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H4K16ac contributes to chromatin compartment reorganization during mitotic and meiotic transitions [RNA-seq]

GSE299090 Mus musculus (mouse) RNA-seq (gene expression) 21 samples Submitted 2026/05/27 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 21 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
21 samples: 7 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)
Chromatin compartments reorganize dramatically during cell cycle transitions, shifting from a compartmentalized interphase to a condensed mitotic configuration in which large-scale compartment signals are attenuated. While histone modifications are linked to compartment identity, their contribution to compartment organization remains unclear.
Read the full summary ↓
Using meiotic (mouse spermatogenesis) and mitotic (mouse neuronal progenitor cell, mNPC) models, we mapped histone landscapes alongside compartment dynamics. We found that histone H4 lysine 16 acetylation (H4K16ac) strongly tracked compartment reorganization, remaining enriched in A compartments during compartmentalization but redistributing upon chromatin compaction. In spermatogenesis, H4K16ac loss on the X chromosome coincided with condensation and H3K9me3 spreading. Machine learning highlighted H4K16ac as a stronger predictor of compartment transitions than H3K27ac. Acute degradation of MOF, the principal H4K16ac acetyltransferase, disrupted both the spatial distribution and global abundance of H4K16ac and progressively impaired compartmentalization in mNPCs. These results position H4K16ac as a histone modification selectively coupled to chromatin compartment transitions.
This dataset
Open GSE299090 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 GSE299090_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 PRJNA1272545 and SRA study SRP590156. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
7 conditions, mostly in triplicate
NPC, MOF-dTAG, dTAG13 (500 nM, 0h), ×3 NPC, MOF-dTAG, dTAG13 (500 nM, 24h), ×3 NPC, MOF-dTAG, dTAG13 (500 nM, 12h), ×3 NPC, MOF-dTAG, dTAG13 (500 nM, 4h), ×3 NPC, MOF-dTAG, dTAG13 (500 nM, 16h), ×3 SPG, WT, ×2 SSC, WT, ×2 SPC, WT ×1 +1 more

Supports a between-group comparison across 19 samples.

How we read this: 7 replicated groups read from 21 sample titles; they account for 19 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
Datasets on a similar topic

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