Partitioning the phenotypic and genetic variances of reaction normsuse asterix (*) to get italics

Pierre de Villemereuil, Luis-Miguel ChevinPlease use the format "First name initials family name" as in "Marie S. Curie, Niels H. D. Bohr, Albert Einstein, John R. R. Tolkien, Donna T. Strickland"

2025

<p>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.</p> <p>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.</p> <p>Overall the toolbox we develop should serve as a basis for an 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.</p>

https://github.com/devillemereuil/CodePartReacNormYou should fill this box only if you chose 'Scripts were used to obtain or analyze the results'. URL must start with http:// or https://

https://github.com/devillemereuil/ReacnormYou should fill this box only if you chose 'Codes have been used in this study'. URL must start with http:// or https://

phenotypic plasticity, quantitative genetics, character-state approach, polynomial approach, non-linear modelling

NonePlease indicate the methods that may require specialised expertise during the peer review process (use a comma to separate various required expertises).

Evolutionary Ecology, Phenotypic Plasticity, Quantitative Genetics

Jarrod Hadfield j.hadfield@ed.ac.uk, Sam Scheiner sscheine@nsf.gov, Carla Sgrò carla.sgro@monash.edu, Bart Haegeman suggested: Thomas Haaland thomas.r.haaland@ntnu.no, Frank Pennekamp suggested: Thibaut Morel-Journel, Frank Pennekamp suggested: Michael Morrisey

e.g. John Doe john@doe.com

No need for them to be recommenders of PCIEvolBiol. Please do not suggest reviewers for whom there might be a conflict of interest. Reviewers are not allowed to review preprints written by close colleagues (with whom they have published in the last four years, with whom they have received joint funding in the last four years, or with whom they are currently writing a manuscript, or submitting a grant proposal), or by family members, friends, or anyone for whom bias might affect the nature of the review - see the code of conduct

2023-09-01 16:42:45

Staffan Jacob