DISENTANGLING THE GENETICS OF COEVOLUTION IN POTAMOPYRGUS ANTIPODARUM AND MICROPHALLUS SP.
Jenkins, Christina Elizabeth
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Theoretical research has consistently demonstrated that host-parasite coevolution is important for many evolutionary transitions such as the evolution of sexual reproduction, ploidy and the evolution of mating systems. In these models, host-parasite interaction is characterized by host resistance and parasites infectivity which is assumed to be based on a matrix of genotype by genotype specificity (GxG). Importantly, a recent trend has demonstrated that the GxG matrix assumed in a given theoretical model will drastically alter the evolutionary outcome of coevolution. Consequently, determining the form of genetic interaction matrices in natural populations is crucial to both understanding coevolution and the resulting evolutionary transitions. In this dissertation, I explore the genetics of host-parasite interactions in three different ways. First, using New Zealand snail, Potamopyrgus antipodarum and its parasite Microphallus sp., I tested the fit of different genetic models by comparing the resistance of triploid and tetraploid hosts, which differ in gene dosage, heterozygosity, and abundance of novel alleles.. In my second chapter, my approach to understanding genetic interactions in the Potamopyrgus - Microphallus system was to find molecular and genetic basis of traits expressed by the Microphallus. Consequently, I generated mRNA sequence data for Microphallus sp.. I then assembled and annotated a reference transcriptome, and placed the parasite taxonomically in the Microphilidae and Digenia phylogeny. Finally, in my third chapter, I developed a technique for finding the genomic regions involved in coevolution. Using genomic data, we can look for SNPs that covary spatially between the host and parasite, as these will be the ones likely involved in coevolution. I tested this technique using simulated populations of hosts and parasites with coevolving loci and varied a number of parameters and models of infection to determine how robust this technique is in different environments.