High-Throughput Screening by RNA Interference

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Tony Rook
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High-Throughput Screening by RNA Interference

Here is a link to a nice review of genome wide RNAi screening methods that was published in the open-access journal Cell Cycle. This should be useful resource for anyone working with high throughput RNAi technologies.

Full-text link:

Stone DJ, Marine S, Majercak J, Ray WJ, Espeseth A, Simon A, Ferrer M. High-Throughput Screening by RNA Interference- Control of Two Distinct Types of Variance. Cell Cycle, 15 April 2007, 6:8, 898-901.


The availability of genome‑wide RNAi libraries has enabled researchers to rapidly assess the functions of thousands of genes; however the fact that these screens are run in living biological systems add complications above and beyond that normally seen in high‑throughput screening (HTS). Specifically, error due to variance in both measurement and biology are large in such screens, leading to the conclusion that the majority of hits are expected to be false positives. Here, we outline basic guidelines for screen development that will help the researcher to control these forms of variance. By running a large number of positive and negative control genes, error of measurement can be accurately estimated and false negatives reduced. Likewise, by using a complex readout for the screen, which is not easily mimicked by other biological pathways and phenomena, false positives, can be minimized. By controlling variance in these ways, the researcher can maximize the utility of genome‑wide RNAi screening.


Genome‑wide siRNA libraries have opened up the era of true functional genomics. Although there have been many claims of functional genomics since the completion of the human genome project at the turn of the millennium, many of these have in fact been expression genomics studies. In many of these studies, function was actually inferred or deduced on the basis of information taken largely from the literature. Therefore, in many cases the derived function is no better than a guess. Although true functional genomics studies have been done using complex experimental readouts from known physiological states or positive controls and pattern matching the resulting readouts (1‑6), RNAi allows for the first time the direct measurement of gene function in pathways of interest on a genome‑wide scale. This approach has been quickly embraced in both academic and industrial research (7-12).

High‑throughput siRNA screens combine the issues particular to both the analysis of HTS and to the study of complex biological systems, and as a result, the researcher has two forms of variance to contend with: measurement and biological. Most experimental scientists are faced with biological variance on a daily basis, but are less concerned with error of measurement as this is often small relative to that found between the organisms in question. On the other hand, HTS laboratories frequently face issues with error of measurement, but are not always forced to contend with the variance introduced when working on living systems. Because both of these forms of variance are present in high‑throughput RNAi screens, consideration of both is paramount in the design and analysis of a genome wide siRNA screen.

References (from article):

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2. Gunther EC, Stone DJ, Rothberg JM, Gerwien RW. A quantitative genomic expression analysis platform for multiplexed in vitro prediction of drug action. Pharmacogenomics J 2005; 5:126‑34.

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7. Gonczy P, Echeverri C, Oegema K, Coulson A, Jones SJ, Copley RR, Duperon J, Oegema J, Brehm M, Cassin E, Hannak E, Kirkham M, Pichler S, Flohrs K, Goessen A, Leidel S, Alleaume AM, Martin C, Ozlu N, Bork P, Hyman AA. Functional genomic analysis of cell division in C. elegans using RNAi of genes on chromosome III. Nature 2000; 408:331‑6

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10. Sonnichsen B, Koski LB, Walsh A, Marschall P, Neumann B, Brehm M, Alleaume AM, Artelt J, Bettencourt P, Cassin E, Hewitson M, Holz C, Khan M, Lazik S, Martin C, Nitzsche B, Ruer M, Stamford J, Winzi M, Heinkel R, Roder M, Finell J, Hantsch H, Jones SJ, Jones M, Piano F, Gunsalus KC, Oegema K, Gonczy P, Coulson A, Hyman AA, Echeverri CJ. Full‑genome RNAi profiling of early embryogenesis in Caenorhabditis elegans. Nature 2005; 434:462‑9.

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12. Majercak J, Ray WJ, Espeseth A, Simon A, Shi XP, Wolffe C, Getty K, Marine S, Stec E, Ferrer M, Strulovici B, Bartz S, Gates A, Xu M, Huang Q, Ma L, Shughrue P, Burchard J, Colussi D, Pietrak B, Kahana J, Beher D, Rosahl T, Shearman M, Hazuda D, Sachs AB, Koblan KS, Seabrook GR, Stone DJ. LRRTM3 promotes processing of amyloid‑precursor protein by BACE1 and is a positional candidate gene for late‑onset Alzheimers disease. �Proc Natl Acad Sci USA 2006; 103:17967‑72.