← BioTransfer GEO Dataset Finder
GEO series

Hepatic translation rewiring in insulin deficiency identifies Reg3α as an insulin-independent glucoregulatory factor

GSE331062 Mus musculus (mouse) RNA-seq (gene expression) 16 samples Submitted 2026/05/22 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: 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.
Summary (written by the submitters)
Insulin deficiency (ID) causes severe metabolic defects and death if untreated. ID affects millions worldwide and insulin therapy remains the only available treatment. However, this approach increases the risk of life-threatening hypoglycemia and does not restore metabolic balance. Thus, insulin therapy is suboptimal. Here, we report that ID reshapes hepatic mRNA translation, characterized by suppression of translation initiation and early elongation, a global reduction in protein synthesis, and extensive remodeling of the hepatic translatome.
Read the full summary ↓
While ID suppresses anabolic and glucose metabolism pathways, it selectively enhances translation of transcripts involved in lipid metabolism and inflammation. Leptin treatment stimulates the translation of regenerating islet-derived protein 3α (Reg3α) in the liver of ID mice. Notably, increased Reg3α expression alone (i.e., without administered insulin and/or leptin) significantly improves hyperglycemia in ID mice. Mechanistically, Reg3α exerts glucose-lowering effects without altering insulin receptor signaling. These findings identify Reg3α as an insulin-independent regulator of glucose homeostasis and reveal hepatic translational control as a previously unrecognized mechanism contributing to metabolic adaptation in ID, with potential therapeutic implications.
This dataset
Open GSE331062 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 GSE331062_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 PRJNA1466814 and SRA study SRP700867. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
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
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.