Diverse modes of T cell receptor sequence convergence define unique functional and cellular phenotypes
Schattgen, S.; Vegesana, K.; Hazelton, W. D.; Minervina, A.; Valkiers, S.; Slowikowski, K.; Smith, N. P.; MGH COVID-19 Team, ; Villani, A.-C.; Thomas, P. G.; Bradley, P.
Show abstract
Single-cell techniques allow concurrent study of gene activity and T cell receptor (TCR) sequences, identifying connections between TCR structure and cell traits. Expanding on our CoNGA software, we present a "metaCoNGA" analysis of 6 million T cells from 91 diverse studies, mapping TCR sequence similarity across tissues and diseases. This approach exposes shared TCR features within specific T cell subsets, including those associated with infection, cancer, and autoimmunity. We introduce a method to identify T cell groups with similar gene expression and biased TCR amino acid composition, providing a systematic framework for classifying diverse unconventional T cells, including KIR+ CD8+ T cells, CD4+ regulatory T cells, and subsets of NKT and MAIT cells. A new TCR clustering approach identifies thousands of convergent TCR sequence clusters hypothesized to target shared antigens. These clusters show coherent gene expression, highlighting the role of antigen exposure in shaping T cell behavior. Finally, we provide a tool for users to merge new data with this resource and rapidly identify T cell features in their data sets. This resource empowers investigations into the complex relationship between TCR sequence and T cell function in human health.
Matching journals
The top 9 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- TCR meta-clonotypes for biomarker discovery with tcrdist3: identification of public, HLA-restricted SARS-CoV-2 associated TCR features 97%
- Population based selection shapes the T cell receptor repertoire during thymic development 97%
- Longitudinal high-throughput TCR repertoire profiling reveals the dynamics of T cell memory formation after mild COVID-19 infection 96%
Similar papers in this journal
- APMAT analysis reveals the association between CD8 T cell receptors, cognate antigen, and T cell phenotype and persistence 95%
- Probabilities of HIV-1 bNAb development in healthy and chronically infected individuals 95%
- Deep learning predictions of TCR-epitope interactions reveal epitope-specific chains in dual alpha T cells 95%
Similar papers in this journal
- The Observed T cell receptor Space database enables paired-chain repertoire mining, coherence analysis and language modelling 97%
- Dynamics of B-cell repertoires and emergence of cross-reactive responses in COVID-19 patients with different disease severity 95%
- The pseudokinase Trib1 regulates the transition of exhausted T cells to a KLR+ CD8+ effector state and its deletion improves checkpoint blockade 94%
Similar papers in this journal
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.