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Maintenance of Fibroblast Identity During Cardiac Reprogramming and Heart Repair [RNA-seq]

GSE305170 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2025/08/19 Platform GPL32071
At a glance

RNA-seq (gene expression) · mouse · 18 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
18 samples: 6 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.
Summary (written by the submitters)
Direct cardiac reprogramming (CR) of fibroblasts into induced cardiomyocytes represents a promising therapeutic avenue to treat heart failure as it would use the injury by-product and transform fibroblasts into new cardiac muscle thereby achieving the unmet medical need of cardiac regeneration. However, low reprogramming efficiency limits its clinical potential.
Read the full summary ↓
Our lab identified four transcription factors playing a conserved role as barriers to CR. Knock-down of these barriers increase CR five-fold compared to MGT (MEF2C; GATA4; TBX5) overexpression alone. Exploration of direct downstream targets of these barriers identified proteoglycan sulfation as potential pathway regulating cell fate stability. Proteoglycan sulfation, specifically Carbohydrate Sulfotransferase 7 (CHST7), was identified as a conserved barrier to CR. Knockdown of Chst7 in mouse and human fibroblasts significantly enhances CR, increasing expression of cardiac-specific markers and promoting sarcomeric organization. Functional screening of proteoglycan core proteins identifies CD44 as a conserved barrier to reprogramming. Additionally, Chst7 and Cd44 functionally interact to mediate cell fate stability. RNA sequencing and transcription factor analysis identify Junb as the main TF mediating Chst7-regulated transcription during CR. Mechanistic studies of Chst7-regulated pathway genes demonstrate that Chst7 knockdown reduces Pip4k2c expression, establishing a novel regulatory axis between Chst7/Cd44/Junb and Pip4k2c. In vivo, shRNA-mediated Pip4k2c knockdown significantly enhances MGT-mediated CR, increasing cardiac muscle content and reducing fibrosis after myocardial infarction. These findings establish proteoglycan sulfation as a key regulator of cell fate stability, offering new opportunities to improve CR therapies. Thus, proteoglycan sulfation-associated genes might represent an innovative target space to enhance CR for therapeutic purposes.
This dataset
Open GSE305170 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 GSE305170_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 PRJNA1304539 and SRA study SRP608149. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly in triplicate
RNA-iMGT-Myh6-eGFP-MEFs, siControl, D0, Biol ×3 RNA-iMGT-Myh6-eGFP-MEFs, siChst7, D0, Biol ×3 RNA-iMGT-Myh6-eGFP-MEFs, siControl, D1, Biol ×3 RNA-iMGT-Myh6-eGFP-MEFs, siChst7, D1, Biol ×3 RNA-iMGT-Myh6-eGFP-MEFs, siControl, D3, Biol ×3 RNA-iMGT-Myh6-eGFP-MEFs, siChst7, D3, Biol ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 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
Datasets on a similar topic

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