Coevolution Drives the Emergence of Complex Traits and Promotes Evolvability

Zaman, Luis; Meyer, Justin R.; Devangam, Suhas; Bryson, David M.; Lenski, Richard E.; Ofria, Charles

doi:10.1371/journal.pbio.1002023

Cited by 105 publications

(105 citation statements)

References 33 publications

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“…Avida [32] is currently the most widely used digital evolution system, and is used to study a wide range of evolutionary and ecological dynamics in populations of self-replicating computer programs. Avida has enabled the evolution of qualitatively novel behaviors such as complex features completely absent in the ancestor organism (ongoing generation of new adaptations) [27], novel collaboration strategies among organisms (ongoing growth of complexity of interactions) [16], and novel ecological interactions through coevolution promoting even greater levels of complexity [58]. Dolson and collaborators are actively testing their complexity barriers in this system, as well as analyzing evolutionary activity statistics.…”

Section: Themes From the Open Discussionmentioning

confidence: 99%

Open-Ended Evolution: Perspectives from the OEE Workshop in York

Taylor¹,

Bedau²,

Channon³

et al. 2016

Artificial Life

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104

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We describe the content and outcomes of the First Workshop on Open-Ended Evolution: Recent Progress and Future Milestones (OEE1), held during the ECAL 2015 conference at the University of York, UK, in July 2015. We briefly summarize the content of the workshopʼs talks, and identify the main themes that emerged from the open discussions. Two important conclusions from the discussions are: (1) the idea of pluralism about OEE-it seems clear that there is more than one interesting and important kind of OEE; and (2) the importance of distinguishing observable behavioral hallmarks of systems undergoing OEE from hypothesized underlying mechanisms that explain why a system exhibits those hallmarks. We summarize the different hallmarks and mechanisms discussed during the workshop, and list the specific systems that were highlighted with respect to particular hallmarks and mechanisms. We conclude by identifying some of the most important open research questions about OEE that are apparent in light of the discussions. The York workshop provides a foundation for a follow-up OEE2 workshop taking place at the ALIFE XV conference in Cancún, Mexico, in July 2016. Additional materials from the York workshop, including talk abstracts, presentation slides, and videos of each talk, are available at http://alife.org/ws/oee1.

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Section: Themes From the Open Discussionmentioning

confidence: 99%

Open-Ended Evolution: Perspectives from the OEE Workshop in York

Taylor¹,

Bedau²,

Channon³

et al. 2016

Artificial Life

Self Cite

104

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“…The key attributes of these experiments include an emphasis on hypothesis testing, tracking of phenotypes (and genotypes) across generations, replication, and potential reproducibility. Beyond those fundamental principles, selection experiments encompass a tremendous range of empirical studies with a wide variety of organisms (69), often including microorganisms and even digital "organisms" (221). Replication is crucial to allow strong inferences regarding both direct and correlated responses, because genetic drift can lead to divergence between selected and control lines for reasons unrelated to functional relationships or pleiotropic gene action (130).…”

Section: Insights Into Evolutionary Pattern and Processmentioning

confidence: 99%

Genetic approaches in comparative and evolutionary physiology

Storz

Bridgham

Kelly

et al. 2015

American Journal of Physiology-Regulatory, Integrative and Comp

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Whole animal physiological performance is highly polygenic and highly plastic, and the same is generally true for the many subordinate traits that underlie performance capacities. Quantitative genetics, therefore, provides an appropriate framework for the analysis of physiological phenotypes and can be used to infer the microevolutionary processes that have shaped patterns of trait variation within and among species. In cases where specific genes are known to contribute to variation in physiological traits, analyses of intraspecific polymorphism and interspecific divergence can reveal molecular mechanisms of functional evolution and can provide insights into the possible adaptive significance of observed sequence changes. In this review, we explain how the tools and theory of quantitative genetics, population genetics, and molecular evolution can inform our understanding of mechanism and process in physiological evolution. For example, lab-based studies of polygenic inheritance can be integrated with field-based studies of trait variation and survivorship to measure selection in the wild, thereby providing direct insights into the adaptive significance of physiological variation. Analyses of quantitative genetic variation in selection experiments can be used to probe interrelationships among traits and the genetic basis of physiological trade-offs and constraints. We review approaches for characterizing the genetic architecture of physiological traits, including linkage mapping and association mapping, and systems approaches for dissecting intermediary steps in the chain of causation between genotype and phenotype. We also discuss the promise and limitations of population genomic approaches for inferring adaptation at specific loci. We end by highlighting the role of organismal physiology in the functional synthesis of evolutionary biology.

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“…The antagonistic nature of host-parasite interactions leads to reciprocal selection of the antagonists on each other that can drive rapid coevolutionary change [1–3]. Hosts are expected to evolve mechanisms to reduce the likelihood of infection and to minimize the fitness costs associated with infections, while parasites are expected to evolve mechanisms to evade the hosts’ defense mechanisms.…”

Section: Introductionmentioning

confidence: 99%

The genetic basis of resistance and matching-allele interactions of a host-parasite system: The Daphnia magna-Pasteuria ramosa model

et al. 2017

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Negative frequency-dependent selection (NFDS) is an evolutionary mechanism suggested to govern host-parasite coevolution and the maintenance of genetic diversity at host resistance loci, such as the vertebrate MHC and R-genes in plants. Matching-allele interactions of hosts and parasites that prevent the emergence of host and parasite genotypes that are universally resistant and infective are a genetic mechanism predicted to underpin NFDS. The underlying genetics of matching-allele interactions are unknown even in host-parasite systems with empirical support for coevolution by NFDS, as is the case for the planktonic crustacean Daphnia magna and the bacterial pathogen Pasteuria ramosa. We fine-map one locus associated with D. magna resistance to P. ramosa and genetically characterize two haplotypes of the Pasteuria resistance (PR-) locus using de novo genome and transcriptome sequencing. Sequence comparison of PR-locus haplotypes finds dramatic structural polymorphisms between PR-locus haplotypes including a large portion of each haplotype being composed of non-homologous sequences resulting in haplotypes differing in size by 66 kb. The high divergence of PR-locus haplotypes suggest a history of multiple, diverse and repeated instances of structural mutation events and restricted recombination. Annotation of the haplotypes reveals striking differences in gene content. In particular, a group of glycosyltransferase genes that is present in the susceptible but absent in the resistant haplotype. Moreover, in natural populations, we find that the PR-locus polymorphism is associated with variation in resistance to different P. ramosa genotypes, pointing to the PR-locus polymorphism as being responsible for the matching-allele interactions that have been previously described for this system. Our results conclusively identify a genetic basis for the matching-allele interaction observed in a coevolving host-parasite system and provide a first insight into its molecular basis.

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Coevolution Drives the Emergence of Complex Traits and Promotes Evolvability

Abstract: Experiments using a digital host-parasite model system show that coevolution can drive the emergence of complex traits and more evolvable genomes. Homepage Title: Parasitism Drives the Evolution of Complexity

Cited by 105 publications

References 33 publications

Open-Ended Evolution: Perspectives from the OEE Workshop in York

Open-Ended Evolution: Perspectives from the OEE Workshop in York

Genetic approaches in comparative and evolutionary physiology

The genetic basis of resistance and matching-allele interactions of a host-parasite system: The Daphnia magna-Pasteuria ramosa model

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