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Transcriptomic Landscape of Hyperthyroidism in Mice Overexpressing Thyroid Stimulating Hormone

GSE279577 Mus musculus (mouse) RNA-seq (gene expression) 21 samples Submitted 2024/10/21 Platform GPL24247
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: 7 conditions, mostly in triplicateGroups 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
Transcriptomic landscape of hyperthyroidism in mice overexpressing thyroid-stimulating hormoneiScience · 2025
Summary (written by the submitters)
Activation of thyroid stimulating hormone receptor (TSHR) fundamentally leads to hyperthyroidism. To elucidate TSHR signaling, we conducted transcriptome analyses for hyperthyroid mice that we generated by overexpressing TSH. TSH overexpression drastically changed their thyroid transcriptome. In particular, enrichment analyses identified the cell cycle, phosphatidylinositol-3 kinase/Akt pathway, and Ras-related protein 1 pathway as possibly associated with goiter development.
Read the full summary ↓
Regarding hyperthyroidism, Slc26a4 was exclusively upregulated with TSH overexpression among genes crucial to thyroid hormone secretion. To verify its significance, we overexpressed TSH in Slc26a4 knockout mice. TSH overexpression caused hyperthyroidism in Slc26a4 knockout mice, equivalent to that in control mice. Thus, we did not observe significant changes in known genes and pathways involved in thyroid hormone secretion with TSH overexpression. Our datasets might include candidate genes that have not yet been identified as regulators of thyroid function. Our transcriptome datasets regarding hyperthyroidism can contribute to future research on TSHR signaling.
Published in
Transcriptomic landscape of hyperthyroidism in mice overexpressing thyroid-stimulating hormone
Yamauchi I, Sugawa T, Hakata T et al. · iScience 2025 · PMID 39811643 · doi:10.1016/j.isci.2024.111565
This dataset
Open GSE279577 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 GSE279577_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 PRJNA1173538 and SRA study SRP538870. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39811643) ↗
Study design
7 conditions, mostly in triplicate
Thyroid, Empty, 1week, ×3 Thyroid, TSH, 1week, ×3 Thyroid, TSH-MMI, 1week, ×3 Thyroid, Empty, 4week, ×3 Thyroid, Empty-MMI, 4week, ×3 Thyroid, TSH, 4week, ×3 Thyroid, TSH-MMI, 4week, ×3

Supports a between-group comparison across 21 samples.

How we read this: 7 replicated groups read from 21 sample titles; they account for 21 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
Datasets on a similar topic

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