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Temporal misexpression of En1 during limb development causes distinct phenotypes [RNA-seq]

GSE277393 Mus musculus (mouse) RNA-seq (gene expression) 33 samples Submitted 2026/05/15 Platform GPL17021
At a glance

RNA-seq (gene expression) · mouse · 33 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
33 samples: 16 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 loss of En1 during limb development causes distinct phenotypesGenes & development · 2026
Summary (written by the submitters)
The precise spatiotemporal regulation of developmental genes is required for proper organogenesis. Engrailed-1 (En1) is essential for dorsal-ventral patterning during mouse limb development from embryonic day E9.5 to E11.5. Previously, we identified the long non-coding RNA locus Maenli, which drives limb-specific En1 expression at E9.5.
Read the full summary ↓
In this study, we investigated the regulatory mechanisms sustaining En1 expression at later developmental stages when Maenli transcriptional activity is drastically reduced. Using in vivo CRISPR editing, we identified two intergenic enhancer elements, LSEE1 and LSEE2, that maintain En1 expression at E10.5 and E11.5. Mice lacking these enhancers exhibit only a subset of the limb malformations observed in En1 and Maenli mutants, suggesting that the timing of En1 misexpression causes distinct phenotypes. These findings underscore the role of temporally restricted activities of cis-regulatory elements, including lncRNA loci and enhancers, in modulating gene expression and explaining subtle differences in complex disease phenotypes.
Published in
Temporal loss of En1 during limb development causes distinct phenotypes
Ringel AR, Benetti N, Magg A et al. · Genes & development 2026 · PMID 41986232 · doi:10.1101/gad.353542.125
This dataset
Open GSE277393 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 GSE277393_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 PRJNA1162101 and SRA study SRP533246. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41986232) ↗
Study design
16 conditions, mostly in duplicate
Somite-E115-CD1WT-Mm ×2 Somite-E105-CD1WT-Mm ×2 MHB-E115-CD1WT-Mm ×2 MHB-E105-CD1WT-Mm ×2 Limb-E11-G4WT-Mm ×2 Limb-E11-G4Del3-Mm ×2 Limb-E11-G4Del2-Mm ×2 Limb-E11-G4Del1-Mm ×2 +9 more

Supports a between-group comparison across 32 samples.

How we read this: 16 replicated groups read from 33 sample titles; they account for 32 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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