title: Cas9-chromatin binding information enables more accurate CRISPR off-target prediction.
abstract: 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 CR: ISPR/Cas9 O: ff-target P: rediction and I: dentification T: ool (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.
authors.affiliation: University of Virginia, School of Medicine, Department of Biochemistry and Molecular Genetics, 1340 Jefferson Park Ave, Jordan Hall, Room: 6240, Charlottesville, VA 22903, USA University of Virginia, Center for Public Health Genomics, Charlottesville VA 22903, USA.
authors.forename: Ritambhara
authors.initials: R
authors.lastname: Singh
authors.affiliation: University of Virginia, School of Medicine, Department of Biochemistry and Molecular Genetics, 1340 Jefferson Park Ave, Jordan Hall, Room: 6240, Charlottesville, VA 22903, USA.
authors.forename: Cem
authors.initials: C
authors.lastname: Kuscu
authors.affiliation: University of Virginia, School of Medicine, Department of Biochemistry and Molecular Genetics, 1340 Jefferson Park Ave, Jordan Hall, Room: 6240, Charlottesville, VA 22903, USA University of Virginia, Department of Computer Science, Charlottesville VA 22903, USA University of Virginia, Department of Public Health Sciences, Charlottesville VA 22903, USA.
authors.forename: Aaron
authors.initials: A
authors.lastname: Quinlan
authors.affiliation: University of Virginia, Center for Public Health Genomics, Charlottesville VA 22903, USA.
authors.forename: Yanjun
authors.initials: Y
authors.lastname: Qi
authors.affiliation: University of Virginia, School of Medicine, Department of Biochemistry and Molecular Genetics, 1340 Jefferson Park Ave, Jordan Hall, Room: 6240, Charlottesville, VA 22903, USA adli@virginia.edu.
authors.forename: Mazhar
authors.initials: M
authors.lastname: Adli
mesh_terms: D000465:Algorithms; D001665:Binding Sites; D064130:CRISPR-Associated Proteins / Q000378:metabolism*; D064113:CRISPR-Cas Systems; D002843:Chromatin / Q000378:metabolism*; D053837:DNA Cleavage; D003851:Deoxyribonucleases / Q000378:metabolism*; D006801:Humans; D017422:Sequence Analysis, DNA; D017423:Sequence Analysis, RNA / Q000379:methods; D012984:Software
chemical_list: D064130:CRISPR-Associated Proteins; D002843:Chromatin; D003851:Deoxyribonucleases