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ORCA-mediated Polycomb Repressive Complex stabilization maintains 3D-genome architecture and controls replication timing

GSE291919 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2026/06/15 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 12 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
12 samples: 12 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
Polycomb-mediated 3D-genome organization controls replication timingScience advances · 2026
Summary (written by the submitters)
Polycomb bodies, also called Polycomb group (PcG) protein complexes, are implicated in gene regulation, especially during development, differentiation, and during the maintenance of tissue-specific functions in multicellular organisms. Predominantly, in transformed cells, PcG bodies  form distinct nuclear foci, within which PcG-bound DNA is localized.
Read the full summary ↓
These structures likely represent misregulated gene expression due to the loss of normal regulatory mechanisms, yet the molecular function of these bodies in cellular homeostasis remains unknown. Using TSA-Seq (Tyramide signal amplification), we provide the first-of-a-kind comprehensive view of the genomic regions, including specific centromeric and telomeric sites that are in proximity to the PcG bodies. Further, these regions are enriched for the repressive histone marks, H3K27me3, H3K9me3 and depleted for active marks, H3K4me3 consistent with a lack of accessible chromatin. We find high density of replication origins around PcG bodies, consistent with the replication factor, ORCA/LRWD1 localizing at these sites. ORCA interacts with the PRC complex, stabilizes the H3K27 methyltransferase, and facilitates the deposition of this histone mark at specific chromatin sites. Loss of ORCA impacts the chromatin organization around the PcG bodies, leading to decompaction of the repeat regions, and enhanced initiation from replication origins. Our results indicate that ORCA interacts with the PcG complex-bound chromatin and maintains a repressed heterochromatin environment to control the timing of replication origin firing.
Published in
Polycomb-mediated 3D-genome organization controls replication timing
Chetlangia N, Thakur BL, Redon CE et al. · Science advances 2026 · PMID 42361181 · doi:10.1126/sciadv.adx7445
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 GSE291919_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1235780 and SRA study SRP570317. Searching any of these in the dataset finder brings you back here.

Study design
12 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 12 sample titles: 12 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
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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.