Glucocorticoid receptor-dependent gene regulatory networks - PubMed (original) (raw)

Glucocorticoid receptor-dependent gene regulatory networks

Phillip Phuc Le et al. PLoS Genet. 2005 Aug.

Abstract

While the molecular mechanisms of glucocorticoid regulation of transcription have been studied in detail, the global networks regulated by the glucocorticoid receptor (GR) remain unknown. To address this question, we performed an orthogonal analysis to identify direct targets of the GR. First, we analyzed the expression profile of mouse livers in the presence or absence of exogenous glucocorticoid, resulting in over 1,300 differentially expressed genes. We then executed genome-wide location analysis on chromatin from the same livers, identifying more than 300 promoters that are bound by the GR. Intersecting the two lists yielded 53 genes whose expression is functionally dependent upon the ligand-bound GR. Further network and sequence analysis of the functional targets enabled us to suggest interactions between the GR and other transcription factors at specific target genes. Together, our results further our understanding of the GR and its targets, and provide the basis for more targeted glucocorticoid therapies.

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Conflict of interest statement

Competing interests. The authors have declared that no competing interests exist.

Figures

Figure 1

Figure 1. Experimental Paradigm for Orthogonal Analysis of Glucocorticoid Receptor Targets

Treatment mice were fasted overnight, then given intraperitoneal injections with dexamethasone. Treatment and control liver lobes were split in half and processed for both RNA and chromatin. RNA was subjected to microarray analysis using the PancChip 5.0 cDNA microarray, which contains over 13,000 transcripts. Location analysis was performed by immunoprecipitating with antiserum raised against the GR. ChIP material was amplified, fluorescently labeled, and hybridized against sheared genomic DNA using the Mouse PromoterChip BCBC-3.0 promoter microarray, which contains approximately 7,000 genomic promoter elements.

Figure 2

Figure 2. ChIP Identifies Known GR Targets in Liver

(A) Agarose gel electrophoresis of PCR products for the known GREs in Mt2 and Tat confirm the specificity of the anti-GR antibody (sc-1002, Santa Cruz) compared to the control preimmune IgG. The PCR product for the genomic locus encoding the 28S ribosomal RNA shows that equal amounts of DNA were loaded into each reaction. (B) QPCR was used to measure the enrichment of Mt2 and Tat in chromatin immunoprecipitated with the anti-GR antiserum from five dexamethasone-treated samples compared to five fed controls, as described in Materials and Methods. The 28S PCR product was used to normalize the samples.

Figure 3

Figure 3. Functional Categories of the Genes Generated by Location Analysis

Location analysis was performed using antiserum against the GR. Three treated and five control samples were amplified, fluorescently labeled, and hybridized to the Mouse PromoterChip BCBC-3.0 promoter microarray in a common reference design. Standard statistical methods identified 302 promoter regions significantly enriched in the treated samples compared to the fed controls (see Materials and Methods). The GO level 4 functional category for each gene was retrieved and the top 20 categories are shown. Note that some genes belong to multiple GO categories.

Figure 4

Figure 4. Quantitative PCR Confirms GR Targets Identified by Location Analysis

The enrichment of GR targets identified by location analysis was measured in the original immunoprecipitated material by QPCR. The graph shows the fold-enrichment of five dexamethasone-treated samples compared to five fed controls. Of fourteen randomly selected GR targets, 12 showed statistically significant enrichment. Fold-enrichment and _p_-values were calculated as described in Materials and Methods. *p < 0.05, **p < 0.01.

Figure 5

Figure 5. Intersection of Expression Data and Location Analysis

Of the genes common to both the cDNA microarray and the promoter microarray, 498 were differentially expressed and 235 were bound by the GR. Intersecting the two lists produced 53 genes in common. This list represents direct, functional targets of the GR in hepatocytes.

Figure 6

Figure 6. A Regulatory Network for the GR

Pathway analysis was seeded with the 53 differentially expressed and GR-bound genes, plus the GR itself, as described in Materials and Methods. Genes in colored, bold text were in the seed set, while all others were brought into the network by the pathway analysis program based on their known relationships to the genes in the seed set. Color indicates induction (red) or repression (green) of expression.

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