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Retrograde mitochondrial signaling governs the identity and maturity of metabolic tissues

GSE262023 Mus musculus (mouse) RNA-seq (gene expression) 46 samples Submitted 2025/01/15 Platform GPL21103Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 46 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
46 samples: 9 conditions, mostly with about 6 replicates eachGroups 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
Retrograde mitochondrial signaling governs the identity and maturity of metabolic tissuesScience (New York, N.Y.) · 2025
Summary (written by the submitters)
Mitochondrial damage is a hallmark of metabolic diseases, including diabetes and metabolic dysfunction-associated steatotic liver disease, yet the consequences of impaired mitochondria in metabolic tissues are often unclear. Here, we report that dysfunctional mitochondrial quality control engages a retrograde (mitonuclear) signaling program that impairs cellular identity and maturity across multiple metabolic tissues.
Read the full summary ↓
Surprisingly, we demonstrate that defects in the mitochondrial quality control machinery, which we observe in pancreatic β cells of humans with diabetes, cause reductions of β cell mass due to dedifferentiation, rather than apoptosis. Utilizing transcriptomic profiling, lineage tracing, and assessments of chromatin accessibility, we find that targeted deficiency anywhere in the mitochondrial quality control pathway (e.g., genome integrity, dynamics, or turnover) activate the mitochondrial integrated stress response and promote cellular immaturity in β cells, hepatocytes, and brown adipocytes. Intriguingly, pharmacologic blockade of mitochondrial retrograde signaling in vivo restores β cell mass and identity to ameliorate hyperglycemia following mitochondrial damage. Thus, we observe that a shared mitochondrial retrograde response controls cellular identity across metabolic tissues and may be a promising target to treat or prevent metabolic disorders.
Published in
Retrograde mitochondrial signaling governs the identity and maturity of metabolic tissues
Walker EM, Pearson GL, Lawlor N et al. · Science (New York, N.Y.) 2025 · PMID 39913641 · doi:10.1126/science.adf2034
This dataset
Open GSE262023 in finder → Find more mouse RNA-seq 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 GSE262023_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: 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 PRJNA1090056 and SRA study SRP496698. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39913641) ↗
Study design
9 conditions, mostly with about 6 replicates each
RNA, islets, Tfam control biol ×8 RNA, islets, Tfam KO biol ×6 RNA, islets, Clec control HFD biol ×6 RNA, liver, control biol ×6 RNA, islets, Clec KO HFD biol ×5 RNA, islets, Clec control RFD biol ×4 RNA, islets, Clec KO RFD biol ×4 RNA, liver, Mfn DKO biol ×4 +1 more

Supports a between-group comparison across 46 samples.

How we read this: 9 replicated groups read from 46 sample titles; they account for 46 of them. 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

+ 6 more — browse all 46 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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