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Single-Cell Transcriptomics of the Human Endocrine Pancreas.


ABSTRACT: Human pancreatic islets consist of multiple endocrine cell types. To facilitate the detection of rare cellular states and uncover population heterogeneity, we performed single-cell RNA sequencing (RNA-seq) on islets from multiple deceased organ donors, including children, healthy adults, and individuals with type 1 or type 2 diabetes. We developed a robust computational biology framework for cell type annotation. Using this framework, we show that ?- and ?-cells from children exhibit less well-defined gene signatures than those in adults. Remarkably, ?- and ?-cells from donors with type 2 diabetes have expression profiles with features seen in children, indicating a partial dedifferentiation process. We also examined a naturally proliferating ?-cell from a healthy adult, for which pathway analysis indicated activation of the cell cycle and repression of checkpoint control pathways. Importantly, this replicating ?-cell exhibited activated Sonic hedgehog signaling, a pathway not previously known to contribute to human ?-cell proliferation. Our study highlights the power of single-cell RNA-seq and provides a stepping stone for future explorations of cellular heterogeneity in pancreatic endocrine cells.

SUBMITTER: Wang YJ 

PROVIDER: S-EPMC5033269 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature

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Single-Cell Transcriptomics of the Human Endocrine Pancreas.

Wang Yue J YJ   Schug Jonathan J   Won Kyoung-Jae KJ   Liu Chengyang C   Naji Ali A   Avrahami Dana D   Golson Maria L ML   Kaestner Klaus H KH  

Diabetes 20160630 10


Human pancreatic islets consist of multiple endocrine cell types. To facilitate the detection of rare cellular states and uncover population heterogeneity, we performed single-cell RNA sequencing (RNA-seq) on islets from multiple deceased organ donors, including children, healthy adults, and individuals with type 1 or type 2 diabetes. We developed a robust computational biology framework for cell type annotation. Using this framework, we show that α- and β-cells from children exhibit less well-d  ...[more]

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