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CAD-C: An engineered nuclease enables repair-free in situ proximity ligation and nucleosome-resolution chromosome walks in human cells [Cut & Tag]

GSE318107 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 10 samples Submitted 2026/08/07 Platform GPL30882
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 10 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
10 samples: 3 × RPE1_Pol2ser5_R1T vs 3 × RPE1_Pol2ser5_R2T vs 2 × RPE1_H3K4me1_R1T vs 2 × RPE1_H3K4me1_R2TGroups 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
CAD-C: An engineered nuclease enables repair-free in situ proximity ligation and nucleosome-resolution chromosome walks in human cellsbioRxiv : the preprint server for biology · 2026
Summary (written by the submitters)
Chromosome conformation capture (3C)-derived methods have become an indispensable tool in the study of gene regulation. The three-dimensional contacts can probe depend strongly on the properties of the enzyme used to fragment chromatin prior to proximity-driven ligation. Micrococcal nuclease (MNase), used in Micro-C, increases resolution at the expense of low ligation efficiency and the need for extensive enzyme titration.
Read the full summary ↓
To overcome these limitations, we engineered a highly active, TEV protease-activatable caspase-activated DNase (CAD) to enable an efficient, low-sequence-bias, and high-resolution proximity ligation assay we call CAD-C. CAD-C was successful on the first attempt for each human cell line tested and the resulting datasets capture loops, TADs, compartments, and stripes similarly to Micro-C. However, compared to Micro-C and Hi-C, CAD-C shows enhanced sensitivity for promoter-enhancer loops. Leveraging the ligation-competent DNA ends produced by CAD cleavage, we show that CAD-C is compatible with a highly streamlined, repair-free protocol and produces multi-step CADwalks, consecutive ligations between nucleosomal or sub-nucleosomal fragments. With these walks, we probe local chromatin fiber folding contacts, nucleosomal and sub-nucleosomal footprints, and long-range nuclear organization regimes in human cell lines. CAD-C is an efficient, robust chromatin structure assay that can span sub-nucleosomal to chromosomal length scales in a single experiment.
Published in
CAD-C: An engineered nuclease enables repair-free in situ proximity ligation and nucleosome-resolution chromosome walks in human cells
Soroczynski J, Westcott LA, Zuo W et al. · bioRxiv : the preprint server for biology 2026 · PMID 42146372 · doi:10.64898/2025.12.22.695891
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 GSE318107_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 PRJNA1416661 and SRA study SRP671499. Searching any of these in the dataset finder brings you back here.

Study design
3 × RPE1_Pol2ser5_R1T vs 3 × RPE1_Pol2ser5_R2T vs 2 × RPE1_H3K4me1_R1T vs 2 × RPE1_H3K4me1_R2T

Supports a between-group comparison across 10 samples.

How we read this: 4 replicated groups read from 10 sample titles; they account for 10 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
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