Browsing by Subject "Evolution (Biology)"
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Item A scientific research center for the Galapagos Islands, Ecuador(Texas Tech University, 1987-05) Naranjo, Ivan JNoneItem Analytical, computational, and statistical approaches to studying speciation(2007) Lemmon, Alan Richard, 1976-; Kirkpatrick, Mark, 1956-; Hillis, David M., 1958-Two of the most challenging goals of evolutionary biology are to reconstruct the evolutionary relationships among all extant species and to understand the process by which new species form. Accomplishing these goals will require accurate computational methods for reconstructing phylogenetic trees, general analytic models of speciation, and powerful statistical tools for studying the process of speciation in natural systems. In the first chapter, I study the effects of improper model assumption on estimates of phylogeny. Using DNA sequence data simulated under a variety of models of sequence evolution, I demonstrate that use of oversimplified models can result in erroneous phylogeny estimates. This result suggests that if the models currently utilized are oversimplified then current estimates of phylogeny may be inaccurate and more complex models need to be developed and employed. In the second and third chapters, I study one process thought to be important in completing the final stages of speciation: reinforcement. Using simulations of a hybrid zone, I show that the process of reinforcement can result in patterns other than reproductive character displacement. I also show that speciation by reinforcement is more likely when the genes involved in reproductive isolation are sex-linked. In the fourth chapter, I develop a statistical method of quantifying the degree of isolation between species undergoing divergence. Using genotype data obtained from natural hybrid zones, this novel method can be used to estimate the fitness of hybrids during different stages of their life cycle. This approach offers a new approach to empirical biologists studying extrinsic postzygotic isolation in natural systems.Item The evolutionary ecology of model microbial communities(2009-05) Harcombe, William Russell; Bull, James J.The biological world is complex. Communities contain a multitude of interacting species, while populations contain extensive genetic variation. How much complexity must one consider to understand patterns and processes of interest? When are species interactions and community properties shaped by evolution? Conversely, when is evolution altered by community context? I test these questions in a series of experiments with simple microbial communities. The first data chapter investigates the impact of competition on the evolution of phage resistance in bacteria. This work demonstrates that community context can dramatically alter the evolution of resistance to phage. Next I tested the impact of evolution on assembly of a three species community. I demonstrate that evolution can influence the content of a microbial community by altering the process of assembly. Finally, I investigated the evolutionary origin and maintenance of cross-feeding mutualisms. This work suggests that species interactions can enable novel evolutionary pathways, and that evolution can significantly increase the productivity of cross-feeding communities. Jointly these experiments suggest that consideration of the interplay between ecological and evolutionary forces can provide insight into the complexity of the natural world.Item Genome organization, mobile DNA, and chromosomal evolution in mammals(Texas Tech University, 2003-05) Parish, Deidre ArthurNot availableItem Mutation: lessons from RNA models(2008-05) Cowperthwaite, Matthew Cranston, 1973-; Meyers, Lauren AncelMutation is a fundamental process in evolution because affects the amount of genetic variation in evolving populations. Molecular-structure models offer significant advantages over traditional population-genetics models for studying mutation, mainly because such models incorporate simple, tractable genotype-to-phenotype maps. Here, I use RNA secondary structure models to study four basic properties of mutation. The first section of this thesis studies the statistical properties of beneficial mutations. According to population genetics theory, the fitness effects of new beneficial mutations will be exponentially distributed. I show that in RNA there is sufficient correlation between a genotype and its point mutant neighbors to produce non-exponential distributions of fitness effects of beneficial mutations. These results suggest that more sophisticated statistical models may be necessary to adequately describe the distribution of fitness effects of new beneficial mutations. The second section of this thesis addresses the dynamics of deleterious mutations in evolving populations. There is a vast body of theoretical work addressing deleterious mutations that almost universally assumes that the fitness effects of deleterious mutations are static. I use an RNA simulation model to show that, at moderately high mutation rates, initially deleterious mutations may ultimately confer beneficial effects to the individuals harboring them. This result suggests that deleterious mutations may play a more important role in evolution than previously thought. The third section of this thesis studies the global patterns of mutations connecting phenotypes in fitness landscapes. I developed a network model to describe global characteristics of the relationship between sequence and structure in RNA fitness landscapes. I show that phenotype abundance varies in a predictable manner and critically influences evolutionary dynamics. A study of naturally occurring functional RNA molecules using a new structural statistic suggests that these molecules are biased towards abundant phenotypes. These results are consistent with an "ascent of the abundant" hypothesis, in which evolution yields abundant phenotypes even when they are not the most fit. The final section of this thesis addresses the evolution of mutation rates infinite asexual populations. I developed an RNA-based simulation model in which each individual's mutation rate is controlled by a neutral modifier locus. Using this model, I show that smaller populations maintain higher mutation rates than larger populations. I also show that genome length and shape of the fitness function do not significantly determine the evolved mutation rate. Lastly, I show that intermediate rates of environmental change favor evolution of the largest mutation rates.