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Liver-specific loss of the transcriptional coregulator ARGLU1 protects against diet-induced obesity in mice through decreased lipid absorption.

GSE317653 Mus musculus (mouse) RNA-seq (gene expression) 16 samples Submitted 2026/02/02 Platform GPL24247
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
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)
New medications that decrease food intake show promise in addressing the global obesity epidemic; however, additional therapies are needed for patients who are intolerant or unresponsive to these drugs. ARGLU1 is a transcriptional coregulator of several nuclear receptors. Herein, we detail the discovery that mice lacking ARGLU1 in hepatocytes (LKO) are resistant to diet-induced obesity, with no difference in food intake, locomotion, or energy expenditure compared to wildtype mice.
Read the full summary ↓
LKO mice have lower plasma and liver cholesterol levels, attributed to impaired lipid absorption secondary to changes in bile acid composition. The decrease in CYP8B1 in LKO mice corresponded to fewer 12α-hydroxylated bile acids, increasing the relative hydrophobicity of bile, which decreased lipid (triglyceride and cholesterol) absorption. LKO mice further showed preferential use of fatty acids as their fuel source, thereby establishing a mechanistic basis for resistance of LKO mice to diet-induced obesity and identifying a new molecular target for obesity.
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 GSE317653_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 PRJNA1414594 and SRA study SRP666618. Searching any of these in the dataset finder brings you back here.

Samples in this study

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