GEO series

Distinct transcriptomic and epigenomic responses of mature oligodendrocytes during disease progression in a mouse model of multiple sclerosis [RNA-seq]

GSE283086 Mus musculus (mouse) Single-cell RNA-seq 15 samples Submitted 2025/07/30 Platform GPL34290

At a glance

Single-cell RNA-seq · mouse · 15 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: 15 samples: 15 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)

Multiple sclerosis (MS) is a chronic demyelinating autoimmune disease which targets mature oligodendrocytes (MOLs) and their myelin. MOLs are transcriptionally heterogeneous, and can transition to immune-like states in the context of MS. However, the intricacies of their dynamics throughout disease progression remain poorly understood.

Read the full summary ↓

Here, we employed simultaneous single-cell multiome ATAC and RNA sequencing targeting oligodendroglia (OLGs) from the experimental autoimmune encephalomyelitis (EAE) MS mouse model, at different stages of the disease course. We found that the transition to immune OLGs states occurs already at early stages of EAE and these persist at late stages of the disease. Interestingly, transcription factor activity suggested immunosuppression activity in MOLs at early stages of EAE and we also observed a transitory activation of a regenerative programme in MOLs at this stage. Importantly, different MOLs present a differential responsiveness to EAE, with MOL2 exhibiting stronger transcriptional immune response than MOL5/6. Moreover, we observed divergence responses at the epigenetic level of MOL2 and MOL5/6 during disease evolution. Thus, our single-cell multiomic resource highlights dynamic and distinct responses of OLG subpopulations to the evolving environment in EAE, which might modulate their response to regenerative therapeutic interventions in MS.

This dataset

Open GSE283086 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 GSE283086_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 PRJNA1191839 and SRA study SRP548217. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

15 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 15 sample titles: 15 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

GSM8655707 Ctrl,replicate1,bulk_RNA-seq
GSM8655708 Ctrl,replicate2,bulk_RNA-seq
GSM8655709 Ctrl,replicate3,bulk_RNA-seq
GSM8655710 IFN-g 24h (+0),replicate1,bulk_RNA-seq
GSM8655711 IFN-g 24h (+0),replicate2,bulk_RNA-seq
GSM8655712 IFN-g 24h (+0),replicate3,bulk_RNA-seq
GSM8655713 IFN-g 24h (+96),replicate1,bulk_RNA-seq
GSM8655714 IFN-g 24h (+96),replicate2,bulk_RNA-seq
GSM8655715 IFN-g 24h (+96),replicate3,bulk_RNA-seq
GSM8655716 2x IFN-g 24h,replicate1,bulk_RNA-seq
GSM8655717 2x IFN-g 24h,replicate2,bulk_RNA-seq
GSM8655718 2x IFN-g 24h,replicate3,bulk_RNA-seq
GSM8655719 1x IFN-g 24h,replicate1,bulk_RNA-seq
GSM8655720 1x IFN-g 24h,replicate2,bulk_RNA-seq
GSM8655721 1x IFN-g 24h,replicate3,bulk_RNA-seq

Datasets on a similar topic

GSE241770 ACSS2 mediates an epigenetic pathway to regulate maternal Beta-cell adaptation and progression of gestational diabetes (scRNA-Seq) 7899 samples shares progression, rna-seq
GSE302857 Multi-tier signaling and epigenomic reprogramming drive microglial inflammatory states and functions associated with demyelination [RNA-seq] 81 samples shares epigenomic, rna-seq
GSE234245 Multiomic Profile Integration Reveals Early Signatures of Amyotrophic Lateral Sclerosis and Suggests the MAPK Pathway as a Therapeutic Target [RNA-Seq] 79 samples shares sclerosis, rna-seq
GSE248585 A conserved epithelial wound-like transcriptional program driven by FOSL1 underlies malignant progression of pancreatic ductal adenocarcinoma (ssRNA-Seq) 46 samples shares progression, rna-seq
GSE279536 Hypoxic stress dysregulates functions of glioma-associated myeloid cells through epigenomic and transcriptional programs [RNA-seq] 38 samples shares epigenomic, rna-seq
GSE231802 IL-1R signaling drives enteric glia-macrophage interaction in colorectal cancer progression [bulkRNA-Seq] 36 samples shares progression, rna-seq
GSE244385 Short-term cold exposure induces persistent epigenomic memory in brown fat [RNA-Seq] 24 samples shares epigenomic, rna-seq
GSE285025 TEAD switches interacting partners along neural progenitor lineage progression to execute distinct functions 23 samples shares progression, distinct

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.