Dataset Information

De-novo identification of PPARgamma/RXR binding sites and direct targets during adipogenesis.

ABSTRACT:

Background

The pathophysiology of obesity and type 2 diabetes mellitus is associated with abnormalities in endocrine signaling in adipose tissue and one of the key signaling affectors operative in these disorders is the nuclear hormone transcription factor peroxisome proliferator-activated receptor-gamma (PPARgamma). PPARgamma has pleiotropic functions affecting a wide range of fundamental biological processes including the regulation of genes that modulate insulin sensitivity, adipocyte differentiation, inflammation and atherosclerosis. To date, only a limited number of direct targets for PPARgamma have been identified through research using the well established pre-adipogenic cell line, 3T3-L1. In order to obtain a genome-wide view of PPARgamma binding sites, we applied the pair end-tagging technology (ChIP-PET) to map PPARgamma binding sites in 3T3-L1 preadipocyte cells.

Methodology/principal findings

Coupling gene expression profile analysis with ChIP-PET, we identified in a genome-wide manner over 7700 DNA binding sites of the transcription factor PPARgamma and its heterodimeric partner RXR during the course of adipocyte differentiation. Our validation studies prove that the identified sites are bona fide binding sites for both PPARgamma and RXR and that they are functionally capable of driving PPARgamma specific transcription. Our results strongly indicate that PPARgamma is the predominant heterodimerization partner for RXR during late stages of adipocyte differentiation. Additionally, we find that PPARgamma/RXR association is enriched within the proximity of the 5' region of the transcription start site and this association is significantly associated with transcriptional up-regulation of genes involved in fatty acid and lipid metabolism confirming the role of PPARgamma as the master transcriptional regulator of adipogenesis. Evolutionary conservation analysis of these binding sites is greater when adjacent to up-regulated genes than down-regulated genes, suggesting the primordial function of PPARgamma/RXR is in the induction of genes. Our functional validations resulted in identifying novel PPARgamma direct targets that have not been previously reported to promote adipogenic differentiation.

Conclusions/significance

We have identified in a genome-wide manner the binding sites of PPARgamma and RXR during the course of adipogenic differentiation in 3T3L1 cells, and provide an important resource for the study of PPARgamma function in the context of adipocyte differentiation.

SUBMITTER: Hamza MS

PROVIDER: S-EPMC2654672 | biostudies-literature | 2009

REPOSITORIES: biostudies-literature

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Publications

De-novo identification of PPARgamma/RXR binding sites and direct targets during adipogenesis.

Hamza Mohamed Sabry MS Pott Sebastian S Vega Vinsensius B VB Thomsen Jane S JS Kandhadayar Gopalan Srinivasan GS Ng Patrick Wei Pern PW Chiu Kuo Ping KP Pettersson Sven S Wei Chia Lin CL Ruan Yijun Y Liu Edison T ET

PloS one 20090320 3

<h4>Background</h4>The pathophysiology of obesity and type 2 diabetes mellitus is associated with abnormalities in endocrine signaling in adipose tissue and one of the key signaling affectors operative in these disorders is the nuclear hormone transcription factor peroxisome proliferator-activated receptor-gamma (PPARgamma). PPARgamma has pleiotropic functions affecting a wide range of fundamental biological processes including the regulation of genes that modulate insulin sensitivity, adipocyte ...[more]

PMID: 19300518

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Project description:Transcription factors are a main component of gene regulation as they activate or repress gene expression by binding to specific binding sites in promoters. The de-novo discovery of transcription factor binding sites in target regions obtained by wet-lab experiments is a challenging problem in computational biology, which has not been fully solved yet. Here, we present a de-novo motif discovery tool called Dispom for finding differentially abundant transcription factor binding sites that models existing positional preferences of binding sites and adjusts the length of the motif in the learning process. Evaluating Dispom, we find that its prediction performance is superior to existing tools for de-novo motif discovery for 18 benchmark data sets with planted binding sites, and for a metazoan compendium based on experimental data from micro-array, ChIP-chip, ChIP-DSL, and DamID as well as Gene Ontology data. Finally, we apply Dispom to find binding sites differentially abundant in promoters of auxin-responsive genes extracted from Arabidopsis thaliana microarray data, and we find a motif that can be interpreted as a refined auxin responsive element predominately positioned in the 250-bp region upstream of the transcription start site. Using an independent data set of auxin-responsive genes, we find in genome-wide predictions that the refined motif is more specific for auxin-responsive genes than the canonical auxin-responsive element. In general, Dispom can be used to find differentially abundant motifs in sequences of any origin. However, the positional distribution learned by Dispom is especially beneficial if all sequences are aligned to some anchor point like the transcription start site in case of promoter sequences. We demonstrate that the combination of searching for differentially abundant motifs and inferring a position distribution from the data is beneficial for de-novo motif discovery. Hence, we make the tool freely available as a component of the open-source Java framework Jstacs and as a stand-alone application at http://www.jstacs.de/index.php/Dispom.

Dataset Information

De-novo identification of PPARgamma/RXR binding sites and direct targets during adipogenesis.

Background

Methodology/principal findings

Conclusions/significance

Publications

De-novo identification of PPARgamma/RXR binding sites and direct targets during adipogenesis.

Similar Datasets

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