← BioTransfer GEO Dataset Finder
GEO series

Divergent Redox Responses of Macular and Peripheral Müller Glia: Implications for Retinal Vulnerability

GSE249894 Homo sapiens (human) Single-cell RNA-seq 20 samples Submitted 2025/12/01 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 20 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
20 samples: 20 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)
The predilection of many conditions, such as macular telangiectasia type 2, for the human macula suggests it may be more susceptible to stress than the peripheral retina. In this study, we have comprehensively investigated the genetic profiling of the macula and peripheral retina in response to stress. We conducted single-cell RNA sequencing analysis on the macula and peripheral retina of four donors cultured ex vivo with or without exposure to light stress.
Read the full summary ↓
We found that the peripheral retina generally exhibited more transcriptional changes than the macula in response to stress. Interestingly, the most pronounced changes were observed in a subgroup of Müller cells that are dominant in the peripheral retina. Genes more abundantly expressed in peripheral retinal Müller cells were mainly associated with stress responses and were more influenced by light stress. In contrast, genes that were highly expressed in Müller cells that predominate in the macula played roles in cellular function and were less influenced by light stress. We identified that Metallothionein 1 (MT1), A Kinase Anchor Protein 12 (AKAP12) and MAF BZIP Transcription Factor F (MafF) were more abundantly expressed in peripheral Müller cells than in macular Müller cells. We found that these genes were also activated in the mouse retina in the early stages of development of subretinal neovascularization. Knockdown of the MT1, AKAP12 and MafF genes in human primary Müller cells reduced cell viability in response to light stress and disrupted several stress response pathways. Taken together, our findings indicate that macular Müller cells are more directed toward maintaining retinal cell function rather than mounting a stress response when they are exposed to stress, which may contribute to the macula’s vulnerability to degenerative disease.
This dataset
Open GSE249894 in finder → Find more human 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 GSE249894_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1051102 and SRA study SRP477369. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
20 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 20 sample titles: 20 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 human 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.