GEO series

Spatial transcriptomics reveals modulation of transcriptional networks across brain regions after auditory threat conditioning

GSE243140 Mus musculus (mouse) Spatial transcriptomics 16 samples Submitted 2025/07/12 Platform GPL19057

At a glance

Spatial transcriptomics · mouse · 16 samples

What it is: Spatial transcriptomicsGene activity measured with its position in a tissue section.
Organism: Mus musculus (mouse)
Samples: 16 samples: 16 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)

Prior research has demonstrated genome-wide transcriptional changes related to fear and anxiety across species, often focusing on individual brain regions or cell types. However, the extent of gene expression differences across brain regions and how these changes interact at the level of transcriptional connectivity remains unclear. To address this, we performed spatial transcriptomics RNAseq analyses in an auditory threat conditioning paradigm in mice.

Read the full summary ↓

We generated a spatial transcriptomic atlas of a coronal mouse brain section covering cortical and subcortical regions, corresponding to histologically defined regions. Our finding revealed widespread transcriptional responses across all brain regions examined, particularly in the medial and lateral habenula, and the choroid plexus. Network analyses highlighted altered transcriptional connectivity between cortical and subcortical regions, emphasizing the role of steroidogenic factor 1. These results provide new insights into the transcriptional networks involved in auditory threat conditioning, enhancing our understanding of molecular and neural mechanisms underlying fear and anxiety disorders.

This dataset

Open GSE243140 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 GSE243140_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: Spatial studies usually ship Space Ranger style folders (count matrix plus tissue images). Look for them among the supplementary files.

Also filed as BioProject PRJNA1016423 and SRA study SRP460344. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

16 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 16 sample titles: 16 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

GSM7779847 35.1, snRNA-seq
GSM7779848 35.2, snRNA-seq
GSM7779849 35.3, snRNA-seq
GSM7779850 35.4, snRNA-seq
GSM7779851 61.1, snRNA-seq
GSM7779852 61.2, snRNA-seq
GSM7779853 61.3, snRNA-seq
GSM7779854 61.4, snRNA-seq
GSM7779855 69.1, snRNA-seq
GSM7779856 69.2, snRNA-seq
GSM7779857 69.3, snRNA-seq
GSM7779858 69.4, snRNA-seq
GSM7779859 79.1, snRNA-seq
GSM7779860 79.2, snRNA-seq
GSM7779861 79.3, snRNA-seq
GSM7779862 79.4, snRNA-seq

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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.