Department of Chemistry, Yonsei University, Seoul, Korea.
Department of Clinical Pharmacology and Therapeutics, College of Medicine, Kyung Hee University, Seoul, Korea.
Exp Mol Med. 2018 Aug 7;50(8):1-14. doi: 10.1038/s12276-018-0071-8.
Rapid progress in the development of next-generation sequencing (NGS) technologies in recent years has provided many valuable insights into complex biological systems, ranging from cancer genomics to diverse microbial communities. NGS-based technologies for genomics, transcriptomics, and epigenomics are now increasingly focused on the characterization of individual cells. These single-cell analyses will allow researchers to uncover new and potentially unexpected biological discoveries relative to traditional profiling methods that assess bulk populations. Single-cell RNA sequencing (scRNA-seq), for example, can reveal complex and rare cell populations, uncover regulatory relationships between genes, and track the trajectories of distinct cell lineages in development. In this review, we will focus on technical challenges in single-cell isolation and library preparation and on computational analysis pipelines available for analyzing scRNA-seq data. Further technical improvements at the level of molecular and cell biology and in available bioinformatics tools will greatly facilitate both the basic science and medical applications of these sequencing technologies.
近年来,下一代测序(NGS)技术的快速发展为复杂的生物系统提供了许多有价值的见解,从癌症基因组学到多样化的微生物群落。基于 NGS 的基因组学、转录组学和表观基因组学技术现在越来越关注单个细胞的特征。这些单细胞分析将使研究人员能够发现新的、潜在意想不到的生物学发现,相对于评估大量群体的传统分析方法。例如,单细胞 RNA 测序(scRNA-seq)可以揭示复杂和罕见的细胞群体,揭示基因之间的调控关系,并跟踪发育过程中不同细胞谱系的轨迹。在这篇综述中,我们将重点介绍单细胞分离和文库制备中的技术挑战,以及用于分析 scRNA-seq 数据的计算分析管道。在分子和细胞生物学以及可用的生物信息学工具方面的进一步技术改进,将极大地促进这些测序技术的基础科学和医学应用。