A method for benchmarking genetic screens reveals a predominant mitochondrial bias

Mahfuzur Rahman, Maximilian Billmann, Michael Costanzo, Michael Aregger, Amy H.Y. Tong, Katherine Chan, Henry N. Ward, Kevin R. Brown, Brenda J. Andrews, Charles Boone, Jason Moffat, Chad L. Myers

Research output: Contribution to journalArticlepeer-review

Abstract

We present FLEX (Functional evaluation of experimental perturbations), a pipeline that leverages several functional annotation resources to establish reference standards for benchmarking human genome-wide CRISPR screen data and methods for analyzing them. FLEX provides a quantitative measurement of the functional information captured by a given gene-pair dataset and a means to explore the diversity of functions captured by the input dataset. We apply FLEX to analyze data from the diverse cell line screens generated by the DepMap project. We identify a predominant mitochondria-associated signal within co-essentiality networks derived from these data and explore the basis of this signal. Our analysis and time-resolved CRISPR screens in a single cell line suggest that the variable phenotypes associated with mitochondria genes across cells may reflect screen dynamics and protein stability effects rather than genetic dependencies. We characterize this functional bias and demonstrate its relevance for interpreting differential hits in any CRISPR screening context. More generally, we demonstrate the utility of the FLEX pipeline for performing robust comparative evaluations of CRISPR screens or methods for processing them.

Original languageEnglish (US)
Article numbere10013
JournalMolecular Systems Biology
Volume17
Issue number5
DOIs
StatePublished - May 2021
Externally publishedYes

Bibliographical note

Funding Information:
We thank members of the Myers, Moffat, Boone, and Andrews laboratory for fruitful discussions. This research was funded by grants from the National Science Foundation (MCB 1818293), the National Institutes of Health (R01HG005084, R01HG005853), the Canadian Institutes for Health Research (MOP‐142375), Ontario Research Fund, Genome Canada (Bioinformatics and Computational Biology program), and the Canada Research Chairs Program. M.B. was supported by a DFG Fellowship (Bi 2086/1‐1).

Publisher Copyright:
© 2021 The Authors. Published under the terms of the CC BY 4.0 license

Keywords

  • CRISPR screens
  • computational evaluation
  • electron transport chain

PubMed: MeSH publication types

  • Journal Article

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