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RNA splicing controls organ-wide maturation of postnatal heart in mice

GSE205438 Mus musculus (mouse) Single-cell RNA-seq 88 samples Submitted 2024/08/20 Platform GPL19057Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 88 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
88 samples: 33 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
RNA splicing controls organ-wide maturation of postnatal heart in miceDevelopmental cell · 2025
Summary (written by the submitters)
Postnatal cardiac development requires the orchestrated maturation of diverse cellular components, for which unifying control mechanisms are still lacking. Using full-length sequencing, we examined the transcriptomic landscape of the maturating mouse heart (E18.5-P28) at single-cell and transcript isoform resolution. We identified dynamically changing intercellular networks as a molecular basis of the maturing heart, and alternative splicing (AS) as a common mechanism that distinguished developmental age.
Read the full summary ↓
Manipulation of RNA-binding proteins (RBPs) remodeled the AS landscape, cardiac cell maturation, and intercellular communication through direct binding of splice targets, which were enriched for functions related to general, as well as cell type-specific, maturation. Overexpression of an RBP NCBP2 in neonatal hearts repressed cardiac maturation. Together, our data suggest AS regulation by RBPs as an organ-level control mechanism in mammalian postnatal cardiac development, and provide insight into the possibility of manipulating RBPs for therapeutic purposes.
Published in
RNA splicing controls organ-wide maturation of postnatal heart in mice
Li Z, Cao C, Zhao Q et al. · Developmental cell 2025 · PMID 39406241 · doi:10.1016/j.devcel.2024.09.018
This dataset
Open GSE205438 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 GSE205438_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 PRJNA845728 and SRA study SRP378784. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39406241) ↗
Study design
33 conditions, mostly in duplicate
P ×10 RNA-seq_adult_CM_GFP ×4 RNA-seq_adult_CM_NCBP2-OE ×4 CLIP-seq.CM_G3BP1 ×3 RNA-seq_neonatal_CM_shG3BP1 ×3 RNA-seq_neonatal_CM_shNCBP2 ×3 RNA-seq_neonatal_CM_shNT ×3 RNA-seq_neonatal_CM_shPTBP1 ×3 +30 more

Supports a between-group comparison across 83 samples.

How we read this: 33 replicated groups read from 88 sample titles; they account for 83 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

+ 48 more — browse all 88 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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