DeRR: A Unique Detecting Method and the First Landscape for T Cells with Dual T Cell Receptors from Large-scale Single Cell Data.

Abstract

While most T cells exclusively express a single T cell receptor (TCR), a distinct subpopulation exhibits dual types of TCR expression (dual-TCR). Although the functional implications of dual-TCR T cells in autoimmunity and immune protection have been documented, their isolation and characterization remain technically challenging, resulting in incomplete characterization of dual-TCR properties. To address this gap, we developed DeRR (Detection of dual T cell Receptors), a computational pipeline specifically designed to identify dual-TCRs in both single-cell TCR and RNA sequencing data (scTCR-seq and scRNA-seq, respectively). Evaluation of extensive datasets validated DeRR's robust performance. Analysis of over 600,000 single T cells from 147 samples revealed the first systematic characterization of dual-TCR T cells, with approximately 17% carrying dual TCR α-chains and 12% displaying dual TCR β-chains. Notably, dual-TCR frequency in cancer was elevated compared to other conditions and demonstrated a positive association with disease duration in autoimmune disorders. However, dual-TCR T cells were uniformly distributed across all T cell subtypes and exhibited greater cross-reactivity than conventional single-TCR T cells, particularly through their secondary TCR chains. Interestingly, the relative expression levels of the two TCRs varied dynamically within dual-TCR T cells. This study provides the first dedicated tool for dual-TCR detection and offers a comprehensive landscape of dual-TCR, significantly advancing our understanding of T cell immunology. The DeRR source code is publicly accessible under the following repositories: GitHub (https://github.com/GuoBioinfoLab/DeRR) and BioCode (https://ngdc.cncb.ac.cn/biocode/tool/7789).