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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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2014
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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 |
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author | Zhong, Rui Kim, Jimi Kim, Hyun Seok Kim, Minsoo Lum, Lawrence Levine, Beth Xiao, Guanghua White, Michael A. Xie, Yang |
author_facet | Zhong, Rui Kim, Jimi Kim, Hyun Seok Kim, Minsoo Lum, Lawrence Levine, Beth Xiao, Guanghua White, Michael A. Xie, Yang |
author_sort | Zhong, Rui |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-4117740 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-41177402014-08-15 Computational detection and suppression of sequence-specific off-target phenotypes from whole genome RNAi screens Zhong, Rui Kim, Jimi Kim, Hyun Seok Kim, Minsoo Lum, Lawrence Levine, Beth Xiao, Guanghua White, Michael A. Xie, Yang Nucleic Acids Res Computational Biology 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. Oxford University Press 2014-09-01 2014-06-27 /pmc/articles/PMC4117740/ /pubmed/24972830 http://dx.doi.org/10.1093/nar/gku306 Text en © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Computational Biology Zhong, Rui Kim, Jimi Kim, Hyun Seok Kim, Minsoo Lum, Lawrence Levine, Beth Xiao, Guanghua White, Michael A. Xie, Yang Computational detection and suppression of sequence-specific off-target phenotypes from whole genome RNAi screens |
title | Computational detection and suppression of sequence-specific off-target phenotypes from whole genome RNAi screens |
title_full | Computational detection and suppression of sequence-specific off-target phenotypes from whole genome RNAi screens |
title_fullStr | Computational detection and suppression of sequence-specific off-target phenotypes from whole genome RNAi screens |
title_full_unstemmed | Computational detection and suppression of sequence-specific off-target phenotypes from whole genome RNAi screens |
title_short | Computational detection and suppression of sequence-specific off-target phenotypes from whole genome RNAi screens |
title_sort | computational detection and suppression of sequence-specific off-target phenotypes from whole genome rnai screens |
topic | Computational Biology |
url | 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 |
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