← BioTransfer GEO Dataset Finder
GEO series

AAV9-medated cardiac expression of lncRNA CARDINAL ameliorate TAC induced hypertrophy

GSE210983 Mus musculus (mouse) RNA-seq (gene expression) 16 samples Submitted 2024/04/22 Platform GPL28457
At a glance

RNA-seq (gene expression) · mouse · 16 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
16 samples: 4 × 39_Sham vs 4 × 39_TAC vs 4 × Ctrl_Sham vs 4 × Ctrl_TACGroups 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
The long noncoding RNA CARDINAL attenuates cardiac hypertrophy by modulating protein translationThe Journal of clinical investigation · 2024
Summary (written by the submitters)
Pathological cardiac hypertrophy is featured by enhanced protein synthesis. Translation inhibition is effective in treating cardiac hypertrophy, yet with systematic side effect. We identified a cardiac-enriched LncRNA CARDINAL, when over-expressed in cardiomyocyte using AAV9 driven by cTNT promoter, ameliorate transaortic constriction (TAC) induced hypertrophy.
Published in
The long noncoding RNA CARDINAL attenuates cardiac hypertrophy by modulating protein translation
He X, Yang T, Lu YW et al. · The Journal of clinical investigation 2024 · PMID 38743498 · doi:10.1172/JCI169112
This dataset
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.

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 GSE210983_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA868412 and SRA study SRP390951. Searching any of these in the dataset finder brings you back here.

Study design
4 × 39_Sham vs 4 × 39_TAC vs 4 × Ctrl_Sham vs 4 × Ctrl_TAC

Supports a between-group comparison across 16 samples.

How we read this: 4 replicated groups read from 16 sample titles; they account for 16 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

Search all mouse RNA-seq datasets in GEO →

Share this dataset

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.