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 markerbased 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.

No abstract

To study the genetic determinism of propagation by cutting, 2,115 individuals of 83 full-sib families of the Eucalyptus urophylla×Eucalyptus grandis hybrid were used as stock plants and propagated by cuttings. Shoot production (PROD) and cutting success (CUT) were measured in two periods corresponding to the dry and rainy seasons. The experiments showed a significant effect of propagation period, suggesting the combined influence of environmental conditions and physiological state of stock plants. Using the linear mixed model (LMM) and the generalized one (GLMM) to take into account the non-normal distribution, the additive and dominance variances were estimated. They were significantly different from zero for PROD and CUT, as was the interaction between genetic effects and periods. The dominance variance was equal or higher than additive variance for both traits (1 < σ 2 D /σ 2 A < 1.5). Broad-and narrow-sense heritabilities change with the model type. For PROD, with LMM, they were moderate (h 2 ss =0.182 and H 2 sl =0.443) but high with GLMM (h 2 ss =0.431 and H 2 sl =0.891). For CUT, the same trend was observed for variances but the genetic control was weaker with heritabilities smaller than 0.3. The selection accuracy (r) was affected by the statistical model, r=0.94 and r=0.42 for PROD using LMM and GLMM, respectively. Genetic correlations between PROD, CUT, and the field growth of clones at 25 months were relatively low. These results are important elements to consider for breeding strategies that target genetic gain for both field growth and cutting success.

No abstract

To assess the genetic and environmental components of gene-expression variation among trees we used RNA-seq technology and Eucalyptus urophylla x grandis hybrid clones tested in field conditions. Leaf and xylem transcriptomes of three 20 month old clones differing in terms of growth, repeated in two blocks, were investigated. Transcriptomes were very similar between ramets. The number of expressed genes was significantly (P<0.05) higher in leaf (25,665±634) than in xylem (23,637±1,241). A pairwise clone comparisons approach showed that 4.5 to 14 % of the genes were diffe­rentially expressed (false discovery rate [FDR]<0.05) in leaf and 7.1 to 16 % in xylem. An assessment of among clone variance components revealed significant results in leaf and xylem in 3431 (248) genes (at FDR<0.2) and 160 (3) (at FDR<0.05), respectively. These two complementary approa­ches displayed correlated results. A focus on the phenylpro­panoid, cellulose and xylan pathways revealed a large majo­rity of low expressed genes and a few highly expressed ones, with RPKM values ranging from nearly 0 to 600 in leaf and 10,000 in xylem. Out of the 115 genes of these pathways, 45 showed differential expression for at least one pair of geno­type, five of which displaying also clone variance compo­nents. These preliminary results are promising in evaluating whether gene expression can serve as possible ‘intermediate phenotypes’ that could improve the accuracy of selection of grossly observable traits.

No abstract