期刊
NUCLEIC ACIDS RESEARCH
卷 43, 期 18, 页码 -出版社
OXFORD UNIV PRESS
DOI: 10.1093/nar/gkv575
关键词
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资金
- University of Virginia School of medicine
- Pilot project (Pediatric Center of Excellence in Nephrology grant) [NIH P50 DK096373]
- V Scholar award from V cancer research foundation
- V scholar Foundation
The CRISPR system has become a powerful biological tool with a wide range of applications. However, improving targeting specificity and accurately predicting potential off-targets remains a significant goal. Here, we introduce a web-based CRISPR/Cas9 Off-target Prediction and Identification Tool (CROP-IT) that performs improved off-target binding and cleavage site predictions. Unlike existing prediction programs that solely use DNA sequence information; CROP-IT integrates whole genome level biological information from existing Cas9 binding and cleavage data sets. Utilizing whole-genome chromatin state information from 125 human cell types further enhances its computational prediction power. Comparative analyses on experimentally validated datasets show that CROP-IT outperforms existing computational algorithms in predicting both Cas9 binding as well as cleavage sites. With a user-friendly web-interface, CROP-IT outputs scored and ranked list of potential off-targets that enables improved guide RNA design and more accurate prediction of Cas9 binding or cleavage sites.
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