Department of General Surgery, Second Affiliated Hospital, Zhengzhou University, Zhengzhou, China.
Department of Science Research and Discipline Construction, Henan Provincial People's Hospital, Jinshui District, Zhengzhou, China.
Adv Exp Med Biol. 2018;1068:149-158. doi: 10.1007/978-981-13-0502-3_12.
The advent of single-cell omics technology has promoted our understanding of the genomic, epigenomic, and transcriptomic heterogeneity in individual cells. Compared to traditional sequencing studies using bulk cells, single-cell transcriptome technology is naturally more dynamic for in depth analysis of genomic variation resulting from cell division and is useful in unraveling the regulatory mechanisms of gene networks in many diseases. However, there are still some limitations of current single-cell RNA sequencing (scRNA-seq) protocols. Biases that arise during the RNA reverse transcription and cDNA pre-amplification steps are the most common problems and play pivotal roles in limiting the quantitative accuracy of scRNA-seq. In this review, we will describe how these biases emerge and impact scRNA-seq protocols. Moreover, we will introduce several current and convenient modified scRNA-seq methods that allow for bias to be decreased and estimated.
单细胞组学技术的出现促进了我们对单个细胞中基因组、表观基因组和转录组异质性的理解。与使用大量细胞的传统测序研究相比，单细胞转录组技术在深入分析细胞分裂引起的基因组变异方面具有天然的优势，并且有助于揭示许多疾病中基因网络的调控机制。然而，目前的单细胞 RNA 测序 (scRNA-seq) 方案仍然存在一些局限性。在 RNA 逆转录和 cDNA 预扩增步骤中产生的偏倚是最常见的问题，这些偏倚在限制 scRNA-seq 的定量准确性方面起着关键作用。在这篇综述中，我们将描述这些偏倚是如何产生的，并影响 scRNA-seq 方案。此外，我们将介绍几种当前和方便的改良 scRNA-seq 方法，这些方法可以减少和估计偏倚。
