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Pooled genetic perturbation screens with image-based phenotypes.
Feldman, David; Funk, Luke; Le, Anna; Carlson, Rebecca J; Leiken, Michael D; Tsai, FuNien; Soong, Brian; Singh, Avtar; Blainey, Paul C.
Affiliation
  • Feldman D; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Funk L; Department of Biochemistry and Institute for Protein Design, University of Washington, Seattle, WA, USA.
  • Le A; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Carlson RJ; Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Leiken MD; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Tsai F; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
  • Soong B; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Singh A; Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Blainey PC; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Nat Protoc ; 17(2): 476-512, 2022 02.
Article in En | MEDLINE | ID: mdl-35022620
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 >106 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.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: RNA, Guide, Kinetoplastida Language: En Journal: Nat Protoc Year: 2022 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: RNA, Guide, Kinetoplastida Language: En Journal: Nat Protoc Year: 2022 Document type: Article