Eucalyptus Breeding for Clonal Forestry

Characterization of glyphosate-tolerant genetically modified eucalyptus

Eucalyptus stands out as one of the most productive tree species for large-scale cultivation. However, like all cultivated crops, it requires specialized management practices, including the control of weeds, pathogens, and pests. Glyphosate is the most widely applied herbicide used in the essential weeding effort, and it ensures the sustainable management of eucalyptus cultivation in Brazil. Given the sensitivity of eucalyptus to glyphosate, existing weed control methods in young eucalyptus farms predominantly rely on protected mechanical or/and knapsack spraying. Both methods contribute to herbicide drift, which compromises tree yield and increases chemical waste due to uneven spraying. This study provides a detailed observation of the physiological parameters and long-term field performance of glyphosate-tolerant (HT), genetically modified (GM) eucalyptus developed by FuturaGene/Suzano S.A. and approved in Brazil for operational deployment. The HT GM eucalyptus events were meticulously evaluated to ensure high levels of glyphosate tolerance. This involved the direct application of herbicide on seedlings in greenhouse studies and on young trees in field conditions. The herbicide-treated GM eucalyptus in all trials demonstrated consistent growth and maintained physiological parameters comparable to their respective non-sprayed wild-type (WT) counterparts. The HT GM eucalyptus represents a significant advancement by enabling the direct application of glyphosate over the top of the trees to control the weeds within the planting row. This innovative approach minimizes the need for frequent mechanical and manual interventions, thereby lowering worker herbicide exposure, reducing the environmental impact of mechanical operations, and enhancing the overall efficiency and sustainability of HT GM eucalyptus stands.

Genetic relationship analysis and core collection construction of Eucalyptus grandis from Dongmen improved variety base: the largest eucalypt germplasm resource in China

BACKGROUND

Eucalyptus grandis, which was first comprehensively and systematically introduced to China in the 1980s, is one of the most important fast-growing tree species in the forestry industry. However, to date, no core collection has been selected from the germplasm resources of E. grandis based on growth and genetic relationship analysis.

RESULTS

In the present study, 545 individuals of E. grandis collected from 28 populations across 5 countries were selected for genetic diversity analysis using 16 selected SSR markers. The polymorphism information content (PIC) was employed to assess genetic diversity, yielding a mean value of 0.707. Genetic structure analysis was conducted on 492 individuals from 13 combined populations, revealing three clusters as the most suitable number. Principal coordinate analysis (PCoA) demonstrated that the populations were divided into three major clusters. Additionally, the analysis of molecular variance (AMOVA) indicated that the majority of variation occurred within populations.

CONCLUSIONS

Based on the criteria for screening the core collection, we constructed a population consisting of 158 individuals and created unique fingerprinting codes. These results provide a crucial theoretical foundation for the protection and utilization of germplasm resources of E. grandis in China, which will be helpful in the selection of genetically distant parents for future multigenerational hybridization programs.

Genome-wide analysis highlights genetic admixture in exotic germplasm resources of Eucalyptus and unexpected ancestral genomic composition of interspecific hybrids

Eucalyptus is an economically important genus comprising more than 890 species in different subgenera and sections. Approximately twenty species of subgenus Symphyomyrtus account for 95% of the world's planted eucalypts. Discrimination of closely related eucalypt taxa is challenging, consistent with their recent phylogenetic divergence and occasional hybridization in nature. Admixture, misclassification or mislabeling of Eucalyptus germplasm resources maintained as exotics have been suggested, although no reports are available. Moreover, hybrids with increased productivity and traits complementarity are planted worldwide, but little is known about their actual genomic ancestry. In this study we examined a set of 440 trees of 16 different Eucalyptus species and 44 interspecific hybrids of multi-species origin conserved in germplasm banks in Brazil. We used genome-wide SNP data to evaluate the agreement between the alleged phylogenetic classification of species and provenances as registered in their historical records, and their observed genetic clustering derived from SNP data. Genetic structure analyses correctly assigned each of the 16 species to a different cluster although the PCA positioning of E. longirostrata was inconsistent with its current taxonomy. Admixture was present for closely related species' materials derived from local germplasm banks, indicating unintended hybridization following germplasm introduction. Provenances could be discriminated for some species, indicating that SNP-based discrimination was directly proportional to geographical distance, consistent with an isolation-by-distance model. SNP-based genomic ancestry analysis showed that the majority of the hybrids displayed realized genomic composition deviating from the expected ones based on their pedigree records, consistent with admixture in their parents and pervasive genome-wide directional selection toward the fast-growing E. grandis genome. SNP data in support of tree breeding provide precise germplasm identity verification, and allow breeders to objectively recognize the actual ancestral origin of superior hybrids to more realistically guide the program toward the development of the desired genetic combinations.

Haplogenome assembly reveals structural variation in Eucalyptus interspecific hybrids

BACKGROUND

De novo phased (haplo)genome assembly using long-read DNA sequencing data has improved the detection and characterization of structural variants (SVs) in plant and animal genomes. Able to span across haplotypes, long reads allow phased, haplogenome assembly in highly outbred organisms such as forest trees. Eucalyptus tree species and interspecific hybrids are the most widely planted hardwood trees with F1 hybrids of Eucalyptus grandis and E. urophylla forming the bulk of fast-growing pulpwood plantations in subtropical regions. The extent of structural variation and its effect on interspecific hybridization is unknown in these trees. As a first step towards elucidating the extent of structural variation between the genomes of E. grandis and E. urophylla, we sequenced and assembled the haplogenomes contained in an F1 hybrid of the two species.

FINDINGS

Using Nanopore sequencing and a trio-binning approach, we assembled the separate haplogenomes (566.7 Mb and 544.5 Mb) to 98.0% BUSCO completion. High-density SNP genetic linkage maps of both parents allowed scaffolding of 88.0% of the haplogenome contigs into 11 pseudo-chromosomes (scaffold N50 of 43.8 Mb and 42.5 Mb for the E. grandis and E. urophylla haplogenomes, respectively). We identify 48,729 SVs between the two haplogenomes providing the first detailed insight into genome structural rearrangement in these species. The two haplogenomes have similar gene content, 35,572 and 33,915 functionally annotated genes, of which 34.7% are contained in genome rearrangements.

CONCLUSIONS

Knowledge of SV and haplotype diversity in the two species will form the basis for understanding the genetic basis of hybrid superiority in these trees.

Accumulated effects of factors determining plant development from somatic embryos of Abies nordmanniana and Abies bornmuelleriana

Despite a much later inception of somatic embryogenesis (SE) propagation protocols for gymnosperms than for angiosperm species, SE is becoming increasingly important due to its applications for commercial forestry. For many conifers, there are however still major bottlenecks in the SE plant production process limiting the use of SE for forestry operations, Christmas tree production and research projects. In the present case study, the effects on plant growth from different cultural factors applied during the SE developmental process were studied in two conifer species of high value for Christmas tree production. Seven clones of Abies nordmanniana and two clones of Abies bornmuelleriana were included in the study. Accumulated effects from cultural treatments were recorded from the start of germination of mature embryos of different quality scores through development into plants in the third growing period. Experimental factors of the cultural treatments included were: germination temperature, germination time, light conditions, survival ex vitro and traits for plant growth and vitality. The results reveal that most of the studied experimental factors influenced plant growth during the first three years however their relative importance was different. Plant survival rate at end of the nursery stage was strongly impacted by germination temperature (p<0.001), initial embryo score (p=0.007), clone (p<0.001) and to a lesser extend week of germination (p=0.017). This case-study highlights and quantifies the strong interrelation between the developmental steps of somatic embryogenesis and show the importance of considering all cultural steps when optimizing SE plant production protocols.

Exploring leaf hydraulic traits to predict drought tolerance of Eucalyptus clones

Ongoing changes in climate, and the consequent mortality of natural and cultivated forests across the globe, highlight the urgent need to understand the plant traits associated with greater tolerance to drought. Here, we aimed at assessing key foliar traits, with a focus on the hydraulic component, that could confer a differential ability to tolerate drought in three commercial hybrids of the most important Eucalyptus species utilized in tropical silviculture: E. urophyla, E. grandis and E. camaldulensis. All genotypes exhibited similar water potential when the 90% stomatal closure (Ψgs90) occurs with Ψgs90 always preceding the start of embolism events. The drought-tolerant hybrid showed a higher leaf resistance to embolism, but the leaf hydraulic efficiency was similar among all genotypes. Other traits presented by the drought-tolerant hybrid were a higher cell wall reinforcement, lower value of osmotic potential at full turgor and greater bulk modulus of elasticity. We also identified that the leaf capacitance after the turgor loss, the ratio between cell wall thickness (t) and lumen breadth (b) ratio (t/b)3, and the minimal conductance might be good proxies for screening drought-tolerant Eucalyptus genotypes. Our findings suggest that xylem resistance to embolism can be an important component of drought tolerance in Eucalyptus in addition to other traits aimed at delaying the development of high tensions in the xylem. Highlight Drought tolerance in tropical Eucalyptus hybrids encompasses a high leaf resistance to embolism and a suite of traits aimed at delaying the development of high tensions in the xylem.

Integrating genome-wide association mapping of additive and dominance genetic effects to improve genomic prediction accuracy in Eucalyptus

Genome-wide association studies (GWAS) is a powerful and widely used approach to decipher the genetic control of complex traits. Still, a significant challenge for dissecting quantitative traits in forest trees is statistical power. This study uses a population consisting of 1,123 samples derived from two successive generations of crosses between Eucalyptus grandis (W. Hill) and E. urophylla (S.T. Blake). All samples have been phenotyped for growth and wood property traits and genotyped using the EuChip60K chip, yielding 37,832 informative single nucleotide polymorphisms (SNPs). We use multi-locus GWAS models to assess additive and dominance effects to identify markers associated with growth and wood property traits in the eucalypt hybrids. Additive and dominance association models identified 78 and 82 significant SNPs across all traits, respectively, which captured between 39 and 86% of the genomic-based heritability. We also used SNPs identified from the GWAS and SNPs using less stringent significance thresholds to evaluate predictive abilities in a genomic selection framework. Genomic selection models based on the top 1% SNPs captured a substantially greater proportion of the genetic variance of traits compared with when we used all SNPs for model training. The prediction ability of estimated breeding values improved significantly for all traits when using either the top 1% SNPs or SNPs identified using a relaxed p value threshold (p < 10^-3 ). This study also highlights the added value of incorporating dominance effects for identifying genomic regions controlling growth traits in trees. Moreover, integrating GWAS results into genomic selection method provides enhanced power relative to discrete associations for identifying genomic variation potentially valuable for forest tree breeding.

Assessing the expected response to genomic selection of individuals and families in Eucalyptus breeding with an additive-dominant model

We report a genomic selection (GS) study of growth and wood quality traits in an outbred F₂ hybrid Eucalyptus population (n=768) using high-density single-nucleotide polymorphism (SNP) genotyping. Going beyond previous reports in forest trees, models were developed for different selection targets, namely, families, individuals within families and individuals across the entire population using a genomic model including dominance. To provide a more breeder-intelligible assessment of the performance of GS we calculated the expected response as the percentage gain over the population average expected genetic value (EGV) for different proportions of genomically selected individuals, using a rigorous cross-validation (CV) scheme that removed relatedness between training and validation sets. Predictive abilities (PAs) were 0.40-0.57 for individual selection and 0.56-0.75 for family selection. PAs under an additive+dominance model improved predictions by 5 to 14% for growth depending on the selection target, but no improvement was seen for wood traits. The good performance of GS with no relatedness in CV suggested that our average SNP density (~25 kb) captured some short-range linkage disequilibrium. Truncation GS successfully selected individuals with an average EGV significantly higher than the population average. Response to GS on a per year basis was ~100% more efficient than by phenotypic selection and more so with higher selection intensities. These results contribute further experimental data supporting the positive prospects of GS in forest trees. Because generation times are long, traits are complex and costs of DNA genotyping are plummeting, genomic prediction has good perspectives of adoption in tree breeding practice.

Evaluating the accuracy of genomic prediction of growth and wood traits in two Eucalyptus species and their F1 hybrids

BACKGROUND

Genomic prediction is a genomics assisted breeding methodology that can increase genetic gains by accelerating the breeding cycle and potentially improving the accuracy of breeding values. In this study, we use 41,304 informative SNPs genotyped in a Eucalyptus breeding population involving 90 E.grandis and 78 E.urophylla parents and their 949 F1 hybrids to develop genomic prediction models for eight phenotypic traits - basic density and pulp yield, circumference at breast height and height and tree volume scored at age three and six years. We assessed the impact of different genomic prediction methods, the composition and size of the training and validation set and the number and genomic location of SNPs on the predictive ability (PA).

RESULTS

Heritabilities estimated using the realized genomic relationship matrix (GRM) were considerably higher than estimates based on the expected pedigree, mainly due to inconsistencies in the expected pedigree that were readily corrected by the GRM. Moreover, the GRM more precisely capture Mendelian sampling among related individuals, such that the genetic covariance was based on the true proportion of the genome shared between individuals. PA improved considerably when increasing the size of the training set and by enhancing relatedness to the validation set. Prediction models trained on pure species parents could not predict well in F1 hybrids, indicating that model training has to be carried out in hybrid populations if one is to predict in hybrid selection candidates. The different genomic prediction methods provided similar results for all traits, therefore either GBLUP or rrBLUP represents better compromises between computational time and prediction efficiency. Only slight improvement was observed in PA when more than 5000 SNPs were used for all traits. Using SNPs in intergenic regions provided slightly better PA than using SNPs sampled exclusively in genic regions.

CONCLUSIONS

The size and composition of the training set and number of SNPs used are the two most important factors for model prediction, compared to the statistical methods and the genomic location of SNPs. Furthermore, training the prediction model based on pure parental species only provide limited ability to predict traits in interspecific hybrids. Our results provide additional promising perspectives for the implementation of genomic prediction in Eucalyptus breeding programs by the selection of interspecific hybrids.

Biotechnology for bioenergy dedicated trees: meeting future energy demands

With the increase in human demands for energy, purpose-grown woody crops could be part of the global renewable energy solution, especially in geographical regions where plantation forestry is feasible and economically important. In addition, efficient utilization of woody feedstocks would engage in mitigating greenhouse gas emissions, decreasing the challenge of food and energy security, and resolving the conflict between land use for food or biofuel production. This review compiles existing knowledge on biotechnological and genomics-aided improvements of biomass performance of purpose-grown poplar, willow, eucalyptus and pine species, and their relative hybrids, for efficient and sustainable bioenergy applications. This includes advancements in tree in vitro regeneration, and stable expression or modification of selected genes encoding desirable traits, which enhanced growth and yield, wood properties, site adaptability, and biotic and abiotic stress tolerance. Genetic modifications used to alter lignin/cellulose/hemicelluloses ratio and lignin composition, towards effective lignocellulosic feedstock conversion into cellulosic ethanol, are also examined. Biotech-trees still need to pass challengeable regulatory authorities’ processes, including biosafety and risk assessment analyses prior to their commercialization release. Hence, strategies developed to contain transgenes, or to mitigate potential transgene flow risks, are discussed.

Regional heritability mapping and genome-wide association identify loci for complex growth, wood and disease resistance traits in Eucalyptus

Although genome-wide association studies (GWAS) have provided valuable insights into the decoding of the relationships between sequence variation and complex phenotypes, they have explained little heritability. Regional heritability mapping (RHM) provides heritability estimates for genomic segments containing both common and rare allelic effects that individually contribute too little variance to be detected by GWAS. We carried out GWAS and RHM for seven growth, wood and disease resistance traits in a breeding population of 768 Eucalyptus hybrid trees using EuCHIP60K. Total genomic heritabilities accounted for large proportions (64-89%) of pedigree-based trait heritabilities, providing additional evidence that complex traits in eucalypts are controlled by many sequence variants across the frequency spectrum, each with small contributions to the phenotypic variance. RHM detected 26 quantitative trait loci (QTLs) encompassing 2191 single nucleotide polymorphisms (SNPs), whereas GWAS detected 13 single SNP-trait associations. RHM and GWAS QTLs individually explained 5-15% and 4-6% of the genomic heritability, respectively. RHM was superior to GWAS in capturing larger proportions of genomic heritability. Equated to previously mapped QTLs, our results highlighted genomic regions for further examination towards gene discovery. RHM-QTLs bearing a combination of common and rare variants could be useful enhancements to incorporate prior knowledge of the underlying genetic architecture in genomic prediction models.