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.
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CRISPR/Cas9 can identify genes related to drug resistance in cancer cells and facilitate research on overcoming this resistance.
“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]
The Results section (“Genetic screens with the Avana and Asiago libraries”; page unavailable) reports CRISPR screens in melanoma cells that identified and validated genes associated with resistance to vemurafenib. The Discussion says improved sgRNA design will facilitate further screening, but our copy does not specifically address research on overcoming drug resistance. (LLM, conf=0.82)
Experimental — accuracy not yet measuredThe CFD algorithm is derived from a CRISPR/Cas9 genetic screen experiment that assessed the off-target effects of thousands of sgRNAs.
“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 sequence of sgRNAs is a crucial factor affecting on-target and off-target efficiency.
“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
Different sgRNAs targeting the same gene locus can have distinct outcomes.
“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 STARS algorithm derived 38 hits, 18 of which were shared across at least two cell lines.
“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
GUIDE-seq assay for sgRNA+119 revealed 11 off-target sites throughout the genome.
“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]
Surface expression changes of other receptors involved in Aβ recognition and uptake might have counteracted the effects of increased TREM2 signaling upon INPP5D haploinsufficiency.
“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]
The Results sections on genetic screens and sgRNA off-target effects discuss CRISPR screening, not Aβ uptake or receptor expression. Searches for INPP5D, TREM2, and amyloid-beta uptake found no passage addressing the proposed counteracting effect; the indexed passages have no page numbers. (LLM, conf=0.78)
Experimental — accuracy not yet measuredAβ can bind to lipoproteins such as clusterin (ApoJ) and ApoE in the brain, which facilitates its clearance by microglia via TREM2.
“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]
The Results section on genetic screens discusses interferon signaling in BV2 cells, not amyloid-β clearance. The only microglia-related item found is a title in the References; searches for Aβ binding to clusterin or ApoE and for TREM2-mediated clearance found no passage addressing the claim. Page numbers are unavailable in our copy. (LLM, conf=0.78)
Experimental — accuracy not yet measured
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Chui, A. J., Okondo, M. C., Rao, S. D., Gai, K., Griswold, A. R., Johnson, D. C., Ball, D. P., Taabazuing, C. Y., Orth-He, E. L., Vittimberga, B. A., et al. (2019) · Science · doi:10.1126/science.aau1208 · Cited by 300 · see citing works
- 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 · 2015: 1
- 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
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