UCLA

Deleterious genetic variation is abundant in wild populations and can contribute to extinction when populations become small and isolated. For example, elevated levels of inbreeding in small populations can expose recessive deleterious mutations as homozygous and depress population fitness. Additionally, increased genetic drift in small populations can result in relaxed selection against weakly deleterious mutations, leading to an accumulation of such mutations that can also contribute to fitness declines. Genomic sequencing tools have enabled a proliferation of studies on the threat of deleterious genetic variation in small populations of conservation concern. However, how to best leverage such data to predict extinction risk in these populations remains unclear. My dissertation aims to provide clarity to this issue by leveraging computational genetic simulations in concert with genomic data to better understand the threat that deleterious genetic variation poses to extinction risk. In my first chapter, I used eco-evolutionary simulations to explore the effects of deleterious genetic variation on extinction risk under a variety of demographic scenarios. These results implicate recessive strongly deleterious mutations as the key drivers of extinction in small populations, as the exposure of such mutations via inbreeding can lead to extinction much faster than the more gradual impacts of weakly deleterious variation. In my second chapter, I applied a similar simulation framework to explore the threat of deleterious genetic variation to extinction risk in the critically endangered vaquita porpoise. My results suggest that the species is genetically well-equipped to recover from a severe bottleneck due to its small historical population size, which implies a low load of recessive strongly deleterious variation that can contribute to future inbreeding depression. In my third chapter, I examined the genomic factors enabling persistence in an isolated population of moose on Isle Royale. My results suggest a role for ‘purging’ of recessive deleterious mutations during a severe founder event for the population as a key factor resulting in the continued health of the population. Finally, in my fourth chapter, I reviewed simulation-based approaches for quantifying genetic load and predicting extinction risk. Here, I aim to encourage other researchers to also employ simulations in studies of deleterious variation in small populations, providing an overview of the components of a simulation of deleterious genetic variation and the relevant model parameters. Altogether, this dissertation provides novel perspectives and approaches for understanding the risks of extinction due to deleterious genetic variation in wild populations.