The Ascent of the Abundant: How Mutational Networks Constrain Evolution

Cowperthwaite, Matthew C.; Economo, Evan P.; Harcombe, William R.; Miller, Eric L.; Meyers, Lauren Ancel

doi:10.1371/journal.pcbi.1000110

Cited by 99 publications

(152 citation statements)

References 38 publications

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“…In contrast, when mutational biases were taken into account (E 2 ), the relationship between evolvability and robustness was nonlinear, with phenotypes of intermediate robustness exhibiting the lowest evolvabilities. These results contrast with those made in RNA systems where E 1 was found to be positively correlated [11], and E 2 negatively correlated, with robustness [20]. However, accessibility and robustness were positively correlated (Fig.…”

Section: Discussioncontrasting

confidence: 69%

“…The first E 1 is simply the proportion of the total number of phenotypes that can be reached via non-neutral point mutations from a given phenotype [11]. The second E 2 provides a more nuanced analysis of the potential to mutate from one phenotype to another [20]. Letting…”

Section: Robustness Evolvability and Accessibilitymentioning

confidence: 99%

“…It takes on low values when a phenotype is adjacent to only a few other phenotypes and its non-neutral mutations are biased toward a subset of these phenotypes. In addition to measuring the propensity to mutate away from a phenotype, we also measure phenotypic accessibility [20], which is formally defined as…”

Section: Robustness Evolvability and Accessibilitymentioning

confidence: 99%

“…By capitalizing on recent developments in the characterization of robustness and evolvability in RNA [11,20], we provide a comprehensive quantitative analysis of the genotype and phenotype spaces in this LGP system. Using a large ensemble of random walks, we then conduct a preliminary exploration of the relationships between robustness, evolvability, and mutation-based search.…”

Section: Introductionmentioning

confidence: 99%

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Robustness, Evolvability, and Accessibility in Linear Genetic Programming

Payne

Banzhaf

et al. 2011

Lecture Notes in Computer Science

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Abstract. Whether neutrality has positive or negative effects on evolutionary search is a contentious topic, with reported experimental results supporting both sides of the debate. Most existing studies use performance statistics, e.g., success rate or search efficiency, to investigate if neutrality, either embedded or artificially added, can benefit an evolutionary algorithm. Here, we argue that understanding the influence of neutrality on evolutionary optimization requires an understanding of the interplay between robustness and evolvability at the genotypic and phenotypic scales. As a concrete example, we consider a simple linear genetic programming system that is amenable to exhaustive enumeration, and allows for the full characterization of these properties. We adopt statistical measurements from RNA systems to quantify robustness and evolvability at both genotypic and phenotypic levels. Using an ensemble of random walks, we demonstrate that the benefit of neutrality crucially depends upon its phenotypic distribution.

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Section: Discussioncontrasting

confidence: 69%

Section: Robustness Evolvability and Accessibilitymentioning

confidence: 99%

Section: Robustness Evolvability and Accessibilitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Robustness, Evolvability, and Accessibility in Linear Genetic Programming

Payne

Banzhaf

et al. 2011

Lecture Notes in Computer Science

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“…Although examples of exaptations occur from the macroscopic to the molecular scale 1-6 and abound also in human evolution 7 , no number of examples could answer how important exaptations are in the origin of adaptations in general. This limitation of case studies can be overcome in those biological systems where one can systematically study many genotypes and the phenotypes they form [8][9][10][11][12] .…”

mentioning

confidence: 99%

A latent capacity for evolutionary innovation through exaptation in metabolic systems

Barve

Wagner

2013

Nature

135

136

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Some evolutionary innovations may originate non-adaptively as exaptations, or pre-adaptations, which are by-products of other adaptive traits. Examples include feathers, which originated before they were used in flight, and lens crystallins, which are light-refracting proteins that originated as enzymes. The question of how often adaptive traits have non-adaptive origins has profound implications for evolutionary biology, but is difficult to address systematically. Here we consider this issue in metabolism, one of the most ancient biological systems that is central to all life. We analyse a metabolic trait of great adaptive importance: the ability of a metabolic reaction network to synthesize all biomass from a single source of carbon and energy. We use novel computational methods to sample randomly many metabolic networks that can sustain life on any given carbon source but contain an otherwise random set of known biochemical reactions. We show that when we require such networks to be viable on one particular carbon source, they are typically also viable on multiple other carbon sources that were not targets of selection. For example, viability on glucose may entail viability on up to 44 other sole carbon sources. Any one adaptation in these metabolic systems typically entails multiple potential exaptations. Metabolic systems thus contain a latent potential for evolutionary innovations with non-adaptive origins. Our observations suggest that many more metabolic traits may have non-adaptive origins than is appreciated at present. They also challenge our ability to distinguish adaptive from non-adaptive traits. include feathers, which originated before they adopted a role in flight 2 , and lens crystallins, light-refracting proteins that originated as enzymes 6 . The incidence of non-adaptive trait origins has profound implications for evolutionary biology, but it has thus far not been possible to study this incidence systematically. We here study it in metabolism, one of the most ancient biological systems that is central to all life. We analyse metabolic traits of great adaptive importance, the ability of a metabolic reaction network to synthesize all biomass from a single (sole) source of carbon and energy. We take advantage of novel computational methods to randomly sample many metabolic networks that can sustain life on any given carbon source, but that contain an otherwise random set of known biochemical reactions. We show that such random networks, required to be viable on one carbon source C, are typically also viable on multiple other carbon sources C new that were not targets of selection. For example, viability on glucose may entail viability on up to 44 other sole carbon sources. Any one adaptation in these metabolic systems typically entails multiple potential exaptations.Metabolic systems thus contain a latent potential for evolutionary innovations with non-adaptive origins. Our observations suggest that many more metabolic traits than currently appreciated may have non-adaptive origins. T...

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Emergence of ATP‐ and GTP‐Binding Aptamers from Single RNA Sequences by Error‐Prone Replication and Selection**

et al. 2023

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The spontaneous emergence of function from diverse RNA sequence pools is widely considered an important transition in the origin of life. Here we show that diverse sequence pools are not a prerequisite for the emergence of function. Starting five independent selection experiments each from a single RNA seed sequence ‐ comprising a central homopolymeric poly‐A (or poly‐U) segment flanked by different conserved primer binding sites ‐ we observe transformation (continuous drift) of the seeds into low diversity sequence pools by mutation, truncation and recombination without ever reaching that of a random pool even after 24 rounds. Upon continuous error prone replication and selection for ATP binding we isolate specific ATP‐ or GTP‐binding aptamers with low micromolar affinities. Our results have implications for early RNA evolution in the light of the high mutation rates associated with both non‐enzymatic and enzymatic prebiotic RNA replication.

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The Ascent of the Abundant: How Mutational Networks Constrain Evolution

Cited by 99 publications

References 38 publications

Robustness, Evolvability, and Accessibility in Linear Genetic Programming

Robustness, Evolvability, and Accessibility in Linear Genetic Programming

A latent capacity for evolutionary innovation through exaptation in metabolic systems

Emergence of ATP‐ and GTP‐Binding Aptamers from Single RNA Sequences by Error‐Prone Replication and Selection**

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