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Beta cell-specific PAK1 enrichment ameliorates diet-induced glucose intolerance by promoting insulin biogenesis and minimizing beta cell apoptosis [ChIP-Seq]

GSE239306 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 2 samples Submitted 2024/09/25 Platform GPL18573
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 2 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Homo sapiens (human)
Samples
2 samples
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
Beta cell-specific PAK1 enrichment ameliorates diet-induced glucose intolerance in mice by promoting insulin biogenesis and minimising beta cell apoptosisDiabetologia · 2025
Summary (written by the submitters)
Aims/ hypothesis: p21 (Cdc42/Rac1) activated Kinase 1 (PAK1) is depleted in type 2 diabetic human islets compared to non-diabetic (ND) human islets, and acute PAK1 restoration to type 2 diabetic human islets can restore insulin secretory function ex vivo. We hypothesized that beta cell specific PAK1 enrichment in vivo carries the capacity to mitigate high-fat diet-induced glucose intolerance by increasing the functional beta cell mass. Methods: Type 2 diabetic or ND human islets expressing exogenous PAK1 specifically in beta cells were used for bulk RNA-sequencing (RNA-seq). Human EndoC-
Published in
Beta cell-specific PAK1 enrichment ameliorates diet-induced glucose intolerance in mice by promoting insulin biogenesis and minimising beta cell apoptosis
Ahn M, Dhawan S, McCown EM et al. · Diabetologia 2025 · PMID 39404845 · doi:10.1007/s00125-024-06286-2
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 GSE239306_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA998794 and SRA study SRP451564. Searching any of these in the dataset finder brings you back here.

Samples in this study

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