Pooled genetic perturbation screens with image-based phenotypes
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 studyi...
| Main Authors: | , , , , , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Springer Science and Business Media LLC
2023
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| Online Access: | https://hdl.handle.net/1721.1/147776 |
| _version_ | 1826209551487074304 |
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| author | Feldman, David Funk, Luke Le, Anna Carlson, Rebecca J Leiken, Michael D Tsai, FuNien Soong, Brian Singh, Avtar Blainey, Paul C |
| author2 | Massachusetts Institute of Technology. Department of Biological Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Biological Engineering Feldman, David Funk, Luke Le, Anna Carlson, Rebecca J Leiken, Michael D Tsai, FuNien Soong, Brian Singh, Avtar Blainey, Paul C |
| author_sort | Feldman, David |
| collection | MIT |
| description | 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. |
| first_indexed | 2024-09-23T14:24:18Z |
| format | Article |
| id | mit-1721.1/147776 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T14:24:18Z |
| publishDate | 2023 |
| publisher | Springer Science and Business Media LLC |
| record_format | dspace |
| spelling | mit-1721.1/1477762023-02-01T03:17:40Z 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 Massachusetts Institute of Technology. Department of Biological Engineering 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. 2023-01-30T14:08:36Z 2023-01-30T14:08:36Z 2022 2023-01-30T14:03:28Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/147776 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). en 10.1038/S41596-021-00653-8 Nature Protocols Creative Commons Attribution 4.0 International license https://creativecommons.org/licenses/by/4.0/ application/pdf Springer Science and Business Media LLC Nature |
| spellingShingle | Feldman, David Funk, Luke Le, Anna Carlson, Rebecca J Leiken, Michael D Tsai, FuNien Soong, Brian Singh, Avtar Blainey, Paul C Pooled genetic perturbation screens with image-based phenotypes |
| title | Pooled genetic perturbation screens with image-based phenotypes |
| title_full | Pooled genetic perturbation screens with image-based phenotypes |
| title_fullStr | Pooled genetic perturbation screens with image-based phenotypes |
| title_full_unstemmed | Pooled genetic perturbation screens with image-based phenotypes |
| title_short | Pooled genetic perturbation screens with image-based phenotypes |
| title_sort | pooled genetic perturbation screens with image based phenotypes |
| url | https://hdl.handle.net/1721.1/147776 |
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