Discoveries in Pancreatic Physiology and Disease Biology Using Single-Cell RNA Sequencing

Haotian Fu,Hao Chen,Lei Qin,Hongwei Sun,Bin Lou,Yilin Zhou,Yunfeng Shan,Hongru Kong,Chaohao Huang,Shengjie Dai

doi:10.3389/fcell.2021.732776

Abstract

Transcriptome analysis is used to study gene expression in human tissues. It can promote the discovery of new therapeutic targets for related diseases by characterizing the endocrine function of pancreatic physiology and pathology, as well as the gene expression of pancreatic tumors. Compared to whole-tissue RNA sequencing, single-cell RNA sequencing (scRNA-seq) can detect transcriptional activity within a single cell. The scRNA-seq had an invaluable contribution to discovering previously unknown cell subtypes in normal and diseased pancreases, studying the functional role of rare islet cells, and studying various types of cells in diabetes as well as cancer. Here, we review the recent in vitro and in vivo advances in understanding the pancreatic physiology and pathology associated with single-cell sequencing technology, which may provide new insights into treatment strategy optimization for diabetes and pancreatic cancer.

Highlights

Sequencing technology is increasingly used to study the endocrine function of the pancreas under physiological and pathological conditions, as well as the driving factors of pancreatic tumor development
The scRNA-seq is a revolutionary technology, its advantage lies in the successful use of unprecedented high resolution to study the biology of diabetes and pancreatic tumors
SRNA-seq and the related computer analyses have transformed the study of complex cells as well as tissues and brought great hope in the field of pancreatic development, there are still issues that need to be addressed

Summary

Introduction

Sequencing technology is increasingly used to study the endocrine function of the pancreas under physiological and pathological conditions, as well as the driving factors of pancreatic tumor development. The latest developments in scRNA-seq technology allowed unprecedented insights into gene expression patterns, which led to the identification of periods of high insulin biosynthesis activity associated with β cells and UPR activation periods associated with ER stress (Muraro et al, 2016; Fang et al, 2019; Wang and Kaestner, 2019). The scRNA-seq technology facilitates the research and analysis of rare cell types in pancreatic islets (Li et al, 2016).

Results

Conclusion