Uncovering a macrophage transcriptional program by integrating evidence from motif scanning and expression dynamics
- PMID: 18369420
- PMCID: PMC2265556
- DOI: 10.1371/journal.pcbi.1000021
Uncovering a macrophage transcriptional program by integrating evidence from motif scanning and expression dynamics
Erratum in
- PLoS Comput Biol. 2008 Mar;4(3). doi: 10.1371/annotation/1c55be5f-ecd7-49be-91c1-91881be60297
- PLoS Comput Biol. 2008 Mar;4(3). doi: 10.1371/annotation/e14ad837-e5ff-4bd5-a5f2-f32e784d75a2
Abstract
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.
Conflict of interest statement
The authors have declared that no competing interests exist.
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