← BioTransfer GEO Dataset Finder
GEO series

Epigenetic modifiers to treat retinal degenerative diseases.

GSE295538 Mus musculus (mouse) RNA-seq (gene expression) 26 samples Submitted 2025/05/13 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 26 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
26 samples: 10 conditions, mostly in duplicateGroups 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)
We have previously demonstrated the ability of inhibitors of LSD1 and HDAC1 to block rod degeneration, preserve vision, maintain rod-specific transcripts and downregulate those involved in inflammation, gliosis, and cell death in the rd10 mouse model of Retinitis Pigmentosa (RP). To extend our findings we tested the hypothesis that broad range of inhibitors of chromatin condensation can prevent photoreceptor degeneration in the rd10 mouse model.
Read the full summary ↓
We used inhibitors for G9A/GLP that catalyzes methylation of H3K9, for EZH2 that catalyzes trimethylation of H3K27 and compared them to the actions of LSD1 and HDAC inhibitors. All the inhibitors decondense chromatin and all preserve, to different extents, retinas from degeneration in rd10mice, but they act through different metabolic pathways. One group of inhibitors, modifiers for LSD1 and EZH2, demonstrate a high level of maintenance of rod-specific transcripts, activation of Ca+2 and Wnt signaling pathways with inhibition of antigen processing and presentation, immune response and microglia phagocytosis. Another group of inhibitors, modifiers for HDAC and G9A/GLP work through upregulation of NGF-stimulated transcription, while down-regulating genes belong to immune response, extracellular matrix, cholesterol signaling and programmed cell death.
This dataset
Open GSE295538 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 GSE295538_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 PRJNA1255151 and SRA study SRP581130. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
10 conditions, mostly in duplicate
group3, control, biol ×4 group1,control, biol ×3 group1, Romidepsin treatment, biol ×3 group4, control, biol ×3 group4, UNC1999 treatment, biol ×3 group2, control, biol ×2 group2, UNC0642 treatment, biol ×2 group3, DZNep treatment, biol ×2 +2 more

Supports a between-group comparison across 26 samples.

How we read this: 10 replicated groups read from 26 sample titles; they account for 26 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.