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Computational detection and suppression of sequence-specific off-target phenotypes from whole genome RNAi screens

A challenge for large-scale siRNA loss-of-function studies is the biological pleiotropy resulting from multiple modes of action of siRNA reagents. A major confounding feature of these reagents is the microRNA-like translational quelling resulting from short regions of oligonucleotide complementarity...

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Detalles Bibliográficos
Autores principales: Zhong, Rui, Kim, Jimi, Kim, Hyun Seok, Kim, Minsoo, Lum, Lawrence, Levine, Beth, Xiao, Guanghua, White, Michael A., Xie, Yang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4117740/
https://www.ncbi.nlm.nih.gov/pubmed/24972830
http://dx.doi.org/10.1093/nar/gku306
Descripción
Sumario:A challenge for large-scale siRNA loss-of-function studies is the biological pleiotropy resulting from multiple modes of action of siRNA reagents. A major confounding feature of these reagents is the microRNA-like translational quelling resulting from short regions of oligonucleotide complementarity to many different messenger RNAs. We developed a computational approach, deconvolution analysis of RNAi screening data, for automated quantitation of off-target effects in RNAi screening data sets. Substantial reduction of off-target rates was experimentally validated in five distinct biological screens across different genome-wide siRNA libraries. A public-access graphical-user-interface has been constructed to facilitate application of this algorithm.