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Comparative analysis of isoproterenol and lipopolysaccharide mediated cytoprotective responses in the heart

GSE307900 Mus musculus (mouse) RNA-seq (gene expression) 23 samples Submitted 2025/10/13 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 23 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
23 samples: 6 conditions, mostly with about 4 replicates eachGroups 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
Comparative analysis of isoproterenol- and lipopolysaccharide-mediated cytoprotective responses in the heartAmerican journal of physiology. Heart and circulatory physiology · 2025
Summary (written by the submitters)
This study aimed to compare the mechanisms by which isoproterenol and lipopolysaccharide induce cytoprotection in the heart. We performed bulk RNA sequencing to compare the transcriptomic effects of isoproterenol and lipopolysaccharide on the heart, to examine features that are shared and unique to each treatment.
Published in
Comparative analysis of isoproterenol- and lipopolysaccharide-mediated cytoprotective responses in the heart
Lim KRQ, Amrute J, Diwan A et al. · American journal of physiology. Heart and circulatory physiology 2025 · PMID 41101778 · doi:10.1152/ajpheart.00594.2025
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 GSE307900_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 PRJNA1327768 and SRA study SRP619600. Searching any of these in the dataset finder brings you back here.

Study design
6 conditions, mostly with about 4 replicates each
Bulk RNA seq, heart, ISO baseline, ×4 Bulk RNA seq, heart, ISO day 7, ×4 Bulk RNA seq, heart, LPS baseline, ×4 Bulk RNA seq, heart, LPS day 1, ×4 Bulk RNA seq, heart, LPS day 7, ×4 Bulk RNA seq, heart, ISO day 1, ×3

Supports a between-group comparison across 23 samples.

How we read this: 6 replicated groups read from 23 sample titles; they account for 23 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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