GEO series

R-loops shape the H2A.Z landscape and promote balanced lineage allocation during differentiation [CUT&Run]

GSE299106 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 20 samples Submitted 2026/03/30 Platform GPL34290

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 20 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: 20 samples: 7 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: R-loops shape the H2A.Z landscape and promote balanced lineage allocation during differentiationGenome research · 2026

Summary (written by the submitters)

R-loops—RNA:DNA hybrids that often form co-transcriptionally—are emerging as key regulators of genome function, yet their roles in shaping chromatin architecture and developmental potential remain incompletely defined. Here, we use inducible Rnaseh1 expression in mouse embryonic stem cells (mESCs) to achieve acute, global R-loop depletion and systematically interrogate their impact on chromatin structure and lineage specification.

Read the full summary ↓

We find that R-loop loss has minimal effect on steady-state gene expression or self-renewal. Instead, it leads to a striking reduction in H2A.Z occupancy at both active and bivalent promoters, accompanied by increased nucleosome density—revealing a previously unrecognized role for R-loops in maintaining promoter architecture. During gastruloid differentiation, R-loop-depleted mESCs exhibit accelerated ectodermal differentiation, along with dysregulation of lineage-specific transcription factors and impaired cell-cell signaling. Consistent with these alterations, R-loop-depleted cells show widespread perturbations in gene regulatory networks across several early cell types. These findings uncover a critical role for R-loops in shaping the H2A.Z chromatin landscape and preserving balanced lineage trajectories during early development, offering new insights into the epigenomic regulation of stem cell fate.

Published in

R-loops shape the H2A.Z landscape and promote balanced lineage allocation during differentiation

Chao CH, Fazzio TG · Genome research 2026 · PMID 42082401 · doi:10.1101/gr.281088.125

This dataset

Open GSE299106 in finder → Find more mouse 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 GSE299106_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 PRJNA1272597 and SRA study SRP590192. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42082401) ↗

Study design

7 conditions, mostly in duplicate

MapR, ×4 MapR, RNaseA, ×4 pA-MNase, ×4 CTCF CUT&RUN, control, ×2 CTCF CUT&RUN, Dox, ×2 IgG CUT&RUN, control, ×2 IgG CUT&RUN, Dox, ×2

Supports a between-group comparison across 20 samples.

How we read this: 7 replicated groups read from 20 sample titles; they account for 20 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

GSM9033050 CTCF CUT&RUN, control, rep1 CTCF CUT&RUN, control,
GSM9033051 CTCF CUT&RUN, control, rep2 CTCF CUT&RUN, control,
GSM9033052 CTCF CUT&RUN, Dox, rep1 CTCF CUT&RUN, Dox,
GSM9033053 CTCF CUT&RUN, Dox, rep2 CTCF CUT&RUN, Dox,
GSM9033054 IgG CUT&RUN, control, rep1 IgG CUT&RUN, control,
GSM9033055 IgG CUT&RUN, control, rep2 IgG CUT&RUN, control,
GSM9033056 IgG CUT&RUN, Dox, rep1 IgG CUT&RUN, Dox,
GSM9033057 IgG CUT&RUN, Dox, rep2 IgG CUT&RUN, Dox,
GSM9033058 MapR, rep1 MapR,
GSM9033059 MapR, rep2 MapR,
GSM9033060 MapR, rep3 MapR,
GSM9033061 MapR, rep4 MapR,
GSM9033062 MapR, RNaseA, rep1 MapR, RNaseA,
GSM9033063 MapR, RNaseA, rep2 MapR, RNaseA,
GSM9033064 MapR, RNaseA, rep3 MapR, RNaseA,
GSM9033065 MapR, RNaseA, rep4 MapR, RNaseA,
GSM9033066 pA-MNase, rep1 pA-MNase,
GSM9033067 pA-MNase, rep2 pA-MNase,
GSM9033068 pA-MNase, rep3 pA-MNase,
GSM9033069 pA-MNase, rep4 pA-MNase,

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