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Jmjd3, a JmjC family histone demethylase, is induced by the transcription factor NF-kB in response to microbial stimuli. Jmjd3 erases H3K27me3, a histone mark associated with transcriptional repression and involved in lineage determination. However, the specific contribution of Jmjd3 induction and H3K27me3 demethylation to inflammatory gene expression remains unknown. Using chromatin immunoprecipitation-sequencing we found that Jmjd3 is preferentially recruited to transcription start sites characterized by high levels of H3K4me3, a marker of gene activity, and RNA polymerase II (Pol_II). Moreover, 70% of lipopolysaccharide (LPS)-inducible genes were found to be Jmjd3 targets. Although most Jmjd3 target genes were unaffected by its deletion, a few hundred genes, including inducible inflammatory genes, showed moderately impaired Pol_II recruitment and transcription. Importantly, most Jmjd3 target genes were not associated with detectable levels of H3K27me3, and transcriptional effects of Jmjd3 absence in the window of time analysed were uncoupled from measurable effects on this histone mark. These data show that Jmjd3 fine-tunes the transcriptional output of LPS-activated macrophages in an H3K27 demethylation-independent manner.
Pubmed ID: 19779457
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Functional genomics data repository supporting MIAME-compliant data submissions. Includes microarray-based experiments measuring the abundance of mRNA, genomic DNA, and protein molecules, as well as non-array-based technologies such as serial analysis of gene expression (SAGE) and mass spectrometry proteomic technology. Array- and sequence-based data are accepted. Collection of curated gene expression DataSets, as well as original Series and Platform records. The database can be searched using keywords, organism, DataSet type and authors. DataSet records contain additional resources including cluster tools and differential expression queries.
View all literature mentionsSet of software modules for performing common ChIP-seq data analysis tasks across the whole genome, including positional correlation analysis, peak detection, and genome partitioning into signal-rich and signal-poor regions. The tools are designed to be simple, fast and highly modular. Each program carries out a well defined data processing procedure that can potentially fit into a pipeline framework. ChIP-Seq is also freely available on a Web interface.
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