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Effects of paternal high cholesterol diet on F1 generation intimal transcriptome

GSE251711 Mus musculus (mouse) RNA-seq (gene expression) 21 samples Submitted 2024/10/08 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 21 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
21 samples: 21 samples, each with a distinct title — no replicated groupsGroups 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
Paternal hypercholesterolemia elicits sex-specific exacerbation of atherosclerosis in offspringJCI insight · 2024
Summary (written by the submitters)
Purpose: To investigate the effects of paternal high cholesterol diet on the F1 intimal transcriptome related to atherosclerosis. Methods:Three-week-old male LDL Receptor-deficient (LDLR-/-) male mice were fed a low-cholesterol diet (LCD) or high-cholesterol diet (HCD) for 8 weeks and then mated with age-matched control LDLR-/- female mice to generate F1 offspring.
Read the full summary ↓
F1 LDLR-/- mice were fed a LCD for 16 weeks. Intimal RNA was extracted by injecting Trizol into the aorta and collecting the flow through for further processing. Results: . Total RNA isolated from the F1 intima were then subjected for RNA-sequencing analysis and results show that paternal hypercholesterolemia led to upregulation of 147 genes in the intimal of F1 female mice, many of which are involved in immune and inflammatory pathways.
Published in
Paternal hypercholesterolemia elicits sex-specific exacerbation of atherosclerosis in offspring
Hernandez R, Li X, Shi J et al. · JCI insight 2024 · PMID 39253968 · doi:10.1172/jci.insight.179291
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 GSE251711_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 PRJNA1055100 and SRA study SRP479294. Searching any of these in the dataset finder brings you back here.

Study design
21 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 21 sample titles: 21 distinct titles with little repetition. 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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