Deciphering Hybrid Larch Reaction Norms Using Random Regression

• Main Authors: Alexandre Marchal, Carl D. Schlichting, Rémy Gobin, Philippe Balandier, Frédéric Millier, Facundo Muñoz, Luc E. Pâques, Leopoldo Sánchez
• Format: Article
• Language: English
• Published: Oxford University Press 2019-01-01
• Series: G3: Genes, Genomes, Genetics
• Subjects: phenotypic plasticity heterosis tree rings traits soil water availability multi-trait model
• Online Access: http://g3journal.org/lookup/doi/10.1534/g3.118.200697

The link between phenotypic plasticity and heterosis is a broad fundamental question, with stakes in breeding. We report a case-study evaluating temporal series of wood ring traits of hybrid larch (Larix decidua × L. kaempferi and reciprocal) in relation to soil water availability. Growth rings record the tree plastic responses to past environmental conditions, and we used random regressions to estimate the reaction norms of ring width and wood density with respect to water availability. We investigated the role of phenotypic plasticity on the construction of hybrid larch heterosis and on the expression of its quantitative genetic parameters. The data came from an intra-/interspecific diallel mating design between both parental species. Progenies were grown in two environmentally contrasted sites, in France. Ring width plasticity with respect to water availability was confirmed, as all three taxa produced narrower rings under the lowest water availability. Hybrid larch appeared to be the most plastic taxon as its superiority over its parental species increased with increasing water availability. Despite the low heritabilities of the investigated traits, we found that the expression of a reliable negative correlation between them was conditional to the water availability environment. Finally, by means of a complementary simulation, we demonstrated that random regression can be applied to model the reaction norms of non-repeated records of phenotypic plasticity bound by a family structure. Random regression is a powerful tool for the modeling of reaction norms in various contexts, especially perennial species.