Search

Targeted sequence capture coupled to high-throughput sequencing has become a powerful method for the study of genome-wide sequence variation. Following our recent development of a genome assembly for the Pink Ipê tree (Handroanthus impetiginosus), a widely distributed Neotropical timber species, we now report the development of a set of 24,751 capture probes for single-nucleotide polymorphisms (SNPs) characterization and genotyping across 18,216 distinct loci, sampling more than 10 Mbp of the species genome. This system identifies nearly 200,000 SNPs located inside or in close proximity to almost 14,000 annotated protein-coding genes, generating quality genotypic data in populations spanning wide geographic distances across the species native range. To provide recommendations for future developments of similar systems for highly heterozygous plant genomes we investigated issues such as probe design, sequencing coverage and bioinformatics, including the evaluation of the capture efficiency and a reassessment of the technical reproducibility of the assay for SNPs recall and genotyping precision. Our results highlight the value of a detailed probe screening on a preliminary genome assembly to produce reliable data for downstream genetic studies. This work should inspire and assist the development of similar genomic resources for other orphan crops and forest trees with highly heterozygous genomes.

Background: The advent of high-throughput genotyping technologies coupled to genomic prediction methods established a new paradigm to integrate genomics and breeding. We carried out whole-genome prediction and contrasted it to a genome-wide association study (GWAS) for growth traits in breeding populations of Eucalyptus benthamii (n =505) and Eucalyptus pellita (n =732). Both species are of increasing commercial interest for the development of germplasm adapted to environmental stresses., Results: Predictive ability reached 0.16 in E. benthamii and 0.44 in E. pellita for diameter growth. Predictive abilities using either Genomic BLUP or different Bayesian methods were similar, suggesting that growth adequately fits the infinitesimal model. Genomic prediction models using ~5000-10,000 SNPs provided predictive abilities equivalent to using all 13,787 and 19,506 SNPs genotyped in the E. benthamii and E. pellita populations, respectively. No difference was detected in predictive ability when different sets of SNPs were utilized, based on position (equidistantly genome-wide, inside genes, linkage disequilibrium pruned or on single chromosomes), as long as the total number of SNPs used was above ~5000. Predictive abilities obtained by removing relatedness between training and validation sets fell near zero for E. benthamii and were halved for E. pellita. These results corroborate the current view that relatedness is the main driver of genomic prediction, although some short-range historical linkage disequilibrium (LD) was likely captured for E. pellita. A GWAS identified only one significant association for volume growth in E. pellita, illustrating the fact that while genome-wide regression is able to account for large proportions of the heritability, very little or none of it is captured into significant associations using GWAS in breeding populations of the size evaluated in this study., Conclusions: This study provides further experimental data supporting positive prospects of using genome-wide data to capture large proportions of trait heritability and predict growth traits in trees with accuracies equal or better than those attainable by phenotypic selection. Additionally, our results document the superiority of the whole-genome regression approach in accounting for large proportions of the heritability of complex traits such as growth in contrast to the limited value of the local GWAS approach toward breeding applications in forest trees.

Background: Eucalyptus species are among the most planted hardwoods in the world because of their rapid growth, adaptability and valuable wood properties. The development and integration of genomic resources into breeding practice will be increasingly important in the decades to come. Bacterial artificial chromosome (BAC) libraries are key genomic tools that enable positional cloning of important traits, synteny evaluation, and the development of genome framework physical maps for genetic linkage and genome sequencing., Results: We describe the construction and characterization of two deep-coverage BAC libraries EG_Ba and EG_Bb obtained from nuclear DNA fragments of E. grandis (clone BRASUZ1) digested with HindIII and BstYI, respectively. Genome coverages of 17 and 15 haploid genome equivalents were estimated for EG_Ba and EG_Bb, respectively. Both libraries contained large inserts, with average sizes ranging from 135 Kb (Eg_Bb) to 157 Kb (Eg_Ba), very low extra-nuclear genome contamination providing a probability of finding a single copy gene ≥ 99.99%. Libraries were screened for the presence of several genes of interest via hybridizations to high-density BAC filters followed by PCR validation. Five selected BAC clones were sequenced and assembled using the Roche GS FLX technology providing the whole sequence of the E. grandis chloroplast genome, and complete genomic sequences of important lignin biosynthesis genes., Conclusions: The two E. grandis BAC libraries described in this study represent an important milestone for the advancement of Eucalyptus genomics and forest tree research. These BAC resources have a highly redundant genome coverage (> 15×), contain large average inserts and have a very low percentage of clones with organellar DNA or empty vectors. These publicly available BAC libraries are thus suitable for a broad range of applications in genetic and genomic research in Eucalyptus and possibly in related species of Myrtaceae, including genome sequencing, gene isolation, functional and comparative genomics. Because they have been constructed using the same tree (E. grandis BRASUZ1) whose full genome is being sequenced, they should prove instrumental for assembly and gap filling of the upcoming Eucalyptus reference genome sequence.

Growth traits in trees are fundamental components of adaptation in a forest ecosystem and of productivity in planted forests. A number of processes determine tree growth, which are controlled by genetic and epigenetic factors that respond dynamically to environmental signals throughout centuries. Advances in genomics have allowed an increased comprehension of the complex mechanisms of tree growth and adaptation. Yet, the application of genomics to improving forest productivity and sustainability still entails capturing a large proportion of the total genetic variation controlling the component traits. Nonetheless, genetics and genomics are unifying disciplines that will serve well to dissect the variables and mechanisms of tree growth and development.

Eucalyptus is the most widely planted hardwood crop in the tropical and subtropical world because of its superior growth, broad adaptability and multipurpose wood properties. Plantation forestry of Eucalyptus supplies high-quality woody biomass for several industrial applications while reducing the pressure on tropical forests and associated biodiversity. This review links current eucalypt breeding practices with existing and emerging genomic tools. A brief discussion provides a background to modern eucalypt breeding together with some current applications of molecular markers in support of operational breeding. Quantitative trait locus (QTL) mapping and genetical genomics are reviewed and an in-depth perspective is provided on the power of association genetics to dissect quantitative variation in this highly diverse organism. Finally, some challenges and opportunities to integrate genomic information into directional selective breeding are discussed in light of the upcoming draft of the Eucalyptus grandis genome. Given the extraordinary genetic variation that exists in the genus Eucalyptus, the ingenuity of most breeders, and the powerful genomic tools that have become available, the prospects of applied genomics in Eucalyptus forest production are encouraging.

Terpenes are economically and ecologically important phytochemicals. Their synthesis is controlled by the terpene synthase (TPS) gene family, which is highly diversified throughout the plant kingdom. The plant family Myrtaceae are characterised by especially high terpene concentrations, and considerable variation in terpene profiles. Many Myrtaceae are grown commercially for terpene products including the eucalypts Corymbia and Eucalyptus. Eucalyptus grandis has the largest TPS gene family of plants currently sequenced, which is largely conserved in the closely related E. globulus. However, the TPS gene family has been well studied only in these two eucalypt species. The recent assembly of two Corymbia citriodora subsp. variegata genomes presents an opportunity to examine the conservation of this important gene family across more divergent eucalypt lineages. Manual annotation of the TPS gene family in C. citriodora subsp. variegata revealed a similar overall number, and relative subfamily representation, to that previously reported in E. grandis and E. globulus. Many of the TPS genes were in physical clusters that varied considerably between Eucalyptus and Corymbia, with several instances of translocation, expansion/contraction and loss. Notably, there was greater conservation in the subfamilies involved in primary metabolism than those involved in secondary metabolism, likely reflecting different selective constraints. The variation in cluster size within subfamilies and the broad conservation between the eucalypts in the face of this variation are discussed, highlighting the potential contribution of selection, concerted evolution and stochastic processes. These findings provide the foundation to better understand terpene evolution within the ecologically and economically important Myrtaceae.

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. [ABSTRACT FROM AUTHOR]

Woody perennial angiosperms (i.e., hardwood trees) are polyphyletic in origin and occur in most angiosperm orders. Despite their independent origins, hardwoods have shared physiological, anatomical, and life history traits distinct from their herbaceous relatives. New high-throughput DNA sequencing platforms have provided access to numerous woody plant genomes beyond the early reference genomes of Populus and Eucalyptus , references that now include willow and oak, with pecan and chestnut soon to follow. Genomic studies within these diverse and undomesticated species have successfully linked genes to ecological, physiological, and developmental traits directly. Moreover, comparative genomic approaches are providing insights into speciation events while large-scale DNA resequencing of native collections is identifying population-level genetic diversity responsible for variation in key woody plant biology across and within species. Current research is focused on developing genomic prediction models for breeding, defining speciation and local adaptation, detecting and characterizing somatic mutations, revealing the mechanisms of gender determination and flowering, and application of systems biology approaches to model complex regulatory networks underlying quantitative traits. Emerging technologies such as single-molecule, long-read sequencing is being employed as additional woody plant species, and genotypes within species, are sequenced, thus enabling a comparative ("evo-devo") approach to understanding the unique biology of large woody plants. Resource availability, current genomic and genetic applications, new discoveries and predicted future developments are illustrated and discussed for poplar, eucalyptus, willow, oak, chestnut, and pecan. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

An abstract of the conference paper "Stability of Genomic Selection prediction models across ages and environments," by Juan J. Acosta and colleagues is presented.

The article offers information on the topics discussed at the International Union of Forestry Research Organizations (IUFRO) Tree Biotechnology Conference held in Bahia, Brazil from June 26-July 2, 2011. The conference focused on tree biotechnology and advances of genomics in regards to forest conservation, tree physiology, and molecular breeeding. It was attended by several scientists and foresters.