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Abstract:
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Mutation 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 . |