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ATAC-seq of synovial sarcoma cell lines treated with the BRD9 PROTAC degrader WA-68

GSE328410 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 17 samples Submitted 2026/06/24 Platform GPL34281
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 17 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)
Topic
Soft tissue sarcomaThis series is part of our curated briefing on it.
Samples
17 samples: 8 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)
Synovial sarcoma (SyS) is driven by the SS18::SSX fusion oncoprotein, which incorporates into GBAF chromatin remodeling complexes and creates a dependency on BRD9. To investigate the effects of BRD9 loss, we performed ChIP-seq, ATAC-seq, and RNA-seq in SyS models following BRD9 degradation. ChIP-seq shows reduced GBAF occupancy at target loci, while ATAC-seq reveals maintained or increased chromatin accessibility.
Read the full summary ↓
RNA-seq demonstrates sustained or elevated expression of target genes. These results indicate that BRD9 is not required for GBAF assembly but instead restrains its remodeling activity, providing a mechanistic explanation for the limited efficacy of BRD9-targeted therapies in SyS.
This dataset
Open GSE328410 in finder → Find more human ChIP / ATAC / CUT&Tag datasets → Soft tissue sarcoma landscape →
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 GSE328410_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 PRJNA1454924 and SRA study SRP692792. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
8 conditions, mostly in duplicate
HS-SY-II ATAC-seq, DMSO, biol ×3 SYO-1 ATAC-seq, DMSO, biol ×2 SYO-1 ATAC-seq, WA-68 (100 nM), biol ×2 HS-SY-II ATAC-seq, WA-68 (100 nM), biol ×2 HS-SY-II ATAC-seq, WA-68 (100 nM), 12 h, biol ×2 HS-SY-II ATAC-seq, WA-68 (100 nM), 24 h, biol ×2 HS-SY-II ATAC-seq, WA-68 (100 nM), 48 h, biol ×2 HS-SY-II ATAC-seq, WA-68 (100 nM), 96 h, biol ×2

Supports a between-group comparison across 17 samples.

How we read this: 8 replicated groups read from 17 sample titles; they account for 17 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
More Soft tissue sarcoma datasets

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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.