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LaBar, T.

Publications and source records attributed to LaBar, T..

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Mapping the Peaks: Fitness Landscapes of the Fittest and the Flattest

BackgroundPopulations exposed to a high mutation rate harbor abundant deleterious genetic variation, leading to depressed mean fitness. This reduction in mean fitness presents an opportunity for selection to restore adaptation through the evolution of mutational robustness. In extreme cases, selection for mutational robustness can lead to \"flat\" genotypes (with low fitness but high robustness) out-competing \"fit\" genotypes with high fitness but low robustness--a phenomenon known as \"survival of the flattest\". While this effect was previously explored using the digital evolution system Avida, a complete analysis of the local fitness landscapes of \"fit\" and \"flat\" genotypes has been lacking, leading to uncertainty about the genetic basis of the survival of the flattest effect.\n\nResultsHere, we repeated the survival of the flattest study and analyzed the mutational neighborhoods of fit and flat genotypes. We found that flat genotypes, compared to the fit genotypes, had a reduced likelihood of deleterious mutations as well as an increased likelihood of neutral and, surprisingly, of lethal mutations. This trend holds for mutants one to four substitutions away from the wild-type sequence. We also found that flat genotypes have, on average, no epistasis between mutations, while fit genotypes have, on average, positive epistasis.\n\nConclusionsOur results demonstrate that the genetic causes of mutational robustness on complex fitness landscapes are multifaceted. While the traditional idea of the survival of the flattest effect emphasized the evolution of increased neutrality, others have argued for increased mutational sensitivity in response to strong mutational loads. Our results show that both increased neutrality and increased lethality can lead to the evolution of mutational robustness. Furthermore, strong negative epistasis is not required for mutational sensitivity to lead to mutational robustness. Overall, these results suggest that mutational robustness is achieved by minimizing heritable deleterious variation.

evolutionary biology

Genome size and the extinction of small populations

Although extinction is ubiquitous throughout the history of life, insight into the factors that drive extinction events are often difficult to decipher. Most studies of extinction focus on inferring causal factors from past extinction events, but these studies are constrained by our inability to observe extinction events as they occur. Here, we use digital evolution to avoid these constraints and study \"extinction in action\". We focus on the role of genome size in driving population extinction, as previous work both in comparative genomics and digital evolution has shown a correlation between genome size and extinction. We find that extinctions in small populations are caused by large genome size. This relationship between genome size and extinction is due to two genetic mechanisms that increase a populations lethal mutational burden: large genome size leads to both an increased lethal mutation rate and an increased likelihood of stochastic reproduction errors and non-viability. We further show that this increased lethal mutational burden is directly due to genome expansions, as opposed to subsequent adaptation after genome expansion. These findings suggest that large genome size can enhance the extinction likelihood of small populations and may inform which natural populations are at an increased risk of extinction.

evolutionary biology