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Isogenic comparison of Airn and Xist reveals core principles of Polycomb recruitment by lncRNAs

GSE230442 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 129 samples Submitted 2025/02/21 Platform GPL19057Platform GPL32159
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 129 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
129 samples: 103 distinct titles, 19 of them repeatedGroups 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
Isogenic comparison of Airn and Xist reveals core principles of Polycomb recruitment by lncRNAsMolecular cell · 2025
Summary (written by the submitters)
The mechanisms and biological roles of Polycomb repressive complex (PRC) recruitment by lncRNAs remain unclear. To gain insight, we expressed two lncRNAs that recruit PRCs to multi-megabase domains, Airn and Xist, from an ectopic locus and compared effects. Unexpectedly, ectopic Airn recruited PRC1 and PRC2 to chromatin with a potency resembling Xist yet did not repress genes.
Read the full summary ↓
Compared to PRC2, PRC1 was more proximal to Airn and Xist, where its enrichment over C-rich elements required the RNA-binding protein HNRNPK. Fusing Airn to Repeat A, the domain required for gene silencing by Xist, enabled gene silencing and altered local patterns but not relative levels of PRC-directed modifications. Our data suggest that endogenously, Airn recruits PRCs to maintain rather than initiate gene silencing; that PRC recruitment occurs independently of Xist Repeat A; and that protein-bridged interactions, not direct RNA contacts, underlie PRC recruitment by Airn, Xist, and other lncRNAs.
Published in
Isogenic comparison of Airn and Xist reveals core principles of Polycomb recruitment by lncRNAs
Trotman JB, Abrash EW, Murvin MM et al. · Molecular cell 2025 · PMID 40118040 · doi:10.1016/j.molcel.2025.02.014
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 GSE230442_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 PRJNA961141 and SRA study SRP434196. Searching any of these in the dataset finder brings you back here.

Study design
103 distinct titles, 19 of them repeated
tsc_rip_input ×9 tsc_rip_epop ×2 tsc_rip_ezh2 ×2 tsc_rip_hnrnpk ×2 tsc_rip_jarid2 ×2 tsc_rip_mtf2 ×2 tsc_rip_ring1b ×2 tsc_rip_rybp ×2 +11 more

Supports a case/control comparison: 60 samples read as cases, 2 as controls.

How we read this: Read from 129 sample titles: 103 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

+ 89 more — browse all 129 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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