A Computational Algorithm to Predict shRNA Potency

Knott, S. R., Maceli, A. R., Erard, N., Chang, K., Marran, K., Zhou, X., Gordon, A., El Demerdash, O., Wagenblast, E., Kim, S., Fellmann, C., Hannon, G. J. (December 2014) A Computational Algorithm to Predict shRNA Potency. Mol Cell, 56 (6). pp. 796-807. ISSN 1097-2765

Abstract

The strength of conclusions drawn from RNAi-based studies is heavily influenced by the quality of tools used to elicit knockdown. Prior studies have developed algorithms to design siRNAs. However, to date, no established method has emerged to identify effective shRNAs, which have lower intracellular abundance than transfected siRNAs and undergo additional processing steps. We recently developed a multiplexed assay for identifying potent shRNAs and used this method to generate approximately 250,000 shRNA efficacy data points. Using these data, we developed shERWOOD, an algorithm capable of predicting, for any shRNA, the likelihood that it will elicit potent target knockdown. Combined with additional shRNA design strategies, shERWOOD allows the ab initio identification of potent shRNAs that specifically target the majority of each gene's multiple transcripts. We validated the performance of our shRNA designs using several orthogonal strategies and constructed genome-wide collections of shRNAs for humans and mice based on our approach.

Item Type: Paper
Additional Information: Molecular cell
Subjects: bioinformatics
bioinformatics > computational biology
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > shRNA
CSHL Authors:
Communities: CSHL Cancer Center Program > Cancer Genetics
CSHL Cancer Center Shared Resources > Flow Cytometry Service
CSHL Cancer Center Shared Resources > Functional Genomics and Genetics Service
CSHL labs > Hannon lab
School of Biological Sciences > Publications
CSHL Cancer Center Shared Resources > DNA Sequencing Service
Depositing User: Matt Covey
Date: 18 December 2014
Date Deposited: 30 Jan 2015 21:15
Last Modified: 04 Nov 2015 20:18
PMCID: PMC4272634
Related URLs:
URI: https://repository.cshl.edu/id/eprint/31160

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