Unbiased reconstruction of a mammalian transcriptional network mediating the differential response to pathogens
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Regev_Unbiased reconstruction.pdf
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1.6 MB
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Checksum (MD5)
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Author(s)
Amit, Ido
Guttman, Mitchell
Leite, Ana Paula
Regev, Aviv
Garber, Manuel
Chevrier, Nicolas
Donner, Yoni
Eisenhaure, Thomas
Grenier, Jennifer K.
Li, Weibo
Alternative Title
Unbiased Reconstruction of a Mammalian Transcriptional Network Mediating Pathogen Responses
Date Issued
September 2009
Journal
Science
Publisher
American Association for the Advancement of Science (AAAS)
Citation
Amit, I., M. Garber, N. Chevrier, A. P. Leite, Y. Donner, T. Eisenhaure, M. Guttman, et al. “Unbiased Reconstruction of a Mammalian Transcriptional Network Mediating Pathogen Responses.” Science 326, no. 5950 (October 8, 2009): 257-263.
Version
Author's final manuscript
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.
MIT Department
Massachusetts Institute of Technology. Computational and Systems Biology Program
Massachusetts Institute of Technology. Department of Biology
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1126/science.1179050
