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Transcriptomic profiling of neonatal mouse ventricular myocytes (NMVMs) under hypoxia and recombinant Serglycin stimulation

GSE318951 Mus musculus (mouse) RNA-seq (gene expression) 9 samples Submitted 2026/06/25 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 9 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
9 samples: 3 × Con vs 3 × Hypoxia vs 3 × Hypoxia+rSRGNGroups 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
Identification and analysis of diagnostic senescence-related gene signatures for acute myocardial infarction based on multi-omics data and machine learningFrontiers in immunology · 2026
Summary (written by the submitters)
To investigate the direct regulatory effects of Serglycin (SRGN) on cardiomyocytes under ischemic conditions, we performed bulk RNA-sequencing on primary neonatal mouse ventricular myocytes (NMVMs). The study includes three experimental groups: Control (Con), Hypoxia, and Hypoxia + recombinant SRGN (rSRGN). NMVMs in the Hypoxia and Hypoxia+rSRGN groups were subjected to oxygen-glucose deprivation (glucose-free and serum-free DMEM) in an anaerobic environment (AnaeroPack-MIC, Mitsubishi A-07) for 6 hours.
Read the full summary ↓
This dataset identifies the transcriptional alterations driven by SRGN in cardiomyocytes during hypoxic stress.
Published in
Identification and analysis of diagnostic senescence-related gene signatures for acute myocardial infarction based on multi-omics data and machine learning
Zhang H, Huang H, Jiang Z et al. · Frontiers in immunology 2026 · PMID 42327787 · doi:10.3389/fimmu.2026.1775092
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 GSE318951_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 PRJNA1420871 and SRA study SRP675881. Searching any of these in the dataset finder brings you back here.

Study design
3 × Con vs 3 × Hypoxia vs 3 × Hypoxia+rSRGN

Supports a between-group comparison across 9 samples.

How we read this: 3 replicated groups read from 9 sample titles; they account for 9 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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