Unbiased reconstruction of a mammalian transcriptional network mediating the differential response to pathogens
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 der...
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
American Association for the Advancement of Science (AAAS)
2014
|
| Online Access: | http://hdl.handle.net/1721.1/85204 https://orcid.org/0000-0001-5773-3211 https://orcid.org/0000-0001-8567-2049 |
| Summary: | 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. |
|---|