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Single-cell transcriptomic and TCR profiling of peripheral double-positive T cells in healthy human blood [scRNA-seq]

GSE304309 Homo sapiens Expression profiling by high throughput sequencing 8 samples 2026/08/01 GPL24676
Summary
CD4+CD8+ double-positive T (DPT) cells are typically associated with thymic development but have also been observed in peripheral blood under physiological and pathological conditions. However, their identity, functional significance, and developmental origin in the periphery remain poorly defined. This project was conducted to comprehensively characterize peripheral DPT cells in healthy human donors using single-cell transcriptomic and T cell receptor (TCR) profiling. We aimed to define the molecular features that distinguish peripheral DPT cells from conventional single-positive CD4+ and CD8+ T (SPT) cells. Through the integration of single-cell RNA sequencing and paired TCR sequencing, we explored their transcriptional profiles, clonal architecture, and potential developmental trajectories. This allowed us to uncover unique gene expression patterns and TCR usage biases that suggest peripheral DPT cells represent a distinct, stable T cell subset rather than a transient or intermediate population. In addition, we developed a machine learning-based classifier that can accurately distinguish DPT cells from conventional T cell subsets using transcriptomic features. This approach enabled the identification of key marker genes and molecular pathways underlying the functional specialization of DPT cells. This dataset provides a valuable resource for the immunology community to further investigate peripheral DPT cells in health and disease. Generated from healthy individuals, it serves as a high-quality reference map of normal peripheral T cell states. In our study, this dataset was further integrated with publicly available single-cell datasets derived from patients with immune-related diseases, enabling comparative analyses to explore how the transcriptional identity and abundance of DPT cells may be altered under pathological conditions. By making this healthy reference dataset publicly available, we aim to support future investigations into T cell heterogeneity, immune dysregulation, and disease-specific perturbations of the T cell compartment.
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