Sequence determinants of improved CRISPR sgRNA design
Open accessAbstract
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.
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Key sequence information previously obtained in SpCas9-WT was further verified in several variants in this study, such as the preference of G base in the gRNA spacer, including the preference of G bases in the PAM-distal region.
“Some of the key sequence information previously obtained in SpCas9-WT was further verified in several variants in our study, such as the preference of G base in the gRNA spacer, including the preference of G bases in the PAM-distal region.”
From Machine learning-based prediction models to guide the selection of Cas9 variants for efficient gene editing (2024) · cites this paper as [45]
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- Authors
- Xu, H., Xiao, T., Chen, C.-H., Li, W., Meyer, C. A., Wu, Q., Wu, D., Cong, L., Zhang, F., Liu, J. S., Brown, M., & Liu, X. S.
- Affiliations
- Harvard University (US)
- Tongji University (CN)
- Broad Institute (US)
- Brigham and Women's Hospital (US)
- ORCID
- Venue
- Genome Research
- Publisher
- Cold Spring Harbor Laboratory
- Published
- 2015-06-10
- Volume
- 25
- Issue
- 8
- Pages
- 1147-1157
- ISSN
- 1088-9051 (ISSN-L)
- 1549-5469
- PMC
- PMC4509999
- OpenAlex
- W1879165674
- Cited by
- 625
- References
- 29
- Citations by year
- 2026: 20 · 2025: 47 · 2024: 59 · 2023: 60 · 2022: 72 · 2021: 77 · 2020: 72 · 2019: 60 · 2018: 47 · 2017: 53 · 2016: 41 · 2015: 16 · 2013: 1
- Type
- posted content
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Genome Research (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc-sa)
- Funders
- National Institute for Health Research (U01 CA180980, R01 GM113242-01)
- National Science Foundation (DMS-1120368)
- Dana-Farber Cancer Institute
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › CRISPR and Genetic Engineering
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA regulation and disease
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Interference and Gene Delivery
- Keywords
- CRISPR/Cas9, single guide RNA design, sequence determinants, knockout efficiency, mutation rate, positive and negative selection
- MeSH terms
- RNA, Guide, CRISPR-Cas Systems, DNA, Humans, Models, Genetic, HL-60 Cells, Computational Biology, Gene Knockout Techniques, Mutation Rate, Clustered Regularly Interspaced Short Palindromic Repeats
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