High-content siRNA screening for target identification and validation

Krausz, Eberhard; Korn, Kerstin

doi:10.1517/17460441.3.5.551

Cited by 8 publications

(2 citation statements)

References 75 publications

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“…4B). 12,32,33 Furthermore, high content screening approaches provide the ultimate advantage of identifying those genes essential for cell viability and at the same time score for those rescuers, the knockdown of which enhances cellular growth, which would have been missed if relying on a low content approach.…”

Section: Discussionmentioning

confidence: 99%

An Arrayed Genome-Scale Lentiviral-Enabled Short Hairpin RNA Screen Identifies Lethal and Rescuer Gene Candidates

Bhinder

Antczak²,

Ramirez³

et al. 2013

ASSAY and Drug Development Technologies

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RNA interference technology is becoming an integral tool for target discovery and validation.; With perhaps the exception of only few studies published using arrayed short hairpin RNA (shRNA) libraries, most of the reports have been either against pooled siRNA or shRNA, or arrayed siRNA libraries. For this purpose, we have developed a workflow and performed an arrayed genome-scale shRNA lethality screen against the TRC1 library in HeLa cells. The resulting targets would be a valuable resource of candidates toward a better understanding of cellular homeostasis. Using a high-stringency hit nomination method encompassing criteria of at least three active hairpins per gene and filtered for potential off-target effects (OTEs), referred to as the Bhinder-Djaballah analysis method, we identified 1,252 lethal and 6 rescuer gene candidates, knockdown of which resulted in severe cell death or enhanced growth, respectively. Cross referencing individual hairpins with the TRC1 validated clone database, 239 of the 1,252 candidates were deemed independently validated with at least three validated clones. Through our systematic OTE analysis, we have identified 31 microRNAs (miRNAs) in lethal and 2 in rescuer genes; all having a seed heptamer mimic in the corresponding shRNA hairpins and likely cause of the OTE observed in our screen, perhaps unraveling a previously unknown plausible essentiality of these miRNAs in cellular viability. Taken together, we report on a methodology for performing large-scale arrayed shRNA screens, a comprehensive analysis method to nominate high-confidence hits, and a performance assessment of the TRC1 library highlighting the intracellular inefficiencies of shRNA processing in general.

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Section: Discussionmentioning

confidence: 99%

An Arrayed Genome-Scale Lentiviral-Enabled Short Hairpin RNA Screen Identifies Lethal and Rescuer Gene Candidates

Bhinder

Antczak²,

Ramirez³

et al. 2013

ASSAY and Drug Development Technologies

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“…Small interfering RNA (siRNA) screening has grown to be a popular strategy 1–3 for discovering new drug targets and elucidating biological pathways. To date, the large-scale screening of siRNA libraries has yielded interesting yet contradictory results.…”

Section: Introductionmentioning

confidence: 99%

Common Seed Analysis to Identify Off-Target Effects in siRNA Screens

et al. 2012

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Genome-scale small interfering RNA (siRNA) screens have become an increasingly popular approach to new target identification and pathway elucidation. However, the large data sets generated from siRNA screens have demonstrated high false-positive rates and the requirement for extensive experimental triage to distinguish true hits. A number of groups have independently reported the presence of siRNAs with identical seed sequences among their top screening hits. Based on these observations, we have developed a comprehensive technique for detecting and visualizing seed-based off-target effects in siRNA screening data. This is accomplished by analyzing the behavior of siRNAs that share identical seed sequences, which we refer to as common seed analysis (CSA). By applying these techniques to primary screening data of the Wnt pathway, we identify 158 distinct seed sequences that have a statistically significant effect on the assay. The promiscuous seed sequences identified in this manner can then be discounted in the analysis of follow-up experiments using single siRNAs. The ability to detect off-target effects when sufficient numbers of siRNAs share a common seed has significant implications for the design of siRNA screening experiments, data analysis, hit selection, and library design.

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