单细胞转录组测序数据分析算法在干细胞研究中的应用

细胞的转录组决定其生理状态,每个细胞的转录组都是唯一的。借助单细胞转录组测序可分析单个干细胞的转录组特征,通过进一步的运算方法可以根据转录组特征对细胞进行细胞状态测定以及系谱分化特征的重建,在干细胞及组织发育研究中发挥了强大的作用,推动了其快速发展,加速了对干细胞分化及组织发育的相关过程及调控路径的认识。尤其是在干细胞领域的应用,得益于新算法的发展,单细胞转录组测序分析可用来阐述干细胞的起源、异质性,尤其是对干细胞的分化过程进行连续观察。本文主要对应用于干细胞分化相关研究的单细胞转录组测序数据新的算法及其应用进行了综述。     

Evidence for diversity in transcriptional profiles of single hematopoietic stem cells

Hematopoietic stem cells replenish all the cells of the blood throughout the lifetime of an animal. Although thousands of stem cells reside in the bone marrow, only a few contribute to blood production at any given time. Nothing is known about the differences between individual stem cells that dictate their particular state of activation readiness. To examine such differences between individual stem cells, we determined the global gene expression profile of 12 single stem cells using microarrays. We showed that at least half of the genetic expression variability between 12 single cells profiled was due to biological variation in 44% of the genes analyzed. We also identified specific genes with high biological variance that are candidates for influencing the state of readiness of individual hematopoietic stem cells, and confirmed the variability of a subset of these genes using single-cell real-time PCR. Because apparent variation of some genes is likely due to technical factors, we estimated the degree of biological versus technical variation for each gene using identical RNA samples containing an RNA amount equivalent to that of single cells. This enabled us to identify a large cohort of genes with low technical variability whose expression can be reliably measured on the arrays at the single-cell level. These data have established that gene expression of individual stem cells varies widely, despite extremely high phenotypic homogeneity. Some of this variation is in key regulators of stem cell activity, which could account for the differential responses of particular stem cells to exogenous stimuli. The capacity to accurately interrogate individual cells for global gene expression will facilitate a systems approach to biological processes at a single-cell level.     

基于单细胞转录组的视网膜母细胞瘤进展特征分析

视网膜母细胞瘤（retinoblastoma,RB）是婴幼儿最常见的眼内恶性肿瘤。在RB进展过程中的关键致病因素目前尚不十分清楚。因此,识别与RB进展密切相关的基因能为病情诊断及基因治疗提供重要信息。然而,肿瘤组织具有很强的细胞异质性,不同病理状态下的细胞,其功能及基因表达都可能呈现显著的差异。本研究从公共基因表达数据库（gene expression omnibus,GEO）下载了1例4个月肿瘤患者和1例2年患者的肿瘤及癌旁组织的单细胞转录组测序数据,从单细胞水平解析不同患病时长的RB肿瘤转录图谱,鉴定与RB进展有潜在关联的细胞亚群及基因集。结果显示,肿瘤组织与癌旁组织在单细胞转录图谱上具有整体的一致性,但视锥前体G1期细胞群、G2期细胞群以及小胶质细胞群在肿瘤与癌旁组织中的分布比例存在明显差异。进一步分析了这3种细胞群在RB肿瘤进展过程中的作用。研究发现,在RB肿瘤的早期阶段,视锥前体细胞在G1期异常增殖,随着RB肿瘤的进展,视锥前体G2期细胞比例显著增加。同时,RB进展过程的小胶质细胞群差异分析结果显示,主要参与免疫应答的关键基因包括RPL23、B2M、HLA家族基因。本研究可为RB发病机制及进展研究提供更多新视角和数据资源。