Integration of single-cell datasets reveals novel transcriptomic signatures of β-cells in human type 2 diabetes.
Détails
Etat: Public
Version: Final published version
Licence: CC BY 4.0
ID Serval
serval:BIB_5F65528ED583
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Integration of single-cell datasets reveals novel transcriptomic signatures of β-cells in human type 2 diabetes.
Périodique
NAR genomics and bioinformatics
ISSN
2631-9268 (Electronic)
ISSN-L
2631-9268
Statut éditorial
Publié
Date de publication
12/2020
Peer-reviewed
Oui
Volume
2
Numéro
4
Pages
lqaa097
Langue
anglais
Notes
Publication types: Journal Article
Publication Status: epublish
Publication Status: epublish
Résumé
Pancreatic islet β-cell failure is key to the onset and progression of type 2 diabetes (T2D). The advent of single-cell RNA sequencing (scRNA-seq) has opened the possibility to determine transcriptional signatures specifically relevant for T2D at the β-cell level. Yet, applications of this technique have been underwhelming, as three independent studies failed to show shared differentially expressed genes in T2D β-cells. We performed an integrative analysis of the available datasets from these studies to overcome confounding sources of variability and better highlight common T2D β-cell transcriptomic signatures. After removing low-quality transcriptomes, we retained 3046 single cells expressing 27 931 genes. Cells were integrated to attenuate dataset-specific biases, and clustered into cell type groups. In T2D β-cells (n = 801), we found 210 upregulated and 16 downregulated genes, identifying key pathways for T2D pathogenesis, including defective insulin secretion, SREBP signaling and oxidative stress. We also compared these results with previous data of human T2D β-cells from laser capture microdissection and diabetic rat islets, revealing shared β-cell genes. Overall, the present study encourages the pursuit of single β-cell RNA-seq analysis, preventing presently identified sources of variability, to identify transcriptomic changes associated with human T2D and underscores specific traits of dysfunctional β-cells across different models and techniques.
Pubmed
Web of science
Open Access
Oui
Création de la notice
22/02/2021 9:56
Dernière modification de la notice
08/08/2024 7:34