GSE155798: Insulin secretory granules release exosomal miR-503 to promote insulin resistance and β-cell senescence.

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Info Studies were incorporated in a barcode, matrix, feature format. This format can be found on the 10x Genomics website for processing of single cell studies to obtain the gene expression matrices. For each study, the metadata incorporated in GEO were manually curated into profiles and the samples were separated based on applicable groups and conditions. The expression data from the cells for the samples within the same profile and condition were aggregated into an expression matrix with the cell barcodes having the sample name appended to it to ensure unique cell names.

Description (from GEO)

Submission Date: Aug 06, 2020

Summary: Since β cell specific miR-503 transgenic (βTG) mice showed metabolic stress induced insulin resistance and β cell dysfunction, we applied single cell sequencing (scSeq) technology to distinguish different cell type in β TG islets and define different phases of β cell subtypes through pseudotime analysis. Islets were isolated and digested at 37℃for 5 min by 0.08 % trypsin containing 0.006 % EDTA to generate islet single cell, cell suspension was centrifuged and resuspended in cold PBS buffer with 0.4% of BSA at the concentration of ~1000/μl, which then was loaded onto the 10X Chromium Controller using Chromium Single Cell 3' v2 reagents. Sequencing library was prepared following the manufacturer's instructions (10X Genomics), and sequenced via a Illumina HiSeq PE150 instrument. 8698 cells were detected from 10-week old wild type (WT, n = 4540 cells) and βTG (n = 4158 cells) mice islets, cells were split to 12 subtypes by using cell ranger software and k-means algorithm. According to specific gene profile we found that βTG islets was infiltrated with Ccr6/Ccr7 positive immune cells, and most β cells in βTG mice islets were defined senescent cells by using GO enrichment and pseudotime analysis. Our study represents the analysis of islet single cell transcriptomes, the results showed that miR-503 highly expression in β cells promotes β cell senescence and diabetes onset.

GEO Accession ID: GSE155798

PMID: No Pubmed ID

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Info Preprocessing and downstream analysis were computed using the scanpy Python library and the steps of processing followed the Seurat vignette. Cells and genes with no expression or very low expression were removed from the dataset based on a predefined threshold. The data was then normalized across the expression within the cells and log normalized. The top 2000 highly variable genes were extracted to be used for downstream analysis. For each of these aggregated data matrices, the clusters were computed using the leiden algorithm. Scanpy was then used to compute the PCA, t-SNE, and UMAPs. The points in the plots are labelled by their corresponding cell type labels. The cell type labels were computed using the wilcoxon method as the differential gene expression method. The top 250 genes were then used for enrichment analysis against the CellMarker library in order to determine the most appropriate cell type label with the lowest p-value.
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