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Zeb2os Hinders Cardiac Healing by Suppressing ZEB2 Reactivation and Cardiomyocyte Dedifferentiation

GSE311091 Mus musculus (mouse) RNA-seq (gene expression) 20 samples Submitted 2026/02/05 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 20 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
20 samples: 5 × RO injection AAV9_CMV_control vs 5 × RO injection AAV9_CMV_Zeb2os vs 5 × RO injection AAV9_hTNNT2_control vs 5 × RO injection AAV9_hTNNT2_Zeb2osGroups 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
Zeb2os Hinders Cardiac Healing by Suppressing ZEB2 Reactivation and Cardiomyocyte DedifferentiationCirculation research · 2026
Summary (written by the submitters)
Background: Long noncoding RNAs (lncRNAs) have emerged as critical regulators in cardiovascular biology, influencing cardiac development, remodeling, and regeneration. Zeb2os, a natural antisense transcript (NATs) of the Zeb2 gene, has been linked to these processes in various organs. While ZEB2 promotes cardiac repair, the role of Zeb2os in these processes remains unclear.
Read the full summary ↓
This study investigates the role of Zeb2os in modulating ZEB2 expression and cardiac remodelling after ischemic injury. Methods: We used adeno-associated virus (AAV9) vectors to overexpress Zeb2os in mouse models of cardiac IR injury. RNA sequencing, immunofluorescence, and high-resolution respirometry were employed to evaluate the effects of Zeb2os delivery on gene expression, ZEB2 reactivation, cardiomyocyte phenotype, scar composition and mitochondrial function. Experiments in cultured cardiomyocytes under hypoxia further explored the regulatory dynamics between Zeb2os and Zeb2. Results: We identified Zeb2os as a hypoxia-responsive lncRNA that displays an inverse and oscillatory expression pattern with Zeb2 in both in vitro and in vivo models of cardiac injury. Functional experiments revealed that Zeb2os negatively regulates ZEB2 expression, impairing the cardiomyocyte dedifferentiation and metabolic remodelling necessary for effective repair. AAV9-mediated delivery of Zeb2os resulted in preserved sarcomere structure, altered scar composition, reduced expression of regenerative genes, and diminished cardiac function following injury. In contrast, silencing of Zeb2os increased ZEB2 protein expression, suggesting a potential therapeutic strategy to enhance repair. Mechanistically, modulation of Zeb2os levels inversely regulated ZEB2 protein expression, whereas ZEB2 modulation had no effect on Zeb2os levels, indicating a unidirectional regulatory axis between the two transcripts. Conclusions: Our findings identify Zeb2os as a stress-responsive inhibitor of ZEB2 reactivation that limits cardiomyocyte plasticity and hinders repair following ischemic injury. Given its specific activity under ischemic conditions, targeting os may represent a novel therapeutic strategy to enhance endogenous cardiac regeneration
Published in
Zeb2os Hinders Cardiac Healing by Suppressing ZEB2 Reactivation and Cardiomyocyte Dedifferentiation
Caliandro R, Ligtermoet ML, Giovou AE et al. · Circulation research 2026 · PMID 41608775 · doi:10.1161/CIRCRESAHA.125.327212
This dataset
Open GSE311091 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 GSE311091_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 PRJNA1368652 and SRA study SRP648052. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41608775) ↗
Study design
5 × RO injection AAV9_CMV_control vs 5 × RO injection AAV9_CMV_Zeb2os vs 5 × RO injection AAV9_hTNNT2_control vs 5 × RO injection AAV9_hTNNT2_Zeb2os

Supports a between-group comparison across 20 samples.

How we read this: 4 replicated groups read from 20 sample titles; they account for 20 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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