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Transcription and Cohesin Direct Genome Positioning and Domain Boundary Plasticity

GSE266505 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 68 samples Submitted 2026/06/25 Platform GPL18573Platform GPL24676Platform GPL30882
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 68 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
Homo sapiens (human)
Samples
68 samples: 68 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.
Paper
Transcription and cohesin direct domain boundary spatial positioning and are linked to Friedreich's ataxiaMolecular cell · 2026
Summary (written by the submitters)
Spatial positioning of the genome and cellular identity have been correlated, but the mechanistic principles underlying 3D genome organization remain unclear. Consequently, our understanding of how compromised genome positioning leads to disease are limited. Here, we demonstrate that a cooperative relationship between gene transcription and cohesin activity directs lamina-associated domain (LAD) boundary plasticity and boundary-proximal gene spatial positioning.
Read the full summary ↓
Transcription mediates LAD boundary fidelity and loss of transcription repositions LAD-boundary genes to the nuclear lamina. The transcriptional repression-mediated repositioning is dependent on cohesin’s loop extrusion activity and cannot be linked to heterochromatin modifiers or compaction status. Further, pathogenic transcriptional silencing of the LAD-boundary gene FXN in Friedrich’s Ataxia is associated with improper peripheral positioning of FXN. Strikingly, loss of cohesin activity is sufficient to reposition mutant FXN away from the nuclear periphery and partially restore FXN transcription. Taken together, we reveal how molecular regulators of distinct genome organization processes collaboratively orchestrate LAD boundary plasticity.
Published in
Transcription and cohesin direct domain boundary spatial positioning and are linked to Friedreich's ataxia
Karnay A, Linares-Saldana R, Wang Q et al. · Molecular cell 2026 · PMID 42127908 · doi:10.1016/j.molcel.2026.04.019
This dataset
Open GSE266505 in finder → Find more human ChIP / ATAC / CUT&Tag 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 GSE266505_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1107477 and SRA study SRP505670. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42127908) ↗
Study design
68 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 68 sample titles: 68 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

+ 28 more — browse all 68 samples with per-sample file links →

Datasets on a similar topic

Search all human ChIP / ATAC / CUT&Tag datasets in GEO →

Share this dataset

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.