Unfavorable genetic correlations between growth and wood quality traits are one of the biggest challenges in advanced conifer breeding programs. To examine and deal with such correlation, increment cores were sampled at breast height from 5,618 trees in 524 open-pollinated families in two 21-year-old Norway spruce progeny trials in southern Sweden, and age trends of genetic variation, genetic correlation, and efficiency of selection were investigated. Wood quality traits were measured on 12-mm increment cores using SilviScan. Heritability was moderate (~0.4-0.5) for wood density and modulus of elasticity (MOE) but low (~0.2) for microfibril angle (MFA). Different age trends were observed for wood density, MFA, and MOE, and the lower heritability of MFA relative to wood density and MOE in Norway spruce contrasted with general trends of the three wood quality traits in pine. Genetic correlations among growth, wood density, MFA, and MOE increased to a considerably high value from pith to bark with unfavorable genetic correlations (−0.6 between growth and wood density, −0.74 between growth and MOE). Age-age genetic correlations reached 0.9 after ring 4 for diameter at breast height (DBH), wood density, MFA, and MOE traits. Early selections at ring 10 for diameter and at ring 6 or 7 for wood quality traits had similar effectiveness as selection conducted at reference ring 15. Selection based on diameter alone produced 19.0 % genetic gain in diameter but resulted in 4.8 % decrease in wood density, 9.4 % decrease in MOE, and 8.0 % increase in MFA. Index selection with a restriction of no change in wood density, MOE, and MFA, respectively, produced relatively lower genetic gains in diameter (16.4, 12.2, and 14.1 %, respectively), indicating such index selection could be implemented to maintain current wood density. Index selection using economic weights is, however, recommended for maximum economic efficiency.

BackgroundGenomic selection (GS) can increase genetic gain by reducing the length of breeding cycle in forest trees. Here we genotyped 1370 control-pollinated progeny trees from 128 full-sib families in Norway spruce (Picea abies (L.) Karst.), using exome capture as genotyping platform. We used 116,765 high-quality SNPs to develop genomic prediction models for tree height and wood quality traits. We assessed the impact of different genomic prediction methods, genotype-by-environment interaction (G × E), genetic composition, size of the training and validation set, relatedness, and number of SNPs on accuracy and predictive ability (PA) of GS.ResultsUsing G matrix slightly altered heritability estimates relative to pedigree-based method. GS accuracies were about 11–14% lower than those based on pedigree-based selection. The efficiency of GS per year varied from 1.71 to 1.78, compared to that of the pedigree-based model if breeding cycle length was halved using GS. Height GS accuracy decreased to more than 30% while using one site as training for GS prediction and using this model to predict the second site, indicating that G × E for tree height should be accommodated in model fitting. Using a half-sib family structure instead of full-sib structure led to a significant reduction in GS accuracy and PA. The full-sib family structure needed only 750 markers to reach similar accuracy and PA, as compared to 100,000 markers required for the half-sib family, indicating that maintaining the high relatedness in the model improves accuracy and PA. Using 4000–8000 markers in full-sib family structure was sufficient to obtain GS model accuracy and PA for tree height and wood quality traits, almost equivalent to that obtained with all markers.ConclusionsThe study indicates that GS would be efficient in reducing generation time of breeding cycle in conifer tree breeding program that requires long-term progeny testing. The sufficient number of trees within-family (16 for growth and 12 for wood quality traits) and number of SNPs (8000) are required for GS with full-sib family relationship. GS methods had little impact on GS efficiency for growth and wood quality traits. GS model should incorporate G × E effect when a strong G × E is detected.

Abstract& Key message Strong genetic correlations were observed between Pilodyn measurement and wood density, and between acoustic velocity and MFA. Combination of Pilodyn penetration and acoustic velocity measurements from standing trees can provide reliable prediction of stiffness of Norway spruce for breeding selection.

The biogeographical relationships between far-separated populations, in particular, those in the mainland and islands, remain unclear for widespread species in eastern Asia where the current distribution of plants was greatly influenced by the Quaternary climate. Deciduous Oriental oak (Quercus variabilis) is one of the most widely distributed species in eastern Asia. In this study, leaf material of 528 Q. variabilis trees from 50 populations across the whole distribution (Mainland China, Korea Peninsular as well as Japan, Zhoushan and Taiwan Islands) was collected, and three cpDNA intergenic spacer fragments were sequenced using universal primers. A total of 26 haplotypes were detected, and it showed a weak phylogeographical structure in eastern Asia populations at species level, however, in the central-eastern region of Mainland China, the populations had more haplotypes than those in other regions, with a significant phylogeographical structure (N ST = 0.751> G ST = 0.690, P<0.05). Q. variabilis displayed high interpopulation and low intrapopulation genetic diversity across the distribution range. Both unimodal mismatch distribution and significant negative Fu’s FS indicated a demographic expansion of Q. variabilis populations in East Asia. A fossil calibrated phylogenetic tree showed a rapid speciation during Pleistocene, with a population augment occurred in Middle Pleistocene. Both diversity patterns and ecological niche modelling indicated there could be multiple glacial refugia and possible bottleneck or founder effects occurred in the southern Japan. We dated major spatial expansion of Q. variabilis population in eastern Asia to the last glacial cycle(s), a period with sea-level fluctuations and land bridges in East China Sea as possible dispersal corridors. This study showed that geographical heterogeneity combined with climate and sea-level changes have shaped the genetic structure of this wide-ranging tree species in East Asia.

Forest trees are ideally suited to association mapping due to their high levels of diversity and low genomic linkage disequilibrium. Using an association mapping approach, single-nucleotide polymorphism (SNP) markers influencing quantitative variation in wood quality were identified in a natural population of Pinus radiata. Of 149 sites examined, 10 demonstrated significant associations (P , 0.05, q , 0.1) with one or more traits after accounting for population structure and experimentwise error. Without accounting for marker interactions, phenotypic variation attributed to individual SNPs ranged from 2 to 6.5%. Undesirable negative correlations between wood quality and growth were not observed, indicating potential to break negative correlations by selecting for individual SNPs in breeding programs. Markers that yielded significant associations were reexamined in an Australian land race. SNPs from three genes (PAL1, PCBER, and SUSY) yielded significant associations. Importantly, associations with two of these genes validated associations with density previously observed in the discovery population. In both cases, decreased wood density was associated with the minor allele, suggesting that these SNPs may be under weak negative purifying selection for density in the natural populations. These results demonstrate the utility of LD mapping to detect associations, even when the power to detect SNPs with small effect is anticipated to be low. N UMEROUS traits of agronomic importance are demonstrated to be under genetic control (Keurentjes et al. 2008), and there is considerable interest in characterizing the causative polymorphisms underlying their quantitative variation. In forest trees, quantitative variation in traits such as mechanical and pulping properties of wood, growth, cold hardiness, and drought acclimation are likely to result from allelic variation within multiple genes (Neale and Savolainen 2004;Oraguzie and Wilcox 2007). Because of the commercial importance of radiata pine (Pinus radiata D. Don), we are exploring the molecular basis of variation in its wood properties using an association genetics approach.Radiata pine wood properties are variable in domesticated populations and exhibit a quantitative mode of inheritance with high heritability, indicating a strong underlying genetic component. High heritabilities have been observed for solid wood traits including density, cellulose microfibril angle (MFA), and modulus of elasticy (MOE) (Baltunis et al. 2007) and for carbohydrate composition, pulp yield, fiber length, and perimeter (Evans et al. 1997;Kibblewhite 1999); and genetic control has been established for several important production traits (Kumar 2004;Dungey et al. 2006;Gapare et al. 2006;Wu et al. 2007).It is anticipated that variation in wood quality will be dependent on variation in numerous genes involved in xylogenesis. Studies of gene expression in developing xylem have revealed genes involved in spatially and temporally regulated processes such as cambial division, cell different...

negative genetic correlations between growth traits and wood properties suggest incorporating multiple traits selection including economic weights for the future Scots pine breeding programs.Abstract & Context The development of multiple trait selection indices for solid (structure) wood production in the Scots pine (Pinus sylvestris L.) breeding program requires genetic variances and covariances estimated among wood quality traits including stiffness. & Aims Genetic control and relationships among Scots pine growth, fiber, and wood quality traits were assessed by estimating heritability, phenotypic and genetic correlation using a Scots pine full-sib family trial. & Method Wood quality traits including clearwood and dynamic acoustic stiffness were measured using SilviScan and Hitman in a 40-year-old progeny trial and by sampling increment cores of 778 trees of 120 families. Genetic parameters were estimated using the mixed model by the ASReml software. & Results Heritability ranged from 0.147 to 0.306 for growth, earlywood, transition wood and latewood proportion traits and from 0.260 to 0.524 for fiber dimension, wood density, MFA and stiffness traits. The highly unfavorable genetic correlation between diameter and whole core density (−0.479) and clearwood stiffness (−0.506) and dynamic acoustic stiffness (−0.382) was observed in this study. & Conclusion The unfavorable genetic correlations between growth traits and stiffness indicate that multiple traits selection using optimal economic weights and optimal breeding strategies are recommended for the advanced Scots pine breeding program.

Mapping the genetic architecture of forest tree traits is important in order to understand the evolutionary forces that have shaped these traits and to facilitate the development of genomic-based breeding strategies. We examined the number, size, and distribution of allelic effects influencing eight types of traits using 30 published mapping studies (linkage and association mapping) in forest trees. The sizes of allelic effects, measured as the phenotypic variance explained, generally showed a severely right-skewed distribution. We estimated the numbers of underlying causal effects (n qtl ) for different trait categories by improving a method previously developed by Otto and Jones (Genetics 156:2093(Genetics 156: -2107(Genetics 156: , 2000. Estimates of n qtl based on association mapping studies were generally higher (median at 643) than those based on linkage mapping (median at 33). Comparisons with simulated linkage and association mapping data suggested that the lower n qtl estimates for the linkage mapping studies could partly be explained by fewer causal loci segregating within the full-sib family populations normally used, but also by the cosegregation of causal loci due to limited recombination. Disease resistance estimates based on linkage mapping studies had the lowest median of four underlying effects, while growth traits based on association mapping had about 580 effects. Theoretically, the capture of 50% of the genetic variation would thus require a population size of about 200 for disease resistance in linkage mapping, while growth traits in association mapping would require about 25,000. The adequacy and reliability of the improved method was successfully verified by applying it to the simulated data.

A total of 1097 cross-sectional wood disks from breast height were sampled from two rotation-aged (27 and 31 years from planting) genetic trials of radiata pine (Pinus radiata D. Don) in Australia to estimate the genetic correlation between early and rotation-aged growth and wood quality traits and the efficiency of early selection. Annual growth-ring width and density, diameter at breast height (DBH), and area-weighted density (AD) from 30 open-pollinated families were measured using X-ray densitometry. Genotype × site interactions were not significant for density and growth traits. Ring density increased steadily from the pith to cambial age 14, and then density had little change in the following years. For AD, the family and individual heritability estimates were about 0.60 and 0.30 after the first 2 years. For DBH, family and individual narrow-sense heritability estimates increased steadily after the first 4 years, and family heritability increased to 0.7 at a cambial age of 11 and had little change thereafter. Individual heritability estimate increased to 0.4 at cambial age 14 and was similar for the later ages. Beyond a cambial age of 5 years, there were strong negative genetic correlations of around –0.80 between AD and DBH. Age–age genetic correlations for AD were high and reached 0.80 and above after cambial age 3. Age–age genetic correlations for DBH were similar to AD, except the first two years. The most efficient early selection year was between ages 4 and 6 years after planting for AD, and between ages 8 and 11 years for DBH.