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Transcriptome of rNLS8 mice and controls injected with non-targeting control ASO

GSE290262 Mus musculus (mouse) RNA-seq (gene expression) 21 samples Submitted 2025/03/08 Platform GPL28457
At a glance

RNA-seq (gene expression) · mouse · 21 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
21 samples: 21 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
Correction of dysregulated lipid metabolism normalizes gene expression in oligodendrocytes and prolongs lifespan in female poly-GA C9orf72 miceNature communications · 2025
Summary (written by the submitters)
We asked how knockdown of genes associated with neurodegeneration using antisense oligonucleotides (ASO) affects disease phenotypes in an inducible TDP-43 transgenic mouse model (rNLS8, Walker et al., Acta Neuropathologica 2015) backcrossed to the C57BL/6 background. This dataset includes only the non-targeting control, which was also used as a replication cohort for transcriptional changes in rNLS8 mice (Rezaei et al., in revision at Nature Communications).
Read the full summary ↓
We show cholesterol dysmetabolism and marker genes of disease-associated oligodendrocytes in the brain of rNLS8 mice. Data from mice receiving the targeting ASOs will be made available upon publication of the manuscript (Kocsis-Jutka et al, in preparation).
Published in
Correction of dysregulated lipid metabolism normalizes gene expression in oligodendrocytes and prolongs lifespan in female poly-GA C9orf72 mice
Rezaei A, Kocsis-Jutka V, Gunes ZI et al. · Nature communications 2025 · PMID 40216746 · doi:10.1038/s41467-025-58634-4
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 GSE290262_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 PRJNA1226927 and SRA study SRP565653. Searching any of these in the dataset finder brings you back here.

Study design
21 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 21 sample titles: 21 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
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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.