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Characterization of pathogen-driven selection at B4galnt2 in house mice


Vallier,  Marie
Guest Group Evolutionary Genomics, Max Planck Institute for Evolutionary Biology, Max Planck Society;


Baines,  John F.
Guest Group Evolutionary Genomics, Max Planck Institute for Evolutionary Biology, Max Planck Society;

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Vallier, M. (2017). Characterization of pathogen-driven selection at B4galnt2 in house mice. PhD Thesis, Christian-Albrechts-Universität zu Kiel, Kiel.

Cite as: http://hdl.handle.net/11858/00-001M-0000-002E-0DC9-8
B4galnt2 is a blood group-related glycosyltransferase that displays cis-regulatory variation for its tissue-specific expression patterns in house mice. The wild type allele, found e.g. in the C57BL/6J laboratory mouse strain, directs intestinal expression of B4galnt2, which is the pattern observed among vertebrates, including humans. An alternative allele class found in the RIIIS/J strain and other mice instead drives expression in blood vessels, which leads to a phenotype similar to type 1 von Willebrand disease (VWD), a common human bleeding disorder. Previous studies showed that alternative B4galnt2 alleles are subject to long-term balancing selection in mice and that variation in B4galnt2 expression influences host-microbe interactions in the intestine. This suggests that the cost of prolonged bleeding in RIIIS/J allele-bearing mice might be outweighed by benefits associated with resistance against gastrointestinal pathogens. However, the conditions under which such trade-offs could lead to the long-term maintenance of disease-associated variation at B4galnt2 are unclear. To understand and characterize the potential pathogen-driven selection acting on B4galnt2 in the wild, I first developed a mathematical model based on an evolutionary game framework with a modified Wright-Fisher process, adjusted to implement diploid individuals. In particular, I focused on heterozygous mice, which express B4galnt2 in both blood vessels and the gastrointestinal tract. By comparing simulated to natural populations, I found that the genotype frequencies observed in nature can be produced by pathogen-driven selection when (i) the fitness cost of bleeding is roughly half that of infection and (ii) both heterozygotes and RIIIS/J homozygotes are protected against infection. The resistance of the heterozygote individuals indicates that a dominant protective function of the RIIIS/J allele is more likely than a protective loss of intestinal expression. However, the nature of the dominant protective function of the RIIIS/J allele remains unknown, as the model suggests that the associated vascular expression is not necessarily linked to the pathogen resistance. Furthermore, I aimed to identify potential pathogens driving the selection at B4galnt2 by sampling and phenotyping over 200 newly collected mice from Southern France, where an intermediate frequency of the RIIIS/J allele is present. Through the multilayer analysis of genetic patterns, signs of inflammation, and intestinal microbial communities, I could associate several bacterial genera to patterns consistent with genotype-dependent host-pathogen interaction. One genus in particular, Morganella, is a likely candidate as it is a well-known opportunistic pathogen and its abundance, prevalence and activity patterns are associated with increased inflammation in mice with intestinal expression of B4galnt2. Finally, I could identify the relevant species of Morganella, which represents a new subspecies of the Morganella morganii group, and possesses virulence-related genes absent from the other Morganella species, which may account for its potential to drive selection at B4galnt2 via genotype-dependent host-pathogen interactions. In conclusion, my work provides new insights into the potential evolutionary dynamics taking place at B4galnt2 in wild populations of house mice, showing that pathogen-driven selection is a likely cause for the maintenance of both B4galnt2 alleles in the wild. Moreover, my work could be applied beyond the scope of murine glycosyltransferases, as the methods that I developed can easily be generalized to other biological models.