Unbiased Reconstruction of a Mammalian Transcriptional Network Mediating Pathogen Responses Export

@article{citeulike:5720536, 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. 10.1126/science.1179050}, author = {Amit, Ido and Garber, Manuel and Chevrier, Nicolas and Leite, Ana P. and Donner, Yoni and Eisenhaure, Thomas and Guttman, Mitchell and Grenier, Jennifer K. and Li, Weibo and Zuk, Or and Schubert, Lisa A. and Birditt, Brian and Shay, Tal and Goren, Alon and Zhang, Xiaolan and Smith, Zachary and Deering, Raquel and McDonald, Rebecca C. and Cabili, Moran and Bernstein, Bradley E. and Rinn, John L. and Meissner, Alex and Root, David E. and Hacohen, Nir and Regev, Aviv}, citeulike-article-id = {5720536}, citeulike-linkout-0 = {http://dx.doi.org/10.1126/science.1179050}, citeulike-linkout-1 = {http://www.sciencemag.org/content/326/5950/257.abstract}, citeulike-linkout-2 = {http://www.sciencemag.org/content/326/5950/257.full.pdf}, citeulike-linkout-3 = {http://www.sciencemag.org/cgi/content/abstract/326/5950/257}, citeulike-linkout-4 = {http://view.ncbi.nlm.nih.gov/pubmed/19729616}, citeulike-linkout-5 = {http://www.hubmed.org/display.cgi?uids=19729616}, day = {9}, doi = {10.1126/science.1179050}, issn = {1095-9203}, journal = {Science}, keywords = {gene\_expression, infectionhost-pathogen\_interaction, systems\_biology, transcription, transcriptome}, month = {October}, number = {5950}, pages = {257--263}, posted-at = {2009-10-09 19:52:15}, priority = {2}, title = {Unbiased Reconstruction of a Mammalian Transcriptional Network Mediating Pathogen Responses}, url = {http://dx.doi.org/10.1126/science.1179050}, volume = {326}, year = {2009} }

TY - JOUR ID - citeulike:5720536 L3 - citeulike-article-id:5720536 N2 - 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. 10.1126/science.1179050 IS - 5950 JF - Science SN - 1095-9203 EP - 263 TI - Unbiased Reconstruction of a Mammalian Transcriptional Network Mediating Pathogen Responses VL - 326 SP - 257 KW - gene_expression KW - infectionhost-pathogen_interaction KW - systems_biology KW - transcription KW - transcriptome AU - Amit, Ido AU - Garber, Manuel AU - Chevrier, Nicolas AU - Leite, Ana AU - Donner, Yoni AU - Eisenhaure, Thomas AU - Guttman, Mitchell AU - Grenier, Jennifer AU - Li, Weibo AU - Zuk, Or AU - Schubert, Lisa AU - Birditt, Brian AU - Shay, Tal AU - Goren, Alon AU - Zhang, Xiaolan AU - Smith, Zachary AU - Deering, Raquel AU - McDonald, Rebecca AU - Cabili, Moran AU - Bernstein, Bradley AU - Rinn, John AU - Meissner, Alex AU - Root, David AU - Hacohen, Nir AU - Regev, Aviv PY - 2009/10/09/ UR - http://dx.doi.org/10.1126/science.1179050 ER -