Single-Cell RNA Sequencing of Human T Cells.
Single-Cell RNA Sequencing of Human T Cells.
复制标题
人类 T 细胞的单细胞 RNA 测序。
作者：
A. Villani;K. Shekhar
了解人类T细胞群体如何利用细胞异质性，可塑性和多样性来实现广泛的功能灵活性，特别是在动态过程中，如发育，分化和抗原反应，是非常适合单细胞分析的核心挑战。通过单个T细胞的转录谱分析对细胞状态和亚群进行无假设评估可以鉴定可能被靶向方法（例如细胞表面抗原上的FACS分选或批量表达分析）掩盖的关系。虽然这种方法与所有细胞类型相关，但它在T细胞的研究中特别令人感兴趣，对于这些T细胞，经典的表型标准现在被认为不足以区分不同的T细胞亚型和过渡状态，并定义与自身免疫和肿瘤相关衰竭中功能失调的T细胞状态相关的变化。本单元描述了一个协议，以产生人类血液CD 4+和CD 8 + T细胞的单细胞转录组文库，并介绍了基本的生物信息学步骤，以处理所得的序列数据，用于进一步的计算分析。我们展示了如何从转录数据中识别细胞亚群，并推导出区分这些状态的特征基因表达特征。我们相信单细胞RNA-seq是一种研究复杂组织中细胞异质性的强大技术，这对免疫系统具有重要价值。
Understanding how populations of human T cells leverage cellular heterogeneity, plasticity, and diversity to achieve a wide range of functional flexibility, particularly during dynamic processes such as development, differentiation, and antigenic response, is a core challenge that is well suited for single-cell analysis. Hypothesis-free evaluation of cellular states and subpopulations by transcriptional profiling of single T cells can identify relationships that may be obscured by targeted approaches such as FACS sorting on cell-surface antigens, or bulk expression analysis. While this approach is relevant to all cell types, it is of particular interest in the study of T cells for which classical phenotypic criteria are now viewed as insufficient for distinguishing different T cell subtypes and transitional states, and defining the changes associated with dysfunctional T cell states in autoimmunity and tumor-related exhaustion. This unit describes a protocol to generate single-cell transcriptomic libraries of human blood CD4+ and CD8+ T cells, and also introduces the basic bioinformatic steps to process the resulting sequence data for further computational analysis. We show how cellular subpopulations can be identified from transcriptional data, and derive characteristic gene expression signatures that distinguish these states. We believe single-cell RNA-seq is a powerful technique to study the cellular heterogeneity in complex tissues, a paradigm that will be of great value for the immune system.
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DOI：
10.1073/pnas.89.7.3010
发表时间：
1992-04-01
影响因子：
11.1
作者：
EBERWINE, J;YEH, H;COLEMAN, P
通讯作者：
COLEMAN, P
影响因子：
2.1
作者：
Johnson, W. Evan;Li, Cheng;Rabinovic, Ariel
通讯作者：
Rabinovic, Ariel
影响因子：
48
作者：
Jean Fan;N. Salathia;R. Liu;Gwendolyn E. Kaeser;Y. Yung;Joseph L. Herman;F. Kaper;Jian-Bing Fan
通讯作者：
Jean Fan;N. Salathia;R. Liu;Gwendolyn E. Kaeser;Y. Yung;Joseph L. Herman;F. Kaper;Jian-Bing Fan
影响因子：
7
作者：
Zhou X;Bailey-Bucktrout S;Jeker LT;Bluestone JA
通讯作者：
Bluestone JA