GEO series

Transient epigenetic changes promote cardiomyocyte differentiation of the subcutaneous adipose stromal vascular fraction

GSE319353 Mus musculus (mouse) RNA-seq (gene expression) 21 samples Submitted 2026/05/01 Platform GPL24247

At a glance

RNA-seq (gene expression) · mouse · 21 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: 21 samples: 7 conditions, mostly in triplicateGroups 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: Transient epigenetic changes promote cardiomyocyte differentiation of the subcutaneous adipose stromal vascular fractionRegenerative therapy · 2026

Summary (written by the submitters)

Introduction: The subcutaneous adipose-tissue-derived stromal vascular fraction (Sa-SVF) contains stem/progenitor cells that rarely transdifferentiate into beating cardiomyocytes. Previously, we developed a culture protocol in which adult murine inguinal Sa-SVF cells reproducibly transdifferentiate into beating cardiomyocyte-like cells (beating CMs) without any specific induction in the primary culture.

Read the full summary ↓

However, the mechanism underlying the differentiation of the Sa-SVF toward the cardiac lineage is unclear. Methods: To identify a key regulator of cardiac differentiation, we investigated sequential changes in global gene expression profiles of Sa-SVF cells during primary culture. Sa-SVF cells were isolated from adult murine inguinal subcutaneous fat pads and cultured using our beating CM induction method. At six time points during primary culture, total RNA was extracted and subjected to RNA-sequencing and quantitative polymerase chain reaction analysis. Results: Beating CMs appeared on day 14. Of 14,574 prefiltered genes, 749 showed significant expression changes (153 upregulated and 596 downregulated, > 2-fold) between days 7 and 14, coinciding with the appearance of beating CMs. Gene ontology analysis highlighted histone deacetylase (HDAC)-associated genes, expression of which was transiently suppressed during the period when cardiac sarcomere-related genes and the transcription factor Mef2c were upregulated. Treatment with an HDAC inhibitor increased cardiac troponin T expression on day 28. Furthermore, treatment of Mef2c-transduced Sa-SVF cells with an HDAC inhibitor markedly augmented cardiac troponin T expression (18-fold vs. control). Conclusions: We identified transient epigenetic modulation—particularly suppression of class II HDACs—as a key driver of Sa-SVF transdifferentiation into cardiomyocytes. These findings provide a mechanistic basis and a potential combinational strategy to enhance SVF-based cardiac regenerative approaches.

Published in

Transient epigenetic changes promote cardiomyocyte differentiation of the subcutaneous adipose stromal vascular fraction

Shinjo Y, Takashima S, Goten C et al. · Regenerative therapy 2026 · PMID 42165033 · doi:10.1016/j.reth.2026.101125

This dataset

Open GSE319353 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 GSE319353_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 PRJNA1423148 and SRA study SRP676740. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42165033) ↗

Study design

7 conditions, mostly in triplicate

P0_day0, ×3 P0_day3, ×3 P0_day7, ×3 P0_day14, ×3 P0_day21, ×3 P0_day28, ×3 P1_day28, ×3

Supports a between-group comparison across 21 samples.

How we read this: 7 replicated groups read from 21 sample titles; they account for 21 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

GSM9516527 P0_day0, rep1 P0_day0,
GSM9516528 P0_day0, rep2 P0_day0,
GSM9516529 P0_day0, rep3 P0_day0,
GSM9516530 P0_day3, rep1 P0_day3,
GSM9516531 P0_day3, rep2 P0_day3,
GSM9516532 P0_day3, rep3 P0_day3,
GSM9516533 P0_day7, rep1 P0_day7,
GSM9516534 P0_day7, rep2 P0_day7,
GSM9516535 P0_day7, rep3 P0_day7,
GSM9516536 P0_day14, rep1 P0_day14,
GSM9516537 P0_day14, rep2 P0_day14,
GSM9516538 P0_day14, rep3 P0_day14,
GSM9516539 P0_day21, rep1 P0_day21,
GSM9516540 P0_day21, rep2 P0_day21,
GSM9516541 P0_day21, rep3 P0_day21,
GSM9516542 P0_day28, rep1 P0_day28,
GSM9516543 P0_day28, rep2 P0_day28,
GSM9516544 P0_day28, rep3 P0_day28,
GSM9516545 P1_day28, rep1 P1_day28,
GSM9516546 P1_day28, rep2 P1_day28,
GSM9516547 P1_day28, rep3 P1_day28,

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