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Irx3 controls a sumoylation-dependent epigenetic switch between adipogenesis and osteogenesis

GSE278972 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 10 samples Submitted 2025/05/29 Platform GPL30172
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 10 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Mus musculus (mouse)
Samples
10 samples
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
IRX3 controls a SUMOylation-dependent differentiation switch in adipocyte precursor cellsNature communications · 2025
Summary (written by the submitters)
Background IRX3 is implicated in genetic predisposition to obesity via the FTO variant locus. IRX3 shows FTO risk allele-dependent upregulation specifically during early adipogenesis, leading to a shift from energy dissipation to fat storage in mature adipocytes. However, how changes in IRX3 expression at one developmental stage affect cellular phenotype at a later stage remains unclear.
Read the full summary ↓
We here hypothesize that IRX3 regulates adipocyte development via transcriptional modulation of epigenetic reprogramming factors. Methods We combined ChIP-, ATAC- and RNA-sequencing to map direct Irx3 target genes in regions of open chromatin during early adipogenesis of wild-type and Irx3-KO preadipocytes. Gene ontology analyses was performed to identify significantly enriched biological pathways. Denaturing western blotting was used to assess sumoylation levels, and the inhibitor ML-792 was used to specifically block sumoylation. Luciferase assays were performed to estimate effects of ML-792 on Pparγ activity. Bodipy lipid staining, immunofluorescence and qPCR were employed to assess adipogenic differentiation in 3D culture. Alkaline phosphatase and Alizarine Red S staining, as well as immunofluorescence and qPCR were used to assess osteogenic differentiation in 3D culture. Results We identified more than 300 Irx3 binding sites in preadipocytes, and these were almost exclusively restricted to promoter regions, with a strong enrichment of genes related to sumoylation, histone modifications and chromatin remodeling. Genes from every step of the sumoylation cycle were bound by Irx3 and differentially expressed in response to Irx3-KO, leading to increased global sumoylation levels in the KO cells. Irx3 ablation and elevated sumoylation inhibited Pparγ activity and adipogenic differentiation in preadipocytes, both of which could be restored by pharmacological inhibition of sumoylation. The Irx3-KO cells demonstrated reduced epigenetic suppression against osteogenesis, resulting in increased osteogenesis in 3D culture. Finally, osteogenesis induced by Irx3 ablation could partially be reversed by inhibition of sumoylation. Conclusions Our study has uncovered IRX3 as a novel upstream regulator of sumoylation, and a potent controller of epigenetic regulators, both directly and indirectly via suppressing global sumoylation levels. This study indicates that the FTO locus promotes obesity via IRX3-mediated suppression of sumoylation, which promotes adipogenic commitment and differentiation through epigenetic programming.
Published in
IRX3 controls a SUMOylation-dependent differentiation switch in adipocyte precursor cells
Bjune JI, Laber S, Lawrence-Archer L et al. · Nature communications 2025 · PMID 40769964 · doi:10.1038/s41467-025-62361-1
This dataset
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE278972_RAW.tar (it can run to tens of gigabytes).

3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

What the files usually look like: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1169864 and SRA study SRP537245. Searching any of these in the dataset finder brings you back here.

Samples in this study

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