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Neuronal-class specific molecular cues drive differential myelination in the cortex

GSE233255 Mus musculus (mouse) Single-cell RNA-seq 25 samples Submitted 2026/06/10 Platform GPL19057
At a glance

Single-cell RNA-seq · mouse · 25 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
25 samples: 8 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)
Myelination represents a unique milestone in vertebrate brain evolution that has enabled the expansion of the brain and emergence of complex neurological functions. Oligodendrocytes are a heterogeneous population of cells that differentially myelinate specific neuronal subtypes, resulting in characteristic amounts and patterns of axonal myelination for each neuronal class across the cortical layers.
Read the full summary ↓
The molecular mechanisms by which neurons communicate with oligodendrocytes to direct subtype-specific myelination remain to be understood. Here, we generated a single-cell molecular map of cortical oligodendrocyte-lineage cells across the different cortical layers, over a time course spanning the process of myelination. We find that mature, myelinating oligodendrocytes are transcriptionally heterogenous, and that more mature subtypes are enriched in the deep layers. We applied differential gene expression analysis of myelinating oligodendrocytes and weakly-myelinated upper-layer projection neurons vs heavily- myelinated deep-layer projection neurons to identify candidate genes that mediate neuronal subtype-specific myelination. We show that deep-layer-specific candidate genes drive an increase in myelination when misexpressed in the upper cortical layers, which is synergistically increased when these candidate factors are co-expressed. Our results demonstrate that gene- expression signatures are essential for neuronal cell-type specific myelin targeting. Identifying these molecular players may offer new therapeutic opportunities for treating demyelinating disorders.
This dataset
Open GSE233255 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 GSE233255_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 PRJNA975571 and SRA study SRP439246. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
8 conditions, mostly in duplicate
P21_Worthington ×4 P7_Worthington ×3 P30_LayerII-IV ×2 P30_LayerV ×2 P30_LayerVI ×2 P90_LayerII-IV ×2 P90_LayerV ×2 P90_LayerVI ×2 +6 more

Supports a between-group comparison across 19 samples.

How we read this: 8 replicated groups read from 25 sample titles; they account for 19 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

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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.