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DGCR8 promotes RNA polymerase II pause release independently of DROSHA [ChIP-seq]

GSE324933 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 32 samples Submitted 2026/07/30 Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 32 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
32 samples: 14 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)
DiGeorge syndrome critical region gene 8 (DGCR8) is best known as the RNA binding subunit of the microprocessor complex required for canonical microRNA (miRNA) biogenesis. Whether DGCR8 also exerts a direct, microprocessor independent function in the RNA polymerase II (Pol II) transcription cycle remains unclear. Here, we combined rapid, acute protein depletion with nascent transcription profiling and uncovered a non-canonical role for DGCR8 in transcriptional control in mouse embryonic stem cells (mESCs).
Read the full summary ↓
We found that DGCR8 broadly occupies promoters and transcription start sites (TSSs) with limited co occupancy by its catalytic microprocessor partner DROSHA. Acute DGCR8 depletion triggers an immediate, genome wide reduction in nascent RNA synthesis that is not phenocopied by acute DROSHA depletion. Mechanistically, DGCR8 loss decreases Pol II engagement at promoters and induces a pervasive blockade in promoter proximal pause release, indicating a direct requirement for DGCR8 in the transition to productive elongation. We further identified physical interactions linking DGCR8 to Enhancer of Rudimentary Homolog (ERH) and the elongation factor SPT5, and showed that acute ERH depletion similarly suppresses nascent transcription. Together, our data implicate a potential model in which promoter bound DGCR8 facilitates Pol II pause release through an ERH–SPT5 linked regulatory network, establishing DGCR8 as a non canonical regulator of the core transcription machinery.
This dataset
Open GSE324933 in finder → Find more mouse 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 GSE324933_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 PRJNA1438123 and SRA study SRP684071. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
14 conditions, mostly in duplicate
mES, dTAG_DGCR8, DMSO, FLAG, ×2 mES, dTAG_DGCR8, dTAG24h, FLAG, ×2 mES, dTAG_DROSHA, DMSO, FLAG, ×2 mES, dTAG_DROSHA, dTAG24h, FLAG, ×2 mES, dTAG_ERH, non_dTAG, SPT5, ×2 mES, dTAG_ERH, dTAG_3h, SPT5, ×2 mES, dTAG_DROSHA, non_dTAG, ERH, ×2 mES, dTAG_DROSHA, non_dTAG, SPT5, ×2 +10 more

Supports a between-group comparison across 28 samples.

How we read this: 14 replicated groups read from 32 sample titles; they account for 28 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
Datasets on a similar topic

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