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Single-cell RNA-seq transcriptomic landscape of human and mouse islets and pathological alterations of diabetes.

ABSTRACT: Single-cell RNA sequencing has paved the way for delineating the pancreatic islet cell atlas and identifying hallmarks of diabetes. However, pathological alterations of type 2 diabetes (T2D) remain unclear. We isolated pancreatic islets from control and T2D mice for single-cell RNA sequencing (scRNA-seq) and retrieved multiple datasets from the open databases. The complete islet cell landscape and robust marker genes and transcription factors of each endocrine cell type were identified. GLRA1 was restricted to beta cells, and beta cells exhibited obvious heterogeneity. The beta subcluster in the T2D mice remarkably decreased the expression of Slc2a2, G6pc2, Mafa, Nkx6-1, Pdx1, and Ucn3 and had higher unfolded protein response (UPR) scores than in the control mice. Moreover, we developed a Web-based interactive tool, creating new opportunities for the data mining of pancreatic islet scRNA-seq datasets. In conclusion, our work provides a valuable resource for a deeper understanding of the pathological mechanism underlying diabetes.

SUBMITTER: Chen K

PROVIDER: S-EPMC9626680 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

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Single-cell RNA-seq transcriptomic landscape of human and mouse islets and pathological alterations of diabetes.

Chen Kai K Zhang Junqing J Huang Youyuan Y Tian Xiaodong X Yang Yinmo Y Dong Aimei A

iScience 20221014 11

Single-cell RNA sequencing has paved the way for delineating the pancreatic islet cell atlas and identifying hallmarks of diabetes. However, pathological alterations of type 2 diabetes (T2D) remain unclear. We isolated pancreatic islets from control and T2D mice for single-cell RNA sequencing (scRNA-seq) and retrieved multiple datasets from the open databases. The complete islet cell landscape and robust marker genes and transcription factors of each endocrine cell type were identified. GLRA1 wa ...[more]

PMID: 36339258

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Project description:IntroductionAdvanced paternal age of reproduction is an increasing trend, especially in developed countries and areas. This trend results in elevated risks of adverse reproductive outcomes such as reduced fertility rates, increased pregnancy loss, and poor childhood health. Yet, a systematic profiling of aging-associated molecular and cellular alterations in testicular tissue is still missing.ObjectivesWe aimed to dissect aging-associated molecular characteristics in testes of mice.MethodsSingle-cell transcriptomic sequencing and analysis were conducted in testes of young (2 months old) and old mice (24 months old). Immunofluorescences and immunochemistry were used to characterize aging-associated phenotypes and verify single cell sequence results.ResultsHere, we constructed the first single-cell transcriptomic atlases of testes of young and old mice. In-depth dissection of aging-dependent transcriptional alterations in specific cell types revealed multiple dysregulated biological processes such as increased 'senescence-associated secretory phenotype' and 'inflammation', which were major aging-associated characteristics. Further analysis of aging-related differentially expressed genes uncovered a disrupted balance of undifferentiated and differentiated spermatogonia stem cells in spermatogonia, indicative of a potential role of spermatogonia stem cells in aging-associated subfertility. Importantly, for the first time, our results identified an increased subtype of aging-specific macrophages, which may contribute to a hostile proinflammatory microenvironment during testicular aging.ConclusionTaken together, our findings depict the distinct single-cell transcriptional features of the aged mouse testes and provide enormous resources for a comprehensive understanding of the cell-type-specific molecular mechanisms underlying mouse testicular aging, which may shed light on developing novel potential diagnostic biomarkers and therapeutic targets for age-associated male subfertility.

Dataset Information

Single-cell RNA-seq transcriptomic landscape of human and mouse islets and pathological alterations of diabetes.

Publications

Single-cell RNA-seq transcriptomic landscape of human and mouse islets and pathological alterations of diabetes.

Similar Datasets

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