Preponderance of additive and non-additive variances for growth, ecophysiological and wood traits in Eucalyptus hybrid genotype-by-spacing interaction

International audienceThe objective of this study was to better understand the underlying gene action in eucalyptus, under different plantation densities, for a different set of traits: growth, bark thickness, ecophysiological, and wood chemical property traits. We estimated the magnitude and relative proportion of the various genetic variance components using a eucalyptus genotype by spacing (G x S) interaction experiment. A clonally replicated progeny test including 888 clones belonging to 64 full-sib families of Eucalyptus urophylla x Eucalyptus grandis hybrid was used to estimate genetic parameters using genomic information to assess relationship matrix. Two densities (833 and 2500 trees/ha) were used representing contrasted environments in terms of individual tree available resource. Results showed that for height and circumference, additive-by-spacing (A x S) interaction variance increased from 18 to 55 months old, while dominance-by-spacing (D x S) interaction variance decreased. For bark thickness, specific leaf area, nitrogen, calcium, and magnesium, A x S interaction variance was preponderant. For wood chemical properties, except with Klason lignin, genetic additive effects strongly interacted with spacing compared to non-additive effects

Data from: Modeling additive and non-additive effects in a hybrid population using genome-wide genotyping: prediction accuracy implications

Hybrids are broadly used in plant breeding and accurate estimation of variance components is crucial for optimizing genetic gain. Genome-wide information may be used to explore models designed to assess the extent of additive and non-additive variance and test their prediction accuracy for the genomic selection. Ten linear mixed models, involving pedigree- and marker-based relationship matrices among parents, were developed to estimate additive (A), dominance (D) and epistatic (AA, AD and DD) effects. Five complementary models, involving the gametic phase to estimate marker-based relationships among hybrid progenies, were developed to assess the same effects. The models were compared using tree height and 3303 single-nucleotide polymorphism markers from 1130 cloned individuals obtained via controlled crosses of 13 Eucalyptus urophylla females with 9 Eucalyptus grandis males. Akaike information criterion (AIC), variance ratios, asymptotic correlation matrices of estimates, goodness-of-fit, prediction accuracy and mean square error (MSE) were used for the comparisons. The variance components and variance ratios differed according to the model. Models with a parent marker-based relationship matrix performed better than those that were pedigree-based, that is, an absence of singularities, lower AIC, higher goodness-of-fit and accuracy and smaller MSE. However, AD and DD variances were estimated with high s.es. Using the same criteria, progeny gametic phase-based models performed better in fitting the observations and predicting genetic values. However, DD variance could not be separated from the dominance variance and null estimates were obtained for AA and AD effects. This study highlighted the advantages of progeny models using genome-wide information

HDY-15-OR0111R_phenotypic_data

experimental data containing informations related to the variables : FAMILLEFEMALEMALEICclonealphaBLOCZONEXYPLOTINDHT3

HDY-15_OR0111R_genotypes

molecular data: tables with row corresponding to male, female and progenies (clones) and columns corresponding to allele dose (0, 1, 2