UC Davis

Many longstanding questions in evolution concern the major forces that shape genetic variation in natural populations: natural selection, genetic drift, mutation, gene flow, and recombination. Their interaction determines the means by which populations adapt and explains patterns of genetic and phenotypic variation within and among populations. In this dissertation, I use recent developments in population genetics to study the genomic signatures of these outcomes and their implications for inferring the history of adaptation and predicting phenotypes.

In chapters 1 and 2, I focus on the process of adaptive introgression, whereby selection favors the spread of alleles introduced by gene flow from another species. For both of these chapters, I develop methods based on coalescent theory that use recombination as a signal to understand how and when introgressed alleles facilitated adaptation to new environments. In chapter 1, I analyzed both ancient- and present-day DNA samples from humans and Neanderthals, determining genomic regions where Neanderthal introgression provided standing variation for future adaptation in human populations. In chapter 2, I analyzed samples from two sister killifish species in which some populations can survive extremely toxic waters from pollution. In resistant Fundulus grandis populations of the Houston ship channel, I identified cases of extremely strong selection acting on rare introgressed variation that was introduced recently from a resistant Fundulus heteroclitus population along the Atlantic coast. Together, these chapters uncover the selection pressures acting on populations and highlight that admixture between closely related species can be a source of adaptive variation immediately and in the long term.

In chapter 3, I provide an evolutionary perspective on the limitations of genome-wide association study results to understand complex trait variation in understudied populations. I model how mutation, stabilizing selection, and genetic drift interact to shape quantitative trait variation and quantify their implications for phenotype prediction across populations when ascertaining underlying genetic variation in a subset of populations.

The combination of theoretical models and analysis of population genomic data in this dissertation provide a rich investigation into the genetics of adaptation and limitations of common approaches in understanding the relationship between genetic and phenotypic variation.