← BioTransfer GEO Dataset Finder
GEO series

The effect of MYT1 and ST18 transcription factor down-regulation on gene expression in human islet cells

GSE307751 Homo sapiens (human) RNA-seq (gene expression) 27 samples Submitted 2026/05/06 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 27 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
Homo sapiens (human)
Samples
27 samples: 11 conditions, mostly in duplicateGroups 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)
Genetic and environmental factors together cause islet beta-cell failure, leading to Type 2 diabetes (T2D). Here, we study how two members of the Myelin transcription factor family (MYT1, MYT1L, and ST18) prevent human beta-cell failure under obesity-related stress. We have reported that these factors are induced by high levels of obesity-related nutrients.
Read the full summary ↓
They prevent beta-cell failure in mouse islets and human beta-cell lines. Their variants are all associated with human T2D, and their downregulation accompanies beta-cell dysfunction during T2D development. By knocking down MYT1 or ST18 separately in primary human donor islets, we show here that they have overlapping but distinct functions. Under normal culture conditions, MYT1-knockdown (KD) causes beta-cell death, while ST18-KD compromises glucose-stimulated insulin secretion. Under obesity-induced metabolic stress in vivo, ST18-KD also causes beta-cell death. These findings led us to explore the molecular mechanisms by which MUYT1/ST18 regulate beta cells. The data presented here are the RNAseq of human islets with knockdown of these factors.
This dataset
Open GSE307751 in finder → Find more human 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 GSE307751_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 PRJNA1327267 and SRA study SRP619115. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
11 conditions, mostly in duplicate
Donor 3_pseudo-islet control ×3 Donor 3_Pseudo-islets MYT1_1KD ×3 Donor 3_Pseudo-islets ST18_1KD ×3 Donor 1_Pseudo-islets MYT1_1KD ×2 Donor 1_Pseudo-islets ST18_KD ×2 Donor 2_pseudo-islet control ×2 Donor 2_Pseudo-islets MYT1_1KD ×2 Donor 2_Pseudo-islets ST18_KD ×2 +5 more

Supports a between-group comparison across 25 samples.

How we read this: 11 replicated groups read from 27 sample titles; they account for 25 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 human 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.