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Diminished arachidonate 5-lipoxygenase perturbs phase separation and transcriptional response of Runx2 to reverse pathological ventricular remodeling

GSE260492 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2024/03/05 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 × LV, WT_NS vs 3 × LV, WT_TAC vs 3 × LV, Alox5ko_NS vs 3 × LV, Alox5ko_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.
Summary (written by the submitters)
Untargeted metabolomics showed that serum 5-HETE (a primary product of Alox5) levels were little changed in patients with cardiac hypertrophy, while Alox5 expression was significantly upregulated in murine hypertensive cardiac samples and human cardiac samples of hypertrophy, which prompted us to test whether high Alox5 levels under hypertensive stimuli were directly associated with pathologic myocardium in an enzymatic activity-independent manner.
Read the full summary ↓
Herein, we revealed that Alox5 deficiency significantly ameliorated transverse aortic constriction (TAC)-induced hypertrophy. Cardiomyocyte-specific Alox5 depletion attenuated hypertensive ventricular remodeling. Conversely, cardiac-specifical Alox5 overexpression showed a pro-hypertrophic cardiac phenotype. Ablation of Alox5 in bone marrow-derived cells did not affect pathological cardiac remodeling and heart failure.
This dataset
Open GSE260492 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 GSE260492_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 PRJNA1081881 and SRA study SRP492382. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
3 × LV, WT_NS vs 3 × LV, WT_TAC vs 3 × LV, Alox5ko_NS vs 3 × LV, Alox5ko_TAC

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
Datasets on a similar topic

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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.