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Single-Cell RNA Sequencing of Human T Cells

  • Alexandra-Chloé VillaniEmail author
  • Karthik ShekharEmail author
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1514)

Abstract

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.

Key words

Single-cell RNA sequencing T cells CD4 CD8 Smart-Seq2 Alignment Clustering Gene expression Markers 

Notes

Acknowledgments

K. S. and A. C. V. thank Brian Haas, Dr. Timothy Tickle, Dr. Petter Brodin, Dr. Sara Garamszegi, Chris Rodman, and Noga Rogel for helpful comments and feedback on the content and organization of the manuscript. K. S. and A. C. V. thank Dr. Aviv Regev and Dr. Nir Hacohen for feedback and support.

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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.Broad Institute of MIT and HarvardCambridgeUSA
  2. 2.Center for Cancer ImmunotherapyMassachusetts General HospitalBostonUSA

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