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- Title
- On the evolution of mutation bias in digital organisms
- Creator
- Rupp, Matthew
- Date
- 2011
- Collection
- Electronic Theses & Dissertations
- Description
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Mutation is one of the primary drivers of genetic change. In this work I study mutation biases, which are sets of different genetic-state inflow probabilities. Mutation biases have the potential to change the composition of genomes over time, leading to divergent short- and long-term evolutionary outcomes. I use digital organisms, self-replicating computer programs, to explore whether or not mutation biases are capable of altering the long-term adaptive behavior of populations; whether...
Show moreMutation is one of the primary drivers of genetic change. In this work I study mutation biases, which are sets of different genetic-state inflow probabilities. Mutation biases have the potential to change the composition of genomes over time, leading to divergent short- and long-term evolutionary outcomes. I use digital organisms, self-replicating computer programs, to explore whether or not mutation biases are capable of altering the long-term adaptive behavior of populations; whether mutation biases can be competitive traits; and whether mutation biases can evolve. I find that mutation biases can alter the long-term adaptive behavior of mutation bias-obligate populations in terms of both mean fitness and complex trait evolution. I also find that mutation biases can compete against one another under a variety of conditions, meaning mutation bias can selectable over relatively-short periods of time. The competitive success of a mutation bias does not always depend upon the presence of beneficial mutations, implicating an increase in the probability of neutral mutations as a sufficient mechanism for bias selection. Finally, I demonstrate that by giving organisms a mutable mutation bias allele, populations preferentially evolve to possess specific biases over others. Overall, this work shows that mutation bias can act as a selectable trait, influencing the evolution of populations with regard to both their internal-genetic and external environments.
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- Title
- On the beneficial effects of deleterious mutations
- Creator
- Covert, Arthur W.
- Date
- 2010
- Collection
- Electronic Theses & Dissertations
- Title
- The evolutionary potential of populations on complex fitness landscapes
- Creator
- Bryson, David Michael
- Date
- 2012
- Collection
- Electronic Theses & Dissertations
- Description
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Evolution is a highly contingent process, where the quality of the solutions produced is affected by many factors. I explore and describe the contributions of three such aspects that influence overall evolutionary potential: the prior history of a population, the type and frequency of mutations that the organisms are subject to, and the composition of the underlying genetic hardware. I have systematically tested changes to a digital evolution system, Avida, measuring evolutionary potential in...
Show moreEvolution is a highly contingent process, where the quality of the solutions produced is affected by many factors. I explore and describe the contributions of three such aspects that influence overall evolutionary potential: the prior history of a population, the type and frequency of mutations that the organisms are subject to, and the composition of the underlying genetic hardware. I have systematically tested changes to a digital evolution system, Avida, measuring evolutionary potential in seven different computational environments ranging in complexity of the underlying fitness landscapes. I have examined trends and general principles that these measurements demonstrate and used my results to optimize the evolutionary potential of the system, broadly enhancing performance. The results of this work show that history and mutation rate play significant roles in evolutionary potential, but the final fitness levels of populations are remarkably stable to substantial changes in the genetic hardware and a broad range of mutation types.
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- Title
- Mechanisms of adaptation and speciation : an experimental study using artificial life
- Creator
- Anderson, Carlos Jesus
- Date
- 2013
- Collection
- Electronic Theses & Dissertations
- Description
-
Detailed experimental studies in evolutionary biology are sometimes difficult--even with model organisms. Theoretical models alleviate some of these difficulties and often provide clean results, but they cannot always capture the complexity of dynamic evolutionary processes. Artificial life systems are tools that fall somewhere between model organisms and theoretical models that have been successfully used to study evolutionary biology. These systems simulate simple organisms that replicate,...
Show moreDetailed experimental studies in evolutionary biology are sometimes difficult--even with model organisms. Theoretical models alleviate some of these difficulties and often provide clean results, but they cannot always capture the complexity of dynamic evolutionary processes. Artificial life systems are tools that fall somewhere between model organisms and theoretical models that have been successfully used to study evolutionary biology. These systems simulate simple organisms that replicate, acquire random mutations, and reproduce differentially; as a consequence, they evolve naturally (i.e., evolution itself is not simulated). Here I use the software Avida to study several open questions on the genetic mechanisms of adaptation and speciation.In Chapter 1 (p. 13), I investigated whether beneficial alleles during adaptation came from new mutations or standing genetic variation--alleles already present in the population. I found that most beneficial alleles came from standing genetic variation, but new mutations were necessary for long-term evolution. I also found that adaptation from standing genetic variation was faster than from new mutations. Finally, I found that recombination brought together beneficial combinations of alleles from standing genetic variation.In Chapter 2 (p. 31), I investigated the probability of compensatory adaptation vs. reversion. Compensatory adaptation is the fixation of mutations that ameliorate the effects of deleterious mutations while the original deleterious mutations remain fixed. I found that compensatory adaptation was very common, but the window of opportunity for reversion was increased when the initial fitness of the population was high, the population size was large, and the mutation rate was high. The reason that the window of opportunity for reversion was constrained was that negative epistatic interactions with compensatory mutations prevented the revertant from being beneficial to the population.In Chapter 3 (p. 58), I showed experimentally that compensatory adaptation can lead to reproductive isolation (specifically, postzygotic isolation). In addition, I found that the strength of this isolation was independent of the effect size of the original deleterious mutations. Finally, I found that both deleterious and compensatory mutations contribute equally to reproductive isolation.Reproductive isolation between populations often evolves as a byproduct of independent adaptation to new environments, but the selective pressures of these environments may be divergent (`ecological speciation') or uniform (`mutation-order speciation'). In Chapter 4 (p. 75), I compared directly the strength of postzygotic isolation generated by ecological and mutation-order processes with and without migration. I found that ecological speciation generally formed stronger isolation than mutation-order speciation and that mutation-order speciation was more sensitive to migration than ecological speciation.Under the Dobzhansky-Muller model of speciation, hybrid inviability or sterility results from the evolution of genetic incompatibilities (DMIs) between species-specific alleles. This model predicts that the number of pairwise DMIs between species should increase quadratically through time, but the few tests of this `snowball effect' have had conflicting results. In Chapter 5 (p. 101), I show that pairwise DMIs accumulated quadratically, supporting the snowball effect. I found that more complex genetic interactions involved alleles that rescued pairwise incompatibilities, explaining the discrepancy between the expected accumulations of DMIs and observation.
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