Unbiased reconstruction of a mammalian transcriptional network mediating pathogen responses

Ido Arnit, Manuel Garber, Nicolas Chevrier, Ana Paula Leite, Yoni Donner, Thomas Eisenhaure, Mitchell Guttman, Jennifer K. Grenier, Weibo Li, Or Zuk, Lisa A. Schubert, Brian Birditt, Tal Shay, Alon Goren, Xiaolan Zhang, Zachary Smith, Raquel Deering, Rebecca C. McDonald, Moran Cabili, Bradley E. BernsteinJohn L. Rinn, Alex Meissner, David E. Root, Nir Hacohen A. Hacohen, Aviv Regev

Research output: Contribution to journalArticlepeer-review

404 Scopus citations

Abstract

Models of mammalian regulatory networks controlling gene expression have been inferred from genomic data but have largely not been validated. We present an unbiased strategy to systematically perturb candidate regulators and monitor cellular transcriptional responses. We applied this approach to derive regulatory networks that control the transcriptional response of mouse primary dendritic cells to pathogens. Our approach revealed the regulatory functions of 125 transcription factors, chromatin modifiers, and RNA binding proteins, which enabled the construction of a network model consisting of 24 core regulators and 76 fine-tuners that help to explain how pathogen-sensing pathways achieve specificity. This study establishes a broadly applicable, comprehensive, and unbiased approach to reveal the wiring and functions of a regulatory network controlling a major transcriptional response in primary mammalian cells.

Original languageAmerican English
Pages (from-to)257-263
Number of pages7
JournalScience
Volume326
Issue number5950
DOIs
StatePublished - 9 Oct 2009
Externally publishedYes

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