Project Summary Genetic variation is the central component of all major evolutionary processes. Differences among individuals’ genomes contribute to phenotypic variation including disease susceptibility and the evolution of adaptation. The exceptional growth in genome sequencing technologies and concomitant acceleration in the development of bioinformatic software has the potential to address longstanding questions about the evolution of genomes. Our lab will continue to lead this scientific endeavor by developing a range of statistical, computational, and experimental techniques. In particular, we will develop uniquely scalable computational methods to infer and to understand the relationships among densely sampled populations such as SARS-CoV-2. We will develop computational techniques to study adaptation and the underpinning of genetic isolation using genomes from admixed populations. Our group will leverage an established genome engineering technique to rearrange parts of genomes that have remained structurally static for more than 100 million years and to determine what molecular and fitness effects underlie this maintenance. Finally, our team will leverage natural variation in intron abundance to determine the molecular consequences and fitness impacts of massive intron gain. Results from this work have profound implications for understanding the origins, effects, and ultimate consequences of genetic variation on evolutionary outcomes in natural populations.