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Spatial mapping of RNA turnover kinetics in the mouse brain [Spatial NT-seq]

GSE249403 Mus musculus (mouse) RNA-seq (gene expression) 20 samples Submitted 2026/06/12 Platform GPL19057
At a glance

RNA-seq (gene expression) · mouse · 20 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
20 samples: 20 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.
Summary (written by the submitters)
Gene regulation requires coordinated control of RNA synthesis and degradation, yet measuring RNA turnover across intact tissues remains challenging. Here we present spatial NT-seq, a method that combines transgenesis-free metabolic RNA labeling with in situ chemical recoding on spatial transcriptomics platforms to co-map newly synthesized and pre-existing RNAs.
Read the full summary ↓
Applying spatial NT-seq to the mouse brain reveals pronounced regional heterogeneity in RNA turnover and identifies the dentate gyrus as a spatial hotspot marked by coordinated up-regulation of basal RNA synthesis and decay. Moreover, spatial NT-seq uncovers rapid, brain region-specific transcriptional and post-transcriptional responses to electroconvulsive stimulation, a clinically relevant treatment for refractory depression. Finally, we leverage computational modeling to identify sequence features and post-transcriptional regulators that shape transcriptome-wide mRNA stability across spatial and cellular contexts in the mouse brain. Together, this integrated “in vivo Timescope” framework provides a spatially resolved view of RNA turnover kinetics and reveals the regulatory architecture of RNA stability in vivo.
This dataset
Open GSE249403 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 GSE249403_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 PRJNA1048986 and SRA study SRP476054. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
20 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 20 sample titles: 20 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
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.