Individual Cryptic Scaling Relationships and the Evolution of Animal Form.

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ID: 57195
2019
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Abstract
Artificial selection offers a powerful tool for the exploration of how selection and development shape the evolution of morphological scaling relationships. An emerging approach models the expression and evolution of morphological scaling relationships as a function of variation among individuals in the developmental mechanisms that regulate trait growth. These models posit the existence of genotype-specific morphological scaling relationships that are unseen or 'cryptic'. Within-population allelic variation at growth-regulating loci determines how these individual cryptic scaling relationships are distributed, and exposure to environmental factors that affect growth determines the size phenotype expressed by each individual on their cryptic, genotype-specific scaling relationship. These models reveal that evolution of the intercept and slope of the population-level static allometry is determined, often in counterintuitive ways, largely by the shape of the distribution of these underlying individual-level scaling relationships. Here we review this modeling framework and present the wing-body size individual cryptic scaling relationships from a population of Drosophila melanogaster. To determine how these models might inform interpretation of published work on scaling relationship evolution, we review studies where artificial selection was applied to alter the parameters of population-level static allometries. Finally, motivated by our review, we outline areas in need of empirical work and describe a research program to address these topics; the approach includes describing the distribution of individual cryptic scaling relationships across populations and environments, empirical testing of the model's predictions, and determining the effects of environmental heterogeneity on realized trait distributions and how this affects allometry evolution.
Reference Key
frankino2019individualintegrative Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Frankino, W Anthony;Bakota, Eric;Dworkin, Ian;Wilkinson, Gerald S;Wolf, Jason B;Shingleton, Alexander W;
Journal integrative and comparative biology
Year 2019
DOI
icz135
URL
Keywords
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