An Introduction to Single-Cell RNA-Seq Analysis and its Applications

Wenqiang Chen, Min Tang

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

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 languageEnglish
Title of host publicationSystems Medicine
Subtitle of host publicationIntegrative, Qualitative and Computational Approaches: Volume 1-3
PublisherElsevier
Pages116-128
Number of pages13
Volume1-3
ISBN (Electronic)9780128160770
ISBN (Print)9780128160787
DOIs
StatePublished - 1 Jan 2020
Externally publishedYes

Keywords

  • Brain sciences
  • Cancer biology
  • Drop-seq
  • Embryo
  • Immunology
  • Integrated medicine
  • Multi-omics
  • Single-cell RNA-seq
  • System biology

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