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Ramsey, Stephen A; Klemm, Sandy L; Zak, Daniel E; Kennedy, Kathleen A; Thorsson, Vesteinn; Li, Bin; Gilchrist, Mark; Gold, Elizabeth S; Johnson, Carrie D; Litvak, Vladimir; Navarro, Garnet; Roach, Jared C; Rosenberger, Carrie M; Rust, Alistair G; Yudkovsky, Natalya; Aderem, Alan; Shmulevich, Ilya
PLoS computational biology, 03/2008, Letnik: 4, Številka: 3Journal Article
Macrophages are versatile immune cells that can detect a variety of pathogen-associated molecular patterns through their Toll-like receptors (TLRs). In response to microbial challenge, the TLR-stimulated macrophage undergoes an activation program controlled by a dynamically inducible transcriptional regulatory network. Mapping a complex mammalian transcriptional network poses significant challenges and requires the integration of multiple experimental data types. In this work, we inferred a transcriptional network underlying TLR-stimulated murine macrophage activation. Microarray-based expression profiling and transcription factor binding site motif scanning were used to infer a network of associations between transcription factor genes and clusters of co-expressed target genes. The time-lagged correlation was used to analyze temporal expression data in order to identify potential causal influences in the network. A novel statistical test was developed to assess the significance of the time-lagged correlation. Several associations in the resulting inferred network were validated using targeted ChIP-on-chip experiments. The network incorporates known regulators and gives insight into the transcriptional control of macrophage activation. Our analysis identified a novel regulator (TGIF1) that may have a role in macrophage activation.
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