MIT Libraries logoDSpace@MIT

MIT
View Item 
  • DSpace@MIT Home
  • MIT Open Access Articles
  • MIT Open Access Articles
  • View Item
  • DSpace@MIT Home
  • MIT Open Access Articles
  • MIT Open Access Articles
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Pooled genetic perturbation screens with image-based phenotypes

Author(s)
Feldman, David; Funk, Luke; Le, Anna; Carlson, Rebecca J; Leiken, Michael D; Tsai, FuNien; Soong, Brian; Singh, Avtar; Blainey, Paul C; ... Show more Show less
Thumbnail
DownloadPublished version (2.108Mb)
Publisher with Creative Commons License

Publisher with Creative Commons License

Creative Commons Attribution

Terms of use
Creative Commons Attribution 4.0 International license https://creativecommons.org/licenses/by/4.0/
Metadata
Show full item record
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.
Date issued
2022
URI
https://hdl.handle.net/1721.1/147776
Department
Massachusetts Institute of Technology. Department of Biological Engineering
Journal
Nature Protocols
Publisher
Springer Science and Business Media LLC
Citation
Feldman, David, Funk, Luke, Le, Anna, Carlson, Rebecca J, Leiken, Michael D et al. 2022. "Pooled genetic perturbation screens with image-based phenotypes." Nature Protocols, 17 (2).
Version: Final published version

Collections
  • MIT Open Access Articles

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

Login

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries
PrivacyPermissionsAccessibilityContact us
MIT
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.