Genotype by environment interactions in forest tree breeding: review of methodology and perspectives on research and application

Genotype by environment interaction (G×E) refers to the comparative performances of genotypes differing among environments, representing differences in genotype rankings or differences in the level of expression of genetic differences among environments. G×E can reduce heritability and overall genetic gain, unless breeding programmes are structured to address different categories of environments. Understanding the impact of G×E, the role of environments in generating G×E and the problems and opportunities is vital to efficient breeding programme design and deployment of genetic material. We review the current main analytical methods for identifying G×E: factor analytic models, biplot analysis and reaction norm. We also review biological and statistical evidence of G×E for growth, form and wood properties in forest species of global economic importance, including some pines, eucalypts, Douglas-fir, spruces and some poplars. Among these species, high levels of G×E tend to be reported for growth traits, with low levels of G×E for form traits and wood properties. Finally, we discuss possible ways of exploiting G×E to maximise genetic gain in forest tree breeding. Characterising the role of environments in generating interactions is seen as the basic platform, allowing efficient testing of candidate genotypes. We discuss the importance of level-of-expression interaction, relative to rank-change interaction, as being greater than in many past reports, especially for deployment decisions. We examine the impacts of G×E on tree breeding, some environmental factors that cause G×E and the strategies for dealing with G×E in tree breeding, and the future role of genomics.     

Heterogeneous variances and genetics by environment interactions in genetic evaluation of crossbred lambs

Accounting for environmental heteroscedasticity and genetics by environment interaction (G×E) in genetic evaluation is important because animals may not perform predictably across environments. The objectives of this study were to evaluate the presence and consequences of heteroscedasticity and G×E on genetic evaluation. The population considered was crossbred lambs sired by terminal sires and reared under commercial conditions in the UK. Data on 6325 lambs sired by Charollais, Suffolk and Texel rams were obtained. The experiment was conducted between 1999 and 2002 on three farms located in England, Scotland and Wales. There were 2322, 2137 and 1866 lambs in England, Scotland and Wales, respectively. A total of 89 sires were mated to 1984 ewes of two types (Welsh and Scottish Mules). Most rams were used for two breeding seasons with some rotated among farms to create genetic links. Lambs were reared on pasture and had their parentage, birth, 5 week, 10 week, and slaughter weights recorded. Lambs were slaughtered at a constant fatness, at which they were ultrasonically scanned for fat and muscle depth. Heteroscedasticity was evaluated in two ways. First, data were separated into three subsets by farm. Within-farm variance component estimates were then compared with those derived from the complete data (Model 1). Second, the combined data were fitted, but with a heterogeneous (by farm) environmental variance structure (Model 2). To investigate G×E, a model with a random farm by sire (F×S) interaction was used (Model 3). The ratio of the F×S variance to total variance was a measure of the level of G×E in the population. Heterogeneity in environmental variability across farm was identified for all traits (P<0.01). Rank correlations of sire estimated breeding value between farms differed for Model 1 for all traits. However, sires ranked similarly (rank correlation of 0.99) for weight traits with Model 2, but less so for ultrasonic measures. Including the F×S interaction (Model 3) improved model fit for all traits. However, the F×S term explained a small proportion of variation in weights (<2%) although more in ultrasonic traits (at least 10%). In conclusion, heteroscedasticity and G×E were not large for these data, and can be ignored in genetic evaluation of weight but, perhaps, not ultrasonic traits. Still, before incorporating heteroscedasticity and G×E into routine evaluations of even ultrasonic traits, their consequences on selection response in the breeding goal should be evaluated.     

Genotype by environment interactions for Pinus radiata in New South Wales, Australia

Historical data from 26 progeny trials in the NSW breeding program was analyzed to determine the extent and practical importance of genotype by environment (G×E) interactions for a range of traits. Significant G×E interaction was present for diameter (DBH) with 75% of the 35 estimated between-site genetic correlations falling below the threshold value of 0.6 where regionalization should be considered. Estimated genetic correlations for stem straightness, branch quality, and outerwood density were much higher, indicating these traits are not as affected by G×E. Levels of G×E for DBH are sufficient to have serious impacts on the expression of genetic gain in deployed material. For DBH, altitude differences between sites appear to be the key factor driving the G×E with a difference of greater than 280 m in altitude leading to a breakdown in correlations. Two groups of sites were identified as having limited G×E within each group: one for sites above 900 m elevation plus a lower-altitude group. Sites included in the higher-altitude group were located across the entire north–south geographic range of NSW. Equations for prediction of site mean DBH indicate that altitude, prior land use, and underlying geology are key driving variables. A more complex model was developed for predicting the between-site genetic correlations for DBH with the model accounting for approximately 50% of the observed variation.     

Detection and stability of quantitative trait loci (QTL) in Eucalyptus globulus

Eucalyptus globulus Labill. ssp. globulus is an important tree species for the pulp and paper industry, and several breeding programmes throughout the world are striving to improve key traits such as growth and wood density. This study aimed to detect quantitative trait loci (QTL) for growth, wood density, relative bark thickness and early flowering in a single full-sib E. globulus family grown across seven sites. Growth was measured a number of times over a 6-year period, enabling temporal stability of growth QTL to be studied. Ten putative QTL (LOD > 2.0) were detected in the single family, which was of moderate size. Based on permutations of the trait data, six of these QTL were significant at the experimentwise significance level of 0.1 for at least one of the four models implemented in analysis to remove site effects. For wood density, two putative QTL explained 20% of the variance for the trait, indicating that a small number of QTL might explain a reasonable proportion of the trait variance. One of these QTL was found to be independent of QTL for growth whereas the second QTL co-segregated with a QTL for relative incremental growth. The marker nearest to this QTL was associated with fast growth but low wood density. A putative growth QTL at year 6 was found to be relatively stable across ages. In addition, it was found that residuals from models based on measurements from across all families across all sites in the trial detected QTL with greater experimentwise significance.     

Quantitative trait loci and candidate genes underlying genotype by environment interaction in the response of Arabidopsis thaliana to drought

Drought stress was imposed on two sets of Arabidopsis thaliana genotypes grown in sand under short‐day conditions and analysed for several shoot and root growth traits. The response to drought was assessed for quantitative trait locus (QTL) mapping in a genetically diverse set of Arabidopsis accessions using genome‐wide association (GWA) mapping, and conventional linkage analysis of a recombinant inbred line (RIL) population. Results showed significant genotype by environment interaction (G×E) for all traits in response to different watering regimes. For the RIL population, the observed G×E was reflected in 17 QTL by environment interactions (Q×E), while 17 additional QTLs were mapped not showing Q×E. GWA mapping identified 58 single nucleotide polymorphism (SNPs) associated with loci displaying Q×E and an additional 16 SNPs associated with loci not showing Q×E. Many candidate genes potentially underlying these loci were suggested. The genes for RPS3C and YLS7 were found to contain conserved amino acid differences when comparing Arabidopsis accessions with strongly contrasting drought response phenotypes, further supporting their candidacy. One of these candidate genes co‐located with a QTL mapped in the RIL population.     

Association of single nucleotide polymorphisms with form traits in three New Zealand populations of radiata pine in the presence of genotype by environment interactions

Associations of single nucleotide polymorphisms (SNP) with the form traits, branch cluster frequency and stem straightness, were studied in three radiata pine (Pinus radiata D. Don) breeding populations. For branch cluster frequency, high genotype by environment (G×E) interactions were found between two sites of the POP1 trial series (Tarawera and Glenledi) and between two sites of the POP2 trial series (Tarawera and Woodhill). For stem straightness, high G×E interactions were found between two sites (Tarawera and Woodhill) in both the POP2 and POP3 trial series. Thirty-two and 26 SNPs were associated with branch cluster frequency and stem straightness respectively, across a number of sites and trial series in a genetic model assuming heterogeneous additive genetic variances across sites. These SNPs had significant associations with branch cluster frequency or stem straightness either in one site only, across sites within a trial series or across different trial series. Seven SNPs had significant associations with branch cluster frequency and seven SNPs with stem straightness across two of three trial series. One SNP had significant association with stem straightness across all three trial series. Strong G×E interactions resulted in fewer significant SNPs in common across the sites among which there were large effect differences. The percentage of genetic variance explained by SNPs showing significant associations ranged from 0.23 to 8.76 % for branch cluster frequency and from 0.37 to 12.75 % for stem straightness. This study showed that SNP effects for a trait change across environments if G×E interactions exist for that trait.     

Genomic reaction norm models exploiting genotype × environment interaction on sexual precocity indicator traits in Nellore cattle

Brazilian beef cattle are raised predominantly on pasture in a wide range of environments. In this scenario, genotype by environment (G×E) interaction is an important source of phenotypic variation in the reproductive traits. Hence, the evaluation of G×E interactions for heifer’s early pregnancy (HP) and scrotal circumference (SC) traits in Nellore cattle, belonging to three breeding programs, was carried out to determine the animal’s sensitivity to the environmental conditions (EC). The dataset consisted of 85 874 records for HP and 151 553 records for SC, from which 1800 heifers and 3343 young bulls were genotyped with the BovineHD BeadChip. Genotypic information for 826 sires was also used in the analyses. EC levels were based on the contemporary group solutions for yearling body weight. Linear reaction norm models (RNM), using pedigree information (RNM_A) or pedigree and genomic information (RNM_H), were used to infer G×E interactions. Two validation schemes were used to assess the predictive ability, with the following training populations: (a) forward scheme—dataset was split based on year of birth from 2008 for HP and from 2011 for SC; and (b) environment-specific scheme—low EC (−3.0 and −1.5) and high EC (1.5 and 3.0). The inclusion of the H matrix in RNM increased the genetic variance of the intercept and slope by 18.55 and 23.00% on average respectively, and provided genetic parameter estimates that were more accurate than those considering pedigree only. The same trend was observed for heritability estimates, which were 0.28–0.56 for SC and 0.26–0.49 for HP, using RNM_H, and 0.26–0.52 for SC and 0.22–0.45 for HP, using RNM_A. The lowest correlation observed between unfavorable (−3.0) and favorable (3.0) EC levels were 0.30 for HP and −0.12 for SC, indicating the presence of G×E interaction. The G×E interaction effect implied differences in animals’ genetic merit and re-ranking of animals on different environmental conditions. SNP marker–environment interaction was detected for Nellore sexual precocity indicator traits with changes in effect and variance across EC levels. The RNM_H captured G×E interaction effects better than RNM_A and improved the predictive ability by around 14.04% for SC and 21.31% for HP. Using the forward scheme increased the overall predictive ability for SC (20.55%) and HP (11.06%) compared with the environment-specific scheme. The results suggest that the inclusion of genomic information combined with the pedigree to assess the G×E interaction leads to more accurate variance components and genetic parameter estimates.     

Exome sequences and multi‐environment field trials elucidate the genetic basis of adaptation in barley

Broadening the genetic base of crops is crucial for developing varieties to respond to global agricultural challenges such as climate change. Here, we analysed a diverse panel of 371 domesticated lines of the model crop barley to explore the genetics of crop adaptation. We first collected exome sequence data and phenotypes of key life history traits from contrasting multi‐environment common garden trials. Then we applied refined statistical methods, including some based on exomic haplotype states, for genotype‐by‐environment (G×E) modelling. Sub‐populations defined from exomic profiles were coincident with barley's biology, geography and history, and explained a high proportion of trial phenotypic variance. Clear G×E interactions indicated adaptation profiles that varied for landraces and cultivars. Exploration of circadian clock‐related genes, associated with the environmentally adaptive days to heading trait (crucial for the crop's spread from the Fertile Crescent), illustrated complexities in G×E effect directions, and the importance of latitudinally based genic context in the expression of large‐effect alleles. Our analysis supports a gene‐level scientific understanding of crop adaption and leads to practical opportunities for crop improvement, allowing the prioritisation of genomic regions and particular sets of lines for breeding efforts seeking to cope with climate change and other stresses.     

Why does the magnitude of genotype‐by‐environment interaction vary?

Genotype‐by‐environment interaction (G × E), that is, genetic variation in phenotypic plasticity, is a central concept in ecology and evolutionary biology. G×E has wide‐ranging implications for trait development and for understanding how organisms will respond to environmental change. Although G × E has been extensively documented, its presence and magnitude vary dramatically across populations and traits. Despite this, we still know little about why G × E is so evident in some traits and populations, but minimal or absent in others. To encourage synthetic research in this area, we review diverse hypotheses for the underlying biological causes of variation in G × E. We extract common themes from these hypotheses to develop a more synthetic understanding of variation in G × E and suggest some important next steps.     

Dissecting apple tree architecture into genetic, ontogenetic and environmental effects: QTL mapping

The present study aimed to dissect tree architectural plasticity into genetic, ontogenetic and environmental effects over the first 4 years of growth of an apple F1 progeny by means of quantitative traits loci (QTL) mapping. Both growth and branching processes were phenotyped on the consecutive annual shoots of different axes within a tree. For each studied trait, predicted values (best linear unbiased predictors, BLUPs) of the genotypic (G) effect or its interaction with tree age (G×A) and climatic year (G×Y) were extracted from mixed linear models of repeated data. These BLUPs, which are independent from autocorrelations between repeated measurements, were used for QTL mapping. QTL detection power was improved by this two-step approach. For each architectural process, numerous QTLs were detected and some particularly interesting co-localised in common genomic regions, for internode lengthening, top diameter, and number and percentage of axillary shoots. When several QTLs were detected for a given trait, global models were estimated, which explained a maximum of 40% of the total variance for both internode length and top diameter and 28% for branching. QTLs detected for BLUPs of G×Y effects were interpreted as resulting from the interaction between genetic maximal potential of growth and climatic factors, while those for G×A effects were interpreted in relation to tree ontogeny. Most of the latter ones were found to be concomitant with key development stages during which the trait average started to decrease, but with different magnitudes depending on genotype. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Quantitative trait dissection analysis in Eucalyptus using RAPD markers: 1. Detection of QTL in interspecific hybrid progeny, stability of QTL expression across different ages

 The objective of this study was to use random amplified polymorphic DNA (RAPD) to determine the genetic location and effects of genomic regions controlling wood density, stem growth and stem form in two species of Eucalyptus. Two hundred F₁ trees generated from an interspecific cross E. urophylla×E. grandis between two elite trees were used. Genetic maps were constructed for each parent with markers segregating in the 1:1 ratio in FS progeny. A total of 86 and 92 markers distributed among 11 linkage groups covered 1295 cM and 1312 cM for the E. urophylla and E. grandis parent, respectively. Traits were measured three times up to selection age (38 months). The magnitude of the phenotypic variation explained by the joint action of the segregating quantitative trait alleles indicated that genetic factors of large effect were involved in the control of the studied characters. Several regions controlling part of the variation for the studied traits were identified by interval mapping. Some regions of the genome exerted effects on more than one trait, providing a genetic explanation for at least some of the correlation between the traits. On the basis of an age-by-age analysis, a partial stability of QTL expression was observed with 68% of the QTL being expressed at two ages and 32% being age-specific. No QTL were significant for all three ages. Taking advantage of repeated measurements on the same material across different ages, we investigated with a maximum statistical power, the effect of marker genotype on traits, with age and QTL×age interaction effects being removed. A two-way analysis of variance made it possible to detect significant marker-trait associations over the period studied. Most of them had already been detected in the annual analysis. This result is very encouraging for the application of marker information to the early selection of hybrid trees to be vegetatively propagated for the production of clonal varieties. Received: 2 December 1996/Accepted: 4 April 1997     

Micro-evolutionary patterns of juvenile wood density in a pine species

Wood density can be considered an adaptive trait, because it ensures the safe and efficient transport of water from the roots to the leaves, mechanical support for the body of the plant and the storage of biological chemicals. Its variability has been extensively described in narrow genetic backgrounds and in wide ranges of forest tree species, but little is known about the extent of natural genetic and phenotypic variability within species. This information is essential to our understanding of the evolutionary forces that have shaped this trait, and for the evaluation of its inclusion in breeding programs. We assessed juvenile wood density, leaf area, total aboveground biomass, and growth in six Pinus pinaster populations of different geographic origins (France, Spain, and Morocco) growing in a provenance-progeny trial. No genetic differentiation was found for wood density, whereas all other traits significantly differed between populations. Heritability of this trait was moderate, with a low additive genetic variance. For retrospective identification of the evolutionary forces acting on juvenile wood density, we compared the distribution of neutral markers (F _ST) and quantitative genetic differentiation (Q _ST). We found that Q _ST was significantly lower than F _ST, suggesting evolutionary stasis. Furthermore, we did not detect any relationship between juvenile wood density and drought tolerance (resistance to cavitation), suggesting that this trait could not be used as a proxy for drought tolerance at the intraspecific level.     

Shifts in trait means and variances in North American tree assemblages: species richness patterns are loosely related to the functional space

One of the key hypothesized drivers of gradients in species richness is environmental filtering, where environmental stress limits which species from a larger species pool gain membership in a local community owing to their traits. Whereas most studies focus on small‐scale variation in functional traits along environmental gradient, the effect of large‐scale environmental filtering is less well understood. Furthermore, it has been rarely tested whether the factors that constrain the niche space limit the total number of coexisting species. We assessed the role of environmental filtering in shaping tree assemblages across North America north of Mexico by testing the hypothesis that colder, drier, or seasonal environments (stressful conditions for most plants) constrain tree trait diversity and thereby limit species richness. We assessed geographic patterns in trait filtering and their relationships to species richness pattern using a comprehensive set of tree range maps. We focused on four key plant functional traits reflecting major life history axes (maximum height, specific leaf area, seed mass, and wood density) and four climatic variables (annual mean and seasonality of temperature and precipitation). We tested for significant spatial shifts in trait means and variances using a null model approach. While we found significant shifts in mean species’ trait values at most grid cells, trait variances at most grid cells did not deviate from the null expectation. Measures of environmental harshness (cold, dry, seasonal climates) and lower species richness were weakly associated with a reduction in variance of seed mass and specific leaf area. The pattern in variance of height and wood density was, however, opposite. These findings do not support the hypothesis that more stressful conditions universally limit species and trait diversity in North America. Environmental filtering does, however, structure assemblage composition, by selecting for certain optimum trait values under a given set of conditions.     

Genotype by production environment interaction for birth and weaning weights in a population of composite beef cattle

The objectives of the present study were: (1) to evaluate the importance of genotype×production environment interaction for the genetic evaluation of birth weight (BW) and weaning weight (WW) in a population of composite beef cattle in Brazil, and (2) to investigate the importance of sire×contemporary group interaction (S×CG) to model G×E and improve the accuracy of prediction in routine genetic evaluations of this population. Analyses were performed with one, two (favorable and unfavorable) or three (favorable, intermediate, unfavorable) different definitions of production environments. Thus, BW and WW records of animals in a favorable environment were assigned to either trait 1, in an intermediate environment to trait 2 or in an unfavorable environment to trait 3. The (co)variance components were estimated using Gibbs sampling in single-, bi- or three-trait animal models according to the definition of number of production environments. In general, the estimates of genetic parameters for BW and WW were similar between environments. The additive genetic correlations between production environments were close to unity for BW; however, when examining the highest posterior density intervals, the correlation between favorable and unfavorable environments reached a value of only 0.70, a fact that may lead to changes in the ranking of sires across environments. The posterior mean genetic correlation between direct effects was 0.63 in favorable and unfavorable environments for WW. When S×CG was included in two- or three-trait analyses, all direct genetic correlations were close to unity, suggesting that there was no evidence of a genotype×production environment interaction. Furthermore, the model including S×CG contributed to prevent overestimation of the accuracy of breeding values of sires, provided a lower error of prediction for both direct and maternal breeding values, lower squared bias, residual variance and deviance information criterion than the model omitting S×CG. Thus, the model that included S×CG can therefore be considered the best model on the basis of these criteria. The genotype×production environment interaction should not be neglected in the genetic evaluation of BW and WW in the present population of beef cattle. The inclusion of S×CG in the model is a feasible and plausible alternative to model the effects of G×E in the genetic evaluations.     

A novel method for identifying nonlinear gene–environment interactions in case–control association studies

The genetic influences on complex disease traits generally depend on the joint effects of multiple genetic variants, environmental factors, as well as their interplays. Gene × environment (G × E) interactions play vital roles in determining an individual’s disease risk, but the underlying genetic machinery is poorly understood. Traditional analysis assuming linear relationship between genetic and environmental factors, along with their interactions, is commonly pursued under the regression-based framework to examine G × E interactions. This assumption, however, could be violated due to nonlinear responses of genetic variants to environmental stimuli. As an extension to our previous work on continuous traits, we proposed a flexible varying-coefficient model for the detection of nonlinear G × E interaction with binary disease traits. Varying coefficients were approximated by a non-parametric regression function through which one can assess the nonlinear response of genetic factors to environmental changes. A group of statistical tests were proposed to elucidate various mechanisms of G × E interaction. The utility of the proposed method was illustrated via simulation and real data analysis with application to type 2 diabetes.     

QTL for tuber morphology traits in diploid potato

A diploid, potato mapping population consisting of 149 individuals was assessed in three consecutive years for important agronomic and quality traits: tuber shape, regularity of tuber shape, eye depth, mean tuber weight, and tuber flesh color. Analysis of variance showed that the genotype had the largest influence on the phenotypic scores but effect of the genotype × year interactions was also strong. Using this data and an existing genetic map, a quantitative trait loci (QTL) analysis was conducted. From four to seven QTL were detected for each trait except tuber flesh color, which was determined by a major QTL on chromosome III explaining 76.8% of the trait variance. Additionally, a minor QTL for flesh color was localized on chromosome II. For the other traits, significant QTL were detected: for tuber shape on chromosome X, for regularity of tuber shape on chromosome III, for eye depth on chromosome IV, and for tuber weight on chromosome I. Some detected QTL confirmed previous studies, but new ones were also identified.     

REDUCED GENETIC VARIANCE AMONG HIGH FITNESS INDIVIDUALS: INFERRING STABILIZING SELECTION ON MALE SEXUAL DISPLAYS IN DROSOPHILA SERRATA

Directional selection is prevalent in nature, yet phenotypes tend to remain relatively constant, suggesting a limit to trait evolution. However, the genetic basis of this limit is unresolved. Given widespread pleiotropy, opposing selection on a trait may arise from the effects of the underlying alleles on other traits under selection, generating net stabilizing selection on trait genetic variance. These pleiotropic costs of trait exaggeration may arise through any number of other traits, making them hard to detect in phenotypic analyses. Stabilizing selection can be inferred, however, if genetic variance is greater among low‐ compared to high‐fitness individuals. We extend a recently suggested approach to provide a direct test of a difference in genetic variance for a suite of cuticular hydrocarbons (CHCs) in Drosophila serrata. Despite strong directional sexual selection on these traits, genetic variance differed between high‐ and low‐fitness individuals and was greater among the low‐fitness males for seven of eight CHCs, significantly more than expected by chance. Univariate tests of a difference in genetic variance were nonsignificant but likely have low power. Our results suggest that further CHC exaggeration in D. serrata in response to sexual selection is limited by pleiotropic costs mediated through other traits.     

桂林岩溶石山青冈群落植物功能性状的尺度变化与关联

研究植物功能性状在不同尺度的变异和关联,对于揭示植物对环境的适应策略和群落构建规律具有重要意义。以岩溶石山青冈群落为研究对象,测量了研究区内20个样方74种木本植物的叶面积、比叶面积和木材密度3个功能性状值,利用性状梯度分析法分析了3个性状在群落内部(α组分)及群落间(β组分)的变异格局及相关性。结果表明:(1)群落内3个植物功能性状的α值范围均大于β值范围,即物种相对于共生物种性状值的变化大于沿着群落平均性状梯度的变化。(2)植物功能性状比叶面积的种内差异引起的变化小于群落水平。(3)叶面积与比叶面积、比叶面积与木材密度、叶面积与木材密度的β组分相关性均最强,而α组分间无相关性或相关性较弱,即叶面积与比叶面积、比叶面积与木材密度、叶面积与木材密度两两性状间的相关性在群落间的依赖程度比群落内共生物种的依赖性要强,暗示物种在群落内和群落间采取不同的生态策略来适应环境。     

Additive and non-additive genetic parameters for multipurpose traits in a clonally replicated incomplete factorial test of <Emphasis Type="Italic">Castanea</Emphasis> spp.

Second-year traits of growth, stem form, terminal flushing, and survival were assessed in 1770 ramets from 295 clones of 16 full-sib families of Castanea spp. Additive, dominance, and epistatic genetic variances were estimated in a clonally replicated incomplete 5?×?4 factorial test. Parents of the mating design were selected mainly on their phenotypes for wood quality (Castanea sativa traditional varieties) and their proven resistance to Phytophthora spp. (Asiatic species and Castanea crenata?×?C. sativa hybrids). Additive genetic variances were estimated to be 1.7–9 times greater than the dominance components. Inferred epistatic variance components showed a significant role in controlling growth traits and branch length. Narrow- and broad-sense heritability estimates showed that terminal flushing date was the most heritable trait, followed by height. The high estimates of half-sib, full-sib, and clonal mean heritabilities for almost all traits suggest that different strategies of backwards and forwards selection could be proposed. The ranking of the breeding values of parents allow us to select the best parents for new crosses and extend the mating design. Favorable genetic correlations were found between growth traits and straightness, so multi-trait selection looks promising. Our results provide the first information on the partitioning of genetic variance in Castanea spp. and a starting point for devising new selection strategies.