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Metabolic reprogramming drives pancreatic β cell neogenesis from α cells [RNA-Seq]

GSE302786 Mus musculus (mouse) RNA-seq (gene expression) 9 samples Submitted 2026/06/18 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 9 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
9 samples: 5 × αTC1 cells, DMSO, 7 days, biol vs 4 × αTC1 cells, EPZ011989, 7 days, biolGroups 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)
Loss of functional β cells is a hallmark of diabetes, and restoring β cell mass remains a critical goal in the quest for a specific therapy. One potential strategy is to convert non-β cells in the islet, such as α cells, into insulin-producing cells. Although several compounds have been identified to induce β cell-like features in α cells, none have yet been successfully translated into clinical applications.
Read the full summary ↓
In this study, we identify PRC2 inhibitors as potent inducers of β cell-enriched gene expression in α cells, acting through modulation of the AR-ETV1 complex. AR inhibition suppresses glycogen synthesis and enhances the pentose phosphate pathway (PPP). Direct metabolic reprogramming with methyl esterified 6-phosphogluconate (ME-6-PG), an intermediate metabolite of the PPP, induces β cell-like features in α cells, stimulate β cell regeneration and ameliorates diabetes. Our findings demonstrate that metabolic reprogramming can drive β cell regeneration and highlight a promising therapeutic strategy for diabetes.
This dataset
Open GSE302786 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 GSE302786_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 PRJNA1292160 and SRA study SRP601344. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
5 × αTC1 cells, DMSO, 7 days, biol vs 4 × αTC1 cells, EPZ011989, 7 days, biol

Supports a between-group comparison across 9 samples.

How we read this: 2 replicated groups read from 9 sample titles; they account for 9 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

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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.