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Effects of loss of KAT6A on histone acetylation and methylation levels, as well as MLL1 and POLR2A occupancy

GSE311724 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 134 samples Submitted 2026/04/20 Platform GPL30172
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 134 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
134 samples: 40 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
KAT6A is essential for developmental control gene expression in neural stem and progenitor cellsPLoS genetics · 2026
Summary (written by the submitters)
Heterozygous variants in the KAT6A gene encoding the histone lysine acetyltransferase KAT6A (MOZ, MYST3) cause Arboleda-Tham syndrome, an intellectual disability syndrome. The profound effects of pathogenic variants in only one allele of KAT6A on cognitive development and functions raises the question what effects heterozygous and homozygous loss of KAT6A may have on gene expression and chromatin modifications, specifically in a neural cell type that is functionally affected by loss of KAT6A.
Read the full summary ↓
To address this question, we established that murine neural stem and progenitor cells form fewer neurons after loss of one and two alleles of Kat6a and used these cells to conduct automated chromatin profiling. We determined within the same cell preparation acetylation at histone H3 lysines 9, 14 and 23, RNA polymerase II (POLR2A) and MLL1 occupancy, as well as levels of methylation at histone H3 lysine 4 (H3K4), the MLL1 target, and compared these chromatin profiling results to the effects of loss of KAT6A on gene expression.
Published in
KAT6A is essential for developmental control gene expression in neural stem and progenitor cells
Voss AK, Eccles S, Wichmann J et al. · PLoS genetics 2026 · PMID 42081590 · doi:10.1371/journal.pgen.1012133
This dataset
Open GSE311724 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 GSE311724_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 PRJNA1370831 and SRA study SRP649655. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42081590) ↗
Study design
40 conditions, mostly in triplicate
H3K9ac, Kat6a+/– proliferating NSPCs, ×4 H3K14ac, Kat6a+/– proliferating NSPCs, ×4 H3K23ac, Kat6a+/– proliferating NSPCs, ×4 MLL1, Kat6a+/– proliferating NSPCs, ×4 H3K4me3, Kat6a+/– proliferating NSPCs, ×4 RNAP2, Kat6a+/– proliferating NSPCs, ×4 IgG, Kat6a+/– proliferating NSPCs, ×4 H3K9ac, Kat6a+/– differentiating NSPCs, ×4 +34 more

Supports a between-group comparison across 132 samples.

How we read this: 40 replicated groups read from 134 sample titles; they account for 132 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

+ 94 more — browse all 134 samples with per-sample file links →

Datasets on a similar topic

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