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  • Title: Can a Network Approach Resolve How Adaptive vs Nonadaptive Plasticity Impacts Evolutionary Trajectories?
    Author: Fischer EK, Ghalambor CK, Hoke KL.
    Journal: Integr Comp Biol; 2016 Nov; 56(5):877-888. PubMed ID: 27400976.
    Abstract:
    Theoretical and empirical work has described a range of scenarios in which plasticity may shape adaptation to a novel environment. For example, recent studies have implicated a role for both adaptive and non-adaptive plasticity in facilitating adaptive evolution, yet we lack a broad mechanistic framework to predict under what conditions each scenario is likely to dominate evolutionary processes. We propose that such a framework requires understanding how transcriptional, protein, and developmental networks change in response to different rearing environments across evolutionary time scales. Our central argument is that these hierarchical networks generate and maintain phenotypic variation in populations, both by buffering organisms from developmental noise and mutational inputs and by exhibiting flexible responses to environmental cues. These network properties in turn lead to predictions about how plasticity should influence adaptive evolution. Because buffering mechanisms allow the build-up of cryptic genetic variation (i.e., genetic variation without phenotypic consequences), the initial response of individuals colonizing novel environments should be a release of genetic and phenotypic variation that selection acts upon; some of which is adaptive and some of which is not. Thus, in the early stages of adaptation, strong selection against maladaptive phenotypes should result in rapid evolution acting on standing cryptic variation. However, over longer time scales, evolutionary change should largely be compensatory, to rebuild robust developmental processes and promote integrated phenotypes. We argue that considering how hierarchical networks respond over developmental and evolutionary time encompasses a more mechanistic understanding of the genotype-phenotype map, and will result in a more predictive framework for understanding the role of plasticity in adaptive evolution.
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