The DOI matches its Crossref record; 53 of the 54 references it cites were found in a registry or an index.
Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9
Open accessAbstract
CRISPR-Cas9–based genetic screens are a powerful new tool in biology. By simply altering the sequence of the single-guide RNA (sgRNA), one can reprogram Cas9 to target different sites in the genome with relative ease, but the on-target activity and off-target effects of individual sgRNAs can vary widely. Here, we use recently devised sgRNA design rules to create human and mouse genome-wide libraries, perform positive and negative selection screens and observe that the use of these rules produced improved results. Additionally, we profile the off-target activity of thousands of sgRNAs and develop a metric to predict off-target sites. We incorporate these findings from large-scale, empirical data to improve our computational design rules and create optimized sgRNA libraries that maximize on-target activity and minimize off-target effects to enable more effective and efficient genetic screens and genome engineering.
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?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Additionally, it can identify genes related to drug resistance in cancer cells and facilitate research on overcoming this resistance [8].”
From A Review of Research on CRISPR/Cas9 Gene Editing Technology in Disease Treatment (2024) · cites this paper as [8]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“The CFD algorithm is derived from a CRISPR/Cas9 genetic screen experiment that assessed the off-target effects of thousands of sgRNAs (Doench et al., 2016).”
From Off-target effects in CRISPR/Cas9 gene editing (2023) · cites this paper as Doench et al., 2016
The cited source says what the claim attributes to it.
In the citing paper
“Primarily, the sequence of sgRNAs is a crucial factor affecting on-target and off target efficiency.”
From Off-target effects in CRISPR/Cas9 gene editing (2023) · cites this paper as Doench et al., 2016
The cited source says what the claim attributes to it.
In the citing paper
“Different sgRNAs targeting the same gene locus can have distinct outcomes”
From Off-target effects in CRISPR/Cas9 gene editing (2023) · cites this paper as Doench et al., 2016
The cited source says what the claim attributes to it.
In the citing paper
“We used the STARS algorithm (Doench et al., 2016) to derive 38 hits, 18 of which were shared across at least two cell lines”
From Multimodal Analysis of Composition and Spatial Architecture in Human Squamous Cell Carcinoma (2020) · cites this paper as Doench et al., 2016
The cited source says what the claim attributes to it.
In the citing paper
“In addition, although our sgRNA pool was designed in silico to minimize the probability of SpCas9 off-target activity52, the GUIDE-seq assay for sgRNA+119 revealed 11 off-target sites throughout the genome (Supplementary Figs. 11h and 4d).”
From Allele specific repair of splicing mutations in cystic fibrosis through AsCas12a genome editing (2019) · cites this paper as [52]
The check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“Although TREM2 has been shown to bind to Aβ and facilitate its uptake80,81, the surface expression changes of other receptors involved in Aβ recognition and uptake might have counteracted the effects of increased TREM2 signaling upon INPP5D haploinsufficiency83,84.”
From INPP5D/SHIP1 regulates endo-lysosomal function and cargo-selective phagocytosis in human microglia (2025) · cites this paper as [83]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“However, Aβ can bind to lipoproteins such as clusterin (ApoJ) and ApoE in the brain82–84, which facilitates its clearance by microglia via TREM281.”
From INPP5D/SHIP1 regulates endo-lysosomal function and cargo-selective phagocytosis in human microglia (2025) · cites this paper as [83]
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
Cites
Fast gapped-read alignment with Bowtie 2
Langmead, B., & Salzberg, S. L. (2012) · Nature Methods · doi:10.1038/nmeth.1923 · Cited by 56,400
Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625
A Programmable Dual-RNA–Guided DNA Endonuclease in Adaptive Bacterial Immunity
Jinek, M., Chylinski, K., Fonfara, I., Hauer, M., Doudna, J. A., & Charpentier, E. (2012) · Science · doi:10.1126/science.1225829 · Cited by 17,116
Multiplex Genome Engineering Using CRISPR/Cas Systems
Cong, L., Ran, F. A., Cox, D., Lin, S., Barretto, R., Habib, N., Hsu, P. D., Wu, X., Jiang, W., Marraffini, L. A., et al. (2013) · Science · doi:10.1126/science.1231143 · Cited by 15,339
Statistical significance for genomewide studies
Storey, J. D., & Tibshirani, R. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1530509100 · Cited by 9,692
RNA-Guided Human Genome Engineering via Cas9
Mali, P., Yang, L., Esvelt, K. M., Aach, J., Guell, M., DiCarlo, J. E., Norville, J. E., & Church, G. M. (2013) · Science · doi:10.1126/science.1232033 · Cited by 9,210
The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity
Barretina, J., Caponigro, G., Stransky, N., Venkatesan, K., Margolin, A. A., Kim, S., Wilson, C. J., Lehár, J., Kryukov, G. V., Sonkin, D., et al. (2012) · Nature · doi:10.1038/nature11003 · Cited by 7,950
Molecular signatures database (MSigDB) 3.0
Liberzon, A., Subramanian, A., Pinchback, R., Thorvaldsdóttir, H., Tamayo, P., & Mesirov, J. P. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr260 · Cited by 7,111
Biopython: freely available python tools for computational molecular biology and bioinformatics
Cock, P. J. A., Antao, T., Chang, J. T., Chapman, B. A., Cox, C. J., Dalke, A., Friedberg, I., Hamelryck, T., Kauff, F., Wilczynski, B., et al. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp163 · Cited by 6,080
Improved vectors and genome-wide libraries for CRISPR screening
Sanjana, N. E., Shalem, O., & Zhang, F. (2014) · Nature Methods · doi:10.1038/nmeth.3047 · Cited by 5,239
Research works printed but not linked: 1
- Steiger, J.H. Tests for comparing elements of a correlation matrix. Psychol. Bull. 87, 245–251 (1980). · DOI · Paper page
Cited by
Sorted by citations
CRISPOR: intuitive guide selection for CRISPR/Cas9 genome editing experiments and screens
Concordet, J., & Haeussler, M. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky354 · Cited by 2,392
Genome editing with CRISPR–Cas nucleases, base editors, transposases and prime editors
Anzalone, A. V., Koblan, L. W., & Liu, D. R. (2020) · Nature Biotechnology · doi:10.1038/s41587-020-0561-9 · Cited by 2,237
CHOPCHOP v3: expanding the CRISPR web toolbox beyond genome editing
Labun, K., Montague, T. G., Krause, M., Cleuren, Y. N. T., Tjeldnes, H., & Valen, E. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz365 · Cited by 2,075
Meyers, R. M., Bryan, J. G., McFarland, J. M., Weir, B. A., Sizemore, A. E., Xu, H., Dharia, N. V., Montgomery, P. G., Cowley, G. S., Pantel, S., et al. (2017) · Nature Genetics · doi:10.1038/ng.3984 · Cited by 1,952
Self-citationHaeussler, M., Schönig, K., Eckert, H., Eschstruth, A., Mianné, J., Renaud, J.-B., Schneider-Maunoury, S., Shkumatava, A., Teboul, L., Kent, J., et al. (2016) · Genome biology · doi:10.1186/s13059-016-1012-2 · Cited by 1,756
Metadata
- Authors
- Doench, J. G., Fusi, N., Sullender, M., Hegde, M., Vaimberg, E. W., Donovan, K. F., Smith, I., Tothova, Z., Wilen, C., Orchard, R., Virgin, H. W., Listgarten, J., & Root, D. E.
- Affiliations
- Broad Institute (US)
- Washington University in St. Louis (US)
- Microsoft Research New England (United States) (US)
- Corresponding author
- Doench, John G
- Listgarten, Jennifer
- Root, David E
- ORCID
- Venue
- Nature Biotechnology
- Published
- 2016-01-18
- Volume
- 34
- Issue
- 2
- Pages
- 184-191
- ISSN
- 0733-222X (ISSN-L)
- 1087-0156
- 1546-1696
- PMC
- PMC4744125
- OpenAlex
- W2252568502
- Semantic Scholar
- b9e5fa707e804d6008e5011b058244437c656a93
- Cited by
- 4,637
- References
- 54
- Citations by year
- 2026: 494 · 2025: 658 · 2024: 569 · 2023: 572 · 2022: 538 · 2021: 499 · 2020: 463 · 2019: 337 · 2018: 258 · 2017: 170 · 2016: 75
- FWCI
- 144.68
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Biotechnology (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Cancer Institute (K12CA087723)
- National Institute of Allergy and Infectious Diseases (U19AI109725, T32AI007163)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › CRISPR and Genetic Engineering
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Interference and Gene Delivery
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA regulation and disease
- Keywords
- sgRNA design, CRISPR/Cas9, off-target effects, on-target activity, genetic screen, off-target prediction, genome editing, human genome, mouse genome
- MeSH terms
- RNA, Guide, CRISPR-Cas Systems, Animals, Drug Resistance, Genetic Engineering, Humans, Gene Library, Genome, Genomics, Cell Line, Tumor, Mice, 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
