AuthorFortier, Alyssa Lyn
MetadataShow full item record
PublisherThe University of Arizona.
RightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
AbstractFactors such as genetic drift and natural selection shape genetic variation between populations. To understand this variation, population geneticists study the populations’ demographic history, Distribution of Fitness E?ects of new mutations (DFE), and dominance coefficient. While current demographic analyses can incorporate two populations, DFE and dominance studies are largely limited to one. The single-population approach assumes independence between populations, though this is not biologically accurate. We hypothesized that two populations would have high, though not perfect, correlation between fitness e?ects for the same mutations. We developed a Mixture Model for the 2D DFE that is robust to demographic changes, dominance conditions, and sample size. We applied it to human and Drosophila melanogaster genome data, finding that the correlation parameter between Drosophila populations varies widely among functional gene groups. In contrast, human gene groups have extremely high correlation values, indicating that selection acts very similarly in both populations. We also conducted simulation studies to infer the dominance coefficient between two populations, ultimately identifying some situations where the method is robust to errors. Overall, these tools will allow other researchers to better understand genetic variation between two populations of the same species.
Degree ProgramHonors College
Molecular and Cellular Biology