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Transposase-assisted in situ capture of recombination DSB hotspots (TAID-seq) [CUT&Tag]

GSE313963 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 45 samples Submitted 2026/01/06 Platform GPL24676Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 45 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
45 samples: 38 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)
Genome-wide profiling of the meiotic recombination initiation sites – DNA double-strand break (DSB) hotspots – is essential for understanding the evolution of species of variable origins in sexually reproducing organisms, and to provide the mechanistic insights into recombination, genetic engineering, and plant or animal breeding.
Read the full summary ↓
While current high-throughput sequencing approaches are powerful tools for detecting DSB hotspots, revealing remarkable mechanisms underlying meiotic recombination, they are often time-consuming, labor-intensive, and, in some occasions, practically impossible owing to large sample inputs. Herein, we present Transposase-assisted in situ capture of recombination DSB hotspots (TAID-seq), an approach that leverages both RNA:DNA hybrids and D-loop intermediates at DSB sites. TAID-seq enables the rapid and efficient genome-wide capture of meiotic DSB hotspots. Compared with existing approaches, the TAID-seq workflow requires as few as 50,000 testicular cells, sequencing depths as low as 8 million (M) reads, and can be completed in under 1.5 days. We show that TAID-seq can recapitulate the global recombination DSB landscape in mice and humans. TAID-seq is compatible with archived frozen tissues, and revealed significant difference in the DSB hotspot patterning in human individuals. Further extended applications of TAID-seq strategy will likely unravel the genome-wide recombination DSB landscapes between sexes, populations, and in more rare species, while also illuminating rules and mechanisms underlying spatiotemporal regulation of recombination in health and disease.
This dataset
Open GSE313963 in finder → Find more 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 GSE313963_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 PRJNA1387446 and SRA study SRP655662. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
38 distinct titles, 5 of them repeated
MRE11_6mM ×3 MRE11_Ctrl ×3 H3K9me3 ×2 H3K27ac ×2 IgG ×2

How we read this: Read from 45 sample titles: 38 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

+ 5 more — browse all 45 samples with per-sample file links →

Datasets on a similar topic

Search all 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.