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SOSHI-seq: a high-throughput screening assay to test the functionality of putative response elements for nuclear hormone receptors.

GSE298259 Mus musculus (mouse) RNA-seq (gene expression) 16 samples Submitted 2025/07/01 Platform GPL16417
At a glance

RNA-seq (gene expression) · mouse · 16 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
16 samples: 6 conditions, mostly in duplicateGroups 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
SOSHI-seq: a high-throughput screening assay to test the functionality of putative response elements for nuclear hormone receptorsScientific reports · 2025
Summary (written by the submitters)
We present a cheap, rapid, and versatile assay called SOSHI-seq (Screening Of Self-transcribed Hormone Inducible response elements coupled to sequencing). The protocol is an adaptation of the STARR-seq method, which allows testing the capacity of thousands of synthetic DNA sequences to act as hormone-response elements. Using the nuclear receptors of thyroid hormone as an example, we show that SOSHI-seq is a suitable complement to ChIP-Seq analysis to identify at genome-wide scale the functional response elements occupied by nuclear receptors in chromatin.
Published in
SOSHI-seq: a high-throughput screening assay to test the functionality of putative response elements for nuclear hormone receptors
Wu S, Guyot R, Zekri Y et al. · Scientific reports 2025 · PMID 41353258 · doi:10.1038/s41598-025-29970-8
This dataset
Open GSE298259 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 GSE298259_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 PRJNA1268581 and SRA study SRP588003. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41353258) ↗
Study design
6 conditions, mostly in duplicate
Bank1 Tralpha no T3 repeat ×2 Bank1 Tralpha with T3 repeat ×2 Bank1 Trbeta no T3 repeat ×2 Bank1 Trbeta with T3 repeat ×2 Bank2 Trbeta no T3 repeat ×2 Bank2 Trbeta with T3 repeat ×2 Bank2 LXRa no T-compound ×1 Bank2 LXRa with T-compound ×1 +2 more

Supports a between-group comparison across 12 samples.

How we read this: 6 replicated groups read from 16 sample titles; they account for 12 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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