GEO series

Targeting EBF2 condensates modulates adipose thermogenesis

GSE297178 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 90 samples Submitted 2026/03/11 Platform GPL34290

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 90 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: 90 samples: 90 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
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.

Summary (written by the submitters)

Brown adipose tissue (BAT) actively dissipates energy and represents a promising therapeutic target for combating obesity. The establishment of the thermogenic gene program is orchestrated by the pioneering transcription factor Early B Cell Factor 2 (EBF2). Here, we identified a low-complexity C-terminal domain (CTD) within EBF2 that drives biomolecular condensation and is essential for thermogenic activation.

Read the full summary ↓

Deletion of the CTD (EBF2 ΔCTD) or mutation of key proline residues within this region did not affect the genomic binding of EBF2, but profoundly impaired its ability to undergo phase separation and to drive brown adipocyte differentiation and thermogenic function both in vitro and in vivo. Fusion of the intrinsic disorder region (IDR) of FUS to EBF2 ΔCTD fully restored its function, whereas fusion with MED1-IDR resulted in distinct phenotypic outcomes. Mechanistically, EBF2 formed condensates with ZFP423, a key repressor of brown adipocyte differentiation. This co-condensation excluded HDAC1 from the complex, establishing a permissive chromatin environment that promotes active transcription. Furthermore, a phase separation-based phenotypic drug screen identified compounds that modulated EBF2 condensate formation and thermogenic genes expression. Our findings reveal phase separation as an emerging regulatory mechanism underlying brown fat determination and suggest that targeting biomolecular condensation offers a novel therapeutic strategy for obesity.

This dataset

Open GSE297178 in finder → Find more mouse ChIP / ATAC / CUT&Tag datasets →

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.

Series matrix ↓

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 GSE297178_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓

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.

Raw reads on ENA ↗

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 PRJNA1262940 and SRA study SRP585224. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

90 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 90 sample titles: 90 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

GSM8984978 KO-CTD,rep1,Day 7,ATAC
GSM8984979 KO-CTD,rep2,Day 7,ATAC
GSM8984980 KO-EBF2,rep1,Day 7,ATAC
GSM8984981 KO-EBF2,rep2,Day 7,ATAC
GSM8984982 KO-EV,rep1,Day 7,ATAC
GSM8984983 KO-EV,rep2,Day 7,ATAC
GSM8984984 KO-EBF2,rep3,Day 0,ATAC
GSM8984985 KO-EBF2,rep4,Day 0,ATAC
GSM8984986 KO-EV,rep5,Day 0,ATAC
GSM8984987 KO-EV,rep6,Day 0,ATAC
GSM8984988 KO-FUS,rep5,Day 0,ATAC
GSM8984989 KO-FUS,rep6,Day 0,ATAC
GSM8984990 KO-P>A,rep3,Day 0,ATAC
GSM8984991 KO-P>A,rep4,Day 0,ATAC
GSM8984992 KO-CTD,rep1,Day 7,H3K27ac
GSM8984993 KO-CTD,rep2,Day 7,H3K27ac
GSM8984994 KO-EBF2,rep1,Day 7,H3K27ac
GSM8984995 KO-EBF2,rep2,Day 7,H3K27ac
GSM8984996 KO-EV,rep1,Day 7,H3K27ac
GSM8984997 KO-EV,rep2,Day 7,H3K27ac
GSM8984998 KO-EBF2,rep1,Day 0,H3K27ac
GSM8984999 KO-EBF2,rep2,Day 0,H3K27ac
GSM8985000 KO-EV,rep1,Day 0,H3K27ac
GSM8985001 KO-EV,rep2,Day 0,H3K27ac
GSM8985002 KO-FUS,rep1,Day 0,H3K27ac
GSM8985003 KO-FUS,rep2,Day 0,H3K27ac
GSM8985004 KO-P>A,rep1,Day 0,H3K27ac
GSM8985005 KO-P>A,rep2,Day 0,H3K27ac
GSM8985006 KO-CTD,rep1,Day 0,Cut&Tag EBF2
GSM8985007 KO-CTD,rep2,Day 0,Cut&Tag EBF2
GSM8985008 KO-EBF2,rep1,Day 0,Cut&Tag EBF2
GSM8985009 KO-EBF2,rep2,Day 0,Cut&Tag EBF2
GSM8985010 KO-EBF2,rep3,Day 0,Cut&Tag EBF2
GSM8985011 KO-EBF2,rep4,Day 0,Cut&Tag EBF2
GSM8985012 KO-FUS,rep5,Day 0,Cut&Tag EBF2
GSM8985013 KO-P>A,rep3,Day 0,Cut&Tag EBF2
GSM8985014 KO-P>A,rep4,Day 0,Cut&Tag EBF2
GSM8985015 KO-EBF2,rep1,Day 0,Cut&Tag Hdac1
GSM8985016 KO-EBF2,rep2,Day 0,Cut&Tag Hdac1
GSM8985017 KO-EV,rep1,Day 0,Cut&Tag Hdac1

+ 50 more — browse all 90 samples with per-sample file links →

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