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Gene-environment interaction elicits dystonia-like features and impaired translational regulation in a DYT-TOR1A mouse model (RNA-Seq)

GSE249875 Mus musculus (mouse) RNA-seq (gene expression) 72 samples Submitted 2024/03/05 Platform GPL30172
At a glance

RNA-seq (gene expression) · mouse · 72 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
72 samples: 12 conditions, mostly with about 6 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
Gene-environment interaction elicits dystonia-like features and impaired translational regulation in a DYT-TOR1A mouse modelNeurobiology of disease · 2024
Summary (written by the submitters)
To elicit a dystonia-like phenotype in a genetically predisposed DYT-TOR1A mouse model (DYT1KI) by performing a right sciatic nerve crush injury. To identify novel pathophysiological pathways and possible biomarker, we performed a multi-omic analysis of three dystonia-relevant brain regions
Published in
Gene-environment interaction elicits dystonia-like features and impaired translational regulation in a DYT-TOR1A mouse model
Reinhold C, Knorr S, McFleder RL et al. · Neurobiology of disease 2024 · PMID 38402912 · doi:10.1016/j.nbd.2024.106453
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 GSE249875_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 PRJNA1051067 and SRA study SRP477348. Searching any of these in the dataset finder brings you back here.

Study design
12 conditions, mostly with about 6 replicates each
RNA CX_wt_naive ×6 RNA CX_wt_crush ×6 RNA CX_tg_naive ×6 RNA CX_tg_crush ×6 RNA STR_wt_naive ×6 RNA STR_wt_crush ×6 RNA STR_tg_naive ×6 RNA STR_tg_crush ×6 +5 more

Supports a between-group comparison across 71 samples.

How we read this: 12 replicated groups read from 72 sample titles; they account for 71 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

+ 32 more — browse all 72 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.