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Dissecting cell-type specific pathophysiological changes in human type-2 diabetic pancreatic islets using single-cell transcriptomic data

GSE221156 Homo sapiens (human) Single-cell RNA-seq 54 samples Submitted 2023/03/30 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 54 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Homo sapiens (human)
Samples
54 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.
Summary (written by the submitters)
Pancreatic islet (dys)function is central to glucose homeostasis and type 2 diabetes (patho)physiology. Human islets consist of multiple endocrine (alpha, beta, delta, gamma), endothelial, and resident/inflitrating immune cells whose coordinated functions modulate glucose mobilization or disposal. Single cell transcriptome profiling (scRNA-seq) studies have been applied to dissect human islet cellular heterogeneity, identify islet cell (sub)populations, and define their molecular repertoire.
Read the full summary ↓
However, precise understanding of cell type-specific alterations in type 2 diabetic vs. non-diabetic individuals is lacking, due in part to the limited number of individuals or single cell transcriptomes per individual profiled for comparison. Here, we create a comprehensive single cell transcriptome atlas of 245,878 human islet cells from 48 individuals spanning non-diabetic (ND), pre-diabetic (PD), and type 2 diabetic (T2D) states and matched for sex, age, and ancestry and define marker gene sets that are robustly expressed across disease states for each of the 14 cell types identified. We observe significant decreases in the number of beta cells sampled from T2D vs. ND or PD donors. Two of eight putative beta cell subpopulations, with ‘high functioning’ and ‘senescent’ cell gene signatures, increase and decrease in T2D donor islets, respectively. Importantly, we identify 511 differentially expressed genes in beta cells from T2D vs. ND donors. This includes monogenic and type 2 diabetes effector genes, such as HNF1A, DGKB, ST6GAL1, and FXYD2, for which genetic and environmental effects on their expression is concordant.  Human beta cell and islet knockdown of selected newly-identified down-regulated genes impairs beta cell viability or function. Together, this study provides new and robust, cell type-resolved insights on the cellular and molecular changes in healthy vs. diabetic human islets and represents a valuable resource to the islet biology and type 2 diabetes communities.
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 GSE221156_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA913127 and SRA study SRP413460. Searching any of these in the dataset finder brings you back here.

Samples in this study

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