Cited by 59CRISPR and Genetic EngineeringSingle-cell and spatial transcriptomicsCell Image Analysis Techniques

Pooled genetic perturbation screens with image-based phenotypes

Open access
Feldman, David, Funk, Luke, Le, Anna, Carlson, Rebecca J., Leiken, Michael D., Tsai, FuNien, Soong, Brian, Singh, Avtar +1 more·2022·Nature Protocols

Abstract

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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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
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
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

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