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Summary: Genome‐wide association studies (GWAS) in plants typically suffer from limited statistical power. An alternative to the logistical and cost challenge of increasing sample sizes is to gain power by meta‐analysis using information from independent studies.We carried out GWAS for growth traits with six single‐marker models and regional heritability mapping (RHM) in four Eucalyptus breeding populations independently and by Joint‐GWAS, using gene and segment‐based models, with data for 3373 individuals genotyped with a communal EUChip60KSNP platform.While single‐single nucleotide polymorphism (SNP) GWAS hardly detected significant associations at high‐stringency in each population, gene‐based Joint‐GWAS revealed nine genes significantly associated with tree height. Associations detected using single‐SNP GWAS, RHM and Joint‐GWAS set‐based models explained on average 3–20% of the phenotypic variance. Whole‐genome regression, conversely, captured 64–89% of the pedigree‐based heritability in all populations. Several associations independently detected for the same SNPs in different populations provided unprecedented GWAS validation results in forest trees. Rare and common associations were discovered in eight genes involved in cell wall biosynthesis and lignification.With the increasing adoption of genomic prediction of complex phenotypes using shared SNPs and much larger tree breeding populations, Joint‐GWAS approaches should provide increasing power to pinpoint discrete associations potentially useful toward tree breeding and molecular applications. [ABSTRACT FROM AUTHOR]

• 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. [ABSTRACT FROM AUTHOR]

The genome-wide heterozygosity at 9590 genes, all heterozygous in a single Eucalyptus grandis parent tree, was examined in a group of 28 S1 offspring. Heterozygosity ranged from 52-79%, averaging 65.5%, much higher than the 50% expected under random segregation, supporting the occurrence of strong (47%) selection against homozygosity. The expected pattern of heterozygosity from theoretical calculations and simulations for recessive detrimentals (pseudo-overdominance) and intrinsic heterozygote advantage was examined and compared with that observed. The observed patterns are consistent with at least several detrimental loci with large effects on both parental chromosomes of the 11 pairs. It is likely that 100 or more genes, many with substantial effects on viability, are contributing to this inbreeding depression. Although our genome-wide analysis of nearly 10 000 genes strongly suggested that pseudo-overdominance was responsible for the observed high inbreeding depression, heterozygote advantage could not be excluded. Finding inconvertible evidence of the cause of inbreeding depression still presents a difficult challenge. This study is the first theoretical examination of the genomic effect of inbreeding in a forest tree and provides an approach to analyze these data to determine the extent and cause of inbreeding depression across other plant genomes. [ABSTRACT FROM AUTHOR]

We used high-density single nucleotide polymorphism ( SNP) data and whole-genome pooled resequencing to examine the landscape of population recombination ( ρ) and nucleotide diversity ( ϴw), assess the extent of linkage disequilibrium ( r2) and build the highest density linkage maps for Eucalyptus., At the genome-wide level, linkage disequilibrium ( LD) decayed within c. 4-6 kb, slower than previously reported from candidate gene studies, but showing considerable variation from absence to complete LD up to 50 kb. A sharp decrease in the estimate of ρ was seen when going from short to genome-wide inter- SNP distances, highlighting the dependence of this parameter on the scale of observation adopted. Recombination was correlated with nucleotide diversity, gene density and distance from the centromere, with hotspots of recombination enriched for genes involved in chemical reactions and pathways of the normal metabolic processes., The high nucleotide diversity ( ϴw = 0.022) of E. grandis revealed that mutation is more important than recombination in shaping its genomic diversity ( ρ/ ϴw = 0.645). Chromosome-wide ancestral recombination graphs allowed us to date the split of E. grandis (1.7-4.8 million yr ago) and identify a scenario for the recent demographic history of the species., Our results have considerable practical importance to Genome Wide Association Studies ( GWAS), while indicating bright prospects for genomic prediction of complex phenotypes in eucalypt breeding. [ABSTRACT FROM AUTHOR]

We used whole genome resequencing of pooled individuals to develop a high-density single-nucleotide polymorphism ( SNP) chip for Eucalyptus. Genomes of 240 trees of 12 species were sequenced at 3.5× each, and 46 997 586 raw SNP variants were subject to multivariable filtering metrics toward a multispecies, genome-wide distributed chip content., Of the 60 904 SNPs on the chip, 59 222 were genotyped and 51 204 were polymorphic across 14 Eucalyptus species, providing a 96% genome-wide coverage with 1 SNP/12-20 kb, and 47 069 SNPs at ≤ 10 kb from 30 444 of the 33 917 genes in the Eucalyptus genome., Given the EUChip60K multi-species genotyping flexibility, we show that both the sample size and taxonomic composition of cluster files impact heterozygous call specificity and sensitivity by benchmarking against 'gold standard' genotypes derived from deeply sequenced individual tree genomes. Thousands of SNPs were shared across species, likely representing ancient variants arisen before the split of these taxa, hinting to a recent eucalypt radiation. We show that the variable SNP filtering constraints allowed coverage of the entire site frequency spectrum, mitigating SNP ascertainment bias., The EUChip60K represents an outstanding tool with which to address population genomics questions in Eucalyptus and to empower genomic selection, GWAS and the broader study of complex trait variation in eucalypts. [ABSTRACT FROM AUTHOR]

Summary [ABSTRACT FROM AUTHOR]

Contents 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. [ABSTRACT FROM AUTHOR]