The DOI matches its Crossref record; the references it cites are not checked yet.
Tools for experimental and computational analyses of off-target editing by programmable nucleases
Open accessAbstract
Genome editing using programmable nucleases is revolutionizing life science and medicine. Off-target editing by these nucleases remains a considerable concern, especially in therapeutic applications. Here we review tools developed for identifying potential off-target editing sites and compare the ability of these tools to properly analyze off-target effects. Recent advances in both in silico and experimental tools for off-target analysis have generated remarkably concordant results for sites with high off-target editing activity. However, no single tool is able to accurately predict low-frequency off-target editing, presenting a bottleneck in therapeutic genome editing, because even a small number of cells with off-target editing can be detrimental. Therefore, we recommend that at least one in silico tool and one experimental tool should be used together to identify potential off-target sites, and amplicon-based next-generation sequencing (NGS) should be used as the gold standard assay for assessing the true off-target effects at these candidate sites. Future work to improve off-target analysis includes expanding the true off-target editing dataset to evaluate new experimental techniques and to train machine learning algorithms; performing analysis using the particular genome of the cells in question rather than the reference genome; and applying novel NGS techniques to improve the sensitivity of amplicon-based off-target editing quantification.
Overview
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.
Integrity signals
Registry
Cites
Statistics
Verification
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.
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?
CRISPR/Cas9 off-target effects can be predicted by in silico tools, which are usually open-source online software conveniently accessed via internet.
“CRISPR/Cas9 off-target effects can be predicted by in silico tools, which are usually open-source online software that can be conveniently accessed via internet (Bao et al., 2021).”
From Off-target effects in CRISPR/Cas9 gene editing (2023) · cites this paper as Bao et al., 2021
The sections on bioinformatic prediction and CRISPR–Cas9 off-target site identification describe computational tools that identify and rank potential off-target sites. The paper mentions an E-CRISP website and makes its own processing scripts available on GitHub, but the passages do not establish that these prediction tools are usually open-source software accessible online. Page numbers are unavailable in our copy. (LLM, conf=0.84)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
The citation lists haven’t been fetched yet
References 143 · Cited by 106
Metadata
- Authors
- Bao, X. R., Pan, Y., Lee, C. M., Davis, T. H., & Bao, G.
- Affiliations
- Arsenal Biosciences (United States) (US)
- Rice University (US)
- University College Cork (IE)
- Corresponding author
- Bao, Gang
- Venue
- Nature Protocols
- Published
- 2020-12-07
- Volume
- 16
- Issue
- 1
- Pages
- 10-26
- ISSN
- 1750-2799 (ISSN-L)
- 1754-2189
- PMC
- PMC8049448
- OpenAlex
- W3111011311
- Cited by
- 106
- References
- 143
- Citations by year
- 2026: 22 · 2025: 17 · 2024: 27 · 2023: 19 · 2022: 13 · 2021: 8
- FWCI
- 1.01
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Nature Protocols (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Arrow@dit (Dublin Institute of Technology) (acceptedVersion)
- Cork Open Research Archive (University College Cork, Ireland) (submittedVersion)
- Funders
- U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (UG3HL151545, R01HL152314, OT2HL154977)
- Cancer Prevention and Research Institute of Texas (RR140081)
- 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
- off-target editing, programmable nucleases, genome editing, in silico analysis, therapeutic genome editing, machine learning
- MeSH terms
- Gene Editing, Animals, Endonucleases, Humans, Genomics, High-Throughput Nucleotide Sequencing, CRISPR-Cas Systems
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
