4.8 Article

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

Journal

CELL
Volume 185, Issue 14, Pages 2559-+

Publisher

CELL PRESS
DOI: 10.1016/j.cell.2022.05.013

Keywords

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Funding

  1. DARPA [HR0011-19-2-0007]
  2. NIH [1RM1 HG009490-01, P30 CA008748, R00-GM130964, R01-GM134539, F31-NS115380]
  3. Howard Hughes Medical Institute
  4. Chan Zuckerberg Initiative
  5. Ludwig Center at MIT
  6. NIH 1DP2 [GM140925-01]
  7. NHGRI [R44HG010558, R44-HG011060]
  8. Fannie and John Hertz Foundation Fellowship
  9. NSF Graduate Research Fellowship

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Understanding the relationships between genotypes and phenotypes is a central goal in genetics. This study demonstrates the use of a high-content phenotypic screening technique, Perturb-seq, to analyze over 2.5 million human cells at a genome-wide scale. Through this analysis, new gene functions and complex cellular phenomena were revealed.
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.

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