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Competition for H2A.Z Between IAP Elements and Gene Promoters is Governed by ANP32E

GSE237806 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 53 samples Submitted 2026/06/16 Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 53 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
53 samples: 18 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.
Summary (written by the submitters)
The histone variant H2A.Z is the most evolutionarily conserved histone protein and among the most well studied chromatin factors in biology, yet several unknowns remain, including the role of H2A.Z in transcriptional regulation and its function at heterochromatic repetitive loci. We find that H2A.Z accumulates at a subset of endogenous retrotransposons, including IAP elements, upon their transcriptional activation, and this build-up occurs at the expense of H2A.Z levels over gene promoters.
Read the full summary ↓
We also find that the H2A.Z removal chaperon ANP32E allows these changes to occur by permitting repetitive elements to gain access to surplus H2A.Z which is not installed at gene promoters. Our results are consistent with a model in which H2A.Z supports transcriptional activation of repetitive elements, and competition for H2A.Z between promoters and repetitive elements underlies transcriptome-wide response to retrotransposon reactivation.
This dataset
Open GSE237806 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 GSE237806_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 PRJNA996648 and SRA study SRP450418. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
18 conditions, mostly in triplicate
ANP32E.KO-DMSO_H2AZ_Expt3 biol ×4 WT_H2AZ_Expt1 biol ×3 ANP32E.KO_H2AZ_Expt1 biol ×3 WT-DMSO_H2AZ_Expt2 biol ×3 WT-DAC_H2AZ_Expt2 biol ×3 ANP32E.KO-DAC_H2AZ_Expt3 biol ×3 WT-DAC_RNA-Seq biol ×3 ANP32E-KO-DAC_RNA-Seq biol ×3 +10 more

Supports a between-group comparison across 53 samples.

How we read this: 18 replicated groups read from 53 sample titles; they account for 53 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

+ 13 more — browse all 53 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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