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Genome-wide Mapping of Topoisomerase Binding Sites Suggests Topoisomerase 3a (TOP3A) as a Reader of Transcription-Replication Conflicts (TRC)

GSE269841 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 15 samples Submitted 2024/07/31 Platform GPL21697
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 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
Homo sapiens (human)
Samples
15 samples: 15 samples, each with a distinct title — no replicated groupsGroups 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
Genome-wide Mapping of Topoisomerase Binding Sites Suggests Topoisomerase 3α (TOP3A) as a Reader of Transcription-Replication Conflicts (TRC)bioRxiv : the preprint server for biology · 2024
Summary (written by the submitters)
Both transcription and replication can take place simultaneously on the same DNA template, potentially leading to transcription-replication conflicts (TRCs) and topological problems. Here we asked which topoisomerase(s) is/are the best candidate(s) for sensing TRC. Genome-wide topoisomerase binding sites were mapped in parallel for all the nuclear topoisomerases (TOP1, TOP2A, TOP2B, TOP3A and TOP3B).
Read the full summary ↓
To increase the signal to noise ratio (SNR), we used ectopic expression of those topoisomerases in H293 cells followed by a modified CUT&Tag method. Although each topoisomerase showed distinct binding patterns, all topoisomerase binding signals positively correlated with gene transcription. TOP3A binding signals were suppressed by DNA replication inhibition. This was also observed but to a lesser extent for TOP2A and TOP2B. Hence, we propose the involvement of TOP3A in sensing both head-on TRCs (HO-TRCs) and codirectional TRCs (CD-TRCs). In which case, the TOP3A signals appear concentrated within the promoters and first 20 kb regions of the 5’ -end of genes, suggesting the prevalence of TRCs and the recruitment of TOP3A in the 5’-regions of transcribed and replicated genes.
Published in
Genome-wide Mapping of Topoisomerase Binding Sites Suggests Topoisomerase 3α (TOP3A) as a Reader of Transcription-Replication Conflicts (TRC)
Zhang H, Sun Y, Saha S et al. · bioRxiv : the preprint server for biology 2024 · PMID 38948815 · doi:10.1101/2024.06.17.599352
This dataset
Open GSE269841 in finder → Find more human 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 GSE269841_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 PRJNA1123844 and SRA study SRP513869. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38948815) ↗
Study design
15 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

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