A pan-disease and population-level single-cell TCRαβ repertoire reference

Recent advances in single-cell technology enable the simultaneous capture of T cell receptor (TCR) sequences and gene expression (GEX), providing an integrated view of T cell function. However, linking TCRαβ information and T cell phenotypes at the population level to elucidate their disease association remains an unaddressed gap. Here, by constructing a large-scale reference of paired single-cell RNA/TCR sequencing (scRNA/TCR-seq) comprising more than 2 million T cells from 70 studies, 1017 biological samples, 583 individuals, and 46 disease conditions, along with their single-cell transcriptome, full-length paired TCR, and human leukocyte antigen (HLA) genotypes, we revealed the intrinsic features of germline-encoded TCR-major histocompatibility complex (MHC) restriction in CD4<sup>+</sup>/CD8<sup>+</sup> lineages. We also observed widely existing public TCRαβs across the population, associated with higher clonal expansion levels and shared HLA alleles. The most publicly shared TCRs are likely to target epitopes from common viruses, such as Epstein-Barr virus (EBV), cytomegalovirus (CMV), and influenza A virus (IAV). Furthermore, we introduced TCR-DeepInsight, a computational framework to identify HLA-shared and disease-associated TCRαβ clusters that exhibit similar TCR sequence and GEX profiles, extensible for researchers to incorporate their data with our reference and characterize potentially functional TCRs. In summary, our work presents a panoramic scTCRαβ reference and computational methods for TCR study.

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Publication Details

Journal
Cell Discovery
Published
2025-10-14
DOI
https://doi.org/10.1038/s41421-025-00836-7
Primary Topic
T-cell and B-cell Immunology
Type
article
Field-Weighted Citation Impact
0.00

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article

A pan-disease and population-level single-cell TCRαβ repertoire reference

Ziwei Xue, Zuozhu Liu, Lize Wu, Ruonan Tian et al.
Cell Discovery
T-cell and B-cell Immunology
article

A pan-disease and population-level single-cell TCRαβ repertoire reference

Ziwei Xue, Zuozhu Liu, Lize Wu, Ruonan Tian, Bing Gao, Linrong Lu, Yadan Bai, Tao Dong, Yu Zhao, Yiru Chen, Bing He, Jianhua Yao, Lie Wang, Wanlu Liu, Yicheng Qi
article en

Abstract

Recent advances in single-cell technology enable the simultaneous capture of T cell receptor (TCR) sequences and gene expression (GEX), providing an integrated view of T cell function. However, linking TCRαβ information and T cell phenotypes at the population level to elucidate their disease association remains an unaddressed gap. Here, by constructing a large-scale reference of paired single-cell RNA/TCR sequencing (scRNA/TCR-seq) comprising more than 2 million T cells from 70 studies, 1017 biological samples, 583 individuals, and 46 disease conditions, along with their single-cell transcriptome, full-length paired TCR, and human leukocyte antigen (HLA) genotypes, we revealed the intrinsic features of germline-encoded TCR-major histocompatibility complex (MHC) restriction in CD4<sup>+</sup>/CD8<sup>+</sup> lineages. We also observed widely existing public TCRαβs across the population, associated with higher clonal expansion levels and shared HLA alleles. The most publicly shared TCRs are likely to target epitopes from common viruses, such as Epstein-Barr virus (EBV), cytomegalovirus (CMV), and influenza A virus (IAV). Furthermore, we introduced TCR-DeepInsight, a computational framework to identify HLA-shared and disease-associated TCRαβ clusters that exhibit similar TCR sequence and GEX profiles, extensible for researchers to incorporate their data with our reference and characterize potentially functional TCRs. In summary, our work presents a panoramic scTCRαβ reference and computational methods for TCR study.

Cell DiscoveryVol. 11(1)
Shanghai Jiao Tong University (CN), Tencent (China) (CN), Renji Hospital (CN), Sir Run Run Shaw Hospital (CN), Edinburgh College (GB), Zhejiang Lab (CN), Second Affiliated Hospital of Zhejiang University (CN), Zhejiang University-University of Edinburgh Institute (CN), First Affiliated Hospital Zhejiang University (CN), Zhejiang University (CN), University of Edinburgh (GB)
Tencent, National Natural Science Foundation of China, Zhejiang University, Sichuan University
Openalex Percentile: Top 70%
T-cell and B-cell Immunology
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