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Accession IconSRP103811

Single-cell transcriptomics of East-Asian pancreatic islets cells

Organism Icon Homo sapiens
Sample Icon 332 Downloadable Samples
Technology Badge IconIllumina HiSeq 4000

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Description
Single-cell RNA-seq (scRNA-seq) of pancreatic islets have reported on a- and ß-cell gene expression in mice and subjects of predominantly European ancestry. We aimed to assess these findings in East-Asian islet-cells. 448 islet-cells were captured from three East-Asian non-diabetic subjects for scRNA-seq. Hierarchical clustering using pancreatic cell lineage genes was used to assign cells into cell-types. Differentially expressed transcripts between a- and ß-cells were detected using ANOVA and in silico replications of mouse and human islet cell genes were performed. We identified 118 a, 105 ß, 6 d endocrine cells and 47 exocrine cells. Besides INS and GCG, 26 genes showed differential expression between a- and ß-cells. 10 genes showed concordant expression as reported in rodents, while FAM46A was significantly discordant. Comparing our East-Asian data with data from primarily European subjects, we replicated several genes implicated in nuclear receptor activations, acute phase response pathway, glutaryl-CoA/tryptophan degradations and EIF2/AMPK/mTOR signaling. Additionally, we identified protein ubiquitination to be associated among East-Asian ß-cells. We report on East-Asian a- and ß-cell gene signatures and substantiate several genes/pathways. We identify expression signatures in East-Asian ß-cells that perhaps reflects increased susceptibility to cell-death and warrants future validations to fully appreciate their role in East-Asian diabetes pathogenesis. Overall design: 448 islet-cells were captured from three East-Asian non-diabetic subjects for scRNA-seq. 223 islet-cells remained after samples QC, and these cells were used for subsequent analyses. Hierarchical clustering using pancreatic cell lineage genes was used to assign cells into cell-types. We identified 118 a and 105 ß endocrine cells in our dataset.
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333
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