The evolutionary origin of complex features

Lenski, Richard E.; Ofria, Charles; Pennock, Robert T.; Adami, Christoph

doi:10.1038/nature01568

Cited by 661 publications

(597 citation statements)

References 24 publications

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“…Large samples of such well-characterized beneficial mutations are necessary for identifying the multiple paths available to adaptive evolution, the similarities and differences between the paths and the consequences that each step along a given path entails for subsequent evolution ( Travisano et al 1995a;Lenski et al 2003;Weinreich et al 2006;Ostrowski et al 2007;Poelwijk et al 2007). …”

Section: Discussionmentioning

confidence: 99%

The genetic basis of parallel and divergent phenotypic responses in evolving populations ofEscherichia coli

2007

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Pleiotropy plays a central role in theories of adaptation, but little is known about the distribution of pleiotropic effects associated with different adaptive mutations. Previously, we described the phenotypic effects of a collection of independently arising beneficial mutations in Escherichia coli. We quantified their fitness effects in the glucose environment in which they evolved and their pleiotropic effects in five novel resource environments. Here we use a candidate gene approach to associate the phenotypic effects of the mutations with the underlying genetic changes. Among our collection of 27 adaptive mutants, we identified a total of 21 mutations (18 of which were unique) encompassing five different loci or gene regions. There was limited resolution to distinguish among loci based on their fitness effects in the glucose environment, demonstrating widespread parallelism in the direct response to selection. However, substantial heterogeneity in mutant effects was revealed when we examined their pleiotropic effects on fitness in the five novel environments. Substitutions in the same locus clustered together phenotypically, indicating concordance between molecular and phenotypic measures of divergence.

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Section: Discussionmentioning

confidence: 99%

The genetic basis of parallel and divergent phenotypic responses in evolving populations ofEscherichia coli

2007

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“…In the context of cellular signaling, the evolution of signaling complexity arises from the interactions of the following three features: a plastic information encoding system, competition for limiting resources, and reproduction. 43 In order to reverse engineer the evolutionary steps that created genomic complexity, we will assume that the evolution of cellular signaling systems is likely to have occurred through incremental change; 44 even if numerous changes rapidly occur, the individual changes themselves can still be described as incremental (see Figure 2). This is not to say that drastic evolutionary changes cannot occur within a short time period, 45 but rather that, typically, one would expect a cellular system to coordinate the intracellular environment around events and changes that contribute to an evolutionary fit cell, and such changes are likely to accrue incrementally.…”

Section: Incremental Evolution Of Cellular Systemsmentioning

confidence: 99%

The evolution of signaling complexity suggests a mechanism for reducing the genomic search space in human association studies

et al. 2004

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The size complexity of the human genome has been traditionally viewed as an obstacle that frustrates efforts aimed at identifying the genetic correlates of complex human phenotypes. As such complex phenotypes are attributed to the combined action of numerous genomic loci, attempts to identify the underlying multi-locus interactions may produce a combinatorial sum of false positives that drown out the real signal. Faced with such grim prospects for successfully identifying the genetic basis of complex phenotypes, many geneticists simply disregard epistatic interactions altogether. However, the emerging picture from systems biology is that the cellular programs encoded by the genome utilize nested signaling hierarchies to integrate a number of loosely coupled, semiautonomous, and functionally distinct genetic networks. The current view of these modules is that connections encoding inter-module signaling are relatively sparse, while the gene-to-gene (protein-to-protein) interactions within a particular module are typically denser. We believe that each of these modules is encoded by a finite set of discontinuous, sequence-specific, genomic intervals that are functionally linked to association rules, which correlate directly to features in the environment. Furthermore, because these environmental association rules have evolved incrementally over time, we explore theoretical models of cellular evolution to better understand the role of evolution in genomic complexity. Specifically, we present a conceptual framework for (1) reducing genomic complexity by partitioning the genome into subsets composed of functionally distinct genetic modules and (2) improving the selection of coding region SNPs, which results in an increased probability of identifying functionally relevant SNPs. Additionally, we introduce the notion of 'genomic closure,' which provides a quantitative measure of how functionally insulated a specific genetic module might be from the influence of the rest of the genome. We suggest that the development and use of theoretical models can provide insight into the nature of biological systems and may lead to significant improvements in computational algorithms designed to reduce the complexity of the human genome.

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“…And yet again and again until what has emerged bears little, if any functional resemblance to the original object. Evolution most likely progresses in a similar fashion (Jacob, 1977;Lenski et al, 2003).…”

Section: Introductionmentioning

confidence: 99%

Pheromone-inducible conjugation in Enterococcus faecalis: A model for the evolution of biological complexity?

Kozlowicz

Dworkin

Dunny

2006

International Journal of Medical Microbiology

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Pheromone-inducible transfer of the plasmid pCF10 in Enterococcus faecalis is regulated using a complicated network of proteins and RNAs. The plasmid itself has been assembled from parts garnered from a variety of sources, and many aspects of the system resemble a biological kluge. Recently several new functions of various pCF10 gene products that participate in regulation of plasmid transfer have been identified. The results indicate that selective pressures controlling the evolution of the plasmid have produced a highly complex regulatory network with multiple biological functions that may serve well as a model for the evolution of biological complexity.

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The evolutionary origin of complex features

Cited by 661 publications

References 24 publications

The genetic basis of parallel and divergent phenotypic responses in evolving populations ofEscherichia coli

The genetic basis of parallel and divergent phenotypic responses in evolving populations ofEscherichia coli

The evolution of signaling complexity suggests a mechanism for reducing the genomic search space in human association studies

Pheromone-inducible conjugation in Enterococcus faecalis: A model for the evolution of biological complexity?

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