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

作者：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

来源：PLoS Computational Biology, 2008, 4(3): e1000021.

DOI：10.1371/journal.pcbi.1000021

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.

• 出版日期2008-3