← BioTransfer GEO Dataset Finder
GEO series

Intestinal epithelial cell EphB4 deficiency on high fat diet-induced obesity

GSE282601 Mus musculus (mouse) RNA-seq (gene expression) 16 samples Submitted 2025/11/30 Platform GPL24247
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: 9 × Duodenum, HFD, F vs 7 × Duodenum, HFD, KOGroups 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.
Summary (written by the submitters)
High-fat diets (HFD) exacerbate excessive lipid absorption by compelling the small intestine (SI) to take in redundant calories, yet host-encoded mechanisms are not fully explored. Previous research demonstrated that intestinal group 3 innate lymphoid cell (ILC3)–interleukin-22 (IL-22)–phosphorylated signal transducer and activator of transcription 3 (pSTAT3) axis fluctuates with feeding rhythms and engages in nutrient absorption.
Read the full summary ↓
We found that prolonged HFD feeding enhances this axis in the proximal SI, leading to adaptively increased lipid absorption. Notably, we identified Eph receptor B4 (EphB4), an intestinal epithelial regulator that interacts with ILC3s microbiota-independently, thereby boosting pre-meal IL-22 secretion and subsequent lipid absorption, elucidating its crucial role in the interplay between diet, immune axis, and metabolism. In HFD-induced obesed mice, deleting EphB4 in intestinal epithelial cells (IECs) reduced proximal intestinal lipid absorption, improved obesity and metabolic disorders.
This dataset
Open GSE282601 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 GSE282601_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 PRJNA1189446 and SRA study SRP546960. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
9 × Duodenum, HFD, F vs 7 × Duodenum, HFD, KO

Supports a between-group comparison across 16 samples.

How we read this: 2 replicated groups read from 16 sample titles; they account for 16 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 →

Share this dataset

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.