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H3S10-phosphorylation spreading in mitosis stably preserves 3D chromatin structure and functions

GSE252349 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 27 samples Submitted 2025/06/30 Platform GPL24676Platform GPL16791
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 27 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
Homo sapiens (human)
Samples
27 samples: 20 distinct titles, 5 of them repeatedGroups 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)
Gene regulatory landscape of a cell is faithfully recapitulated in daughter cell despite widespread loss of epigenetic marks, transcription and 3D chromatin structure during cell division. How a cell remembers its gene regulatory landscape through mitosis is poorly understood. Recently, a histone modification that spreads on chromatin was postulated to be a preserver of chromatin state.
Read the full summary ↓
Unlike most histone modifications, mitotic cells gain H3S10p but its mitotic bookmarking roles are unknown. Here, we show that as the cell loses its interphase-specific chromatin structure, spreading of H3S10p occurs throughout active chromatin domains. The level of spreading is proportional to the activity of a domain. H3S10pmarked chromatin domains are formed earlier post mitosis. Further, within the domains, promoters but not enhancers are hyper-marked by H3S10p. Using mitosis specific expression of H3S10 and its mutants (H3S10A and H3S10D), we reveal that the loss of mitotic H3S10p causes widespread opening of promoters, resulting in abrupt transcription in the next interphase. We propose that H3S10p spreading preserves the 3D-chromatin epigenetic memory where it acts as a rheostat to fine-tune gene transcription in recently divided cells.
This dataset
Open GSE252349 in finder → Find more human 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 GSE252349_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 PRJNA1060269 and SRA study SRP480910. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
20 distinct titles, 5 of them repeated
ChIP-seq_H3S10p_Asyn_Repeat ×3 ChIP-seq_H3S10p_Mit_Repeat ×3 RNA-seq_S10_Post-mit_7h_Repeat ×2 RNA-seq_S10A_Post-mit_7h_Repeat ×2 RNA-seq_S10D_Post-mit_7h_Repeat ×2

How we read this: Read from 27 sample titles: 20 distinct titles with little repetition. 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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