Combining experiments, bioinformatics, and mathematical modelling, we find large heterogeneity in naive T cell clone sizes.

An analysis of T cell receptor occurrence patterns that accounts for MHC restriction reveals striking imprints of common viral pathogens and patterns of TCR-HLA sequence covariation in a large human cohort.

The integration of pHLA binding and pHLA-TCR analysis effectively improves the precision of insilico neoantigen prioritization, potentially enhancing personalized immunotherapies for colorectal cancer.

A new perception of the organization of T-cell receptor repertoires in mice and humans, based on high-throughput sequencing and CDR3 sequence similarity, indicates hubs of cross-species public sequences forming evolutionary conserved 'foci of attention' of T cell immunity.

Trans genetic variation in TdT and Artemis loci impacts V(D)J recombination probabilities.

Deep learning improves estimation of T cell receptor cohort frequencies and learns the rules of VDJ recombination, potentially making it helpful for vaccine design.

Distance-based TCR analysis enables grouping of biochemically similar clonotypes into meta-clonotypes that have increased publicity, and therefore statistical power, for population-level detection of antigen-specific T cells in infection and vaccination.

Sequence signatures can be used to discriminate between selected and non-selected immune repertoires at different stages only at the collective population level but not at the level of single cells.

Longitudinal tracking of individual T-cell clones reveals the expansion of pre-existing T-cell memory in response to SARS-CoV-2 infection.

High-throughput sequencing of the memory T cell receptor repertoire and machine learning can predict robust antibody and CD4 T cell response to de novo hepatitis B vaccine.