| 摘要: |
| 近年来,高通量测序技术(Next-generation sequencing,NGS)快速发展,已广泛应用于生命科学各个领域,但传统的混合细胞测序(Bulk cell sequencing)检测的是细胞群体的总平均反应,无法反应每个细胞的真实情况,这会影响研究者对细胞功能认知的准确性。单细胞测序技术(Single cell sequencing,sc-Seq)的出现,从一定程度上解决了传统测序固有的缺陷。单细胞测序是针对单个细胞的RNA或DNA进行测序,能够准确测出单个细胞的基因结构和表达状态,从而分析相同表型细胞的异质性。本文首先介绍单细胞测序的原理、测序类型和测序平台,有助于理解单细胞测序和在进行科研项目时设计合适的项目方案。进一步介绍单细胞转录组测序的分析流程和各种常用的分析工具或软件,并重点阐述单细胞转录组测序分析中的细胞聚类和拟时序分析的原理和研究进展,为进行单细胞转录组测序数据分析提供参考。最后,本文简述了单细胞测序研究热度、单细胞测序的应用、挑战和展望等,有助于更全面地认识单细胞测序。 |
| 关键词: 单细胞测序 生物信息分析 高通量测序 |
| DOI：10.12113/202010004 |
| 分类号:Q-3 |
| 文献标识码:A |
| 基金项目:深圳市可持续发展专项(深科技创新〔2020〕180号,专2019N002) |
|
| Recent progress in single cell sequencing |
|
CAO Lichao1, BA Ying2, ZHANG Hezi2
|
|
(1.College of Life Sciences, Northwest University, Xi'an 710127, China; 2. Shenzhen Nuclear Gene Technology Co., Ltd., Shenzhen 518071, Guangdong,China)
|
| Abstract: |
| In recent years, as the next-generation sequencing technology developed rapidly, it has been widely used in various fields of life science. However, The traditional bulk cell sequencing methods detect the total average reactions of cell groups and are unable to reflect the actual situation of each cell, which may affect the accuracy of understanding of the cell function. The emergence of single cell sequencing technology has solved the inherent defects of traditional sequencing to a certain extent. Single cell sequencing can accurately detect the gene structure and expression status of a single cell in RNA or DNA level, which is important for analyzing the heterogeneity of different cells with the same phenotype. In this study, the principle, sequencing method, and platform of single cell sequencing were briefly introduced, which is helpful to understand single cell sequencing and design the appropriate project scheme in scientific research projects. Then, the single cell transcriptome sequencing analysis pipeline and various commonly used analysis tools or software were summarized, and the principle and the research progress of cell clustering and trajectory analysis in single cell transcriptome sequencing were elaborated, which can provide reference for data analysis of single cell transcriptome sequencing. Finally, the research trends of single cell sequencing, as well as the application, challenge, and prospect of single cell sequencing were presented, which is helpful to understand single cell sequencing more comprehensively. |
| Key words: Single cell sequencing Bioinformatics analysis High-throughput sequencing |
