Fikret Isik

Genomic selection in forest tree breeding: the concept and an outlook to the future

Using large numbers of DNA markers to predict genetic merit [genomic selection (GS)] is a new frontier in plant and animal breeding programs. GS is now routinely used to select superior bulls in dairy cattle breeding. In forest trees, a few empirical proof of-concept studies suggest that GS could be successful. However, application of GS in forest tree breeding is still in its infancy. The major hurdle is lack of high throughput genotyping platforms for trees, and the high genotyping costs, though, the cost of genotyping will likely decrease in the future. There has been a growing interest in GS among tree breeders, forest geneticists, and tree improvement managers. A broad overview of pedigree reconstruction and GS is presented. Underlying reasons for failures of marker-assisted selection were summarized and compared with GS. Challenges of GS in forest tree breeding and the outlook for the future are discussed, and a GS plan for a cloned loblolly pine breeding population is presented. This review is intended for tree breeders, forest managers, scientist and students who are not necessarily familiar with genomic or quantitative genetics jargon.

Relationships between acoustic variables and different measures of stiffness in standing Pinus taeda trees

Acoustic tools are increasingly used to estimate standing-tree (dynamic) stiffness; however, such techniques overestimate static stiffness, the standard measurement for determining modulus of elasticity (MOE) of wood. This study aimed to identify correction methods for standing-tree estimates making dynamic and static stiffness comparable. Sixty Pi- nus taeda L. trees, ranging from 14 to 19 years old, obtained from genetic tests established in the southeastern United States, were analyzed. Standing-tree acoustic velocities were measured using the TreeSonic tool. Acoustic velocities were also recorded in butt logs cut from the same trees using the Director HM200. A strong but biased relationship between tree and log velocities was observed, with tree velocities 32% higher (on average) than the corresponding log velocities. Two correction methods, one for calibrating tree velocities and one for accounting for differences in wood moisture con- tent, were used to determine an adjusted MOE. After correction, adjusted MOE estimates were in good agreement with static longitudinal MOE values measured on clearwood specimens obtained from the trees, and no systematic bias was ob- served. The results of this study show that acoustic estimates of MOE on standing trees largely depend on how the data are processed and the reference method used.

Genomic Estimated Breeding Values Using Genomic Relationship Matrices in a Cloned Population of Loblolly Pine

Replacement of the average numerator relationship matrix derived from the pedigree with the realized genomic relationship matrix based on DNA markers might be an attractive strategy in forest tree breeding for predictions of genetic merit. We used genotypes from 3461 single-nucleotide polymorphism loci to estimate genomic relationships for a population of 165 loblolly pine (Pinus taeda L.) individuals. Phenotypes of the 165 individuals were obtained from clonally replicated field trials and were used to estimate breeding values for growth (stem volume). Two alternative methods, based on allele frequencies or regression, were used to generate the genomic relationship matrices. The accuracies of genomic estimated breeding values based on the genomic relationship matrices and breeding values estimated based on the average numerator relationship matrix were compared. On average, the accuracy of predictions based on genomic relationships ranged between 0.37 and 0.74 depending on the validation method. We did not detect differences in the accuracy of predictions based on genomic relationship matrices estimated by two different methods. Using genomic relationship matrices allowed modeling of Mendelian segregation within full-sib families, an important advantage over a traditional genetic evaluation system based on pedigree. We conclude that estimation of genomic relationships could be a powerful tool in forest tree breeding because it accurately accounts both for genetic relationships among individuals and for nuisance effects such as location and replicate effects, and makes more accurate selection possible within full-sib crosses.

Systems Biology of Lignin Biosynthesis in Populus trichocarpa: Heteromeric 4-Coumaric Acid:Coenzyme A Ligase Protein Complex Formation, Regulation, and Numerical Modeling

This work shows that 4CL, an enzyme in monolignol biosynthesis, is found as a heterotetrameric complex of two isoforms in Populus trichocarpa. The activity of the heterotetramer can be described by a mathematical model that explains the effects of each isoform with mixtures of substrates and three types of inhibition, providing insights into the regulation of metabolic flux for this pathway. As a step toward predictive modeling of flux through the pathway of monolignol biosynthesis in stem differentiating xylem of Populus trichocarpa, we discovered that the two 4-coumaric acid:CoA ligase (4CL) isoforms, 4CL3 and 4CL5, interact in vivo and in vitro to form a heterotetrameric protein complex. This conclusion is based on laser microdissection, coimmunoprecipitation, chemical cross-linking, bimolecular fluorescence complementation, and mass spectrometry. The tetramer is composed of three subunits of 4CL3 and one of 4CL5. 4CL5 appears to have a regulatory role. This protein–protein interaction affects the direction and rate of metabolic flux for monolignol biosynthesis in P. trichocarpa. A mathematical model was developed for the behavior of 4CL3 and 4CL5 individually and in mixtures that form the enzyme complex. The model incorporates effects of mixtures of multiple hydroxycinnamic acid substrates, competitive inhibition, uncompetitive inhibition, and self-inhibition, along with characteristic of the substrates, the enzyme isoforms, and the tetrameric complex. Kinetic analysis of different ratios of the enzyme isoforms shows both inhibition and activation components, which are explained by the mathematical model and provide insight into the regulation of metabolic flux for monolignol biosynthesis by protein complex formation.

Genetic variation and relationships to growth traits for microfibril angle, wood density and modulus of elasticity in a Picea abies clonal trial in southern Sweden

Abstract Genetic variation in wood density, microfibril angle (MFA), wood stiffness (MOE), height, diameter and volume was investigated in a 26-year-old Norway spruce [(Picea abies (L.) Karst.] clonal trial in southern Sweden. Wood quality measurements were performed on 10 mm increment cores using SilviScan. For MFA, mean values of annual rings showed the highest value (30°) at ring 2 counting from the pith, followed by a steep decrease and a gradual stabilization around ring 12 at approximately 14°. MOE showed a monotonic increase from 5 GPa to 14 GPa when moving from pith to bark. High broad-sense heritability values were found for wood density (0.48), MFA (0.41) and MOE (0.50). All growth traits displayed heritability values of similar magnitudes as reported in earlier studies. The generally high age–age correlations between different sections of the wood cores suggested that early selection for wood quality traits would be successful. Owing to unfavorable genetic correlations between volume and MOE, the correlated response indicated that selection for volume only at age 10 would result in a 0.27% decrease in weighted MOE at age 26 for every 1% increase in volume.

Near infrared calibration models for the estimation of wood density in Pinus taeda using repeated sample measurements

Near infrared (NIR) diffuse reflectance was used for the estimation of air-dry density and basic density in wood radial strip samples obtained at breast height (1.4 m) from 60 Pinus taeda trees established in three progeny tests in the south-eastern United States. NIR calibration models were fitted using raw spectra and pre-processed spectra with second derivative, multiplicative scatter correction and orthogonal signal correction. Successful calibrations were obtained for both wood properties using data collected in consecutive 10 mm sections from the samples. Data pre-processing did not result in model improvements compared to the models fitted using raw data. The effects of using repeated measures were evaluated by incorporating serial correlation into the partial least squares regression algorithm. The empirical autocorrelation of the normalised residuals showed that serial dependence among residuals was successfully removed by using an autoregressive correlation structure of second order. However, because the initial dependence among observations was not strong, the predictions were similar using the modified algorithm to those obtained with the traditional approach. These results indicate that the use of repeated measurements does not represent a serious problem for the development of NIR calibration models for the prediction of wood properties using radial samples measured in 10 mm sections and that the specification of the correlation structure may not be required when the models are used only for predictive purposes.

Genome-wide distribution of genetic diversity and linkage disequilibrium in a mass-selected population of maritime pine

BackgroundThe accessibility of high-throughput genotyping technologies has contributed greatly to the development of genomic resources in non-model organisms. High-density genotyping arrays have only recently been developed for some economically important species such as conifers. The potential for using genomic technologies in association mapping and breeding depends largely on the genome wide patterns of diversity and linkage disequilibrium in current breeding populations. This study aims to deepen our knowledge regarding these issues in maritime pine, the first species used for reforestation in south western Europe.ResultsUsing a new map merging algorithm, we first established a 1,712 cM composite linkage map (comprising 1,838 SNP markers in 12 linkage groups) by bringing together three already available genetic maps. Using rigorous statistical testing based on kernel density estimation and resampling we identified cold and hot spots of recombination. In parallel, 186 unrelated trees of a mass-selected population were genotyped using a 12k-SNP array. A total of 2,600 informative SNPs allowed to describe historical recombination, genetic diversity and genetic structure of this recently domesticated breeding pool that forms the basis of much of the current and future breeding of this species. We observe very low levels of population genetic structure and find no evidence that artificial selection has caused a reduction in genetic diversity. By combining these two pieces of information, we provided the map position of 1,671 SNPs corresponding to 1,192 different loci. This made it possible to analyze the spatial pattern of genetic diversity (He) and long distance linkage disequilibrium (LD) along the chromosomes. We found no particular pattern in the empirical variogram of He across the 12 linkage groups and, as expected for an outcrossing species with large effective population size, we observed an almost complete lack of long distance LD.ConclusionsThese results are a stepping stone for the development of strategies for studies in population genomics, association mapping and genomic prediction in this economical and ecologically important forest tree species.

In situ wood quality assessment in Douglas-fir

The genetic control and phenotypic and genotypic correlations among wood density, modulus of elasticity, height, diameter, and volume were assessed using 967 trees representing 20 unrelated 32-year-old coastal Douglas-fir full-sib families growing on four (spaced and pruned vs. control) comparable test sites. Generally, no significant differences were observed between treatments, indicating their limited effect at assessment time. Family effect did not differ for the growth traits; however, significant differences were observed for wood density and both in situ methods (drilling resistance and acoustic velocity). Growth and wood quality attributes, individually, produced high and positive phenotypic and genetic correlations; however, high and negative correlations were observed between individual variables belonging to the two suites of attributes. Individual tree heritabilities were low for growth (0.04 to 0.08) and modest to high for wood quality attributes (0.14 to 0.68). The observed heritabilities and phenotypic and genotypic correlations imply modest to strong genetic control; however, they operated in opposing direction. The significant and consistent genetic correlations between the in situ methods and wood density and stiffness support their use as a non-destructive and economic assessment approach. The reliability of the in situ assessments was verified through cumulative pith-to-bark wood density assessment, resulting in inconsistent genetic and phenotypic correlations for early growth years. These latter findings imply that caution should be used in employing these in situ techniques as early screening tools in breeding programs.

Performance of genomic prediction within and across generations in maritime pine

BackgroundGenomic selection (GS) is a promising approach for decreasing breeding cycle length in forest trees. Assessment of progeny performance and of the prediction accuracy of GS models over generations is therefore a key issue.ResultsA reference population of maritime pine (Pinus pinaster) with an estimated effective inbreeding population size (status number) of 25 was first selected with simulated data. This reference population (n = 818) covered three generations (G0, G1 and G2) and was genotyped with 4436 single-nucleotide polymorphism (SNP) markers. We evaluated the effects on prediction accuracy of both the relatedness between the calibration and validation sets and validation on the basis of progeny performance. Pedigree-based (best linear unbiased prediction, ABLUP) and marker-based (genomic BLUP and Bayesian LASSO) models were used to predict breeding values for three different traits: circumference, height and stem straightness. On average, the ABLUP model outperformed genomic prediction models, with a maximum difference in prediction accuracies of 0.12, depending on the trait and the validation method. A mean difference in prediction accuracy of 0.17 was found between validation methods differing in terms of relatedness. Including the progenitors in the calibration set reduced this difference in prediction accuracy to 0.03. When only genotypes from the G0 and G1 generations were used in the calibration set and genotypes from G2 were used in the validation set (progeny validation), prediction accuracies ranged from 0.70 to 0.85.ConclusionsThis study suggests that the training of prediction models on parental populations can predict the genetic merit of the progeny with high accuracy: an encouraging result for the implementation of GS in the maritime pine breeding program.

Variation in juvenile traits of natural black poplar (Populus nigra L.) clones in Turkey

Natural black poplar (Populus nigra L.) clones sampled from river courses were tested in the arid southeast region of Turkey, using a randomized complete block field design with four replications. Clones were laid out in row plots of eight ramets each. Height and apical dominance were assessed at age one year; diameter, survival, bole straightness and branchiness were measured at age two years. Clones differed significantly in survival, growth and quality traits. The results showed that promising clones exist in natural populations. Two commercial clones out of four did not grow as fast as the top new selection clones. For bole straightness, three commercial clones had significantly lower grading scores than the top best 14 clones. Principal components analysis indicated that growth, apical dominance and branching are the most important traits distinguishing black poplar clones. Diameter had a moderate correlation (0.34) with bole straightness. Relationships between geographic variables (elevation, latitude and longitude) with growth and stem quality traits were weak. Considerable genetic variation was observed among clones for all the traits. Genetic differences among the clones accounted for 27% (survival, bole straightness) to 39% (height) of the total variance. Broad-sense individual heritability ranged from 0.27 (survival) to 0.37 (apical dominance). Clonal mean heritabilities were higher than individual heritabilities and ranged from 0.60 (survival) to 0.82 (diameter), implying considerable gain could be realized via selective improvement methods.