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Genomic Selection (GS) in tree breeding optimizes genetic gains by leveraging genomic data to enable early selection of seedlings without phenotypic data reducing breeding cycle and increasing selection intensity. Traditional assessments of the potential of GS in forest trees have typically focused on model performance using cross-validation within the same generation but evaluating effectively realized predictive ability (RPA) across generations is crucial. This study estimated RPAs for volume growth (VOL), wood density (WD), and pulp yield (PY) across four generations breeding of Eucalyptus grandis. The training set spanned three generations, including 34,461 trees with three-year growth data, 6,014 trees with wood quality trait data, and 1,918 trees with 12,695 SNPs (single nucleotide polymorphisms) data. Employing single-step genomic BLUP, we compared the genomic predictions of breeding values (GEBVs) for 1,153 fourth-generation full-sib seedlings in the greenhouse with their later-collected phenotypic estimated breeding values (EBVs) at age three years. RPAs were estimated using three GS targets (individual trees, trees within families, and families), two selection criteria (single- and multiple-trait), and training populations of either all 1,918 genotyped trees or the 67 direct ancestors of the selection candidates. RPAs were higher for wood quality traits (0.33 to 0.59) compared to VOL (0.14 to 0.19) and improved for wood traits (0.42 to 0.75) but not for VOL when trained only with direct ancestors, highlighting the challenges in accurately predicting growth traits. GS was more effective at excluding bottom-ranked candidates than selecting top-ranked ones. The between-family GS approach outperformed individual-tree selection for VOL (0.11 to 0.16) and PY (0.72 to 0.75), but not for WD (0.43 vs. 0.42). Furthermore, higher levels of relatedness and lower genotype by environment (G × E) interaction between training and testing populations enhanced RPAs for VOL (0.39). In summary, despite limited effectiveness in ranking top VOL individuals, GS effectively identified low-performing individuals and families. These multi-generational findings underscore GS's potential in tree breeding, stressing the importance of considering relatedness and G × E interaction for optimal performance. [ABSTRACT FROM AUTHOR]

Eastern cottonwood (Populus deltoides Bartr. ex Marsh.) is an important forest tree, with elite genotypes propagated mainly as unrooted dormant cuttings. Several areas where P. deltoides is planted periodically experience flooding episodes. The aims of this work were to analyze the early rooting capability and flooding tolerance of a P. deltoides full-sib family, and to identify growth, wood, and leaf traits that correlate with flooding tolerance. We analyzed the early rooting capability of the parental genotypes and 30 clones from the [F.sub.1] generation under greenhouse conditions. The rooting percentage of the cuttings ranged from 50% to 100%. There was a positive genetic correlation between shoot weight and root traits (number, biomass, and total length). In a separate experiment, 2-month-old plants growing in pots from the same genotypes were subjected to two treatments: watering (control) and flooding for 35 days. Most genotypes showed an intermediate flooding tolerance with respect to the parental clones. Height, diameter, growth rate, biomass, plant leaf area, leaf number, and leaf increase rate had a positive phenotypic correlation with flooding tolerance, while wood density did not. Height and diameter are traits recommended for selection because they correlate with flooding tolerance, are easy to measure, and have moderate to high narrow sense heritability. Key words: eastern cottonwood, greenhouse cuttings, early rooting, narrow sense heritability, genetic correlation. Peuplier delto'ide (Populus deltoides Bart. ex Marsh.) est une essence forestiere importante dont les genotypes elites sont propages sous forme de boutures dormantes non racinees. Plusieurs regions ou P. deltoides est plante sont sujettes aux inondations. Les objectifs de cette etude consistaient a analyser la capacite d'enracinement precoce et la tolerance aux inondations d'une fratrie de P. deltoides et a identifier les caracteres de croissance, du bois et des feuilles qui sont correles avec la tolerance aux inondations. Nous avons analyse la capacite d'enracinement precoce des genotypes parentaux et de 30 clones de la generation [F.sub.1] en serre. Le pourcentage d'enracinement des boutures variait de 50% a 100%. Il y avait une correlation genetique positive entre le poids des pousses et les caracteres des racines (nombre, biomasse et longueur totale). Dans une experience distincte, des plants ages de deux mois croissant en pot et issus des memes genotypes ont ete soumis a deux traitements: arroses (temoins) ou inondes pendant 35 jours. La plupart des genotypes ont montre une tolerance intermediaire aux inondations relativement aux clones parentaux. La hauteur, le diametre, le taux de croissance, la biomasse, la surface foliaire des plants, le nombre de feuilles et le taux d'accroissement des feuilles avaient une correlation phenotypique positive avec la tolerance aux inondations tandis que ce n'etait pas le cas de la densite du bois. On recommande d'utiliser les caracteres de hauteur et de diametre pour la selection parce qu'ils sont correles a la tolerance aux inondations, sont faciles a mesurer et ont une heritabilite au sens strict qui varie de moderee a elevee. [Traduit par la Redaction] Mots-cles: peuplier delto'ide, boutures cultivees en serre, enracinement precoce, heritabilite au sens strict, correlation genetique., Introduction Eastern cottonwood (Populus deltoides Bart. ex Marsh.) is widely cultivated either as a pure species or as selected parents of interspecific hybrids in temperate regions worldwide because of its [...]

Unaccounted for spatial variability leads to bias in estimating genetic parameters and predicting breeding values from forest genetic trials. Previous attempts to account for large-scale continuous spatial variation employed spatial coordinates in the direction of the rows (or columns). In this research, we use an individual-tree mixed model and the tensor product of B-spline bases with a proper covariance structure for the random knot effects to account for spatial variability. Dispersion parameters were estimated using Bayesian techniques via Gibbs sampling. The procedure is illustrated with data from a progeny trial of Eucalyptus globulus subsp. globulus Labill. Four different models were used in the sequel. The first model included block effects and the three other models included a surface on a grid of either 8 * 8, 12 x 12, or 18 * 18 knots. The three models with B-splines displayed a sizeable lower value of the deviance information criterion than the model with blocks. Also, the mixed models fitting a surface displayed a consistent reduction in the posterior mean of [[sigma].sup.2.sub.e], an increase in the posterior means of [[sigma].sup.2.sub.A] and [h.sup.2.sub.DBH], and an increase of 66% (for parents) or 60% (for offspring) in the accuracy of breeding values. Le fait de ne pas tenir compte de la variabilite spatiale engendre des biais dans l'estimation des parametres genetiques et la prediction des valeurs en croisement qui sont faites a partir des tests en genetique forestiere. Les tentatives anterieures pour prendre en compte la variabilite spatiale continue a grande echelle etaient basees sur les coordonnes spatiales dans la direction des rangs (ou colonnes). Dans la presente etude, les auteurs ont employe un modele mixte base sur les valeurs d'arbres individuels et le produit tensoriel de B-splines avec une structure de covariance adequate pour les effets aleatoires de noeuds afin de tenir compte de la variabilite spatiale. Les parametres de dispersion ont ete evalues a l'aide de l'echantillonnage de Gibbs, une methode basee sur les statistiques bayesiennes. L'approche analytique est illustree a l'aide de donnees provenant d'un test de descendances d'Eucalyptus globulus subsp. globulus Labill. Les auteurs ont utilise quatre modeles differents dans la suite d'analyses. Le premier modele incluait des effets de blocs alors que les trois autres modeles impliquaient une surface couchee sur un reseau de 8 * 8, 12 * 12 ou 18 * 18 noeuds. Les trois derniers modeles qui impliquaient des B-splines affichaient une valeur sensiblement plus faible quant au critere d'information sur la deviation comparativement au modele avec les blocs. De plus, les modeles mixtes qui s'ajustaient a une surface demontraient une reduction constante de leur moyenne a posteriori de [[sigma].sup.2.sub.e], une augmentation de leurs moyennes a posteriori de [[sigma].sup.2.sub.A] et de [h.sup.2.sub.DBH], et une augmentation de 66% (pour les parents) et de 60% (pour les descendants) de la precision des valeurs en croisement. [Traduit par la Redaction], Introduction Forest genetic trials are prone to a high degree of environmental heterogeneity as compared with other cultivated plants (Libby and Cockerham 1980): trees are large living organisms and occupy [...]

Abstract: In forest genetics, restricted maximum likelihood (REML) estimation of (co)variance components from normal multiple-trait individual-tree models is affected by the absence of observations in any trait and individual. Missing [...]

Injury from sampling increment cores may induce defense responses in trees, which may vary between species and reflect differing defense allocation strategies against attack by insects and pathogens. We recorded presence of systemic induction of traumatic resin ducts from early-season increment coring in mature white spruce (Picea glauca) and lodgepole pine (Pinus contorta var. latifolia) trees. In the year of coring, traumatic resin ducts formed three months later, 20 cm below the initial coring site in the xylem of white spruce and showed little variation in response among the spruce families. In contrast, lodgepole pine did not form traumatic resin ducts in trees cored earlier in the growing season. Although traumatic resin ducts are induced by biotic and abiotic disturbances, we found a species-specific defense response to increment coring in two common boreal forest tree species. [ABSTRACT FROM AUTHOR]

Genetic parameters for growth, stem straightness, and branch quality were estimated in five progeny trials of Pinus elliottii var. elliottii (PEE) × Pinus caribaea var. hondurensis (PCH) F1 hybrid measured at ages three, five, and seven years. The trials comprised 133 full-sib families from the tree breeding program initiated by the National Institute of Agricultural Technology. Single-site analyses showed that the average individual-tree narrow- and broad-sense heritability estimates were respectively 0.24 and 0.53 for diameter and 0.34 and 0.47 for total height. Average estimated heritabilities were low to moderate for stem straightness (< 0.18), branch diameter (< 0.26), and branch angle (from 0.28 to 0.33). Bivariate analyses showed that the estimated additive and family genetic correlations between diameter and height were consistently high and positive (> 0.84). However, genetic correlations between growth variables and stem straightness, branch diameter, and branch angle were not significant in general. The average estimated additive genetic correlation between sites was high for growth trait and stem straightness (> 0.70), while for branch diameter and angle, the correlations between sites ranged from 0.19 to 0.99. The implications of these results for genetic improvement strategies based on PEE × PCH F1 hybrid in Argentina are discussed. [ABSTRACT FROM AUTHOR]

The promise of association genetics to identify genes or genomic regions controlling complex traits has generated a flurry of interest. Such phenotype-genotype associations could be useful to accelerate tree breeding cycles, increase precision and selection intensity for late expressing, low heritability traits. However, the prospects of association genetics in highly heterozygous undomesticated forest trees can be severely impacted by the presence of cryptic population and pedigree structure. To investigate how to better account for this, we compared the GLM and five combinations of the Unified Mixed Model (UMM) on data of a low-density genome-wide association study for growth and wood property traits carried out in a Eucalyptus globulus population (n = 303) with 7,680 Diversity Array Technology (DArT) markers. Model comparisons were based on the degree of deviation from the uniform distribution and estimates of the mean square differences between the observed and expected p-values of all significant marker-trait associations detected. Our analysis revealed the presence of population and family structure. There was not a single best model for all traits. Striking differences in detection power and accuracy were observed among the different models especially when population structure was not accounted for. The UMM method was the best and produced superior results when compared to GLM for all traits. Following stringent correction for false discoveries, 18 marker-trait associations were detected, 16 for tree diameter growth and two for lignin monomer composition (S∶G ratio), a key wood property trait. The two DArT markers associated with S∶G ratio on chromosome 10, physically map within 1 Mbp of the ferulate 5-hydroxylase (F5H) gene, providing a putative independent validation of this marker-trait association. This study details the merit of collectively integrate population structure and relatedness in association analyses in undomesticated, highly heterozygous forest trees, and provides additional insights into the nature of complex quantitative traits in Eucalyptus. [ABSTRACT FROM AUTHOR]

The promise of association genetics to identify genes or genomic regions controlling complex traits has generated a flurry of interest. Such phenotype-genotype associations could be useful to accelerate tree breeding cycles, increase precision and selection intensity for late expressing, low heritability traits. However, the prospects of association genetics in highly heterozygous undomesticated forest trees can be severely impacted by the presence of cryptic population and pedigree structure. To investigate how to better account for this, we compared the GLM and five combinations of the Unified Mixed Model (UMM) on data of a low-density genome-wide association study for growth and wood property traits carried out in a Eucalyptus globulus population (n = 303) with 7,680 Diversity Array Technology (DArT) markers. Model comparisons were based on the degree of deviation from the uniform distribution and estimates of the mean square differences between the observed and expected p-values of all significant marker-trait associations detected. Our analysis revealed the presence of population and family structure. There was not a single best model for all traits. Striking differences in detection power and accuracy were observed among the different models especially when population structure was not accounted for. The UMM method was the best and produced superior results when compared to GLM for all traits. Following stringent correction for false discoveries, 18 marker-trait associations were detected, 16 for tree diameter growth and two for lignin monomer composition (S∶G ratio), a key wood property trait. The two DArT markers associated with S∶G ratio on chromosome 10, physically map within 1 Mbp of the ferulate 5-hydroxylase (F5H) gene, providing a putative independent validation of this marker-trait association. This study details the merit of collectively integrate population structure and relatedness in association analyses in undomesticated, highly heterozygous forest trees, and provides additional insights into the nature of complex quantitative traits in Eucalyptus. [ABSTRACT FROM AUTHOR]

Maximization of genetic gain in forest tree breeding programs is contingent on the accuracy of the predicted breeding values and precision of the estimated genetic parameters. We investigated the effect of the combined use of contemporary pedigree information and genomic relatedness estimates on the accuracy of predicted breeding values and precision of estimated genetic parameters, as well as rankings of selection candidates, using single-step genomic evaluation (HBLUP). In this study, two traits with diverse heritabilities [tree height (HT) and wood density (WD)] were assessed at various levels of family genotyping efforts (0, 25, 50, 75, and 100%) from a population of white spruce ( Picea glauca ) consisting of 1694 trees from 214 open-pollinated families, representing 43 provenances in Québec, Canada. The results revealed that HBLUP bivariate analysis is effective in reducing the known bias in heritability estimates of open-pollinated populations, as it exposes hidden relatedness, potential pedigree errors, and inbreeding. The addition of genomic information in the analysis considerably improved the accuracy in breeding value estimates by accounting for both Mendelian sampling and historical coancestry that were not captured by the contemporary pedigree alone. Increasing family genotyping efforts were associated with continuous improvement in model fit, precision of genetic parameters, and breeding value accuracy. Yet, improvements were observed even at minimal genotyping effort, indicating that even modest genotyping effort is effective in improving genetic evaluation. The combined utilization of both pedigree and genomic information may be a cost-effective approach to increase the accuracy of breeding values in forest tree breeding programs where shallow pedigrees and large testing populations are the norm., (Copyright © 2017 Ratcliffe et al.)