A million-scale pan-disease single-cell TCRαβ repertoire reference atlas 3470

Abstract Description T cell function is defined by both T cell receptors (TCR) and T cell gene expression (GEX). Although single-cell technology enables the simultaneous capture of TCR and GEX information, the lack of a reference atlas and computational tools hinders our ability to uncover the fundamental TCR usage rules and to efficiently characterize disease-associated TCRs. Here, through the collection of million-scale reference atlas of paired single-cell RNA/TCR sequencing (scRNA/TCR-seq) comprising 46 diverse disease conditions, we revealed the intrinsic features of TCR-MHC restriction in CD4+/CD8+ lineages, and observed the widely-existing public TCRαβ pairs across individuals, which is correlated to higher clonal expansion levels and similar gene expression profiles. Building upon the reference atlas, we introduced TCR-DeepInsight, a computational framework featuring both GEX and TCR, with a disease specificity scoring system that enables the characterization of disease-associated TCR clusters with similar TCR sequences and transcriptome profiles. Our study provides a valuable tool for researchers to integrate their datasets with the large-scale scRNA/TCR-seq reference atlas and identify disease-associated TCR sequences comprehensively and robustly. Funding Sources National Natural Science Foundation of China 31930038, 32100718, U21A20199, 32170551. Fundamental Research Funds for the Central Universities 226-2022-00134. Tencent AI Lab Rhino Bird Research Funding RBFR2022015. Topic Categories Computational and Systems Immunology (COMP)