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CREB3 gain of functions variants protect against ALS

GSE291695 Mus musculus (mouse) Single-nucleus RNA-seq 57 samples Submitted 2025/04/02 Platform GPL21103
At a glance

Single-nucleus RNA-seq · mouse · 57 samples

What it is
Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue). 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
57 samples: 57 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.
Paper
CREB3 gain of function variants protect against ALSNature communications · 2025
Summary (written by the submitters)
Amyotrophic lateral sclerosis (ALS) is a fatal and rapidly evolving neurodegenerative disease arising from the loss of glutamatergic corticospinal neurons (CSN) and cholinergic motoneurons (MN). Here, we performed comparative cross-species transcriptomics of CSN using published snRNA-seq data from the motor cortex of ALS and control postmortem tissues, and performed longitudinal single cell RNA-seq data on male Sod1G86R mice.
Read the full summary ↓
We report that CSN undergo ER stress and altered mRNA translation, and identify the transcription factor CREB3 and its regulatory network as a resilience marker of ALS, not only amongst vulnerable neuronal populations, but across all neuronal populations as well as other cell types. Using genetic and epidemiologic analyses we further identify the rare variant CREB3R119G (rs11538707) as a positive disease modifier in ALS. Through gain of function, CREB3R119G decreases the risk of developing ALS and the motor progression rate of ALS patients.
Published in
CREB3 gain of function variants protect against ALS
Megat S, Marques C, Hernán-Godoy M et al. · Nature communications 2025 · PMID 40140376 · doi:10.1038/s41467-025-58098-6
This dataset
Open GSE291695 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 GSE291695_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 PRJEB32180 and SRA study ERP114828. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40140376) ↗
Study design
57 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 57 sample titles: 57 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

+ 17 more — browse all 57 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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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.