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Myocardial Reprogramming by HMGN1 Underlies Heart Defects in Trisomy 21 [scRNA-seq]

GSE306773 Mus musculus (mouse) Single-cell RNA-seq 29 samples Submitted 2025/08/28 Platform GPL21103Platform GPL20301
At a glance

Single-cell RNA-seq · mouse · 29 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
29 samples: 10 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
Myocardial reprogramming by HMGN1 underlies heart defects in trisomy 21Nature · 2025
Summary (written by the submitters)
Congenital heart defects (CHD) are the most common form of developmental abnormalities, occurring in ~1% of live births, and can arise due to altered dosage of genes essential for cardiogenesis. Aneuploidy accounts for nearly 15% of CHD and the most frequent form involves trisomy of chromosome 21 (Ch21), resulting in Down Syndrome (DS).
Read the full summary ↓
Here we used single cell RNA-seq, CRISPR-activation with single cell RNA-seq, single cell ATAC-seq and Cut&Tag epigenomic profiling to define the molecular disruptions occuring with Trisomy 21 and upregulation of the Ch21 epigenetic factor HMGN1. These experiments were performed in human pluripotent stem cells (hiPSCs) or in directed differentiation to cardiomyocyte lineages at days 10 and 20.
Published in
Myocardial reprogramming by HMGN1 underlies heart defects in trisomy 21
Ranade SS, Li F, Whalen S et al. · Nature 2025 · PMID 41125893 · doi:10.1038/s41586-025-09593-9
This dataset
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.

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 GSE306773_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1312080 and SRA study SRP614027. Searching any of these in the dataset finder brings you back here.

Study design
10 conditions, mostly in duplicate
scRNA_CROPtimecourse_endogenous_CROP ×6 scRNA_CROPtimecourse_amplicon_CROP ×6 scRNA_E115_tg ×3 scRNA_E115_wt ×2 scRNA_E115_het ×2 scRNA_VPR_DSCAM ×2 scRNA_VPR_DYRK1A ×2 scRNA_WiCell_B ×2 +2 more

Supports a between-group comparison across 29 samples.

How we read this: 10 replicated groups read from 29 sample titles; they account for 29 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
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