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

Authors
 Rui Zhong  ;  Jimi Kim  ;  Hyun Seok Kim  ;  Minsoo Kim  ;  Lawrence Lum  ;  Beth Levine  ;  Guanghua Xiao  ;  Michael A. White  ;  Yang Xie 
Citation
 NUCLEIC ACIDS RESEARCH, Vol.42(13) : 8214-8222, 2014 
Journal Title
 NUCLEIC ACIDS RESEARCH 
ISSN
 0305-1048 
Issue Date
2014
MeSH
Algorithms ; Base Sequence ; Cell Line ; Genomics/methods* ; Humans ; MicroRNAs/chemistry ; RNA Interference* ; RNA, Small Interfering/chemistry
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.
Files in This Item:
T201403091.pdf Download
DOI
10.1093/nar/gku306
Appears in Collections:
1. College of Medicine (의과대학) > BioMedical Science Institute (의생명과학부) > 1. Journal Papers
Yonsei Authors
Kim, Hyun Seok(김현석) ORCID logo https://orcid.org/0000-0003-4498-8690
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/99706
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