GEO series

Mechanism of SETX-BRCA1-BARD1 complex in resolution of R-loops and transcription-replication conflicts

GSE292585 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 10 samples Submitted 2026/01/16 Platform GPL24676

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: 10 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: Resolution of R-loops and transcription-replication conflicts by SETX-BRCA1-BARD1 complexNature structural & molecular biology · 2026

Summary (written by the submitters)

Senataxin (SETX), a RNA-DNA helicase, is recruited to transcription pause sites via the tumor suppressor BRCA1. Here, we define the mechanism by which SETX-BRCA1 resolves transcription-associated R-loops to prevent deleterious outcomes. Specifically, we show that SETX unwinds R-loops, and that the complex of BRCA1 and its obligatory partner BARD1 binds R-loops and stimulates R-loop unwinding by SETX.

Read the full summary ↓

Importantly, BRCA1-BARD1 alleviates the inhibitory effect of RAD52 on SETX-mediated R-loop unwinding. We also demonstrate that phosphorylation of Ser642 in SETX promotes its interaction with BRCA1 via the tandem BRCT domain of the latter. Accordingly, mutations in the catalytic domain or Ser642 in SETX lead to R-loop accumulation, transcription-replication conflicts, replication fork stalling, and DNA double strand breaks in human cells. Our results thus establish the molecular basis for functional synergy between SETX and BRCA1-BARD1 in R-loop resolution and the mitigation of transcription-replication conflicts to preserve genome integrity.

Published in

Resolution of R-loops and transcription-replication conflicts by SETX-BRCA1-BARD1 complex

Dutta A, Ji JH, Syed S et al. · Nature structural & molecular biology 2026 · PMID 41917467 · doi:10.1038/s41594-026-01778-8

This dataset

Open GSE292585 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 GSE292585_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 PRJNA1240259 and SRA study SRP572200. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41917467) ↗

Study design

10 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 10 sample titles: 10 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

GSM8862076 HAP1, SETX KO, DRIP(REP1)
GSM8862077 HAP1, SETX KO, DRIP(REP2)
GSM8862078 HAP1, SETX KO, DRIP(REP3)
GSM8862079 HAP1, SETX KO, DRIP(INPUT)
GSM8862080 HAP1, SETX KO, DRIP(RNH)
GSM8862081 HAP1, SETX WT, DRIP(REP1)
GSM8862082 HAP1, SETX WT, DRIP(REP2)
GSM8862083 HAP1, SETX WT, DRIP(REP3)
GSM8862084 HAP1, SETX WT, DRIP(INPUT)
GSM8862085 HAP1, SETX WT, DRIP(RNH)

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GSE236546 CDK12 prevents MYC-induced transcription-replication conflicts [ChIP-seq] 2 samples shares transcription-replication, conflicts
GSE273019 A novel method for characterizing cell-cell interactions at single-cell resolution reveals unique signatures in blood T cell-monocyte complexes during infection 67 samples shares resolution, complex
GSE236553 CDK12 prevents MYC-induced transcription-replication conflicts 48 samples shares transcription-replication, conflicts
GSE268017 Transcription-Replication conflicts are linked to histone H3K79 methylation and R-loop dependent nucleosome eviction 37 samples shares transcription-replication, conflicts

Search all human 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.