Publisher
The University of Arizona.Rights
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction, presentation (such as public display or performance) of protected items is prohibited except with permission of the author.Abstract
Large asexual populations often have complicated evolutionary dynamics due to their large influxes of beneficial mutations. Competition among the lineages that arise leads to the loss of many beneficial mutations, a phenomenon known as clonal interference. Several alleles and loci are involved in this process, which has made the study of asexual adaptation with clonal interference challenging to undertake. Traveling wave models in population genetics overcome these challenges, and over the last two decades, their application has significantly advanced our understanding of asexual adaptation, with several key results that shed light on how population parameters shape rates of adaptation, levels of genetic diversity and the structures of genealogies. In this work, I develop and discuss the application of two novel traveling models that build on the work of Desai and Fisher (2007). The first is a two-dimensional traveling wave that describes asexual adaptation with two fitness-associated traits. Analysis and simulations of this model are given in chapters two and three, along with a brief discussion of two major results: (1) the long-term features of trait interactions from clonal interference appear like functional constraints, and (2) the stalling of evolution in a trait from clonal interference with another is dependent on both selection coefficients and mutation rates. The second model discussed in this work includes a traveling wave over absolute fitness space to study the fitness dynamics responsible for long-term persistence and extinction in large asexual populations. In chapter four, I provide a brief overview of the model's construction with details surrounding key assumptions needed to appropriately describe absolute adaptation; analysis and results obtained from approximations to this model are subsequently presented.Type
textElectronic Dissertation
Degree Name
Ph.D.Degree Level
doctoralDegree Program
Graduate CollegeMathematics