GEO series

Phase separation of RNA-binding protein promotes polymerase binding and transcription

GSE150399 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 58 samples Submitted 2020/05/12 Platform GPL17021Platform GPL21273

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 58 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: Mus musculus (mouse)
Samples: 58 samples
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)

An RNA-involved phase-separation model has been proposed for transcription control. Yet, the molecular links that connect RNA to the transcription machinery remain missing. Here we find RNA-binding proteins (RBPs) constitute half of the chromatin proteome in embryonic stem cells (ESCs), and some are colocalized with RNA polymerase (Pol) II at promoters and enhancers.

Read the full summary ↓

Biochemical analyses of representative RBPs show that the paraspeckle protein PSPC1 inhibits the RNA-induced premature release of Pol II, and makes use of RNA as multivalent molecules to enhance the formation of transcription condensates and subsequent phosphorylation and release of Pol II. This synergistic interplay enhances polymerase engagement and activity via the RNA-binding and phase-separation activities of PSPC1. In ESCs, auxin-induced acute degradation of PSPC1 leads to genome-wide defects in Pol II binding and nascent transcription. We propose that promoter-associated RNAs and their binding proteins synergize the phase separation of polymerase condensates to promote active transcription.

This dataset

Open GSE150399 in finder → Find more mouse RNA-seq 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 GSE150399_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 PRJNA631979 and SRA study SRP261306. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Samples in this study

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+ 58 more — browse all 58 samples with per-sample file links →

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Search all mouse RNA-seq 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.