Abstract
Single-cell transcriptomics analysis has gained enormous popularity in recent years. By profiling gene expression in individual cells of complex tissues, single-cell RNA-sequencing (scRNA-seq) allows for obtaining complete landscapes during dynamic biological processes, identifying rare cell types within highly heteronomous tissues, and revealing unexpected cellular diversity that is previously ignored or unaddressed. In this article, we aim to provide readers with an introduction to scRNA-seq analysis. First, we will briefly discuss the needs of single-cells analysis and explain why previous single-cell studies, such as single-cell proteomics and many other single-cell measurements, could not meet the research needs. Then, we will describe procedures and early development of scRNA-seq analysis and highlight two seminal reports of droplet-based scRNA-seq, namely Drop-seq, as a major breakthrough in the field. Further, we will outline several key applications of scRNA-seq in addressing long-standing questions in early embryonic development, immunology, cancer biology, and brain sciences, and discuss how these advancements revolutionized and deepened our understanding of biomedical processes. Last, we will introduce several recent integrative applications of scRNA-seq with other technology domains, such as whole-cell patch-clamp recording, CRISPR- or shRNA-based pooled screen, and imaging-based in situ hybridization. Therefore, advancement of this integrative and qualitative technique in high-throughput genome-wide sequencing will enable us developing novel diagnostic and therapeutic approaches of major human diseases.
Original language | English |
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Title of host publication | Systems Medicine |
Subtitle of host publication | Integrative, Qualitative and Computational Approaches: Volume 1-3 |
Publisher | Elsevier |
Pages | 116-128 |
Number of pages | 13 |
Volume | 1-3 |
ISBN (Electronic) | 9780128160770 |
ISBN (Print) | 9780128160787 |
DOIs | |
State | Published - 1 Jan 2020 |
Externally published | Yes |
Keywords
- Brain sciences
- Cancer biology
- Drop-seq
- Embryo
- Immunology
- Integrated medicine
- Multi-omics
- Single-cell RNA-seq
- System biology