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Rotational settings quantize nucleosome movement by chromatin regulators

GSE314045 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 15 samples Submitted 2025/12/22 Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 15 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
15 samples: 13 distinct titles, 2 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)
Proper nucleosome positioning is essential for gene regulation and genomic integrity. The need for nucleosomes to be assembled throughout the genome has to be balanced with known intrinsic sequence preferences of nucleosomes. Current models posit that chromatin regulators override the intrinsic preferences to establish the nucleosome landscapes observed in vivo.
Read the full summary ↓
Here, in contrast, we find that chromatin regulators take advantage of both the preference of the nucleosomes for A/T dinucleotides to face inward and G/C outward every 10 bp relative to the histone surface and the existing dinucleotide frequencies of the genome to move nucleosomes in discrete 10 bp steps. We find that the rotational settings of nucleosomes are identical in vivo and in vitro in yeast. Remodelers and transcription elongation change the preference among the alternative translational positions 10 bp apart that a given rotational setting allows. Our results support a model where strong rotational settings introduce a 10 bp ratchet for nucleosome mobilization, leading to quantized shifts in nucleosome positions in yeast and mouse cells.
This dataset
Open GSE314045 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 GSE314045_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 PRJNA1389648 and SRA study SRP655812. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
13 distinct titles, 2 of them repeated
mESCs, DMSO, 3min, ×2 mESCs, DMSO, 9min, ×2

How we read this: Read from 15 sample titles: 13 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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