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Benchmark of chromatin-protein interaction methods in haploid round spermatids

GSE286751 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 14 samples Submitted 2025/05/13 Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 14 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
14 samples: 7 conditions, mostly in duplicateGroups 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-protein interactions are fundamental for the regulation of gene transcription. While ChIP-seq has long been the standard method for mapping these interactions, emerging techniques such as CUT&RUN and CUT&Tag, which offer advantages including low input requirements and high signal-to-noise ratios, have garnered attention. However, these enzyme-based tagmentation approaches may introduce potential biases, and comparative assessment with ChIP-seq remain absent.
Read the full summary ↓
This study aims to systematically evaluate and compare the performance of ChIP-seq, CUT&Tag, and CUT&RUN for profiling genome-wide transcription factors and histone modifications binding. This study provides a comprehensive evaluation of ChIP-seq, CUT&Tag, and CUT&RUN for detecting active and repressive histone modifications as well as transcription factor binding. Our results show that all three methods reliably detect histone modifications and transcription factor enrichment, with CUT&Tag demonstrating a relatively higher signal-to-noise ratio. Rigorous peak comparison analysis identified differential enrichment sites detected by the three methods. Additionally, we observed a notable correlation between CUT&Tag signal intensity and chromatin accessibility, suggesting the potential for CUT&Tag to detect regions of active chromatin.
This dataset
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.

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 GSE286751_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1209986 and SRA study SRP557085. Searching any of these in the dataset finder brings you back here.

Study design
7 conditions, mostly in duplicate
Mouse round spermatids, H3K4me3, CUTNTag, ×2 Mouse round spermatids, H3K27me3, CUTNTag, ×2 Mouse round spermatids, CTCF, CUTNTag, ×2 Mouse round spermatids, H3K4me3, CUTNRUN, ×2 Mouse round spermatids, H3K27me3, CUTNRUN, ×2 Mouse round spermatids, CTCF, CUTNRUN, ×2 Mouse round spermatids, ATAC-seq, ×2

Supports a between-group comparison across 14 samples.

How we read this: 7 replicated groups read from 14 sample titles; they account for 14 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

Search all mouse ChIP / ATAC / CUT&Tag datasets in GEO →

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.