Thermal adaptation of the phage G4 and molecular evolution of RNA secondary structure Public Deposited

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  • March 22, 2019
  • Knies, Jennifer Lynn
    • Affiliation: School of Medicine, Curriculum in Genetics and Molecular Biology
  • The focus of this dissertation has been to investigate the predictability of evolution. This has been done in two ways. The larger part of this thesis is devoted to using thermal adaptation as a model system for investigating adaptation to novel environments. The second and smaller part of this thesis makes and tests a prediction for evolution in RNA secondary structure. Thermal adaptation is a useful model for studying common patterns of evolution, because the proximate mechanisms (e.g. biochemical rate processes) that determine the effects of temperature on growth or performance and the evolutiona ry causes of thermal adaptation are known. Two specific hypotheses about thermal adaptation are: (1) Thermal constraints on reaction rates will cause cold-adapted species to have lower maximal growth rates than hotter- adapted species at their thermal optima (i.e. "Hotter is better"), and (2) A trade-off between protein stability and activity underlies performance tradeoffs observed at different temperatures. These predictions were investigated by developing the bacteriophage G4 as a model experimental system. The growth rate of G4- like phages isolated from nature was examined over a wide temperature range and a positive correlation was detected between the phages maximal growth rates and optimal temperatures. By evolving multiple independent phage populations at high and low temperatures, I was able to detect common patterns of adaptation to high temperatures (e.g. increased thermal stability), but I did not detect any loss of themal stability in the populations evolved at low temperatures. By combining analyses of lab evolved and natural isolates of these phage, I showed that the nature of thermal constraints are predictable and repeatable. Lastly, I investigated interactions between within RNA secondary structure that place limits on the rate and trajectory of molecular evolution. A population genetics model of such interactions was used to predict that rate variation at interacting sites should be higher than rate variation at independent sites. This prediction was tested in eight RNA secondary structures by comparing the ratio of transition to transversion substitutions in paired sites to the ratio in unpaired sites. Six of the eight structures show an excellent match to the quantitative predictions of the population genetics model. These findings suggest use of the transition-transversion rate ratio as a simple diagnostic to validate proposed secondary structures.
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  • In Copyright
  • Burch, Christina L.
Degree granting institution
  • University of North Carolina at Chapel Hill
  • Open access

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