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Intestinal epithelial cell NCoR deficiency ameliorates obesity and metabolic syndrome

GSE237833 Mus musculus (mouse) RNA-seq (gene expression) 14 samples Submitted 2024/08/01 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 14 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
14 samples: 14 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
Intestinal epithelial cell NCoR deficiency ameliorates obesity and metabolic syndromeActa pharmaceutica Sinica. B · 2024
Summary (written by the submitters)
Obesity has emerged as a common disease worldwide. Risks of developing other metabolic diseases, such as Type 2 diabetes are also higher in obese population. However, current treatment options are limited. Here we discovered a new approach for mitigating obesity and metabolic disorders by targeting intestinal nuclear receptor corepressor (NCoR).
Read the full summary ↓
In mice with diet-induced obesity, NCoR deficiency in intestinal epithelial cells (IECs) improved obesity, insulin resistance, and glucose intolerance, corrected atherogenic dyslipidemia, and reduced hepatic steatosis. These effects were mediated through regulation of energy expenditure, energy harvest, and gut hormone secretion. Mechanistically, NCoR deficiency in IECs stimulated peroxisome proliferator-activated receptor α (PPARα) signaling pathway-mediated succinate production and thermogenesis. Intestinal cholesterol excretion was induced by derepression of intestinal liver X receptor (LXR), and triglyceride and fatty acid absorption in the upper intestine was reduced by disrupted bile acid synthesis and altered bile acid composition. In the distal intestine, increased fatty acid uptake stimulated glucagon-like peptide-1 (GLP-1) secretion and improved glycemic control.
Published in
Intestinal epithelial cell NCoR deficiency ameliorates obesity and metabolic syndrome
Hou S, Yu H, Liu C et al. · Acta pharmaceutica Sinica. B 2024 · PMID 39807334 · doi:10.1016/j.apsb.2024.09.019
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 GSE237833_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 PRJNA996902 and SRA study SRP450566. Searching any of these in the dataset finder brings you back here.

Study design
14 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 14 sample titles: 14 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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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.