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Altered pathways in Cockayne syndrome: Involvement of MAPK, PI3K-Akt, extracellular matrix, inflammation, and neuronal signaling

GSE288213 Mus musculus (mouse) RNA-seq (gene expression) 30 samples Submitted 2025/08/28 Platform GPL10010
At a glance

RNA-seq (gene expression) · mouse · 30 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
30 samples: 6 conditions, mostly with about 5 replicates eachGroups 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
Altered pathways in Cockayne syndrome: Involvement of MAPK, PI3K-Akt, extracellular matrix, inflammation, and neuronal signalingDNA repair · 2025
Summary (written by the submitters)
Cockayne syndrome (CS), a disorder characterized by neurodegeneration and a segmental progeroid phenotype, is caused by mutations in CSA or CSB genes, which codify proteins necessary for the DNA repair pathway known as transcription-coupled nucleotide excision repair (TC-NER). To further elucidate the biological pathways associated with this aging-related neurodegenerative phenotype, we analyzed CS transcriptome datasets.
Read the full summary ↓
We performed RNA-seq on the brains of one Csa-/- mouse model and a respecitive wild-type mouse (C57-Black6J background) in three different age timepoints (45 days, 12 months, 24 months). RNA-seq was performed in 5 lanes using AB SOLiD system.
Published in
Altered pathways in Cockayne syndrome: Involvement of MAPK, PI3K-Akt, extracellular matrix, inflammation, and neuronal signaling
Kajitani GS, Tomaz MA, Leandro GDS et al. · DNA repair 2025 · PMID 40570619 · doi:10.1016/j.dnarep.2025.103861
This dataset
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.

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 GSE288213_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1216576 and SRA study SRP560369. Searching any of these in the dataset finder brings you back here.

Study design
6 conditions, mostly with about 5 replicates each
WT brain 1m15d 1 ×5 WT brain 12m 1 ×5 WT brain 24m 1 ×5 Csa brain 1m15d 1 ×5 Csa brain 12m 1 ×5 Csa brain 24m 1 ×5

Supports a between-group comparison across 30 samples.

How we read this: 6 replicated groups read from 30 sample titles; they account for 30 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.