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.
MeSH Terms
Animals
Bacteria/immunology
Chromatin Assembly and Disassembly
DNA, Single-Stranded/immunology
Dendritic Cells/immunology,metabolism
Feedback, Physiological
Gene Expression Profiling
Gene Expression Regulation
Gene Regulatory Networks
Inflammation/immunology,metabolism
Lipopeptides/immunology
Lipopolysaccharides/immunology
Mice
Mice, Inbred C57BL
Poly I-C/immunology
RNA-Binding Proteins/metabolism
Toll-Like Receptors/agonists
Transcription Factors/metabolism
Transcription, Genetic
Viruses/immunology
Chemicals
DNA, Single-Stranded
Lipopeptides
Lipopolysaccharides
Pam(3)CSK(4) peptide
RNA-Binding Proteins
Toll-Like Receptors
Transcription Factors
Poly I-C
Authors & Affiliations
25 authors, click to expand affiliations / ORCID
Amit Ido
Broad Institute of MIT and Harvard, 7 Cambridge Center, Cambridge, MA 02142, USA.
Garber Manuel
Chevrier Nicolas
Leite Ana Paula
Donner Yoni
Eisenhaure Thomas
Guttman Mitchell
Grenier Jennifer K
Li Weibo
Zuk Or
Schubert Lisa A
Birditt Brian
Shay Tal
Goren Alon
Zhang Xiaolan
Smith Zachary
Deering Raquel
McDonald Rebecca C
Cabili Moran
Bernstein Bradley E
Rinn John L
Meissner Alex
Root David E
Hacohen Nir
Regev Aviv
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