A genome-wide atlas of human cell morphology
A key challenge of the modern genomics era is developing empirical data-driven representations of gene function. Here we present the first unbiased morphology-based genome-wide perturbation atlas in human cells, containing three genome-wide genotype-phenotype maps comprising CRISPR-Cas9-based knockouts of >20,000 genes in >30 million cells. Our optical pooled cell profiling platform (PERISCOPE) combines a destainable high-dimensional phenotyping panel (based on Cell Painting) with optical sequencing of molecular barcodes and a scalable open-source analysis pipeline to facilitate massively parallel screening of pooled perturbation libraries. This perturbation atlas comprises high-dimensional phenotypic profiles of individual cells with sufficient resolution to cluster thousands of human genes, reconstruct known pathways and protein-protein interaction networks, interrogate subcellular processes and identify culture media-specific responses. Using this atlas, we identify the poorly characterized disease-associated TMEM251/LYSET as a Golgi-resident transmembrane protein essential for mannose-6-phosphate-dependent trafficking of lysosomal enzymes. In sum, this perturbation atlas and screening platform represents a rich and accessible resource for connecting genes to cellular functions at scale.
Authors
- Celeste Diaz (ORCID: https://orcid.org/0000-0002-1365-2425)
- Calvin H. Jan (ORCID: https://orcid.org/0000-0001-9033-4028)
- Meraj Ramezani (ORCID: https://orcid.org/0000-0002-2906-4986)
- Joaquín Pérez‐Schindler (ORCID: https://orcid.org/0000-0003-3141-8859)
- Paul C. Blainey (ORCID: https://orcid.org/0000-0002-4889-8783)
- María E. Lozada
- Erin Weisbart (ORCID: https://orcid.org/0000-0002-6437-2458)
- Thiago M. Batista (ORCID: https://orcid.org/0000-0001-6971-1191)
- Beth A. Cimini (ORCID: https://orcid.org/0000-0001-9640-9318)
- Melina Claussnitzer (ORCID: https://orcid.org/0000-0003-2450-736X)
- Anne E. Carpenter (ORCID: https://orcid.org/0000-0003-1555-8261)
- James T. Neal (ORCID: https://orcid.org/0000-0002-3962-8570)
- John Yong (ORCID: https://orcid.org/0000-0002-4914-2259)
- Sanam L. Kavari (ORCID: https://orcid.org/0000-0002-1224-733X)
- Avtar Singh (ORCID: https://orcid.org/0000-0001-5509-8330)
- Shantanu Singh (ORCID: https://orcid.org/0000-0003-3150-3025)
- Julia Bauman (ORCID: https://orcid.org/0000-0001-9488-529X)
- Marzieh Haghighi
- Gregory P. Way (ORCID: https://orcid.org/0000-0002-0503-9348)
- Eddy Leardini (ORCID: https://orcid.org/0009-0004-8090-0355)
- Gunjan Jetley
- Jenlu Pagnotta (ORCID: https://orcid.org/0000-0001-5027-2256)
Institutions
- Broad Institute (US)
- Foundation Center (US)
- Massachusetts General Hospital (US)
- Novo Nordisk (United States) (US)
- IIT@MIT (US)
- Allen Institute (US)
- University of Pennsylvania (US)
- Stanford University (US)
Publication Details
- Journal
- Nature Methods
- Published
- 2025-01-27
- DOI
- https://doi.org/10.1038/s41592-024-02537-7
- Citations
- 37
- Primary Topic
- Cell Image Analysis Techniques
- Type
- article
- Field-Weighted Citation Impact
- 58.82
Funders
- Novo Nordisk Fonden
- National Institute of General Medical Sciences