A network of human functional gene interactions from knockout fitness screens in cancer cells

Author:

Kim Eiru1,Dede Merve12,Lenoir Walter F12ORCID,Wang Gang1,Srinivasan Sanjana12,Colic Medina12,Hart Traver13ORCID

Affiliation:

1. Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

2. UTHealth Graduate School of Biomedical Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

3. Department of Cancer Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

Abstract

Genetic interactions mediate the emergence of phenotype from genotype. The systematic survey of genetic interactions in yeast showed that genes operating in the same biological process have highly correlated genetic interaction profiles, and this observation has been exploited to infer gene function in model organisms. Such assays of digenic perturbations in human cells are also highly informative, but are not scalable, even with CRISPR-mediated methods. As an alternative, we developed an indirect method of deriving functional interactions. We show that genes having correlated knockout fitness profiles across diverse, non-isogenic cell lines are analogous to genes having correlated genetic interaction profiles across isogenic query strains and similarly imply shared biological function. We constructed a network of genes with correlated fitness profiles across 276 high-quality CRISPR knockout screens in cancer cell lines into a “coessentiality network,” with up to 500-fold enrichment for co-functional gene pairs, enabling strong inference of gene function and highlighting the modular organization of the cell.

Funder

NIH/NCI

Cancer Prevention Research Institute of Texas

NIH/NIGMS

Prostate Cancer Foundation

Publisher

Life Science Alliance, LLC

Subject

Health, Toxicology and Mutagenesis,Plant Science,Biochemistry, Genetics and Molecular Biology (miscellaneous),Ecology

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