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Effect of IL-6 Trans-Signaling Blockade by sgp130 overexpression on hepatic gene expression in the context of mature-onset obesity in mice

GSE307940 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2025/09/30 Platform GPL17021
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: 12 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
Blockade of Interleukin-6 Trans-signaling in the Presence of Certain Gut Microbiota Induces Mature-onset Obesity in MiceGastro hep advances · 2026
Summary (written by the submitters)
Interleukin-6 (IL-6) performs multiple roles in regulating metabolic pathways in both mice and man. Here, we examined the age-dependent metabolic phenotype of mice overexpressing sgp130 (SGP mice), which specifically blocks IL-6 trans-signaling. Transgenic SGP mice engineered to block IL-6 trans-signaling and wild-type (WT) littermates were raised to 6 and 14 months of age.
Read the full summary ↓
RNA-seq analyses were performed on liver samples as a function of age and genotype. At ~6 months of age, weight gain, body fat accumulation, hepatosteatosis, hyperglycemia, and macrophage recruitment to adipose tissue emerged and progressed with age in SGP mice. IL-6/sIL-6R blockade strongly reduced STAT3 phosphorylation in the liver. RNA-seq analyses of mouse livers revealed genotype-related changes in gene expression profiles attributable to bacterial byproducts. Depletion of the gut microbiota by antibiotic treatment from the age of 6 months reversed the obese phenotype in transgenic mice, confirming the crucial role of the microbiome in the phenotype. These findings reveal the crucial functions of IL-6 trans-signaling in preventing mature-onset body fat accumulation induced by certain intestinal microbiota.
Published in
Blockade of Interleukin-6 Trans-signaling in the Presence of Certain Gut Microbiota Induces Mature-onset Obesity in Mice
Lanton T, Eidelshtein D, Rachmilewitz J et al. · Gastro hep advances 2026 · PMID 41362820 · doi:10.1016/j.gastha.2025.100819
This dataset
Open GSE307940 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 GSE307940_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 PRJNA1327856 and SRA study SRP619742. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41362820) ↗
Study design
12 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 12 sample titles: 12 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
Datasets on a similar topic

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