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

GSE299110 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2026/03/30 Platform GPL34290
At a glance

RNA-seq (gene expression) · mouse · 18 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
18 samples: 6 conditions, mostly in triplicateGroups 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 GSE299110 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 GSE299110_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 PRJNA1272599 and SRA study SRP590255. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42082401) ↗
Study design
6 conditions, mostly in triplicate
gastruloid differentiation day0 (0hr), contro… ×3 gastruloid differentiation day0 (0hr), Dox, ×3 gastruloid differentiation day3 (72hrs), cont… ×3 gastruloid differentiation day3 (72hrs), Dox, ×3 gastruloid differentiation day5 (120hrs), con… ×3 gastruloid differentiation day5 (120hrs), Dox, ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 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
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