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Evolution of the Multigene Family

A Case of Dynamically Evolving Genes at Major Histocompatibility Complex
  • Tomoko Ohta

Summary

It is now known that many multigene families exist in eukaryote genomes. Multigene families that are known to be evolving under continued occurrence of unequal crossing-over and gene conversion provide a different picture of evolution from that of the conventional population genetics. As an example of an evolving multigene family, evolution and variation at major histocompatibility complex loci are reviewed. Exceptionally high polymorphisms at the class I and class II loci of major histocompatibility complex (MHC) has been of great interest for many years. In addition, recent studies indicate that amino acid substitution at antigen recognition sites (ARS) is more rapid than synonymous substitution, contrary to the general pattern of nucleotide substitution in evolution. However, such acceleration seems to be limited to a certain period after gene duplication. In order to explain such an unusual pattern, a population genetic model of diversifying selection is constructed. To make the model fit the data, diversifying selection needs to work on enhancing diversity not only between alleles at the same locus, but also between genes at different loci belonging to the gene family. Gene conversion among genes is also incorporated by choosing parameter values that are thought to be realistic. Simulation studies reveal that very weak selection at individual amino acid sites can explain the unusual pattern of evolution and polymorphism at MHC loci under this model. The applicability of the present model is discussed by surveying other examples, such as evolution of protease inhibitors and immunogloblin variable regions that show a similar pattern of acceleration of amino acid substitutions.

Keywords

Major Histocompatibility Complex Gene Conversion Multigene Family Synonymous Substitution Amino Acid Site 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Tokyo 1991

Authors and Affiliations

  • Tomoko Ohta
    • 1
  1. 1.National Institute of GeneticsMishimaJapan

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