GEO series

U1 snRNP regulates alternative promoter activity by inhibiting premature polyadenylation [CUT&RUN]

GSE252391 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 24 samples Submitted 2025/05/19 Platform GPL24676

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 24 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: 24 samples: 8 conditions, mostly in triplicateGroups 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 and splicing are inherently intertwined. Accumulating evidence support a role of splicing factors in mediating this coupling. U1 small nuclear ribonucleoprotein particle (U1 snRNP), a key splicing factor, acts as the initial building block of the spliceosome, interacting with nascent pre-mRNA at 5' splice sites. In addition to its role in splicing, U1 snRNP is crucial for preventing premature cleavage and polyadenylation, enabling long-distance transcription elongation.

Read the full summary ↓

Here, we show that U1snRNP can regulate the usage of alternative promoters through its role in inhibiting premature polyadenylation. Using antisense oligonucleotides to inhibit U1 snRNP, we first observed a markedly decrease in downstream promoter activity at the newly synthesized RNA level. Interestingly, U1 snRNP inhibition selectively impacts downstream promoters of genes featuring premature polyadenylation sites located between two promoters. Overexpressing a wild-type U1 snRNP or a gene-specific U1 snRNP designed to inhibit premature polyadenylation sites restores downstream promoter activity. Conversely, introducing a premature polyadenylation site between two promoters reduces downstream promoter activity. Exploring the underlying molecular mechanisms, we identified a substantial decrease in serine 5 phosphorylation levels in newly recruited RNA polymerase II at downstream promoters following U1 snRNP inhibition, and reduced chromatin accessibility in the vicinity of downstream promoters. Overall, our model is consistent with productive transcription from upstream promoters triggering downstream promoter activation in the presence of U1 snRNP by destabilizing nucleosomes and promoting promoter escape at downstream promoters.

This dataset

Open GSE252391 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 GSE252391_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 PRJNA1051052 and SRA study SRP477314. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

8 conditions, mostly in triplicate

CUT&RUN_H3K4me3_Ctrl ×3 CUT&RUN_H3K4me3_U1AMO ×3 CUT&RUN_RNAPII_Ctrl ×3 CUT&RUN_RNAPII_U1AMO ×3 CUT&RUN_Ser2P_Ctrl ×3 CUT&RUN_Ser2P_U1AMO ×3 CUT&RUN_Ser5P_Ctrl ×3 CUT&RUN_Ser5P_U1AMO ×3

Supports a between-group comparison across 24 samples.

How we read this: 8 replicated groups read from 24 sample titles; they account for 24 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

GSM8000694 CUT&RUN_H3K4me3_Ctrl1 CUT&RUN_H3K4me3_Ctrl
GSM8000695 CUT&RUN_H3K4me3_Ctrl2 CUT&RUN_H3K4me3_Ctrl
GSM8000696 CUT&RUN_H3K4me3_Ctrl3 CUT&RUN_H3K4me3_Ctrl
GSM8000697 CUT&RUN_H3K4me3_U1AMO1 CUT&RUN_H3K4me3_U1AMO
GSM8000698 CUT&RUN_H3K4me3_U1AMO2 CUT&RUN_H3K4me3_U1AMO
GSM8000699 CUT&RUN_H3K4me3_U1AMO3 CUT&RUN_H3K4me3_U1AMO
GSM8000700 CUT&RUN_RNAPII_Ctrl1 CUT&RUN_RNAPII_Ctrl
GSM8000701 CUT&RUN_RNAPII_Ctrl2 CUT&RUN_RNAPII_Ctrl
GSM8000702 CUT&RUN_RNAPII_Ctrl3 CUT&RUN_RNAPII_Ctrl
GSM8000703 CUT&RUN_RNAPII_U1AMO1 CUT&RUN_RNAPII_U1AMO
GSM8000704 CUT&RUN_RNAPII_U1AMO2 CUT&RUN_RNAPII_U1AMO
GSM8000705 CUT&RUN_RNAPII_U1AMO3 CUT&RUN_RNAPII_U1AMO
GSM8000706 CUT&RUN_Ser2P_Ctrl1 CUT&RUN_Ser2P_Ctrl
GSM8000707 CUT&RUN_Ser2P_Ctrl2 CUT&RUN_Ser2P_Ctrl
GSM8000708 CUT&RUN_Ser2P_Ctrl3 CUT&RUN_Ser2P_Ctrl
GSM8000709 CUT&RUN_Ser2P_U1AMO1 CUT&RUN_Ser2P_U1AMO
GSM8000710 CUT&RUN_Ser2P_U1AMO2 CUT&RUN_Ser2P_U1AMO
GSM8000711 CUT&RUN_Ser2P_U1AMO3 CUT&RUN_Ser2P_U1AMO
GSM8000712 CUT&RUN_Ser5P_Ctrl1 CUT&RUN_Ser5P_Ctrl
GSM8000713 CUT&RUN_Ser5P_Ctrl2 CUT&RUN_Ser5P_Ctrl
GSM8000714 CUT&RUN_Ser5P_Ctrl3 CUT&RUN_Ser5P_Ctrl
GSM8000715 CUT&RUN_Ser5P_U1AMO1 CUT&RUN_Ser5P_U1AMO
GSM8000716 CUT&RUN_Ser5P_U1AMO2 CUT&RUN_Ser5P_U1AMO
GSM8000717 CUT&RUN_Ser5P_U1AMO3 CUT&RUN_Ser5P_U1AMO

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