Partitioning the phenotypic and genetic variances of reaction norms

  1. Pierre de Villemereuil
  2. Luis-Miguel Chevin

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Abstract

Many traits show plastic phenotypic variation across environments, captured by their norms of reaction. These reaction norms may be discrete or continuous, and can substantially vary in shape across organisms and traits, making it difficult to compare amounts and types of plasticity among (or even within) studies. In addition, the evolutionary potential of phenotypic traits and their plasticity in heterogeneous environments critically depends on how reaction norms vary genetically, but there is no consensus on how this should be quantified. Here, we propose a partitioning of phenotypic variance across genotypes and environments that jointly address these challenges. We start by distinguishing the components of phenotypic variance arising from the average reaction norm across genotypes, genetic variation in reaction norms (with additive and non-additive components), and a residual that cannot be predicted from the genotype and the environment. We then further partition the genetic variance of the trait (additive or not) into an environment-blind component and a component arising from genetic variance in plasticity. We show that the additive components can be expressed, and further decomposed according to the relative contributions from each parameter, using what we describe as the reaction norm gradient. This allows for a very general framework applicable from the character-state to curve-parameter approaches, including polynomial functions, or arbitrary non-linear models. To facilitate the use of this variance decomposition, we provide the Reacnorm R package, including a practical tutorial. Overall the toolbox we develop should serve as a basis for a unifying and deeper understanding of the variation and genetics of reaction norms and plasticity, as well as more robust comparative studies of plasticity across organisms and traits.

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  1. Version published to 10.24072/pcjournal.515
  2. Peer Community in Evolutionary Biology

    Phenotypic plasticity can lead to rapid and important changes of trait distributions depending on environmental conditions, with important consequences for population dynamics, species interactions and adaptation. To better understand the evolution and importance of plasticity, we need to improve our ability to quantify and compare phenotypic plasticity among organisms, and estimate the evolutionary potential of plastic capacity. Plasticity is classically quantified through regression slopes, with units of traits per environment that by definition vary across organisms, traits and studies, and makes complex the comparison of how does plasticity vary across biological units, especially when linear versus quadratic reaction norms are considered. A clear methodology to quantify phenotypic plasticity in a way that allow for comparison across traits, organisms and environments is lacking.

    In this contribution, Pierre de Villemereuil and Luis-Miguel Chevin clarify key concepts about variability and evolutionary potential of plasticity, and propose an efficient method to partition phenotypic variance between genotype and environment. Expanding from the classical (too) simple regression slope approach, and directly integrating the genetic variability of plasticity, they provide a clear framework to quantify the part of phenotypic variance resulting from phenotypic plasticity, integrate the role of the shape of reaction norms, and estimate the heritable variation of trait plasticity. They integrate this method in a R package named Reacnorm, with step by step decision tree, that should greatly help the applicability of this framework.

    The authors here propose a contribution that simultaneously clarify key concepts and challenges about plasticity and reaction norms, being very interesting on the theoretical side, and is directly and quite simply applicable to any trait and organism. This should help and stimulate comparative studies of how does plasticity vary across traits, organisms and environmental contexts, both using already published datasets and through new experiments.

    References

    Pierre de Villemereuil, Luis-Miguel Chevin (2025) Partitioning the phenotypic and genetic variances of reaction norms. EcoEvorxiv, ver.4 peer-reviewed and recommended by PCI Evol Biol https://doi.org/10.32942/X2NC8B

  3. Version published to 10.32942/x2nc8b