A monoallelic immunopeptidome atlas of 10 prevalent canine DLA-88 alleles

Authors

Miyamae, J., Murakami, K., Hemmi, H.

Abstract

Characterization of naturally processed MHC class I (MHC-I)-bound peptides is essential for defining allele-specific peptide-binding features and understanding the functional consequences of MHC-I polymorphism. However, immunopeptidome analyses of dog leukocyte antigen (DLA) class I (DLA-I) molecules remain limited and comprehensive monoallelic ligand datasets for prevalent DLA-88 alleles are still lacking. Here, we established canine melanoma-derived cell populations expressing individual functional DLA-88 alleles and generated a monoallelic immunopeptidome atlas of prevalent DLA-88 alleles. Using liquid chromatography-tandem mass spectrometry, we identified 32,702 naturally processed peptides of 7 to15 amino acids across 10 DLA-88 alleles, substantially expanding the available DLA-88 immunopeptidome landscape. These 10 alleles exhibited canonical peptide length distributions and allele-specific binding motifs that reflected variation in binding-groove pseudo-sequences defined from human MHC-I peptide-contact residues. Ligand sharing between DLA-88 alleles was associated with binding site distance. Incorporation of the comprehensively characterized DLA-88 ligand datasets in this study increased by more than fourfold the number of published canine DLA-I alleles with ligand-characterized reference alleles predicted to have similar peptide-binding features. We also found that antigen-processing signatures were highly conserved with those reported in humans. As a proof-of-concept application, we selected 54 DLA-88-bound peptides identified in our immunopeptidome analysis as candidate peptides for canine cancer immunotherapy by evaluating the normal tissue expression profiles of their source proteins. This DLA-88 immunopeptidome atlas provides insights into allele-dependent differences in antigen presentation and represents a valuable resource for developing accurate DLA-88-binding peptide prediction tools and supporting peptide-based immunological studies in dogs.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 13 Oct 2026.

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