The evolutionary origin of complex

Department of Microbiology & Molecular Genetics, Michigan State University, East Lansing, Michigan 48824, USA.
Nature (Impact Factor: 42.35). 06/2003; 423(6936):139-44. DOI: 10.1038/nature01568
Source: PubMed

ABSTRACT A long-standing challenge to evolutionary theory has been whether it can explain the origin of complex organismal features. We examined this issue using digital organisms--computer programs that self-replicate, mutate, compete and evolve. Populations of digital organisms often evolved the ability to perform complex logic functions requiring the coordinated execution of many genomic instructions. Complex functions evolved by building on simpler functions that had evolved earlier, provided that these were also selectively favoured. However, no particular intermediate stage was essential for evolving complex functions. The first genotypes able to perform complex functions differed from their non-performing parents by only one or two mutations, but differed from the ancestor by many mutations that were also crucial to the new functions. In some cases, mutations that were deleterious when they appeared served as stepping-stones in the evolution of complex features. These findings show how complex functions can originate by random mutation and natural selection.

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    • "Fitness can be estimated by the ratio of necessary energy for an organism to execute the instructions in its genome and the required number of instructions to produce an offspring (Adami, 1998; Elena et al., 2007), but the realized fitness depends on the organism's interaction with others and the vagaries of chance. The mandatory energy for reproduction is provided to a digital organism in the form of discrete quanta, called " Single- Instruction Processing " units, or SIPs (Lenski et al., 2003; Adami, 2006; Elena et al., 2007). The rate at which an organism acquires energy depends on its genome length and a coefficient which is related to the interactions between the organism's computational metabolism and its environment. "
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    ABSTRACT: There is little doubt in scientific circles that--counting from the origin of life towards today--evolution has led to an increase in the amount of information stored within the genomes of the biosphere. This trend of increasing information on average likely holds for every successful line of descent, but it is not clear whether this increase is due to a general law, or whether it is a secondary effect linked to an overall increase in fitness. Here, we use "digital life" evolution experiments to study whether information is under selection if treated as an organismal trait, using the Price equation. By measuring both sides of the equation individually in an adapting population, the strength of selection on a trait appears as a "gap" between the two terms of the right-hand-side of the Price equation. We find that information is strongly selected (as it encodes all fitness-producing traits) by comparing the strength of selection on information to a weakly selected trait (sequence length), as well as to a neutral marker. We observe that while strength of selection on arbitrary traits can vary during an experiment (including reversing sign), information is a selectable trait that must increase in a fixed environment.
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    • "To explore questions surrounding the evolution of kin inclusivity levels, we use the Avida digital evolution platform [17], which has been used previously to study the properties of evolving systems (e.g., [10] and [16]). Within Avida, digital organisms, which are computer programs that selfreplicate and potentially incur mutations, compete with neighboring organisms for resources, including space. "
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    GECCO 2014, Vancouver, BC, Canada; 07/2014
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    • " of biological systems (Lenski et al., 2003; Gompel et al., 2005; Capra et al., 2012; Finnigan et al., 2012). Metabolism is a defining property of cellular life, often depicted as a complex network of chemical transformations mediated by a multitude of enzymes (Weng & Noel, 2012b). "
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    ABSTRACT: As sessile organisms, land plants have exploited their metabolic systems to produce a panoply of structurally and functionally diverse natural chemicals and polymers to adapt to challenging ecosystems. Many of these core and specialized metabolites confer chemical shields against a multitude of abiotic stresses, while others play important roles in plants' interactions with their biotic environments. Plant specialized metabolites can be viewed as complex traits in the sense that the biosynthesis of these molecules typically requires multistep metabolic pathways comprising numerous specific enzymes belonging to diverse protein fold families. Resolving the evolutionary trajectories underlying the emergence of these specialized metabolic pathways will impact a fundamental question in biology - how do complex traits evolve in a Darwinian fashion? Here, I discuss several general patterns observed in rapidly evolving specialized metabolic systems in plants, and surmise mechanistic features at enzyme, pathway and organismal levels that rationalize the remarkable malleability of these systems through stepwise evolution. Future studies, focused on fine sampling of metabolic enzymes and pathways in phylogenetically related plant species, or employing directed evolution strategies in synthetic systems, will significantly broaden our perspective on how biological complexity arises at the metabolic level.
    New Phytologist 07/2013; 201(4). DOI:10.1111/nph.12416 · 6.55 Impact Factor
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