← BioTransfer GEO Dataset Finder
GEO series

Preadipocyte uncoupling protein 1 expression invoked by fibroblast growth factors imprints on post-differentiation white and brown adipocyte function

GSE306159 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2025/08/22 Platform GPL34328
At a glance

RNA-seq (gene expression) · mouse · 18 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Mus musculus (mouse)
Samples
18 samples: 18 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.
Paper
Preadipocyte Uncoupling Protein 1 Expression Invoked by Fibroblast Growth Factors Imprints on Post-Differentiation White and Brown Adipocyte PhenotypeFASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2025
Summary (written by the submitters)
The presence of uncoupling protein 1 (UCP1) is a hallmark of thermogenic adipocytes and enables heat production by dissipating energy from mitochondrial proton motive force as heat. The purpose of its recently discovered presence in preadipocytes in response to certain fibroblast growth factors (FGFs) remains elusive. In this study, we systematically investigated the potential of all paracrine FGFs to invoke Ucp1 expression in murine preadipocytes derived from interscapular brown and inguinal white adipose tissue.
Read the full summary ↓
The factors FGF2, FGF4, FGF8, and FGF9 induced Ucp1 expression in undifferentiated preadipocytes, with FGF2 acting most potently and rapidly. This premature Ucp1 induction did not translate into increased Ucp1 thermogenic activity after full adipogenic differentiation. Notably, preadipocyte treatment with FGFs and parallel Ucp1 expression led to a sustained suppression of interferon-stimulated genes after differentiation. Preadipocyte Ucp1 was required and sufficient for this lasting imprint. Thus, FGF-induced Ucp1 expression in preadipocytes programs a lasting post-differentiation anti-inflammatory status.
Published in
Preadipocyte Uncoupling Protein 1 Expression Invoked by Fibroblast Growth Factors Imprints on Post-Differentiation White and Brown Adipocyte Phenotype
Kuellmer K, Mönch C, Roch W et al. · FASEB journal : official publication of the Federation of American Societies for Experimental Biology 2025 · PMID 41099430 · doi:10.1096/fj.202502663R
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 GSE306159_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1309609 and SRA study SRP610733. Searching any of these in the dataset finder brings you back here.

Study design
18 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 18 sample titles: 18 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
Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

Share this dataset

Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.