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Augmenting AMPA receptor signaling following spinal cord injury increases ependymal-derived stem/progenitor cell (epNSPC) migration and promotes functional recovery

GSE295949 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2025/10/31 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 12 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Mus musculus (mouse)
Samples
12 samples: 4 × group1_no SCI vs 4 × group2_SCI vs 4 × group3_SCI+CX546Groups 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)
Using lineage tracing in adult mice, we demonstrate that pharmacological blockade of AMPARs reduces epNSPC proliferation and migration after cervical SCI. Similarly, knocking out AMPAR subunits in Foxj1+ ependymal cells and their progeny abolishes glutamate-mediated AMPA currents and impairs the migration of epNSPCs after SCI.
Read the full summary ↓
Augmenting AMPAR signaling with ampakines maintains the acute maturation reversal of epNSPCs into the chronic injury period, enhances ependymal-glial cell contacts, which may contribute to the spatial distribution and migratory pattern of activated ependymal cells, ameliorates the decrease in corticospinal tract excitability subacutely after SCI, and improves long-term neurobehavioral recovery. Together this work uncovers a neurotransmitter receptor-dependent mechanism of epNSPC activation following injury, which may be targeted to harness the regenerative potential of the spinal cord.
This dataset
Open GSE295949 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 GSE295949_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1256851 and SRA study SRP582214. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
4 × group1_no SCI vs 4 × group2_SCI vs 4 × group3_SCI+CX546

Supports a between-group comparison across 12 samples.

How we read this: 3 replicated groups read from 12 sample titles; they account for 12 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.