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Genome-Scale CRISPR-Mediated Control of Gene Repression and Activation
Open accessAbstract
While the catalog of mammalian transcripts and their expression levels in different cell types and disease states is rapidly expanding, our understanding of transcript function lags behind. We present a robust technology enabling systematic investigation of the cellular consequences of repressing or inducing individual transcripts. We identify rules for specific targeting of transcriptional repressors (CRISPRi), typically achieving 90%-99% knockdown with minimal off-target effects, and activators (CRISPRa) to endogenous genes via endonuclease-deficient Cas9. Together they enable modulation of gene expression over a ∼1,000-fold range. Using these rules, we construct genome-scale CRISPRi and CRISPRa libraries, each of which we validate with two pooled screens. Growth-based screens identify essential genes, tumor suppressors, and regulators of differentiation. Screens for sensitivity to a cholera-diphtheria toxin provide broad insights into the mechanisms of pathogen entry, retrotranslocation and toxicity. Our results establish CRISPRi and CRISPRa as powerful tools that provide rich and complementary information for mapping complex pathways.
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“Compared with gain-of-function perturbations, a higher proportion of loss-of-function perturbations yield phenotypes in growth and chemical-genetic screens, especially for members of protein complexes (Gilbert et al., 2014; Horlbeck et al., 2016).”
From Mapping information-rich genotype-phenotype landscapes with genome-scale Perturb-seq (2022) · cites this paper as Gilbert et al., 2014
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“For example, CRISPRi (interference)23–25 and CRISPRa (activation)26–30 technologies utilize catalytically inactive Cas9 (dCas9) fused to either a transcriptional repressor (e.g., KRAB, Krüppel associated box) or a transcriptional activator (e.g., VPR, VP64-p65-Rta).”
From Large-scale CRISPR screening in primary human 3D gastric organoids enables comprehensive dissection of gene-drug interactions (2025) · cites this paper as [28]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“Alternatives to DNA cleavage-induced editing include using CRISPR-Cas9 for direct chemical sequence alteration (base editing) 25,26 , providing RNA templates for gene alteration (prime editing) 27,28 , and for transcriptional control (CRISPR interference, CRISPRi; CRISPR activation, CRISPRa) 29,30 (Fig. 3).”
From The promise and challenge of therapeutic genome editing (2020) · cites this paper as [30]
Experimental — accuracy not yet measuredIn the citing paper
“Pooling gene perturbations greatly improves scalability, but is not compatible with imaging of complex and dynamic cellular phenotypes.”
From Optical Pooled Screens in Human Cells (2019) · cites this paper as Gilbert et al., 2014
In the citing paper
“Striking examples are familial mutations causing neurodegenerative diseases, such as hereditary motor and sensory neuropathies (Charcot-Marie-Tooth disease), which can be caused by mutations in ubiquitously expressed trafficking factors (RAB7A, DNM2, DYNC1H1), or aminoacyl-tRNA synthetases (AARS, GARS, HARS, MARS)2.”
From Genome-wide CRISPRi/a screens in human neurons link lysosomal failure to ferroptosis (2021) · cites this paper as [2]
In the citing paper
“In addition to gene expression, gene function can also be cell type-specific, as evidenced by the fact that mutations in broadly expressed or housekeeping genes can lead to cell-type specific defects and disease states.”
From Genome-wide CRISPRi/a screens in human neurons link lysosomal failure to ferroptosis (2021) · cites this paper as [2]
In the citing paper
“CRISPRa evaluates gain-of-function phenotypes and can provide complementary insight to CRISPR knockout or CRISPRi-based loss-of-function screens42.”
From CRISPR-based functional genomics for neurological disease (2020) · cites this paper as [42]
In the citing paper
“CRISPRi-based gene knockdown may result in weaker phenotypes than full gene knockout, however it is non-toxic in iPSCs and iPSC-derived cells76, inducible76 and reversible42, thereby enabling time-resolved analysis of gene function76.”
From CRISPR-based functional genomics for neurological disease (2020) · cites this paper as [42]
In the citing paper
“CRISPRi represents an important advance over RNAi, since it lacks the pervasive off-target effects (Gilbert et al., 2014) inherent to RNAi-based screening approaches (Adamson et al., 2012; Jackson et al., 2003; Kaelin, 2012).”
From CRISPR Interference-Based Platform for Multimodal Genetic Screens in Human iPSC-Derived Neurons (2019) · cites this paper as Gilbert et al., 2014
In the citing paper
“Second, it is inducible and reversible (Gilbert et al., 2014)”
From CRISPR Interference-Based Platform for Multimodal Genetic Screens in Human iPSC-Derived Neurons (2019) · cites this paper as Gilbert et al., 2014
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Metadata
- Authors
- Gilbert, L. A., Horlbeck, M. A., Adamson, B., Villalta, J. E., Chen, Y., Whitehead, E. H., Guimaraes, C., Panning, B., Ploegh, H. L., Bassik, M. C., Qi, L. S., Kampmann, M., & Weissman, J. S.
- Affiliations
- QB3 (US)
- University of California, San Francisco (US)
- Whitehead Institute for Biomedical Research (US)
- Corresponding author
- Kampmann, Martin
- Weissman, Jonathan S.
- ORCID
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2014-10
- Volume
- 159
- Issue
- 3
- Pages
- 647-661
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC4253859
- OpenAlex
- W2152505144
- Cited by
- 2,728
- References
- 60
- Citations by year
- 2026: 190 · 2025: 211 · 2024: 265 · 2023: 212 · 2022: 261 · 2021: 285 · 2020: 285 · 2019: 255 · 2018: 221 · 2017: 214 · 2016: 182 · 2015: 125 · 2014: 14
- FWCI
- 73.17
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc-nd)
- eScholarship (California Digital Library) (submittedVersion)
- PMC
- Funders
- Howard Hughes Medical Institute
- National Institutes of Health (DP5OD017887, 1dp2hd084069-01)
- National Institute on Aging (P01AG010770)
- National Institute on Drug Abuse (R01DA036858)
- National Cancer Institute (K99CA181494, U01CA168370)
- National Institute of General Medical Sciences (T32GM008284, P50GM081879, R01GM100341, P50GM102706, R01GM100518)
- National Institute of Biomedical Imaging and Bioengineering (T32EB009383)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › CRISPR and Genetic Engineering
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Interference and Gene Delivery
- Keywords
- CRISPR interference, CRISPR activation, transcriptional repression, transcriptional activation, gene essentiality, tumor suppressor, cholera toxin, diphtheria toxin, pathogen entry, retrotranslocation, off-target effects
- MeSH terms
- Cell Line, Cholera Toxin, Diphtheria Toxin, Genetic Techniques, Humans, Transcription, Genetic, Genome, Human, 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.
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