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RNAseq of motor neurons with differential vulnerability to ALS isolated from the SOD1G93A mouse model of ALS

GSE244538 Mus musculus (mouse) Single-cell RNA-seq 54 samples Submitted 2025/07/07 Platform GPL13112
At a glance

Single-cell RNA-seq · mouse · 54 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
54 samples: 54 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)
ALS is characterised by thedegeneration of somaticmotor neurons (MNs), that control voluntary muscle, while visceral motor neurons remain preserved. Some somatic motor neurons are also relatively resilient to degeneration, including oculomotor and trochlear motor neurons that regulate eye movement.In this study we aim to investigate the longitudinal transcriptional dynamics of resistant and vulnerable MN populations in response to the SOD1G93A ALS-causative mutation.
Read the full summary ↓
We have conducted bulk RNA sequencing of MNs isolated from the SOD1G93A mouse at presymptomatic (p56) and symptomatic (p112) stages using laser capture microdissection followed by Smart-seq2 RNA sequencing. Oculomotor and trochlear (CN3/4) MN, and visceral MNs from the vagus nucleus (CN10) represent resilient neuron groups that were analysed. MNs from the lumbar spinal cord (SC) and hypoglossal (CN12) nucleus were utilised as two vulnerable populations.
This dataset
Open GSE244538 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 GSE244538_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 PRJNA1023517 and SRA study SRP464310. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
54 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 54 sample titles: 54 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

+ 14 more — browse all 54 samples with per-sample file links →

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.