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Temporal constraints on enhancer usage and enhancer-promoter connectivity shape the regulation of limb gene transcription [RNA-seq]

GSE262004 Mus musculus (mouse) RNA-seq (gene expression) 99 samples Submitted 2024/03/22 Platform GPL24247Platform GPL21103
At a glance

RNA-seq (gene expression) · mouse · 99 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
99 samples: 37 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
Temporal constraints on enhancer usage shape the regulation of limb gene transcriptionNature communications · 2026
Summary (written by the submitters)
The repertoire of enhancers orchestrating gene expression during embryonic development shapes the forms and functions of organs. Within regulatory landscapes, enhancers control their target genes through spatially distinct or overlapping activities. However, the temporal specificity of enhancers repertoires—how their activities change over time to dynamically influence gene expression—is less well characterized.
Read the full summary ↓
In this study, we introduce the regulatory trajectory framework to monitor how enhancer landscapes govern gene transcription in vivo across extensive developmental periods. This paradigm conceptually involves transcriptional initiation, marking the beginning of gene expression, followed by its maintenance over time, and ultimately decommissioning, leading to gene repression. To track and sort cells undergoing these distinct phases, we devised a transgenic recorder approach at the Shox2 model locus. Through this method, we discovered that cells maintaining Shox2 transcription in early and late limb development relies on distinct, temporally restricted enhancer repertoires. We demonstrate that eliminating early- or late-acting enhancers only transiently affects Shox2 expression indicating that these enhancer repertoires function independently. Additionally, we found that changes in the locus' 3D topology associate with enhancer activities and that a rapid loss of enhancer-promoter contacts occurs during decommissioning. Finally, we show that the decommissioning of the Shox2 locus can be actively driven by Hoxd13, a gene which expression is known to antagonize Shox2. Overall, our work uncovers the dependency of developmental genes on enhancers with temporally restricted activities to generate complex expression patterns over time and shed light on the dynamics of enhancer-promoter interactions.
Published in
Temporal constraints on enhancer usage shape the regulation of limb gene transcription
Rouco R, Rauseo A, Darbellay F et al. · Nature communications 2026 · PMID 41526337 · doi:10.1038/s41467-025-66055-6
This dataset
Open GSE262004 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 GSE262004_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 PRJNA1090023 and SRA study SRP496665. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41526337) ↗
Study design
37 conditions, mostly in duplicate
eFL_Shox2trac_E105 ×5 eFL_Shox2Δearly_E105 ×5 eFL_Shox2trac_E145 ×5 eFL_Shox2Δearly_E145 ×4 eFL_Shox2Δlate_E115 ×4 eFL_Shox2Δlate_E145 ×4 HL_Shox2trac_E115_LowEYFP ×3 eFL_Shox2trac_E115 ×3 +32 more

Supports a between-group comparison across 96 samples.

How we read this: 37 replicated groups read from 99 sample titles; they account for 96 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

+ 59 more — browse all 99 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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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.