Population Genomics of Polistes Wasps

The molecular mechanisms influencing the evolution of social behaviour in insects are of great interest and have been the focus of many recent studies. Chapter one of this thesis reviews several major hypotheses regarding the evolution of sociality. Chapter two outlines the methodological steps taken to generate a high quality population genomic data set for primitively eusocial paper wasps in the genus Polistes. The third chapter of the thesis uses the dataset generated in chapter two to estimate patterns of natural selection on the Polistes genome, and to evaluate the importance of novel and caste biased genes on the fitness of this primitively eusocial species

Understanding the evolutionary origin and ancestral composition of honey bee (Apis mellifera) populations.

The honey bee, Apis mellifera, is arguably the most important managed pollinator globally. Yet despite its economic and ecological importance, there are still several unknowns regarding the species ancestral origin and ancestral complexity. Understanding the genetic composition of native and managed honey bee colonies is imperative for resolving the species life history and elucidating how ancestry may inform management strategies. In this dissertation, I take a deep dive into the evolutionary origins of Apis mellifera and learn how ancestral complexity has shaped the composition of contemporary populations. In Chapter two, I settle a long-standing debate about the ancestral origins of the species. I find that Apis mellifea diverged out of Western Asia via at least three colonization routes, which resulted in the evolution of at least seven genetically distinct lineages. Interesting, I find that these lineages were able to adapt to their current distribution by repeated selection among a core set of genes. In Chapter three, I take a closer look at the genetic complexity of managed Canadian honey bees by estimating the ancestral composition of colonies using the genomic dataset from Chapter two. I find that patterns of ancestry differ between Canadian provinces, and that admixture correlates strongly with levels of genetic diversity. Interestingly, I find that genomic intervals with elevated levels of admixture segregate non-randomly in the genome and are associated with genes related to parasite and xenobiotic tolerance. Though admixture may bear advantages for managed colonies, admixture among honey bee is not always valued. In Chapter four and five I make use of the ancestral composition of invasive Africanized honey bees to develop assays to identify and track populations. This was achieved using machine learning models to choose the most informative single nucleotide polymorphisms (Chapter 4) and insertion-deletion (Chapter 5) markers that best delineate Africanized genetics from managed European colonies. My research addresses many gaps in our understanding of honey bee origins and ancestral complexity