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- Title
- An analysis of fitness in long-term asexual evolution experiments
- Creator
- Wiser, Michael J.
- Date
- 2015
- Collection
- Electronic Theses & Dissertations
- Description
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Evolution is the central unifying concept of modern biology. Yet it can be hard to study in natural system, as it unfolds across generations. Experimental evolution allows us to ask questions about the process of evolution itself: How repeatable is the evolutionary process? How predictable is it? How general are the results? To address these questions, my collaborators and I carried out experiments both within the Long-Term Evolution Experiment (LTEE) in the bacteria Escherichia coli, and the...
Show moreEvolution is the central unifying concept of modern biology. Yet it can be hard to study in natural system, as it unfolds across generations. Experimental evolution allows us to ask questions about the process of evolution itself: How repeatable is the evolutionary process? How predictable is it? How general are the results? To address these questions, my collaborators and I carried out experiments both within the Long-Term Evolution Experiment (LTEE) in the bacteria Escherichia coli, and the digital evolution software platform Avida. In Chapter 1, I focused on methods. Previous research in the LTEE has relied on one particular way of measuring fitness, which we know becomes less precise as fitness differentials increase. I therefore decided to test whether two alternate ways of measuring fitness would improve precision, using one focal population. I found that all three methods yielded similar results in both fitness and coefficient of variation, and thus we should retain the traditional method.In Chapter 2, I turned to measuring fitness in each of the populations. Previous work had considered fitness to change as a hyperbola. A hyperbolic function is bounded, and predicts that fitness will asymptotically approach a defined upper bound; however, we knew that fitness in these populations routinely exceeded the asymptotic limit calculated from a hyperbola fit to the earlier data. I instead used to a power law, a mathematical function that does not have an upper bound. I found that this function substantially better describes fitness in this system, both among the whole set of populations, and in most of the individual populations. I also found that the power law models fit on just early subsets of the data accurately predict fitness far into the future. This implies that populations, even after 50,000 generations of evolution in consistent environment, are so far from the tops of fitness peaks that we cannot detect evidence of those peaks.In Chapter 3, I examined to how variance in fitness changes over long time scales. The among-population variance over time provides us information about the adaptive landscape on which the populations have been evolving. I found that among-population variance remains significant. Further, competitions between evolved pairs of populations reveal additional details about fitness trajectories than can be seen from competitions against the ancestor. These results demonstrate that our populations have been evolving on a complex adaptive landscape.In Chapter 4, I examined whether the patterns found in Chapter 2 apply to a very different evolutionary system, Avida. This system incorporates many similar evolutionary pressures as the LTEE, but without the details of cellular biology that underlie nearly all organic life. I find that in both the most complex and simplest environments in Avida, fitness also follows the same power law dynamics as seen in the LTEE. This implies that power law dynamics may be a general feature of evolving systems, and not dependent on the specific details of the system being studied.
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- Title
- Evolving cooperative, energy-conserving, agent-based systems
- Creator
- Beckmann, Benjamin Edward
- Date
- 2010
- Collection
- Electronic Theses & Dissertations
- Title
- On the beneficial effects of deleterious mutations
- Creator
- Covert, Arthur W.
- Date
- 2010
- Collection
- Electronic Theses & Dissertations
- Title
- On the evolution of mutation bias in digital organisms
- Creator
- Rupp, Matthew
- Date
- 2011
- Collection
- Electronic Theses & Dissertations
- Description
-
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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