Benchmarking and integrating genome-wide CRISPR off-target detection and prediction. Issue 20 (2nd November 2020)

• Record Type: Journal Article
• Authors: Yan, Jifang; Xue, Dongyu; Chuai, Guohui; Gao, Yuli; Zhang, Gongchen; Liu, Qi
• Is Part Of: Nucleic acids research. Volume 48:Issue 20(2020)
• Page Start: 11370
• Page End: 11379
• Publication Date: 2020-11-02
• Subjects: Nucleic acids -- Periodicals; Molecular biology -- Periodicals; 572.805
• DOI: 10.1093/nar/gkaa930
• Languages: English
• ISSNs: 0305-1048

Abstract

Abstract: Systematic evaluation of genome-wide Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) off-target profiles is a fundamental step for the successful application of the CRISPR system to clinical therapies. Many experimental techniques and in silico tools have been proposed for detecting and predicting genome-wide CRISPR off-target profiles. These techniques and tools, however, have not been systematically benchmarked. A comprehensive benchmark study and an integrated strategy that takes advantage of the currently available tools to improve predictions of genome-wide CRISPR off-target profiles are needed. We focused on the specificity of the traditional CRISPR SpCas9 system for gene knockout. First, we benchmarked 10 available genome-wide off-target cleavage site (OTS) detection techniques with the published OTS detection datasets. Second, taking the datasets generated from OTS detection techniques as the benchmark datasets, we benchmarked 17 available in silico genome-wide OTS prediction tools to evaluate their genome-wide CRISPR off-target prediction performances. Finally, we present the first one-stop i ntegrated G enome-W ide O ff-target cleavage S earch platform ( iGWOS ) that was specifically designed for the optimal genome-wide OTS prediction by integrating the available OTS prediction algorithms with an AdaBoost ensemble framework.