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Distinct Roles for SETα and SETβ in Early Cell Fate Decisions [RNA-Seq]

GSE260530 Mus musculus (mouse) RNA-seq (gene expression) 91 samples Submitted 2026/02/18 Platform GPL17021Platform GPL30172
At a glance

RNA-seq (gene expression) · mouse · 91 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
91 samples: 35 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
Distinct roles for SETα and SETβ in early cell fate decisionsNucleic acids research · 2026
Summary (written by the submitters)
SET, the nuclear proto-oncogene, is primarily expressed as SETα in embryonic stem cells. Upon pluripotency exit, a transcriptional switch driven by alternative promoters causes SETβ to largely replace SETα expression. Functional distinctions between the two isoforms have been difficult to ascertain, partly due to the redundancy between SETα and SETβ in their protein structure and activity.
Read the full summary ↓
In this study, we use embryonic stem cells (ESCs) with inducible SET isoform-specific expression to investigate the differences between both SET isoforms. Time-course RNA-seq analyses in SET-KO backgrounds as well as isoform-specific ChIP-seq experiments reveal regulatory functions for SETα and SETβ. Despite sharing many binding sites and binding partners, SETα has a stronger activation function on its target genes, while SETβ downregulates FGF4. As KLF5 specifically regulates SETα, this implicates SET isoform switching at the KLF5/FGF signalling axis during primitive endoderm specification. Together, we propose a model of how distinct roles of SETα and SETβ may regulate cell identity in the early blastocyst.
Published in
Distinct roles for SETα and SETβ in early cell fate decisions
Lim PSL, Mishne E, Nissim-Rafinia M et al. · Nucleic acids research 2026 · PMID 41665009 · doi:10.1093/nar/gkag105
This dataset
Open GSE260530 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 GSE260530_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 PRJNA1081950 and SRA study SRP492445. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41665009) ↗
Study design
35 conditions, mostly in duplicate
ESC, WT, ×6 ESC, alpha KO, ×6 ESC, beta KO, ×4 ESC, WT SETa, alpha 24h addback experiment ×3 ESC, WT SETb, beta 24h addback experiment ×3 ESC, KO, alpha 24h addback experiement ×3 ESC, KO, beta 24h addback experiment ×3 ESC, WT SETa, ×3 +30 more

Supports a between-group comparison across 88 samples.

How we read this: 35 replicated groups read from 91 sample titles; they account for 88 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

+ 51 more — browse all 91 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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