← BioTransfer GEO Dataset Finder
GEO series

Decoupling oxidative resilience from reprogramming to rejuvenate the RPE and restore vision [GSTA4_RNA-seq_3]

GSE304040 Mus musculus (mouse) RNA-seq (gene expression) 24 samples Submitted 2026/06/11 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 24 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
24 samples: 6 conditions, mostly with about 4 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.
Summary (written by the submitters)
OCT4, SOX2, and KLF4 (OSK) Yamanaka factors can reverse age-related epigenetic changes, yet alternate mechanisms by which they promote tissue resilience remain poorly understood. Oxidative stress contributes to retinal pigmented epithelium (RPE) degeneration in age-related macular degeneration. Here, we show that OSK expression in RPE promotes Tet2-independent oxidative resilience through acute, memory-free transcriptomic changes, and restores visual function in aged mice.
Read the full summary ↓
Integrative functional genomics helped identify GSTA4, a detoxifying enzyme that clears the lipid peroxidation byproduct 4-HNE, as a key OSK downstream effector. OSK directly and dynamically activates GSTA4, recapitulating a stem cell-derived stress resilience program. GSTA4 overexpression alone enhances oxidative resilience, rejuvenates the aged RPE transcriptome, and reverses visual decline while avoiding OSK’s pleiotropic effects. GSTA4 is upregulated across diverse lifespan-extending interventions suggesting a broader pro-longevity role. These findings uncover a previously unrecognized protective axis directly regulated by OSK, that can be decoupled from reprogramming, providing a framework for developing more precise rejuvenation therapies.
This dataset
Open GSE304040 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 GSE304040_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 PRJNA1298816 and SRA study SRP604608. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly with about 4 replicates each
3-months ×4 24-months ×4 3-months-OSK ×4 24-months-OSK ×4 3-months-OSKonoff ×4 24-months-OSKonoff ×4

Supports a between-group comparison across 24 samples.

How we read this: 6 replicated groups read from 24 sample titles; they account for 24 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
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.