Aidan O'Brien1, Timothy L Bailey1. 1. Genomics and Computational Biology, Institute for Molecular Bioscience, The University of Queensland, Brisbane, Qld. 4072, Australia.
Abstract
UNLABELLED: A number of technologies, including CRISPR/Cas, transcription activator-like effector nucleases and zinc-finger nucleases, allow the user to target a chosen locus for genome editing or regulatory interference. Specificity, however, is a major problem, and the targeted locus must be chosen with care to avoid inadvertently affecting other loci ('off-targets') in the genome. To address this we have created 'Genome Target Scan' (GT-Scan), a flexible web-based tool that ranks all potential targets in a user-selected region of a genome in terms of how many off-targets they have. GT-Scan gives the user flexibility to define the desired characteristics of targets and off-targets via a simple 'target rule', and its interactive output allows detailed inspection of each of the most promising candidate targets. GT-Scan can be used to identify optimal targets for CRISPR/Cas systems, but its flexibility gives it potential to be adapted to other genome-targeting technologies as well. AVAILABILITY AND IMPLEMENTATION: GT-Scan can be run via the web at: http://gt-scan.braembl.org.au.
UNLABELLED: A number of technologies, including CRISPR/Cas, transcription activator-like effector nucleases and zinc-finger nucleases, allow the user to target a chosen locus for genome editing or regulatory interference. Specificity, however, is a major problem, and the targeted locus must be chosen with care to avoid inadvertently affecting other loci ('off-targets') in the genome. To address this we have created 'Genome Target Scan' (GT-Scan), a flexible web-based tool that ranks all potential targets in a user-selected region of a genome in terms of how many off-targets they have. GT-Scan gives the user flexibility to define the desired characteristics of targets and off-targets via a simple 'target rule', and its interactive output allows detailed inspection of each of the most promising candidate targets. GT-Scan can be used to identify optimal targets for CRISPR/Cas systems, but its flexibility gives it potential to be adapted to other genome-targeting technologies as well. AVAILABILITY AND IMPLEMENTATION: GT-Scan can be run via the web at: http://gt-scan.braembl.org.au.
Authors: Jeffrey C Miller; Michael C Holmes; Jianbin Wang; Dmitry Y Guschin; Ya-Li Lee; Igor Rupniewski; Christian M Beausejour; Adam J Waite; Nathaniel S Wang; Kenneth A Kim; Philip D Gregory; Carl O Pabo; Edward J Rebar Journal: Nat Biotechnol Date: 2007-07-01 Impact factor: 54.908
Authors: Richard Gabriel; Angelo Lombardo; Anne Arens; Jeffrey C Miller; Pietro Genovese; Christine Kaeppel; Ali Nowrouzi; Cynthia C Bartholomae; Jianbin Wang; Geoffrey Friedman; Michael C Holmes; Philip D Gregory; Hanno Glimm; Manfred Schmidt; Luigi Naldini; Christof von Kalle Journal: Nat Biotechnol Date: 2011-08-07 Impact factor: 54.908
Authors: Martin Jinek; Krzysztof Chylinski; Ines Fonfara; Michael Hauer; Jennifer A Doudna; Emmanuelle Charpentier Journal: Science Date: 2012-06-28 Impact factor: 47.728
Authors: Prashant Mali; Luhan Yang; Kevin M Esvelt; John Aach; Marc Guell; James E DiCarlo; Julie E Norville; George M Church Journal: Science Date: 2013-01-03 Impact factor: 47.728
Authors: Patrick D Hsu; David A Scott; Joshua A Weinstein; F Ann Ran; Silvana Konermann; Vineeta Agarwala; Yinqing Li; Eli J Fine; Xuebing Wu; Ophir Shalem; Thomas J Cradick; Luciano A Marraffini; Gang Bao; Feng Zhang Journal: Nat Biotechnol Date: 2013-07-21 Impact factor: 54.908
Authors: Matthew C Canver; Maximilian Haeussler; Daniel E Bauer; Stuart H Orkin; Neville E Sanjana; Ophir Shalem; Guo-Cheng Yuan; Feng Zhang; Jean-Paul Concordet; Luca Pinello Journal: Nat Protoc Date: 2018-04-12 Impact factor: 13.491