Cited by 4,741CRISPR and Genetic EngineeringRNA regulation and diseaseRNA Interference and Gene Delivery

DNA targeting specificity of RNA-guided Cas9 nucleases

Open access
Hsu, Patrick D, Scott, David A, Weinstein, Joshua A, Ran, F Ann, Konermann, Silvana, Agarwala, Vineeta, Li, Yinqing, Fine, Eli J +6 more·2013·Nature Biotechnology

Abstract

The Streptococcus pyogenes Cas9 (SpCas9) nuclease can be efficiently targeted to genomic loci by means of single-guide RNAs (sgRNAs) to enable genome editing. Here, we characterize SpCas9 targeting specificity in human cells to inform the selection of target sites and avoid off-target effects. Our study evaluates >700 guide RNA variants and SpCas9-induced indel mutation levels at >100 predicted genomic off-target loci in 293T and 293FT cells. We find that SpCas9 tolerates mismatches between guide RNA and target DNA at different positions in a sequence-dependent manner, sensitive to the number, position and distribution of mismatches. We also show that SpCas9-mediated cleavage is unaffected by DNA methylation and that the dosage of SpCas9 and sgRNA can be titrated to minimize off-target modification. To facilitate mammalian genome engineering applications, we provide a web-based software tool to guide the selection and validation of target sequences as well as off-target analyses.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/nbt.2647

Cites

29 of 29 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Off-target cleavages of Cas9 nucleases that cause oncogenic mutations in the genome have been reported extensively.

    “For example, off-target cleavages of the Cas9 nucleases that cause oncogenic mutations in the genome have been reported extensively [123,124].”

    From Utility of iPSC-Derived Cells for Disease Modeling, Drug Development, and Cell Therapy (2022) · cites this paper as [123]

    The paper’s Abstract reports SpCas9-induced indel mutations at predicted genomic off-target loci in human cells, supporting the off-target cleavage portion of the claim. It does not identify those mutations as oncogenic or report that oncogenic mutations from Cas9 off-target cleavage have been extensively documented. (LLM, conf=0.88)

    Experimental — accuracy not yet measured
  • The off-target sites are often sgRNA-dependent, since Cas9 is known to tolerate up to 3 mismatches between sgRNA and genomic DNA.

    “The off-target sites are often sgRNA-dependent, since Cas9 is known to tolerate up to 3 mismatches between sgRNA and genomic DNA (Fu et al., 2013; Hsu et al., 2013; Wang et al., 2016a).”

    From Off-target effects in CRISPR/Cas9 gene editing (2023) · cites this paper as Hsu et al., 2013

    The passages indexed under Abstract (no page provided) report sgRNA-dependent off-target cleavage and show that mismatch number and position affect Cas9 activity. They do not support an unqualified three-mismatch tolerance: three or more interspaced mismatches eliminated detectable cleavage at the vast majority of loci studied. (LLM, conf=0.84)

    Experimental — accuracy not yet measured
  • Off-target effects remain a major challenge for CRISPR/Cas systems in translational medicine.

    “Although CRISPR/Cas systems exhibit tremendous potential in translational medicine, off-target effects remain a major challenge (Fu et al., 2013; Hsu et al., 2013; Pacesa et al., 2022).”

    From Off-target effects in CRISPR/Cas9 gene editing (2023) · cites this paper as Hsu et al., 2013

    The paper’s Abstract (page unavailable) documents off-target editing in human cells and describes ways to minimize it, supporting the claim that off-target effects are a challenge for Cas9 genome editing. It does not specifically assess translational medicine or establish how major that challenge is in clinical use. (LLM, conf=0.81)

    Experimental — accuracy not yet measured
  • The MIT algorithm weights the position effect of mismatches in the sgRNA to generate a score to evaluate off-target effects.

    “The algorithm of MIT weights the position effect of the mismatches in the sgRNA to generate a score to evaluate off-target effects (Hsu et al., 2013; Haeussler et al., 2016).”

    From Off-target effects in CRISPR/Cas9 gene editing (2023) · cites this paper as Hsu et al., 2013

  • The PAM sequence adjacent to the target sequence greatly affects the editing efficiency and editing range of Cas9.

    “The PAM sequence adjacent to the target sequence greatly affects the editing efficiency and editing range of Cas9.”

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Hsu, P. D., Scott, D. A., Weinstein, J. A., Ran, F. A., Konermann, S., Agarwala, V., Li, Y., Fine, E. J., Wu, X., Shalem, O., Cradick, T. J., Marraffini, L. A., Bao, G., & Zhang, F.
Affiliations
  • Broad Institute (US)
  • Georgia Institute of Technology (US)
  • Koch Institute for Integrative Cancer Research At MIT (US)
  • Rockefeller University (US)
Corresponding author
Zhang, Feng
Venue
Nature Biotechnology
Published
2013-07-21
Volume
31
Issue
9
Pages
827-832
ISSN
  • 0733-222X (ISSN-L)
  • 1087-0156
  • 1546-1696
OpenAlex
W2036176224
Cited by
4,741
References
29
Citations by year
2026: 242 · 2025: 300 · 2024: 304 · 2023: 331 · 2022: 372 · 2021: 424 · 2020: 416 · 2019: 422 · 2018: 463 · 2017: 438 · 2016: 402 · 2015: 297 · 2014: 269 · 2013: 53
FWCI
152.56
Type
journal article
Language
en
Open access
Locations
  • Nature Biotechnology (publishedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
  • DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion)
  • PMC
Funders
  • National Science Foundation
  • Howard Hughes Medical Institute
  • Damon Runyon Cancer Research Foundation
  • McKnight Foundation
  • Life Sciences Research Foundation
  • National Institutes of Health (R01‐grant, GM34277)
  • Harvard Stem Cell Institute
  • National Institute of Mental Health (DP1MH100706)
  • National Eye Institute (PN2EY018244)
  • National Cancer Institute (R01CA133404)
  • National Institute of General Medical Sciences (R01GM034277, R01 GM34277, T32GM007753)
  • National Institute of Diabetes and Digestive and Kidney Diseases (R01DK097768)
  • National Center for Chronic Disease Prevention and Health Promotion (DP1‑MH100706)
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
SpCas9, single guide RNA, genome editing, off-target effects, mismatch tolerance, DNA methylation, indel mutations, guide RNA design, target site selection, HEK293T cells, web-based design tool
MeSH terms
Bacterial Proteins, Base Sequence, Deoxyribonucleases, DNA, Genetic Engineering, Molecular Sequence Data, Streptococcus pyogenes, Transcription Factors, Base Pair Mismatch, RNA, Small Untranslated

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review