利用单细胞RNA测序和参考图谱进行T细胞克隆分析。

Massimo Andreatta, Paul Gueguen, Nicholas Borcherding, Santiago J Carmona
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引用次数: 0

摘要

T细胞被赋予T细胞抗原受体(TCR),赋予它们识别特定抗原和装载抗原特异性适应性免疫反应的能力。由于TCR序列在每个naïve T细胞中都是不同的,因此它们可以作为分子条形码,通过增殖、分化和迁移来跟踪具有克隆相关性和共享抗原特异性的T细胞。单细胞RNA测序提供了单个细胞中TCR序列和转录状态的耦合信息,使t细胞克隆型特异性分析成为可能。在本协议中,我们概述了基于R软件包Seurat, ProjecTILs和scRepertoire的计算工作流程,以执行t细胞状态和克隆分析scRNA-seq数据。给定具有TCR序列信息的scRNA-seq t细胞数据集,使用ProjecTILs方法通过参考投影自动标注细胞状态。TCR信息用于跟踪单个克隆型,评估其克隆扩增,增殖率,对特定分化状态的偏好以及t细胞亚型之间的克隆重叠。我们提供了完全可复制的R代码来执行这些分析并生成有用的可视化,这些可视化可以根据协议用户的需求进行调整。关键特征scRNA-seq和scTCR-seq配对数据的计算分析使用ProjecTILs通过参考分析表征t细胞功能状态使用scRepertoire探索t细胞克隆结构将t细胞克隆性与转录组状态联系起来研究克隆扩增与功能表型之间的关系图表概述
本文章由计算机程序翻译,如有差异,请以英文原文为准。

T Cell Clonal Analysis Using Single-cell RNA Sequencing and Reference Maps.

T Cell Clonal Analysis Using Single-cell RNA Sequencing and Reference Maps.

T Cell Clonal Analysis Using Single-cell RNA Sequencing and Reference Maps.

T Cell Clonal Analysis Using Single-cell RNA Sequencing and Reference Maps.

T cells are endowed with T-cell antigen receptors (TCR) that give them the capacity to recognize specific antigens and mount antigen-specific adaptive immune responses. Because TCR sequences are distinct in each naïve T cell, they serve as molecular barcodes to track T cells with clonal relatedness and shared antigen specificity through proliferation, differentiation, and migration. Single-cell RNA sequencing provides coupled information of TCR sequence and transcriptional state in individual cells, enabling T-cell clonotype-specific analyses. In this protocol, we outline a computational workflow to perform T-cell states and clonal analysis from scRNA-seq data based on the R packages Seurat, ProjecTILs, and scRepertoire. Given a scRNA-seq T-cell dataset with TCR sequence information, cell states are automatically annotated by reference projection using the ProjecTILs method. TCR information is used to track individual clonotypes, assess their clonal expansion, proliferation rates, bias towards specific differentiation states, and the clonal overlap between T-cell subtypes. We provide fully reproducible R code to conduct these analyses and generate useful visualizations that can be adapted for the needs of the protocol user. Key features Computational analysis of paired scRNA-seq and scTCR-seq data Characterizing T-cell functional state by reference-based analysis using ProjecTILs Exploring T-cell clonal structure using scRepertoire Linking T-cell clonality to transcriptomic state to study relationships between clonal expansion and functional phenotype Graphical overview.

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