Single-Cell Sequencing and Organoids: A Powerful Combination for Modelling Organ Development and Diseases

Yuebang Yin, Peng Yu Liu, Yinghua Shi*, Ping Li*

*Corresponding author for this work

Research output: Chapter/Conference proceedingChapterAcademic

4 Citations (Scopus)

Abstract

The development and function of a particular organ and the pathogenesis of various diseases remain intimately linked to the features of each cell type in the organ. Conventional messenger RNA- or protein-based methodologies often fail to elucidate the contribution of rare cell types, including some subpopulations of stem cells, short-lived progenitors and circulating tumour cells, thus hampering their applications in studies regarding organ development and diseases. The scRNA-seq technique represents a new approach for determining gene expression variability at the single-cell level. Organoids are new preclinical models that recapitulate complete or partial features of their original organ and are thought to be superior to cell models in mimicking the sophisticated spatiotemporal processes of the development and regeneration and diseases. In this review, we highlight recent advances in the field of scRNA-seq, organoids and their current applications and summarize the advantages of using a combination of scRNA-seq and organoid technology to model diseases and organ development.

Original languageEnglish
Title of host publicationReviews of Physiology, Biochemistry and Pharmacology
Pages189-210
Number of pages22
Volume179
ISBN (Electronic) 978-3-030-74289-8
DOIs
Publication statusE-pub ahead of print - 23 Feb 2021

Publication series

SeriesReviews of Physiology, Biochemistry and Pharmacology
ISSN0303-4240

Bibliographical note

Funding Information:
Fig. 1 A schematic diagram depicting the use of a combination of organoid technology and scRNA-seq in modelling organ development and diseases. Various types of organoids are cultured from distinct organs, dispersed into single cells and subjected to 10X Genomics scRNA-seq, followed by the application of cyber-based algorithms for several purposes, including (1) the discovery of rare/novel cell and gene markers, (2) analysis of cellular heterogeneity of native organs, (3) delineation of cell differentiation pathways, (4) identification of gene expression variability at the single-cell level and (5) modelling of diseases Acknowledgements This work was supported by the National Natural Science Foundation of China (Grant # 61976249), the Science and Technology Program of Guangdong Province (Grant # 2019A050505007) and the Earmarked Fund for Modern Agro-industry Technology Research System of China (Grant # CARS-34).

Funding Information:
This work was supported by the National Natural Science Foundation of China (Grant # 61976249), the Science and Technology Program of Guangdong Province (Grant # 2019A050505007) and the Earmarked Fund for Modern Agro-industry Technology Research System of China (Grant # CARS-34). All authors thank Prof. Hugo R. de Jonge (Department of Gastroenterology and Hepatology, Erasmus Medical Center, the Netherlands) for offering suggestions and comments and polishing the language in the manuscript.

Publisher Copyright:
© 2021, Springer Nature Switzerland AG.

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