 2:831-838.


(3) Wang, S., et al.: Tools for target identification and validation. Curr Opin Chem Biol 2004, 8:371-377.


(4) Fire, A., Xu,S., Montgomery, M.K., Kostas, S.A., Driver, S.E., Mello, C.C.: Potent and specific genetic interference by double-stranded RNA in Caenorhabditis elegans. Nature 1998, 391:806-811.


(5) Elbashir et al.: Duplexes of 21-nucleotide RNAs mediate RNA interference in cultured mammalian cells. Nature 2001, 411:494-498.


(6) Slide prepared for the Pre-Conference Workshop ‘RNAi in Practice: A User’s Guide to Assays and Screening in Mammalian Cells’ of IBC’s Drug Discovery & Development Week, Boston, 4.8.2009.


(7) Anon: Whither RNAi? Editorial. Nat. Cell Biol 2003, 5:489-490.


(8) Echeverri, C.J., Perrimon, N.: High-throughput RNAi screening in cultured cells: a user's guide. Nat Rev Genet 2006, 7:373-384.


(9) Echeverri et al.: Minimizing the risk of reporting false positives in large-scale RNAi screens. Nat Methods 2006, 3:777-779.


(10) Krausz, E.: High-content siRNA screening. Mol Biosyst 2007, 3:232-240.


(11) Elbashir et al.: Analysis of gene function in somatic mammalian cells using small interfering RNAs. Methods 2002, 26:199-213.


(12) Weil et al.: Targeting the kinesin Eg5 to monitor siRNA transfection in mammalian cells. Biotechniques 2002, 33:1244-1248.

Eg5 siRNA: 5’-CUGAAGACCUGAAGACAAUtt-3’ (sense strand); 5’-AUUGUCUUCAGGUCUUCAGtt-3’ (antisense)


(13) Neumann et al.: HT RNAi screening by time-lapse imaging of live human cells. Nat Methods 2006, 3:385-390.


(14) Krausz, E.: 96-well Electroporation for Plasmids and Oligonucleotides. amaxa's workshop on RNAi and Nucleofection, September 11, 2007, Dresden, Germany.


(15) Sachse, Krausz et al.: High throughput RNA interference strategies for target discovery and validation using synthetic short interfering RNAs: functional genomics investigations of biological pathways. Methods Enzymol 2005, 392:242-277.  


(16) Krausz et al.: Optimising high throughput RNAi-based assays using transient transfection of synthetic siRNAs in cultured mammalian cells. In Engelke D.R. (ed): RNA Interference (RNAi)- Nuts & Bolts of RNAi Technology, p. 131-168, DNA Press LLC, (2003).





Dr. Eberhard Krauß, Wiesbaden, Germany