title: Sequence determinants of improved CRISPR sgRNA design.
abstract: The CRISPR/Cas9 system has revolutionized mammalian somatic cell genetics. Genome-wide functional screens using CRISPR/Cas9-mediated knockout or dCas9 fusion-mediated inhibition/activation (CRISPRi/a) are powerful techniques for discovering phenotype-associated gene function. We systematically assessed the DNA sequence features that contribute to single guide RNA (sgRNA) efficiency in CRISPR-based screens. Leveraging the information from multiple designs, we derived a new sequence model for predicting sgRNA efficiency in CRISPR/Cas9 knockout experiments. Our model confirmed known features and suggested new features including a preference for cytosine at the cleavage site. The model was experimentally validated for sgRNA-mediated mutation rate and protein knockout efficiency. Tested on independent data sets, the model achieved significant results in both positive and negative selection conditions and outperformed existing models. We also found that the sequence preference for CRISPRi/a is substantially different from that for CRISPR/Cas9 knockout and propose a new model for predicting sgRNA efficiency in CRISPRi/a experiments. These results facilitate the genome-wide design of improved sgRNA for both knockout and CRISPRi/a studies.
authors.affiliation: Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, Massachusetts 02115, USA; Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts 02215, USA;
authors.forename: Han
authors.initials: H
authors.lastname: Xu
authors.affiliation: Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, Massachusetts 02115, USA; Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts 02215, USA; Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts 02115, USA;
authors.forename: Tengfei
authors.initials: T
authors.lastname: Xiao
authors.affiliation: Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, Massachusetts 02215, USA;
authors.forename: Chen-Hao
authors.initials: CH
authors.lastname: Chen
authors.affiliation: Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, Massachusetts 02115, USA; Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts 02215, USA;
authors.forename: Wei
authors.initials: W
authors.lastname: Li
authors.affiliation: Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, Massachusetts 02115, USA; Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts 02215, USA;
authors.forename: Clifford A
authors.initials: CA
authors.lastname: Meyer
authors.affiliation: Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, Massachusetts 02115, USA; Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts 02215, USA; Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai, 200092 China;
authors.forename: Qiu
authors.initials: Q
authors.lastname: Wu
authors.affiliation: Department of Statistics, Harvard University, Cambridge, Massachusetts 02138, USA;
authors.forename: Di
authors.initials: D
authors.lastname: Wu
authors.affiliation: Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA; McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA;
authors.forename: Le
authors.initials: L
authors.lastname: Cong
authors.affiliation: Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA; McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA;
authors.forename: Feng
authors.initials: F
authors.lastname: Zhang
authors.affiliation: Department of Statistics, Harvard University, Cambridge, Massachusetts 02138, USA;
authors.forename: Jun S
authors.initials: JS
authors.lastname: Liu
authors.affiliation: Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts 02215, USA; Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts 02115, USA; Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02215, USA.
authors.forename: Myles
authors.initials: M
authors.lastname: Brown
authors.affiliation: Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, Massachusetts 02115, USA; Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts 02215, USA;
authors.forename: X Shirley
authors.initials: XS
authors.lastname: Liu
mesh_terms: D064112:Clustered Regularly Interspaced Short Palindromic Repeats; D019295:Computational Biology / Q000379:methods*; D004247:DNA / Q000032:analysis; D055786:Gene Knockout Techniques; D018922:HL-60 Cells; D006801:Humans; D008957:Models, Genetic; D059645:Mutation Rate; D000094704:RNA, Guide, CRISPR-Cas Systems / Q000378:metabolism*
chemical_list: D000094704:RNA, Guide, CRISPR-Cas Systems; D004247:DNA