TY - JOUR
T1 - T Cell Clonal Analysis Using Single-cell RNA Sequencing and Reference Maps
AU - Andreatta, Massimo
AU - Gueguen, Paul
AU - Borcherding, Nicholas
AU - Carmona, Santiago J.
N1 - Publisher Copyright:
© 2023 The Authors.
PY - 2023/8/20
Y1 - 2023/8/20
N2 - 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.
AB - 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.
KW - Reference projection
KW - scRNA-seq
KW - scTCR-seq
KW - Single-cell analysis
KW - T-cell clone
KW - T-cell receptor
KW - TCR
KW - Transcriptomics
UR - http://www.scopus.com/inward/record.url?scp=85169335354&partnerID=8YFLogxK
U2 - 10.21769/BioProtoc.4735
DO - 10.21769/BioProtoc.4735
M3 - Article
C2 - 37638293
AN - SCOPUS:85169335354
SN - 2331-8325
VL - 13
JO - Bio-protocol
JF - Bio-protocol
IS - 16
M1 - e4735
ER -