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MI-883 Constitutes a Novel Dual-Action Ligand Targeting Constitutive Androstane Receptor and Pregnane X Receptor for Hypercholesterolemia Intervention

GSE262786 Mus musculus (mouse) RNA-seq (gene expression) 10 samples Submitted 2025/01/14 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 10 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
10 samples: 5 × liver, PXR-CAR-CYP3A4/3A7_control vs 5 × liver, PXR-CAR-CYP3A4/3A7_ MI-883Groups 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
The hypolipidemic effect of MI-883, the combined CAR agonist/ PXR antagonist, in diet-induced hypercholesterolemia modelNature communications · 2025
Summary (written by the submitters)
We describe the effect of a novel combined human CAR agonist/PXR antagonist MI-883 on the liver transcriptome. RNA-seq transcriptomic data in control (n=5) and MI-883-treated (n=5) humanized PXR-CAR-CYP3A4/3A7 male mice fed with high-fat diet demonstrate that MI-883 significantly regulates genes involved in xenobiotic metabolism, and fatty acid and cholesterol homeostasis. This compound thus reduces plasma cholesterol levels and enhances fecal bile acid excretion.
Published in
The hypolipidemic effect of MI-883, the combined CAR agonist/ PXR antagonist, in diet-induced hypercholesterolemia model
Dusek J, Mejdrová I, Dohnalová K et al. · Nature communications 2025 · PMID 39915454 · doi:10.1038/s41467-025-56642-y
This dataset
Open GSE262786 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 GSE262786_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 PRJNA1093382 and SRA study SRP500496. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39915454) ↗
Study design
5 × liver, PXR-CAR-CYP3A4/3A7_control vs 5 × liver, PXR-CAR-CYP3A4/3A7_ MI-883

Supports a between-group comparison across 10 samples.

How we read this: 2 replicated groups read from 10 sample titles; they account for 10 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

Search all mouse RNA-seq datasets in GEO →

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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.