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A network of human functional gene interactions from knockout fitness screens in cancer cells.
Kim, Eiru; Dede, Merve; Lenoir, Walter F; Wang, Gang; Srinivasan, Sanjana; Colic, Medina; Hart, Traver.
Afiliación
  • Kim E; Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Dede M; Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Lenoir WF; UTHealth Graduate School of Biomedical Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Wang G; Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Srinivasan S; UTHealth Graduate School of Biomedical Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Colic M; Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Hart T; Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Life Sci Alliance ; 2(2)2019 04.
Article en En | MEDLINE | ID: mdl-30979825
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.
Asunto(s)

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Redes Reguladoras de Genes / Técnicas de Inactivación de Genes / Neoplasias Límite: Humans Idioma: En Revista: Life Sci Alliance Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Redes Reguladoras de Genes / Técnicas de Inactivación de Genes / Neoplasias Límite: Humans Idioma: En Revista: Life Sci Alliance Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos