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Splicing Factor RBM22 Broadly Affects RNA Polymerase II 5' Pausing, Elongation Rate and Termination and Prevents Genome Instability [ChIP-seq]

GSE220316 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 64 samples Submitted 2024/03/10 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: 16 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)
Splicing factors are vital for the regulation of RNA splicing, but the underlying molecular mechanisms of their involvement in transcriptional processes remain poorly understood. Here, we describe a direct role of splicing factor RBM22 in coordinating multiple steps of RNA Polymerase II (RNAPII) transcription in human cells. The RBM22 protein widely occupies the RNAPII-transcribed gene locus in the nucleus.
Read the full summary ↓
Loss of RBM22 promotes RNAPII pause release, reduces elongation velocity and provokes transcriptional readthrough genome-wide, coupled with downstream-of-gene (DoG) transcript production and genome instability. RBM22 preferentially binds to the hyperphosphorylated, transcriptionally engaged RNAPII and coordinates its dynamics by regulating the homeostasis of the 7SK-P-TEFb complex and the association between RNAPII and SPT5 at the chromatin level. Our results uncover the multifaceted role of RBM22 in orchestrating the transcriptional program of RNAPII, and provide evidence implicating a splicing factor in both RNAPII elongation kinetics and termination control.
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 GSE220316_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA909633 and SRA study SRP411832. Searching any of these in the dataset finder brings you back here.

Study design
16 conditions, mostly in duplicate
POLR2G_ChIP_22KD ×2 POLR2G_ChIP_NC ×2 POLR2G_Input_22KD ×2 POLR2G_Input_NC ×2 SPT5_ChIP_22KD ×2 SPT5_ChIP_NC ×2 SPT5_Input_22KD ×2 SPT5_Input_NC ×2 +40 more

Supports a between-group comparison across 32 samples.

How we read this: 16 replicated groups read from 64 sample titles; they account for 32 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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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.