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健康和2型糖尿病状态下胰岛β细胞的伪时间排序单细胞转录组学

Pseudotime Ordering Single-Cell Transcriptomic of β Cells Pancreatic Islets in Health and Type 2 Diabetes.

作者信息

Bao Kaixuan, Cui Zhicheng, Wang Hui, Xiao Hui, Li Ting, Kong Xingxing, Liu Tiemin

机构信息

Human Phenome Institute, Fudan University, 825 Zhangheng Road, Shanghai, 201203 China.

State Key Laboratory of Genetic Engineering, School of Life Sciences, and Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, 200438 China.

出版信息

Phenomics. 2021 Oct 19;1(5):199-210. doi: 10.1007/s43657-021-00024-z. eCollection 2021 Oct.

Abstract

UNLABELLED

β cells are defined by the ability to produce and secret insulin. Recent studies have evaluated that human pancreatic β cells are heterogeneous and demonstrated the transcript alterations of β cell subpopulation in diabetes. Single-cell RNA sequence (scRNA-seq) analysis helps us to refine the cell types signatures and understand the role of the β cells during metabolic challenges and diseases. Here, we construct the pseudotime trajectory of β cells from publicly available scRNA-seq data in health and type 2 diabetes (T2D) based on highly dispersed and highly expressed genes using Monocle2. We identified three major states including 1) Normal branch, 2) Obesity-like branch and 3) T2D-like branch based on biomarker genes and genes that give rise to bifurcation in the trajectory. β cell function-maintain-related genes, insulin expression-related genes, and T2D-related genes enriched in three branches, respectively. Continuous pseudotime spectrum might suggest that β cells transition among different states. The application of pseudotime analysis is conducted to clarify the different cell states, providing novel insights into the pathology of β cells in T2D.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material is available at 10.1007/s43657-021-00024-z.

摘要

未标注

β细胞是由产生和分泌胰岛素的能力来定义的。最近的研究评估了人类胰腺β细胞是异质性的,并证明了糖尿病中β细胞亚群的转录改变。单细胞RNA测序(scRNA-seq)分析有助于我们细化细胞类型特征,并了解β细胞在代谢挑战和疾病中的作用。在这里,我们使用Monocle2基于高度分散和高表达的基因,从健康和2型糖尿病(T2D)的公开可用scRNA-seq数据构建β细胞的伪时间轨迹。基于生物标志物基因和导致轨迹分叉的基因,我们确定了三个主要状态,包括1)正常分支,2)肥胖样分支和3)T2D样分支。β细胞功能维持相关基因、胰岛素表达相关基因和T2D相关基因分别在三个分支中富集。连续的伪时间谱可能表明β细胞在不同状态之间转变。进行伪时间分析的应用以阐明不同的细胞状态,为T2D中β细胞的病理学提供了新的见解。

补充信息

在线版本包含补充材料,可在10.1007/s43657-021-00024-z获取。

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