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Limb cell-fate commissioning is guided by widespread coordinated genome detachment from the nuclear lamina [Multiome]

GSE293955 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 10 samples Submitted 2026/07/15 Platform GPL34290Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 10 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Mus musculus (mouse)
Samples
10 samples: 10 samples, each with a distinct title — no replicated groupsGroups 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.
Summary (written by the submitters)
Diverse forms of heterochromatin block inappropriate transcription and safeguard differentiation and cell identity. Yet, how and when heterochromatin is reconfigured to facilitate changes in cell-fate remains a key open question. Here, we address this by mapping a prevalent heterochromatic feature - genome-lamina interactions - relative to transcription in single-cells during mouse embryogenesis.
Read the full summary ↓
We find that lamina-genome interactions remain relatively uniform following gastrulation but are extensively reconfigured during organogenesis in diverse tissues. Focusing on limb development, we demonstrate that genome-lamina interactions are selectively released at key developmental genes and their surrounding regulatory domains in early multipotent progenitors. Strikingly, this “lamina-release” often precedes later gene expression, suggesting it primes regulatory domains for future potential activation. Lamina-release also coincides with the putative binding of crucial limb transcription factors and so is closely intertwined with the regulatory machinery that drives limb formation. Conversely, we show that CTCF-defined boundaries of topologically-associated domains (TADs) constrains the spread of lamina-release at a limb gene locus. This ensures independent heterochromatin dynamics between neighbouring domains. Together, this suggests a previously unrecognised process where genome-lamina interactions are selectively dismantled at regulatory domains to transition loci toward more permissive chromatin states, thereby potentiating cell-type specific activation. Our work thus reveals how systematic heterochromatin reorganization links to developmental multipotency, providing mechanistic insight into how progenitors traverse diverse cell-fates in vivo.
This dataset
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.

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 GSE293955_RAW.tar (it can run to tens of gigabytes).

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.

What the files usually look like: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1245249 and SRA study SRP575922. Searching any of these in the dataset finder brings you back here.

Study design
10 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 10 sample titles: 10 distinct titles with little repetition. 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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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.