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Meta-analysis of major histocompatibility complex (MHC) class IIA reveals polymorphism and positive selection in many vertebrate species.

Donald C DearbornSophie WarrenFrank Hailer
Published in: Molecular ecology (2022)
Pathogen-mediated selection and sexual selection are important drivers of evolution. Both processes are known to target genes of the major histocompatibility complex (MHC), a gene family encoding cell-surface proteins that display pathogen peptides to the immune system. The MHC is also a model for understanding processes such as gene duplication and trans-species allele sharing. The class II MHC protein is a heterodimer whose peptide-binding groove is encoded by an MHC-IIA gene and an MHC-IIB gene. However, our literature review found that class II MHC papers on infectious disease or sexual selection included IIA data only 18% and 9% of the time, respectively. To assess whether greater emphasis on MHC-IIA is warranted, we analysed MHC-IIA sequence data from 50 species of vertebrates (fish, amphibians, birds, mammals) to test for polymorphism and positive selection. We found that the number of MHC-IIA alleles within a species was often high, and covaried with sample size and number of MHC-IIA genes assayed. While MHC-IIA variability tended to be lower than that of MHC-IIB, the difference was only ~25%, with ~3 fewer IIA alleles than IIB. Furthermore, the unexpectedly high MHC-IIA variability showed clear signatures of positive selection in most species, and positive selection on MHC-IIA was stronger in fish than in other surveyed vertebrate groups. Our findings underscore that MHC-IIA can be an important target of selection. Future studies should therefore expand the characterization of MHC-IIA at both allelic and genomic scales, and incorporate MHC-IIA into models of fitness consequences of MHC variation.
Keyphrases
  • genome wide
  • systematic review
  • healthcare
  • gene expression
  • randomized controlled trial
  • mental health
  • physical activity
  • machine learning
  • binding protein
  • artificial intelligence