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Prevention of cholestatic liver disease through BCL6-FXR enterohepatic crosstalk [RNA-seq]

GSE290309 Mus musculus (mouse) RNA-seq (gene expression) 16 samples Submitted 2026/02/11 Platform GPL30172
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: 16 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
Prevention of Cholestatic Liver Disease Through BCL6-FXR Enterohepatic CrosstalkCellular and molecular gastroenterology and hepatology · 2026
Summary (written by the submitters)
Bile acid (BA) metabolism must be tightly regulated because BAs serve as metabolic signaling molecules but become cytotoxic at high levels. The farnesoid X receptor (FXR) is a crucial bile acid sensor, but our understanding of its regulation and coordination with other transcription factors is limited. Here, we found that B cell lymphoma 6 (Bcl6) functions along with FXR to control bile acid levels.
Read the full summary ↓
We found that mice lacking hepatic BCL6 (Bcl6LKO) had increased BA synthesis and serum levels. In line with this, Bcl6LKO mice had elevated serum cholesterol, the upstream substrate for BA synthesis, as well as reduced expression of the hepatic BA re-uptake transporter sodium-taurocholate cotransporting polypeptide (NTCP). Furthermore, loss of BCL6 reduced hepatic fibroblast growth factor 4 (FGFR4) expression, causing dysregulated entero-hepatic BA feedback signaling. To better understand the relative contribution of BCL6 and FXR in regulating BA homeostasis, we generated mice with a combined deletion of hepatic BCL6 and FXR (Bcl6LKOFxrKO). Critically, combined deletion of FXR and hepatic BCL6 caused massive elevations in BA synthesis/levels compared to loss of Fxr or Bcl6 alone, which resulted in cholestatic liver damage. Mechanistically, we found that Bcl6LKO FxrKO mice had an almost complete loss of hepatic Shp expression, causing high levels of the rate-limiting BA synthesis enzyme CYP7A1. Together, these findings demonstrate that BCL6 and FXR function together to limit BA synthesis and protect the liver from cholestatic injury.
Published in
Prevention of Cholestatic Liver Disease Through BCL6-FXR Enterohepatic Crosstalk
Fruzyna E, Sommars MA, Omura Y et al. · Cellular and molecular gastroenterology and hepatology 2026 · PMID 41389875 · doi:10.1016/j.jcmgh.2025.101706
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 GSE290309_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 PRJNA1227463 and SRA study SRP565901. Searching any of these in the dataset finder brings you back here.

Study design
16 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 16 sample titles: 16 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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