The DOI matches its Crossref record; 61 of the 66 references it cites were found in a registry or an index.
High-throughput analysis of the activities of xCas9, SpCas9-NG and SpCas9 at matched and mismatched target sequences in human cells
Open accessAbstract
The applications of clustered regularly interspaced short palindromic repeats (CRISPR)-based genome editing can be limited by a lack of compatible protospacer adjacent motifs (PAMs), insufficient on-target activity and off-target effects. Here, we report an extensive comparison of the PAM-sequence compatibilities and the on-target and off-target activities of Cas9 from Streptococcus pyogenes (SpCas9) and the SpCas9 variants xCas9 and SpCas9-NG (which are known to have broader PAM compatibility than SpCas9) at 26,478 lentivirally integrated target sequences and 78 endogenous target sites in human cells. We found that xCas9 has the lowest tolerance for mismatched target sequences and that SpCas9-NG has the broadest PAM compatibility. We also show, on the basis of newly identified non-NGG PAM sequences, that SpCas9-NG and SpCas9 can edit six previously unedited endogenous sites associated with genetic diseases. Moreover, we provide deep-learning models that predict the activities of xCas9 and SpCas9-NG at the target sequences. The resulting deeper understanding of the activities of xCas9, SpCas9-NG and SpCas9 in human cells should facilitate their use.
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“The “OFF-target” library contained thousands of known off-target sites: 431 off target sites of 13 gRNAs detected by GUIDE-seq or Digenome-seq, 805 gRNA-target pairs of 3 gRNAs evaluated by similarly oligonucleotide synthesis method.”
From Machine learning-based prediction models to guide the selection of Cas9 variants for efficient gene editing (2024) · cites this paper as [30]
In the citing paper
“Although some Cas9 variants have comparable editing activity and specificity with SpCas9 at a few target sites, high-throughput analysis is still lacking.”
From Machine learning-based prediction models to guide the selection of Cas9 variants for efficient gene editing (2024) · cites this paper as [30]
In the citing paper
“Across all four Cas9 variants and WT Cas9, the wobble transition was more tolerated, which was reflected by higher relative indel frequency compared to other mismatch types (Figure 3C).”
From Machine learning-based prediction models to guide the selection of Cas9 variants for efficient gene editing (2024) · cites this paper as [30]
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Metadata
- Authors
- Kim, H. K., Lee, S., Kim, Y., Park, J., Min, S., Choi, J. W., Huang, T. P., Yoon, S., Liu, D. R., & Kim, H. H.
- Affiliations
- Yonsei University (KR)
- Seoul National University (KR)
- Broad Institute (US)
- ORCID
- Venue
- Nature Biomedical Engineering
- Published
- 2020-01-14
- Volume
- 4
- Issue
- 1
- Pages
- 111-124
- ISSN
- 2157-846X (ISSN-L)
- OpenAlex
- W2999201570
- Cited by
- 145
- References
- 66
- Citations by year
- 2026: 19 · 2025: 18 · 2024: 23 · 2023: 22 · 2022: 20 · 2021: 26 · 2020: 17
- FWCI
- 6.89
- Type
- journal article
- Language
- en
- Open access
- Licence
- Locations
- Nature Biomedical Engineering (publishedVersion)
- PubMed (publishedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion)
- YUHSpace (Yonsei University Medical Library) (submittedVersion, cc-by-nc-nd)
- Funders
- Foundation for the National Institutes of Health (RM1 HG009490, R01 EB022376, R35 GM118062)
- Howard Hughes Medical Institute (David Liu)
- National Research Foundation of Korea (2017R1A2B3004198, 2017M3A9B4062403, 2018R1A5A2025079)
- Ministry of Health and Welfare (HI17C0676, HI16C1012)
- 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
- Health Sciences › Medicine › Oncology › CAR-T cell therapy research
- Keywords
- SpCas9, protospacer adjacent motif, on-target activity, off-target effects, CRISPR gene editing
- MeSH terms
- Gene Editing, CRISPR-Associated Protein 9, Deep Learning, Genetic Vectors, Humans, Streptococcus pyogenes, Lentivirus, HEK293 Cells, CRISPR-Cas Systems
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