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The spatial zonation of the placental vasculature is specified by epigenetic mechanisms

GSE280168 Mus musculus (mouse) RNA-seq (gene expression) 383 samples Submitted 2024/11/21 Platform GPL21626
At a glance

RNA-seq (gene expression) · mouse · 383 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Mus musculus (mouse)
Samples
383 samples: 383 samples, each with a distinct title — no replicated groupsGroups 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
The spatial zonation of the murine placental vasculature is specified by epigenetic mechanismsDevelopmental cell · 2025
Summary (written by the submitters)
The labyrinthian fetoplacental capillary network is of vital importance for proper nourishment of the developing embryo. An inadequate function of the maternal-fetal circulation has emerged as one of the primary causes of placental insufficiency. Here, we show that the spatial zonation of the placental labyrinth vasculature is controlled by flow-regulated epigenetic mechanisms.
Read the full summary ↓
The spatial and temporal analysis of gene transcription revealed a gradual change in the expression of epigenetic enzymes with the de novo DNA methyltransferase 3a (DNMT3A) as primary enzyme introducing DNA methylation in cells of the vascular system. Loss of Dnmt3a resulted in DNA hypomethylation and disturbance of the spatial-zonated placental gene expression. The resulting global DNA hypomethylation impaired the angiogenic capacity of endothelial cells. Global as well as endothelium-predominant deletion of Dnmt3a resulted in impaired placental vascularization and fetal growth retardation. A meta-analysis of human placental endothelial cell gene expression identified an association between preeclampsia and reduction of DNMT3A. Collectively, our study identified DMNT3A as critical methylome-regulator of placental endothelial cell gene expression and function with clinical implications for the pathogenesis of placental dysfunction, as it occurs during preeclampsia or fetal growth retardation.
Published in
The spatial zonation of the murine placental vasculature is specified by epigenetic mechanisms
Gehrs S, Jakab M, Gutjahr E et al. · Developmental cell 2025 · PMID 39814015 · doi:10.1016/j.devcel.2024.12.037
This dataset
Open GSE280168 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 GSE280168_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1176678 and SRA study SRP540457. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39814015) ↗
Study design
383 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 383 sample titles: 383 distinct titles with little repetition. 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

+ 343 more — browse all 383 samples with per-sample file links →

Datasets on a similar topic

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.