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RNA Polymerase II coordinates histone deacetylation at active promoters

GSE277183 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 158 samples Submitted 2024/09/18 Platform GPL30173Platform GPL24676Platform GPL18573
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 158 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
158 samples: 120 distinct titles, 14 of them repeatedGroups 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)
Nucleosomes at actively transcribed promoters have specific histone post-transcriptional modifications and histone variants. These features are thought to contribute to the formation and maintenance of a permissive chromatin environment. Recent reports have drawn conflicting conclusions about whether these histone modifications depend on transcription.
Read the full summary ↓
We used triptolide to inhibit transcription initiation and degrade RNA Polymerase II and interrogated the effect on histone modifications. Transcription initiation was dispensable for de novo and steady-state histone acetylation at transcription start sites (TSSs) and enhancers. However, at steady state, blocking transcription initiation increased the levels of histone acetylation and H2AZ incorporation at active TSSs. These results demonstrate that deposition of specific histone modifications at TSSs is not dependent on transcription and that transcription limits the maintenance of these marks.
This dataset
Open GSE277183 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 GSE277183_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 PRJNA1160989 and SRA study SRP532660. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
120 distinct titles, 14 of them repeated
Trip_A12_K27ac_CnT ×8 Untr_A12_K27ac_CnT ×8 Aux_HCTaidRPB1_K27ac_CnT ×5 Untr_HCTaidRPB1_K27ac_CnT ×5 Trip_A12_K27ac_CHIP ×4 Untr_A12_K27ac_CHIP ×4 Aux_HCTaidRPB1_H3K4me3_CnT ×3 Untr_HCTaidRPB1_H3K4me3_CnT ×3 +6 more

How we read this: Read from 158 sample titles: 120 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

+ 118 more — browse all 158 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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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.