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Effect of corticosterone on the gene expression in the context of global hippocampal transcription

GSE280140 Mus musculus (mouse) RNA-seq (gene expression) 48 samples Submitted 2025/06/04 Platform GPL28457
At a glance

RNA-seq (gene expression) · mouse · 48 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
48 samples
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
Effect of Corticosterone on Gene Expression in the Context of Global Hippocampal TranscriptionInternational journal of molecular sciences · 2025
Summary (written by the submitters)
The composition of genomic mediators of glucocorticoids in brain remains elusive because of common problem of low statistical power of experiments and associated very low consistency of transcriptomic data. Other issues is underrepresentation of chronic experiments and interpretation of differentially expressed genes without understanding their contribution to the total transcriptomic activity.
Read the full summary ↓
To fill existing gaps in knowledge we have performed a large transcriptomic experiment (48 mice in total) testing effects of prolonged treatment with corticosterone (5, 14 and 28 days) on hippocampal transcriptome (RNA sequencing) and, next, we have assessed the contribution of differentially expressed genes to total transcriptomic activity. The experiment showed that prolonged treatment with the corticosterone induced a set of transcriptomic effects that were replicable across treatment durations including genes relevant for human PTSD (Opalin, Pllp, Ttyh2, Lpar1) and prolonged stress in animals (Cnp, Fam163a, Fcrls, Tmem125). Part of affected genes is specific for oligodendrocytes, neurons, astrocytes, immune cells, vascular system and brain ventricles indicating that glucocorticoids may affect all components of the central nervous system. The data showed also that the largest changes in expression of corticosterone-responsive genes are restricted to genes that have relatively low expression level and small contribution to the overall pool of mRNAs in the hippocampus. As a result, even large change in terms of the number of affected genes leads to small change in the number of mRNA copies. This means, in turn, that the transcriptomic changes induced by corticosterone are a low-cost effects for the brain.
Published in
Effect of Corticosterone on Gene Expression in the Context of Global Hippocampal Transcription
Juszczak GR, Stankiewicz AM, Starzyński RR et al. · International journal of molecular sciences 2025 · PMID 40430058 · doi:10.3390/ijms26104889
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 GSE280140_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 PRJNA1176536 and SRA study SRP540401. Searching any of these in the dataset finder brings you back here.

Samples in this study

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