Pooled genetic perturbation screens with image-based phenotypes
Open accessAbstract
Discovery of the genetic components underpinning fundamental and disease-related processes is being rapidly accelerated by combining efficient, programmable genetic engineering with phenotypic readouts of high spatial, temporal and/or molecular resolution. Microscopy is a fundamental tool for studying cell biology, but its lack of high-throughput sequence readouts hinders integration in large-scale genetic screens. Optical pooled screens using in situ sequencing provide massively scalable integration of barcoded lentiviral libraries (e.g., CRISPR perturbation libraries) with high-content imaging assays, including dynamic processes in live cells. The protocol uses standard lentiviral vectors and molecular biology, providing single-cell resolution of phenotype and engineered genotype, scalability to millions of cells and accurate sequence reads sufficient to distinguish >10 6 perturbations. In situ amplification takes ~2 d, while sequencing can be performed in ~1.5 h per cycle. The image analysis pipeline provided enables fully parallel automated sequencing analysis using a cloud or cluster computing environment.
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Measurements can be coupled with systematic perturbations.
“along with the ability to couple these measurements with systematic perturbations.27–29”
From How to build the virtual cell with artificial intelligence: Priorities and opportunities (2024) · cites this paper as [29]
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- Authors
- Feldman, D., Funk, L., Le, A., Carlson, R. J., Leiken, M. D., Tsai, F., Soong, B., Singh, A., & Blainey, P. C.
- Affiliations
- Broad Institute (US)
- Corresponding author
- Blainey, Paul C.
- Venue
- Nature Protocols
- Published
- 2022-01-12
- Volume
- 17
- Issue
- 2
- Pages
- 476-512
- ISSN
- 1750-2799 (ISSN-L)
- 1754-2189
- PMC
- PMC9654597
- OpenAlex
- W4206247338
- Cited by
- 59
- References
- 75
- Citations by year
- 2026: 11 · 2025: 19 · 2024: 14 · 2023: 9 · 2022: 6
- FWCI
- 3.92
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Nature Protocols (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
- Funders
- U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute (HG006193)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › CRISPR and Genetic Engineering
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Cell Image Analysis Techniques
- Keywords
- CRISPR screen, in situ sequencing, high-content imaging, live-cell imaging, automated image analysis, single-cell resolution, high-throughput screening
- MeSH terms
- RNA, Guide, CRISPR-Cas Systems, Genetic Testing, Humans, Image Processing, Computer-Assisted, Phenotype, Gene Library, Lentivirus, RNA, Guide, Kinetoplastida, High-Throughput Nucleotide Sequencing
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 ›
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