Computational Biology Program, Fred Hutch Cancer Research Center, Seattle, United States; Molecular and Cellular Biology Program, University of Washington, Seattle, United States
Aisha Souquette
Department of Immunology, St. Jude Children’s Research Hospital, Memphis, United States; Department of Microbiology, Immunology, and Biochemistry, University of Tennessee Health Science Center, Memphis, United States
David M Levine
Department of Biostatistics, University of Washington, Seattle, United States
Stefan A Schattgen
Department of Immunology, St. Jude Children’s Research Hospital, Memphis, United States
E Kaitlynn Allen
Department of Immunology, St. Jude Children’s Research Hospital, Memphis, United States
Guillermina Kuan
Centro Nacional de Diagnóstico y Referencia, Ministry of Health, Managua, Nicaragua; Sustainable Sciences Institute, Managua, Nicaragua
Noah Simon
Department of Biostatistics, University of Washington, Seattle, United States
Angel Balmaseda
Centro Nacional de Diagnóstico y Referencia, Ministry of Health, Managua, Nicaragua; Sustainable Sciences Institute, Managua, Nicaragua
Aubree Gordon
Department of Epidemiology, University of Michigan, Ann Arbor, United States
Paul G Thomas
Department of Immunology, St. Jude Children’s Research Hospital, Memphis, United States
Computational Biology Program, Fred Hutch Cancer Research Center, Seattle, United States; Department of Genome Sciences, University of Washington, Seattle, United States; Department of Statistics, University of Washington, Seattle, United States; Howard Hughes Medical Institute, Seattle, United States
Computational Biology Program, Fred Hutch Cancer Research Center, Seattle, United States; Institute for Protein Design, Department of Biochemistry, University of Washington, Seattle, United States
Every T cell receptor (TCR) repertoire is shaped by a complex probabilistic tangle of genetically determined biases and immune exposures. T cells combine a random V(D)J recombination process with a selection process to generate highly diverse and functional TCRs. The extent to which an individual’s genetic background is associated with their resulting TCR repertoire diversity has yet to be fully explored. Using a previously published repertoire sequencing dataset paired with high-resolution genome-wide genotyping from a large human cohort, we infer specific genetic loci associated with V(D)J recombination probabilities using genome-wide association inference. We show that V(D)J gene usage profiles are associated with variation in the TCRB locus and, specifically for the functional TCR repertoire, variation in the major histocompatibility complex locus. Further, we identify specific variations in the genes encoding the Artemis protein and the TdT protein to be associated with biasing junctional nucleotide deletion and N-insertion, respectively. These results refine our understanding of genetically-determined TCR repertoire biases by confirming and extending previous studies on the genetic determinants of V(D)J gene usage and providing the first examples of trans genetic variants which are associated with modifying junctional diversity. Together, these insights lay the groundwork for further explorations into how immune responses vary between individuals.