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Genetic and Epigenetic Regulation of Pvt1 Monoallelic Expression [ChIP-seq]

GSE287456 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 70 samples Submitted 2025/09/26 Platform GPL19057Platform GPL34290Platform GPL21103
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 70 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
70 samples: 29 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.
Paper
Genetic and chromatin regulation of Pvt1 monoallelic expressionCell reports · 2025
Summary (written by the submitters)
Each gene exists as two copies in the same nucleus of mammalian cells. Although most genes are equivalently controlled on both alleles, Random Monoallelic Expressing (RME) genes stably maintain the expression from only one of two alleles, but the mechanisms and functional consequences of RME remains unclear. Here we performed allele-specific RNA-seq on over 100 neural progenitor cell (NPC) clonal lines to reveal the extent of RME for genes across clonal lines.
Read the full summary ↓
Interestingly out of 297 autosomal RME genes, Pvt1, a well-studied oncogenic long non-coding RNA, is monoallelically expressed with a skewed genetic bias towards the Castaneous allele in F1-hybrid NPCs. In the absence of genetic differences, allelic tracking by gene editing reveals Pvt1 undergoes balanced RME that is maintained across somatic cell generations. Leveraging our large RNA-seq data set and the genetic skew, we use differential gene expression analysis on clonal lines based on their Pvt1 allelic status to reveal a transcription factor, TFAP2a, with differential binding at the Pvt1 promoter, providing a mechanism for the initiation and allelic choice for RME genes. Additionally, we demonstrate monoallelic Pvt1 expression results in an increase in Pvt1 expression leading to a growth advantage relative to Pvt1 biallelic expressing clonal lines These findings provide an example of how genetic differences can skew a stochastic process which results in an epigenetic phenomenon with a phenotypic consequence in early development.
Published in
Genetic and chromatin regulation of Pvt1 monoallelic expression
Luong C, Chen M, Belk JA et al. · Cell reports 2025 · PMID 41223055 · doi:10.1016/j.celrep.2025.116554
This dataset
Open GSE287456 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 GSE287456_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 PRJNA1213043 and SRA study SRP558485. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41223055) ↗
Study design
29 conditions, mostly in duplicate
Ch1_NPC_H2AK119ub Biological repliacate ×2 Ch1_NPC_H3K27ac_Ab Biological repliacate ×2 Ch1_NPC_H3K27me3 Biological repliacate ×2 Ch1_NPC_H3K4me2 Biological repliacate ×2 Ch1_NPC_H3K4me3 Biological repliacate ×2 Ch1_NPC_H3K9me3 Biological repliacate ×2 Ch1_NPC_input Biological repliacate ×2 Ch8_NPC_H2AK119ub Biological repliacate ×2 +33 more

Supports a between-group comparison across 58 samples.

How we read this: 29 replicated groups read from 70 sample titles; they account for 58 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

+ 30 more — browse all 70 samples with per-sample file links →

Datasets on a similar topic

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