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Single cell profiling reveals three endothelial to hematopoietic transitions with divergent isoform expression landscapes [scRNA-Seq]

GSE274544 Mus musculus (mouse) Single-cell RNA-seq 1494 samples Submitted 2025/09/19 Platform GPL19057Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 1494 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Mus musculus (mouse)
Samples
1494 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.
Paper
Single-cell profiling reveals three endothelial-to-hematopoietic transitions with divergent isoform expression landscapesNature cardiovascular research · 2025
Summary (written by the submitters)
Hemogenic endothelium (HE) is recognized as the origin of all definitive blood cells including hematopoietic stem cells (HSC). However, the mechanisms governing the hematopoietic progenitor versus HSC fate choice within the HE remains unknown. To explore this, we combined differentiation assays with full-length single-cell transcriptome data for extra-embryonic yolk sac (YS) and intra-embryonic aorta–gonad–mesonephros (AGM) region HE populations.
Read the full summary ↓
We identified and localized three differentiation trajectories, each containing a distinct HE subset and potential: erythro-myeloid progenitor-primed HE in the YS plexus, lympho-myeloid progenitor-primed HE in large YS arteries, and HSC-primed HE in the AGM. Chromatin modifiers and spliceosome components were enriched AGM HE. Nanopore long-read sequencing identified AGM specific, functionally unique, splice variants of stemness-associated factors Runx1, Mecom, and Dnmt3b. Our data indicate that isoform expression changes are associated with HSC generation and provide a unique resource for studying cell fate decisions in HE.
Published in
Single-cell profiling reveals three endothelial-to-hematopoietic transitions with divergent isoform expression landscapes
Neo WH, Fadlullah MZH, Bhatnagar H et al. · Nature cardiovascular research 2025 · PMID 41219569 · doi:10.1038/s44161-025-00740-z
This dataset
Open GSE274544 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 GSE274544_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1147181 and SRA study SRP525873. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41219569) ↗
Study design
A cohort of 1494 individual samples

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

How we read this: Sample titles run Cell_0071 … Cell_1701 and carry no group information.

Samples in this study

+ 1454 more — browse all 1494 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

Share this dataset

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.