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Telomere recapping via gene therapy as a therapeutic strategy for cardio-renal syndromes type 4 [NX]

GSE310208 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2026/04/01 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 12 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
12 samples: 3 × heart, rep sham and injected with saline, vs 3 × heart, rep sham and injected with JV101, vs 3 × heart, rep 5/6 nephrectomy and injected with saline, vs 3 × heart, rep 5/6 nephrectomy and injected with JV101,Groups 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)
Cardio-renal syndromes type 4 (CRS4) is defined as heart failure driven by chronic kidney disease (CKD). Cardiovascular mortality is the leading cause of mortality in advanced CKD patients. Current medical treatments exhibit limited efficacy. This study demonstrates that telomere shortening in cardiomyocytes is characteristic of CRS4.
Read the full summary ↓
We engineered an adeno-associated virus9 (AAV9) gene therapy overexpressing catalytic inactive and nuclear localized human telomerase reverse transcriptase (modhTERT) under cardiac troponin T (cTnT) promotor. Overexpression of modhTERT recapped myocardial telomeres, reversed cardiac dysfunction, cardiac hypertrophy, cardiac fibrosis and mitochondrial dysfunction in two CRS4 animal models: 5/6 nephrectomy and Angiotensin II-high salt-uninephrectomy murine models.
This dataset
Open GSE310208 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 GSE310208_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 PRJNA1365273 and SRA study SRP645488. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
3 × heart, rep sham and injected with saline, vs 3 × heart, rep sham and injected with JV101, vs 3 × heart, rep 5/6 nephrectomy and injected with saline, vs 3 × heart, rep 5/6 nephrectomy and injected with JV101,

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.