Mapping information-rich genotype-phenotype landscapes with genome-scale Perturb-seq

Joseph M Replogle; Reuben A Saunders; Angela N Pogson; Jeffrey A Hussmann; Alexander Lenail; Alina Guna; Lauren Mascibroda; Eric J Wagner; Karen Adelman; Gila Lithwick-Yanai; Nika Iremadze; Florian Oberstrass; Doron Lipson; Jessica L Bonnar; Marco Jost; Thomas M Norman; Jonathan S Weissman

doi:10.1016/j.cell.2022.05.013

Mapping information-rich genotype-phenotype landscapes with genome-scale Perturb-seq

Cell. 2022 Jul 7;185(14):2559-2575.e28. doi: 10.1016/j.cell.2022.05.013. Epub 2022 Jun 9.

Authors

Joseph M Replogle¹, Reuben A Saunders², Angela N Pogson³, Jeffrey A Hussmann³, Alexander Lenail⁴, Alina Guna⁵, Lauren Mascibroda⁶, Eric J Wagner⁷, Karen Adelman⁸, Gila Lithwick-Yanai⁹, Nika Iremadze⁹, Florian Oberstrass⁹, Doron Lipson⁹, Jessica L Bonnar³, Marco Jost¹⁰, Thomas M Norman¹¹, Jonathan S Weissman¹²

Affiliations

¹ Medical Scientist Training Program, University of California, San Francisco, San Francisco, CA 94158, USA; Tetrad Graduate Program, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA; Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA 02142, USA; Whitehead Institute for Biomedical Research, Massachusetts Institute of Technology, Cambridge, MA 02142, USA.
² Tetrad Graduate Program, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA; Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA 02142, USA; Whitehead Institute for Biomedical Research, Massachusetts Institute of Technology, Cambridge, MA 02142, USA.
³ Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA; Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA 02142, USA; Whitehead Institute for Biomedical Research, Massachusetts Institute of Technology, Cambridge, MA 02142, USA.
⁴ Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA 02142, USA; Whitehead Institute for Biomedical Research, Massachusetts Institute of Technology, Cambridge, MA 02142, USA.
⁵ Whitehead Institute for Biomedical Research, Massachusetts Institute of Technology, Cambridge, MA 02142, USA.
⁶ Department of Biochemistry & Molecular Biology, The University of Texas Medical Branch at Galveston, Galveston, TX 77555, USA.
⁷ Department of Biochemistry & Molecular Biology, The University of Texas Medical Branch at Galveston, Galveston, TX 77555, USA; Department of Biochemistry & Biophysics, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA.
⁸ Department of Biological Chemistry and Molecular Pharmacology, Blavatnik Institute, Harvard Medical School, Boston, MA 02115, USA.
⁹ Ultima Genomics, Newark, CA 94560, USA.
¹⁰ Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Microbiology, Harvard Medical School, Boston, MA 02115, USA.
¹¹ Program for Computational and Systems Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA. Electronic address: normantm@mskcc.org.
¹² Department of Cellular and Molecular Pharmacology, University of California, San Francisco, San Francisco, CA 94158, USA; Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA 02142, USA; Whitehead Institute for Biomedical Research, Massachusetts Institute of Technology, Cambridge, MA 02142, USA; David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02142, USA; Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02142, USA. Electronic address: weissman@wi.mit.edu.

Abstract

A central goal of genetics is to define the relationships between genotypes and phenotypes. High-content phenotypic screens such as Perturb-seq (CRISPR-based screens with single-cell RNA-sequencing readouts) enable massively parallel functional genomic mapping but, to date, have been used at limited scales. Here, we perform genome-scale Perturb-seq targeting all expressed genes with CRISPR interference (CRISPRi) across >2.5 million human cells. We use transcriptional phenotypes to predict the function of poorly characterized genes, uncovering new regulators of ribosome biogenesis (including CCDC86, ZNF236, and SPATA5L1), transcription (C7orf26), and mitochondrial respiration (TMEM242). In addition to assigning gene function, single-cell transcriptional phenotypes allow for in-depth dissection of complex cellular phenomena-from RNA processing to differentiation. We leverage this ability to systematically identify genetic drivers and consequences of aneuploidy and to discover an unanticipated layer of stress-specific regulation of the mitochondrial genome. Our information-rich genotype-phenotype map reveals a multidimensional portrait of gene and cellular function.

Keywords: CRISPR; Integrator complex; Perturb-seq; cell biology; chromosomal instability; genetic screens; genotype-phenotype map; mitochondrial genome stress response; single-cell RNA sequencing.

Publication types

Research Support, Non-U.S. Gov't
Research Support, N.I.H., Extramural

MeSH terms

CRISPR-Cas Systems / genetics
Chromosome Mapping
Genomics*
Genotype
Phenotype
Single-Cell Analysis* / methods

Abstract

Publication types

MeSH terms

Grants and funding