Uncovering a macrophage transcriptional program by integrating evidence from motif scanning and expression dynamics.

oleh: Stephen A Ramsey, Sandy L Klemm, Daniel E Zak, Kathleen A Kennedy, Vesteinn Thorsson, Bin Li, Mark Gilchrist, Elizabeth S Gold, Carrie D Johnson, Vladimir Litvak, Garnet Navarro, Jared C Roach, Carrie M Rosenberger, Alistair G Rust, Natalya Yudkovsky, Alan Aderem, Ilya Shmulevich

Format: Article
Diterbitkan: Public Library of Science (PLoS) 2008-03-01

Deskripsi

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.