Survival of the Curviest: Noise-Driven Selection for Synergistic Epistasis

Wilkins, Jon F.; McHale, Peter; Gervin, Joshua; Lander, Arthur D.

doi:10.1371/journal.pgen.1006003

Cited by 5 publications

(8 citation statements)

References 55 publications

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“…Increased severity of deleterious mutations can lead to population-level robustness as purifying selection is more effective against strongly-deleterious mutations. It has also been proposed that increased negative (or synergistic) epistasis can evolve as a mechanism to increase the strength of purifying selection and hence robustness [26,46].…”

Section: Discussionmentioning

confidence: 99%

“…Indeed, the differences in the distribution of fitness effects [17] (that is, the local fitness landscapes) between fit genotypes and flat genotypes have not been explored. While it is generally assumed that mutational robustness evolves due to the evolution of an increased number of neutral mutational neighbors [18,39,41], other authors have argued that increased mutational sensitivity may evolve [3,23,26,32,46]. Additionally, recent work has indicated that populations evolving under strong genetic drift are expected to evolve "drift-robust" genetic architectures, giving rise to genotypes with a decreased likelihood of small-effect deleterious mutations and an increased likelihood of neutral and/or strongly-deleterious mutations [25].…”

Section: Introductionmentioning

confidence: 99%

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

2019

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Populations 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 fitness through the evolution of mutational robustness. In extreme cases, selection for mutational robustness can lead to flat genotypes (with low fitness but high robustness) outcompeting 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. Here, we repeated the survival-of-the-flattest study and analyzed the mutational neighborhoods of fit and flat genotypes. We found that the 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. Our 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 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.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

2019

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“…10 On the other hand, statistical genetic evidence for a contribution of epistasis to phenotypes in higher organisms is scant, and theoretical analyses arrive at disparate conclusions regarding the significance of epistasis in complex traits and disease. 11,12 Why the results conflict is hotly debated. 13 One, uncommonly discussed reason is that the contribution of epistasis could vary with the fitness cost of a phenotype.…”

Section: Introductionmentioning

confidence: 99%

“…13 One, uncommonly discussed reason is that the contribution of epistasis could vary with the fitness cost of a phenotype. 12 Natural selection indisputably eliminates deleterious mutations, but selection may also increase the robustness of pathways to perturbation by shaping genetic interactions and networks. 14 We reasoned that a comparative analysis of the genetic architecture of four CHD phenotypes under the same mutation could illuminate the problem.…”

Section: Introductionmentioning

confidence: 99%

The fitness cost of a congenital heart defect shapes its genetic architecture

Akhirome¹,

Sd²,

Ra³

et al. 2019

Preprint

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Background:In newborns, severe congenital heart defects are rarer than mild ones. The reason why is unknown, but presumably related to a liability threshold that rises with the severity of a defect. Because the same genetic mutation can cause different defects, other variables may contribute to pushing an individual past a defect-specific liability threshold. We consider here how variables in the genetic architecture of a heart defect depend upon its fitness cost, as defined by the likelihood of survival to reproductive age in natural history studies. Methods:We phenotyped ~10,000 Nkx2-5 +/newborn mice, a model of human congenital heart disease, from two inbred strain crosses. Genome-wide association analyses detected loci that modify the risk of an atrial septal defect, membranous or muscular ventricular septal defect, or atrioventricular septal defect. The number of loci, heritability and quantitative effects on risk of pairwise (G×GNkx) and higher-order (G×G×GNkx) epistasis between the loci and Nkx2-5 mutation were examined as a function of the fitness cost of a defect.Results: Nkx2-5 +/mice have pleiotropic heart defects; about 70% have normal hearts. The model recapitulates the epidemiological relationship between the severity and incidence of a heart defect. Neither the number of modifier loci nor heritability depends upon the severity of a defect, but G×GNkx and G×G×GNkx effects on risk do. Interestingly, G×G×GNkx effects are three times more likely to suppress risk when the genotypes at the first two loci are homozygous and from the same, rather than opposite strains in a cross. Syn-and anti-homozygous genotypes at G×G×GNkx interactions can have an especially large impact on the risk of an atrioventricular septal defect. Conclusions:Given a modestly penetrant mutation, epistasis contributes more to the risk of severe than mild congenital heart defect. Conversely, genetic compatibility between interacting

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Section: Introductionmentioning

confidence: 99%

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

Franklin

LaBar

Adami

2018

Preprint

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Background Populations 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.

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Survival of the Curviest: Noise-Driven Selection for Synergistic Epistasis

Cited by 5 publications

References 55 publications

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

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

The fitness cost of a congenital heart defect shapes its genetic architecture

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

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