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A mathematical framework for evo-devo dynamics

View ORCID ProfileMauricio González-Forero
doi: https://doi.org/10.1101/2021.05.17.444499
Mauricio González-Forero
aSchool of Biology, University of St Andrews, Dyers Brae, St Andrews, KY16 9TH, Fife, UK
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  • ORCID record for Mauricio González-Forero
  • For correspondence: mgf3@st-andrews.ac.uk
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Abstract

Natural selection acts on phenotypes constructed over development, which raises the question of how development affects evolution. Classic evolutionary theory indicates that development affects evolution by modulating the genetic covariation upon which selection acts, thus affecting genetic constraints. However, whether genetic constraints are relative, thus diverting adaptation from the direction of steepest fitness ascent, or absolute, thus blocking adaptation in certain directions, remains uncertain. This limits understanding of long-term evolution of developmentally constructed phenotypes. Here we formulate a general tractable mathematical framework that integrates age progression, explicit development (i.e., the construction of the phenotype across life subject to developmental constraints), and evolutionary dynamics, thus describing the evolutionary developmental (evo-devo) dynamics. The framework yields simple equations that can be arranged in a layered structure that we call the evo-devo process, whereby five core elementary components generate all equations including those mechanistically describing genetic covariation and the evo-devo dynamics. The framework recovers evolutionary dynamic equations in gradient form and describes the evolution of genetic covariation from the evolution of genotype, phenotype, environment, and mutational covariation. This shows that genotypic and phenotypic evolution must be followed simultaneously to yield a dynamically sufficient description of long-term phenotypic evolution in gradient form, such that evolution described as the climbing of a fitness landscape occurs in “geno-phenotype” space. Genetic constraints in geno-phenotype space are necessarily absolute because the phenotype is related to the genotype by development. Thus, the long-term evolutionary dynamics of developed phenotypes is strongly non-standard: (1) evolutionary equilibria are either absent or infinite in number and depend on genetic covariation and hence on development; (2) developmental constraints determine the admissible evolutionary path and hence which evolutionary equilibria are admissible; and (3) evolutionary outcomes occur at admissible evolutionary equilibria, which do not generally occur at fitness landscape peaks in geno-phenotype space, but at peaks in the admissible evolutionary path where “total genotypic selection” vanishes if exogenous plastic response vanishes and mutational variation exists in all directions of genotype space. Hence, selection and development jointly define the evolutionary outcomes if absolute mutational constraints and exogenous plastic response are absent, rather than the outcomes being defined only by selection. Moreover, our framework provides formulas for the sensitivities of a recurrence and an alternative method to dynamic optimization (i.e., dynamic programming or optimal control) to identify evolutionary outcomes in models with developmentally dynamic traits. These results show that development has major evolutionary effects.

Highlights

  • We formulate a framework integrating evolutionary and developmental dynamics.

  • We derive equations describing the evolutionary dynamics of traits considering their developmental process.

  • This yields a description of the evo-devo process in terms of closed-form formulas that are simple and insightful, including for genetic covariance matrices.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • This is a major revision improving the interpretation of genetic traits, relationship of the framework to quantitative genetics, connections to previous literature, illustration of how morphological development is incorporated, explanation of socio-devo dynamics phase, and connection to work enabling empirical inference of developmental maps. Previous submissions included Andy Gardner as co-author, but Andy has generously asked not to be co-author as he felt his contributions did not meet his standards for authorship.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted September 07, 2022.
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A mathematical framework for evo-devo dynamics
Mauricio González-Forero
bioRxiv 2021.05.17.444499; doi: https://doi.org/10.1101/2021.05.17.444499
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A mathematical framework for evo-devo dynamics
Mauricio González-Forero
bioRxiv 2021.05.17.444499; doi: https://doi.org/10.1101/2021.05.17.444499

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