Evolutionary dynamics of the natural Drosophila microbiome

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All known organisms on earth are associated with microorganisms. Pathogenic microorganisms can exert strong selection pressures on their hosts. As a consequence genes involved in pathogen defense often take part in an evolutionary arms race with pathogens, and hence are among the fastest evolving genes. On the other hand, microbes have facilitated a plethora of major adaptive evolutionary innovations of their metazoan hosts. Nonetheless, studies that aim at understanding how organisms adapt to the environment often neglect the role of the microbiome in the adaptive process. D. melanogaster lives in a microbe rich environment, rotting fruit. Its phenotype and fitness are strongly microbiome dependent. This suggests that D. melanogaster is under selection to evolve mechanisms to control its associated microbiome. This means to shape the microbiome for its benefit. In order for selection pressure to result in adaptive evolution of host control, the selected traits have to be variable and have to have a heritable genetic component. We hypothesize that in the only evolutionary relevant setting, under natural conditions, (i) the D. melanogaster associated microbiome varies, (ii) there is a component of this variation that depends on host genotype, (iii) the variation in the underlying loci is shaped by natural selection. We address these hypotheses in a work program including two major project parts. In the first part, we will perform a microbiome Genome Wide Association Study (mGWAS) using 1000 samples collected in Europe, leveraging the resources of the European Drosophila Population Genomics Consortium (DrosEU). This will allow us to quantify the contribution of host genetic factors to microbiome variation and to identify the underpinning loci (mQTL). Drosophila is exceptionally well suited for such a study because it has (i) low levels of linkage disequilibrium that allows to pinpoint mQTLs to the SNP level, (ii) low levels of populations structure that could interfere with GWAS, (iii) a relatively simple microbiome that facilitates a cost effective and detailed assessment, (iv) an almost unrivaled genetic tractability for experimental assessment of mGWAS results. In a second step, we will analyze the mGWAS results in an evolutionary framework, to understand the ultimate forces that shape the variation at microbiome-interacting loci on a genomic level. Therefore, we will use state of the art population genomic methods including, but not limited to novel tests to detect polygenic selection on complex traits. In addition to analyzing potentially varying selective pressures across Europe, we will leverage publicly available population genetic data from the ancestral range of flies to test whether the expansion from Africa and colonization of temperate climates was accompanied by selection on microbiome interacting loci.