UcTCRp: a TCRβ-based framework for quantitative MAIT- and iNKT-associated repertoire-state profiling

Abstract MAIT and iNKT cells are conventionally identified using invariant or semi-invariant TCRα chains, antigen-loaded tetramers, or transcriptomic phenotypes. These requirements limit their detection in public and clinical immune-repertoire datasets that contain only TCRβ sequences. Here we present UcTCRp, a TCRβ-only framework for profiling MAIT- and iNKT-associated repertoire states in bulk immune repertoires. UcTCRp integrates V-gene context and CDR3β sequence features using a transformer-based representation pretrained on more than one million TCRβ sequences and supervised with curated cross-species MAIT, iNKT and conventional T cell references. The framework defines conserved model-informative TCRβ features, uses V-matched negative sampling to reduce germline-segment shortcuts, and generalizes across independent human and mouse datasets. In paired scRNA-seq/scTCR-seq datasets, UcTCRp recovered transcriptome-defined MAIT and iNKT cells and identified additional MAIT-like candidates supported by receptor evidence but missed by expression-only annotation. Bulk calibration against paired single-cell references and synthetic spike-in experiments established operating characteristics for repertoire-level abundance estimation. These results establish unpaired TCRβ repertoires as an actionable substrate for reconstructing unconventional T cell-associated immune states, enabling archived repertoire resources to be repurposed for systems-level studies of tissue immunity, disease and therapeutic response.