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A hepatocyte-specific transcriptional program driven by Rela and Stat3 exacerbates experimental colitis in mice by modulating bile synthesis

GSE243307 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2024/06/23 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 12 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
12 samples: 3 × WT untreated vs 3 × WT treated vs 3 × Rela and Stat3 knockout untreated vs 3 × Rela and Stat3 knockout treatedGroups 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
A hepatocyte-specific transcriptional program driven by Rela and Stat3 exacerbates experimental colitis in mice by modulating bile synthesiseLife · 2024
Summary (written by the submitters)
RelA and Stat3, often collaboratively, induce the synthesis of an array of factors,which orchestrate multiorgan crosstalk in health and diseases. RelA and Stat3 functions in theintestinal epithelial cells are known to tune colon inflammation. If their hepatic activity also impacts inflammation in the gut remains unclear. Here, we reveal that the combined deficiency of RelA and Stat3 specifically in hepatocytes ameliorates DSS-induced experimental colitis.
Read the full summary ↓
Our transcriptomics analyses identified that they activated a hepatic gene program, which directed the expression of alternate bile synthesis pathway genes. Our metabolomics studies substantiated that an absence of RelA and Stat3 in hepatocytes led to a reduced accumulation of inflammatory bile acids, particularly chenodeoxycholic acid, not only in the liver but also in the gut. Indeed, knockout mice displayed a lessened expression of only in the liver but also in the gut. Indeed, knockout mice displayed a lessened expression of inflammatory cytokines and a diminished recruitment of inflammatory cells in the gut upon colitogenic insults; on the other hand, supplementing chenodeoxycholic acid was sufficient to restore the colitogenic sensitivity in these mice. In sum, we suggest that the engagement of inflammatory transcription factors in distant tissues promotes intestinal pathologies via metabolic wiring.
Published in
A hepatocyte-specific transcriptional program driven by Rela and Stat3 exacerbates experimental colitis in mice by modulating bile synthesis
Jyotsna, Sarkar B, Yadav M et al. · eLife 2024 · PMID 39137024 · doi:10.7554/eLife.93273
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 GSE243307_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 PRJNA1017780 and SRA study SRP460720. Searching any of these in the dataset finder brings you back here.

Study design
3 × WT untreated vs 3 × WT treated vs 3 × Rela and Stat3 knockout untreated vs 3 × Rela and Stat3 knockout treated

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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
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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.