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Age-impaired remyelination is associated with dysregulated microglial transitions.

GSE281947 Mus musculus (mouse) Single-cell RNA-seq 12 samples Submitted 2025/08/01 Platform GPL21103
At a glance

Single-cell RNA-seq · mouse · 12 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
Mus musculus (mouse)
Samples
12 samples: 10 distinct titles, 2 of them repeatedGroups 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
Age-impaired remyelination is associated with dysregulated microglial transitionsNature communications · 2025
Summary (written by the submitters)
Multiple sclerosis (MS) is a chronic, inflammatory condition characterized by demyelination and neurodegeneration. Regeneration of lost myelin, or remyelination, occurs in people with MS but is prone to failure and impaired with age. Remyelination is facilitated by microglia but our understanding of the microglial response during remyelination is incomplete.
Read the full summary ↓
Here, we profiled the microglial response in the lysolecithin mouse model of remyelination using single-cell RNA sequencing. We found several distinct microglial states during the early stages of remyelination that coalesced into a resolved microglial state defined by myelin transcripts. This resolved state was also present in MS brains. As remyelination becomes inefficient with age, we profiled microglia from both young and middle-aged mice during remyelination and found a delay in several microglial states, in concordance with delayed remyelination. Overall, microglia synchronously initiate a multi-faceted response during efficient remyelination in young mice, which becomes dysregulated with age.
Published in
Age-impaired remyelination is associated with dysregulated microglial transitions
Zia S, Traetta ME, Baaklini CS et al. · Nature communications 2025 · PMID 41224757 · doi:10.1038/s41467-025-64906-w
This dataset
Open GSE281947 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 GSE281947_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 PRJNA1186235 and SRA study SRP545329. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41224757) ↗
Study design
10 distinct titles, 2 of them repeated
spinal cord, 2-month-old, LPC, C57/Bl6, naïve, ×2 spinal cord, 2-month-old, LPC, C57/Bl6, 7 DPI, ×2

How we read this: Read from 12 sample titles: 10 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

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