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

Nucleic Acids Res. 2014 Jul;42(13):8214-22. doi: 10.1093/nar/gku306. Epub 2014 Jun 27.

Abstract

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.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Algorithms
  • Base Sequence
  • Cell Line
  • Genomics / methods*
  • Humans
  • MicroRNAs / chemistry
  • RNA Interference*
  • RNA, Small Interfering / chemistry

Substances

  • MicroRNAs
  • RNA, Small Interfering