吞吐量
转录组
计算生物学
单细胞测序
DNA测序
计算机科学
生物
遗传学
基因
外显子组测序
突变
操作系统
基因表达
无线
作者
Shanqing Huang,Weixiong Shi,Shiyu Li,Qian Fan,Chaoyong Yang,Jiao Cao,Lingling Wu
出处
期刊:Lab on a Chip
[Royal Society of Chemistry]
日期:2024-01-01
卷期号:24 (10): 2601-2621
被引量:12
摘要
Cells are the fundamental building blocks of living systems, exhibiting significant heterogeneity. The transcriptome connects the cellular genotype and phenotype, and profiling single-cell transcriptomes is critical for uncovering distinct cell types, states, and the interplay between cells in development, health, and disease. Nevertheless, single-cell transcriptome analysis faces daunting challenges due to the low abundance and diverse nature of RNAs in individual cells, as well as their heterogeneous expression. The advent and continuous advancements of next-generation sequencing (NGS) and third-generation sequencing (TGS) technologies have solved these problems and facilitated the high-throughput, sensitive, full-length, and rapid profiling of single-cell RNAs. In this review, we provide a broad introduction to current methodologies for single-cell transcriptome sequencing. First, state-of-the-art advancements in high-throughput and full-length single-cell RNA sequencing (scRNA-seq) platforms using NGS are reviewed. Next, TGS-based long-read scRNA-seq methods are summarized. Finally, a brief conclusion and perspectives for comprehensive single-cell transcriptome analysis are discussed.
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