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Nucleolar Stress-inducing Compounds Influence rDNA occupancy of RNA Polymerase I Transcription Machinery

GSE284654 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 64 samples Submitted 2024/12/24 Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 64 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
64 samples: 32 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)
Transcription of ribosomal RNA (rRNA) by RNA Polymerase I (Pol I) is often upregulated in cancer to facilitate rapid cell growth and proliferation, and has emerged as a potential target for chemotherapeutic agents. BMH-21 and Pt(II) chemotherapeutic agent oxaliplatin are well documented as inhibitors of Pol I activity, however the underlying mechanisms for this inhibition are not completely understood.
Read the full summary ↓
Here, we applied chromatin immunoprecipitation sequencing (ChIP-seq) techniques and immunofluorescence imaging to probe the influence of oxaliplatin and BMH-21 on Pol I machinery. We demonstrate oxaliplatin and BMH-21 induce early nucleolar stress leading to the formation of “nucleolar caps” containing Pol I and upstream binding factor (UBF) which corresponds with broad reductions in ribosomal DNA (rDNA) occupancy of Pol I. Distinct occupancy patterns for the two compounds are revealed in ChIP-seq experiments. Taken together, our findings suggest that in vivo, oxaliplatin does not induce Pol I inhibition via interrupting a specific step in Pol I transcription , while treatment with BMH-21 induced unique polymerase stalling at the promoter and terminator regions of the human ribosomal RNA gene.
This dataset
Open GSE284654 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 GSE284654_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 PRJNA1200042 and SRA study SRP552370. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
32 conditions, mostly in duplicate
A549 cells, control, (Input), ×2 A549 cells, control, Pol I (ChIP), ×2 A549 cells, control, UBF (ChIP), ×2 A549 cells, control, mock IgG (ChIP), ×2 A549 cells, oxaliplatin, (Input), ×2 A549 cells, oxaliplatin, Pol I (ChIP), ×2 A549 cells, oxaliplatin, UBF (ChIP), ×2 A549 cells, oxaliplatin, mock IgG (ChIP), ×2 +24 more

Supports a between-group comparison across 64 samples.

How we read this: 32 replicated groups read from 64 sample titles; they account for 64 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

+ 24 more — browse all 64 samples with per-sample file links →

Datasets on a similar topic

Search all human ChIP / ATAC / CUT&Tag datasets in GEO →

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