Large‐scale image‐based profiling of single‐cell phenotypes in arrayed CRISPR‐Cas9 gene perturbation screens
Abstract High‐content imaging using automated microscopy and computer vision allows multivariate profiling of single‐cell phenotypes. Here, we present methods for the application of the CISPR‐Cas9 system in large‐scale, image‐based, gene perturbation experiments. We show that CRISPR‐Cas9‐mediated ge...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Springer Nature
2018-01-01
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| Series: | Molecular Systems Biology |
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| Online Access: | https://doi.org/10.15252/msb.20178064 |
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| _version_ | 1849738657114619904 |
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| author | Reinoud de Groot Joel Lüthi Helen Lindsay René Holtackers Lucas Pelkmans |
| author_facet | Reinoud de Groot Joel Lüthi Helen Lindsay René Holtackers Lucas Pelkmans |
| author_sort | Reinoud de Groot |
| collection | DOAJ |
| description | Abstract High‐content imaging using automated microscopy and computer vision allows multivariate profiling of single‐cell phenotypes. Here, we present methods for the application of the CISPR‐Cas9 system in large‐scale, image‐based, gene perturbation experiments. We show that CRISPR‐Cas9‐mediated gene perturbation can be achieved in human tissue culture cells in a timeframe that is compatible with image‐based phenotyping. We developed a pipeline to construct a large‐scale arrayed library of 2,281 sequence‐verified CRISPR‐Cas9 targeting plasmids and profiled this library for genes affecting cellular morphology and the subcellular localization of components of the nuclear pore complex (NPC). We conceived a machine‐learning method that harnesses genetic heterogeneity to score gene perturbations and identify phenotypically perturbed cells for in‐depth characterization of gene perturbation effects. This approach enables genome‐scale image‐based multivariate gene perturbation profiling using CRISPR‐Cas9. |
| format | Article |
| id | doaj-art-e67e8fc76407428ca04ef6ee6d6bb2f7 |
| institution | DOAJ |
| issn | 1744-4292 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Springer Nature |
| record_format | Article |
| series | Molecular Systems Biology |
| spelling | doaj-art-e67e8fc76407428ca04ef6ee6d6bb2f72025-08-20T03:06:29ZengSpringer NatureMolecular Systems Biology1744-42922018-01-0114111010.15252/msb.20178064Large‐scale image‐based profiling of single‐cell phenotypes in arrayed CRISPR‐Cas9 gene perturbation screensReinoud de Groot0Joel Lüthi1Helen Lindsay2René Holtackers3Lucas Pelkmans4Institute of Molecular Life Sciences, University of ZürichInstitute of Molecular Life Sciences, University of ZürichInstitute of Molecular Life Sciences, University of ZürichInstitute of Molecular Life Sciences, University of ZürichInstitute of Molecular Life Sciences, University of ZürichAbstract High‐content imaging using automated microscopy and computer vision allows multivariate profiling of single‐cell phenotypes. Here, we present methods for the application of the CISPR‐Cas9 system in large‐scale, image‐based, gene perturbation experiments. We show that CRISPR‐Cas9‐mediated gene perturbation can be achieved in human tissue culture cells in a timeframe that is compatible with image‐based phenotyping. We developed a pipeline to construct a large‐scale arrayed library of 2,281 sequence‐verified CRISPR‐Cas9 targeting plasmids and profiled this library for genes affecting cellular morphology and the subcellular localization of components of the nuclear pore complex (NPC). We conceived a machine‐learning method that harnesses genetic heterogeneity to score gene perturbations and identify phenotypically perturbed cells for in‐depth characterization of gene perturbation effects. This approach enables genome‐scale image‐based multivariate gene perturbation profiling using CRISPR‐Cas9.https://doi.org/10.15252/msb.20178064arrayed libraryCRISPR‐Cas9functional genomicsnuclear pore complexsingle‐cell phenotypic profiling |
| spellingShingle | Reinoud de Groot Joel Lüthi Helen Lindsay René Holtackers Lucas Pelkmans Large‐scale image‐based profiling of single‐cell phenotypes in arrayed CRISPR‐Cas9 gene perturbation screens Molecular Systems Biology arrayed library CRISPR‐Cas9 functional genomics nuclear pore complex single‐cell phenotypic profiling |
| title | Large‐scale image‐based profiling of single‐cell phenotypes in arrayed CRISPR‐Cas9 gene perturbation screens |
| title_full | Large‐scale image‐based profiling of single‐cell phenotypes in arrayed CRISPR‐Cas9 gene perturbation screens |
| title_fullStr | Large‐scale image‐based profiling of single‐cell phenotypes in arrayed CRISPR‐Cas9 gene perturbation screens |
| title_full_unstemmed | Large‐scale image‐based profiling of single‐cell phenotypes in arrayed CRISPR‐Cas9 gene perturbation screens |
| title_short | Large‐scale image‐based profiling of single‐cell phenotypes in arrayed CRISPR‐Cas9 gene perturbation screens |
| title_sort | large scale image based profiling of single cell phenotypes in arrayed crispr cas9 gene perturbation screens |
| topic | arrayed library CRISPR‐Cas9 functional genomics nuclear pore complex single‐cell phenotypic profiling |
| url | https://doi.org/10.15252/msb.20178064 |
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