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

IF 12.5 1区 生物学 Q1 CELL BIOLOGY
Ziwei Xue, Lize Wu, Bing Gao, Ruonan Tian, Yiru Chen, Yicheng Qi, Tianze Dong, Yadan Bai, Yu Zhao, Bing He, Lie Wang, Zuozhu Liu, Jianhua Yao, Linrong Lu, Wanlu Liu
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引用次数: 0

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+/CD8+ 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.

泛疾病和人群水平单细胞TCRαβ库参考。
单细胞技术的最新进展能够同时捕获T细胞受体(TCR)序列和基因表达(GEX),从而提供T细胞功能的综合视图。然而,将TCRαβ信息与群体水平上的T细胞表型联系起来以阐明它们的疾病关联仍然是一个未解决的空白。在这里,通过构建大规模的单细胞RNA/TCR配对测序(scRNA/TCR-seq)参考,包括来自70项研究、1017个生物样本、583个个体和46种疾病的200多万个T细胞,以及它们的单细胞转录组、全长配对TCR和人类白细胞抗原(HLA)基因型,我们揭示了CD4+/CD8+谱系中种系编码的TCR-主要组织相容性复合体(MHC)限制的内在特征。我们还观察到在人群中广泛存在的公共TCRαβs,与较高的克隆扩增水平和共享的HLA等位基因相关。最公开共享的tcr可能针对常见病毒的表位,如eb病毒、巨细胞病毒和甲型流感病毒。此外,我们引入了TCR- deepinsight,这是一个计算框架,用于识别具有相似TCR序列和GEX谱的hla共享和疾病相关的TCRαβ簇,可扩展,供研究人员将其数据与我们的参考数据相结合,并表征潜在的功能TCR。总之,我们的工作为TCR研究提供了一个全景的scTCRαβ参考和计算方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Cell Discovery
Cell Discovery Biochemistry, Genetics and Molecular Biology-Molecular Biology
CiteScore
24.20
自引率
0.60%
发文量
120
审稿时长
20 weeks
期刊介绍: Cell Discovery is a cutting-edge, open access journal published by Springer Nature in collaboration with the Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences (CAS). Our aim is to provide a dynamic and accessible platform for scientists to showcase their exceptional original research. Cell Discovery covers a wide range of topics within the fields of molecular and cell biology. We eagerly publish results of great significance and that are of broad interest to the scientific community. With an international authorship and a focus on basic life sciences, our journal is a valued member of Springer Nature's prestigious Molecular Cell Biology journals. In summary, Cell Discovery offers a fresh approach to scholarly publishing, enabling scientists from around the world to share their exceptional findings in molecular and cell biology.
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