{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,2]],"date-time":"2026-11-02T22:33:53Z","timestamp":1793658833322,"version":"4.5.1"},"reference-count":43,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T00:00:00Z","timestamp":1780012800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Immunol."],"abstract":"<jats:p>\n                    T cells must co-recognize peptide and HLA, yet the extent to which this specificity is shaped by germline-driven TCR\u2013HLA contacts has remained difficult to quantify. Leveraging population-scale TCR\n                    <jats:italic>\u03b2<\/jats:italic>\n                    repertoires linked to donor HLA genotypes inferred using validated imputation models, we construct allele-specific TCR V\n                    <jats:italic>\u03b2<\/jats:italic>\n                    gene usage profiles and normalize them to repertoire-wide baselines to derive interpretable HLA-V\n                    <jats:italic>\u03b2<\/jats:italic>\n                    preference vectors. We demonstrate that different HLA alleles shape distinct biases in the usage frequency of V\n                    <jats:italic>\u03b2<\/jats:italic>\n                    gene segments among the public TCRs that engage those alleles: certain V\n                    <jats:italic>\u03b2<\/jats:italic>\n                    genes are over-represented for particular HLA alleles. Similarities in HLA amino-acid sequence predict similarities in both their V\n                    <jats:italic>\u03b2<\/jats:italic>\n                    preferences and peptide-binding motifs. A residue-level analysis disentangles HLA positions primarily associated with V\n                    <jats:italic>\u03b2<\/jats:italic>\n                    engagement from those primarily associated with peptide motifs; the V\n                    <jats:italic>\u03b2<\/jats:italic>\n                    -associated HLA positions localize to canonical TCR-facing helices, whereas peptide-associated HLA positions track binding pockets, revealing distinct molecular routes by which HLA polymorphism shapes the TCR and peptide sides of recognition. CMV exposure stratifications confirmed these V\n                    <jats:italic>\u03b2<\/jats:italic>\n                    preference vectors are not explained by any shift of repertoire composition associated with a dominant infection. Together, these data support that germline-driven constraints set the landscape of TCR\u2013HLA compatibility. These HLA-specific TCR V\n                    <jats:italic>\u03b2<\/jats:italic>\n                    biases are a biological prior that provide a foundation for better understanding of TCR-pHLA specificity as a whole and should be accounted for in future evaluation of any TCR-pHLA specificity prediction methods.\n                  <\/jats:p>","DOI":"10.3389\/fimmu.2026.1816068","type":"journal-article","created":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T08:31:40Z","timestamp":1780043500000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["HLA alleles shape distinct biases in the usage preferences of TCR V\u03b2 segments"],"prefix":"10.3389","volume":"17","author":[{"given":"Leonardo V.","family":"Castorina","sequence":"first","affiliation":[{"name":"Microsoft Research","place":["Redmond, WA, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matthew T.","family":"Noakes","sequence":"additional","affiliation":[{"name":"Adaptive Biotechnologies","place":["Seattle, WA, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lorenzo","family":"Pisani","sequence":"additional","affiliation":[{"name":"Microsoft Research","place":["Redmond, WA, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julia","family":"Greissl","sequence":"additional","affiliation":[{"name":"Microsoft Research","place":["Redmond, WA, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Harlan","family":"Robins","sequence":"additional","affiliation":[{"name":"Adaptive Biotechnologies","place":["Seattle, WA, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haiyin","family":"Chen-Harris","sequence":"additional","affiliation":[{"name":"Adaptive Biotechnologies","place":["Seattle, WA, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"H. 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