Evaluation of In-Field Inoculation Methods for Characterization of Macadamia Germplasm to Husk Spot Incidence and Severity.

Husk spot, a fungal disease of macadamia pericarps (Pseudocercospora macadamiae), induces premature abscission in several major commercial cultivars. Breeding for resistance to husk spot is a priority of the Australian macadamia industry. Due to the large tree size of macadamia and high numbers of progeny in breeding populations, inoculating for resistance screening is laborious and time consuming. Previously utilized methods included direct applications of P. macadamiae suspensions and the hanging of bags of diseased husks above developing fruit in tree canopies. In this study, both methods were modified to allow for efficient application in large-scale breeding populations, and their efficacy was evaluated. Two quantities of diseased husk per bag, 'large' (75 g) and 'small' (30 g), and two concentrations of sprayed P. macadamiae suspensions, 'stock' (5 × 105 propagules/ml) and 'dilute' (2.5 × 105 propagules/ml), were tested across two fruiting seasons. Treatments were compared against a control (sterile water) in commercial cultivars A38 and A4. Husk spot incidence and severity produced by small bags were significantly affected by season. A significant season effect was less common for other treatments. All four treatments infected over 50% of target fruit in each season, but the highest husk spot incidence across both seasons (≥85%) was produced from large bags. Overall, the large bags were the most reliable method for infection of target fruit. Results also demonstrate the importance of considering the effect of season when selecting husk spot inoculation methods.

The influence of genetic structure on phenotypic diversity in the Australian mango (Mangifera indica) gene pool.

Genomic selection is a promising breeding technique for tree crops to accelerate the development of new cultivars. However, factors such as genetic structure can create spurious associations between genotype and phenotype due to the shared history between populations with different trait values. Genetic structure can therefore reduce the accuracy of the genotype to phenotype map, a fundamental requirement of genomic selection models. Here, we employed 272 single nucleotide polymorphisms from 208 Mangifera indica accessions to explore whether the genetic structure of the Australian mango gene pool explained variation in trunk circumference, fruit blush colour and intensity. Multiple population genetic analyses indicate the presence of four genetic clusters and show that the most genetically differentiated cluster contains accessions imported from Southeast Asia (mainly those from Thailand). We find that genetic structure was strongly associated with three traits: trunk circumference, fruit blush colour and intensity in M. indica. This suggests that the history of these accessions could drive spurious associations between loci and key mango phenotypes in the Australian mango gene pool. Incorporating such genetic structure in associations between genotype and phenotype can improve the accuracy of genomic selection, which can assist the future development of new cultivars.

Multi-environment genomic prediction for soluble solids content in peach (Prunus persica).

Genotype-by-environment interaction (G × E) is a common phenomenon influencing genetic improvement in plants, and a good understanding of this phenomenon is important for breeding and cultivar deployment strategies. However, there is little information on G × E in horticultural tree crops, mostly due to evaluation costs, leading to a focus on the development and deployment of locally adapted germplasm. Using sweetness (measured as soluble solids content, SSC) in peach/nectarine assessed at four trials from three US peach-breeding programs as a case study, we evaluated the hypotheses that (i) complex data from multiple breeding programs can be connected using GBLUP models to improve the knowledge of G × E for breeding and deployment and (ii) accounting for a known large-effect quantitative trait locus (QTL) improves the prediction accuracy. Following a structured strategy using univariate and multivariate models containing additive and dominance genomic effects on SSC, a model that included a previously detected QTL and background genomic effects was a significantly better fit than a genome-wide model with completely anonymous markers. Estimates of an individual's narrow-sense and broad-sense heritability for SSC were high (0.57-0.73 and 0.66-0.80, respectively), with 19-32% of total genomic variance explained by the QTL. Genome-wide dominance effects and QTL effects were stable across environments. Significant G × E was detected for background genome effects, mostly due to the low correlation of these effects across seasons within a particular trial. The expected prediction accuracy, estimated from the linear model, was higher than the realised prediction accuracy estimated by cross-validation, suggesting that these two parameters measure different qualities of the prediction models. While prediction accuracy was improved in some cases by combining data across trials, particularly when phenotypic data for untested individuals were available from other trials, this improvement was not consistent. This study confirms that complex data can be combined into a single analysis using GBLUP methods to improve understanding of G × E and also incorporate known QTL effects. In addition, the study generated baseline information to account for population structure in genomic prediction models in horticultural crop improvement.

Genomic selection and genetic gain for nut yield in an Australian macadamia breeding population.

BACKGROUND: Improving yield prediction and selection efficiency is critical for tree breeding. This is vital for macadamia trees with the time from crossing to production of new cultivars being almost a quarter of a century. Genomic selection (GS) is a useful tool in plant breeding, particularly with perennial trees, contributing to an increased rate of genetic gain and reducing the length of the breeding cycle. We investigated the potential of using GS methods to increase genetic gain and accelerate selection efficiency in the Australian macadamia breeding program with comparison to traditional breeding methods. This study evaluated the prediction accuracy of GS in a macadamia breeding population of 295 full-sib progeny from 32 families (29 parents, reciprocals combined), along with a subset of parents. Historical yield data for tree ages 5 to 8 years were used in the study, along with a set of 4113 SNP markers. The traits of focus were average nut yield from tree ages 5 to 8 years and yield stability, measured as the standard deviation of yield over these 4 years. GBLUP GS models were used to obtain genomic estimated breeding values for each genotype, with a five-fold cross-validation method and two techniques: prediction across related populations and prediction across unrelated populations. RESULTS: Narrow-sense heritability of yield and yield stability was low (h2 = 0.30 and 0.04, respectively). Prediction accuracy for yield was 0.57 for predictions across related populations and 0.14 when predicted across unrelated populations. Accuracy of prediction of yield stability was high (r = 0.79) for predictions across related populations. Predicted genetic gain of yield using GS in related populations was 474 g/year, more than double that of traditional breeding methods (226 g/year), due to the halving of generation length from 8 to 4 years. CONCLUSIONS: The results of this study indicate that the incorporation of GS for yield into the Australian macadamia breeding program may accelerate genetic gain due to reduction in generation length, though the cost of genotyping appears to be a constraint at present.

Wild Origins of Macadamia Domestication Identified Through Intraspecific Chloroplast Genome Sequencing.

Identifying the geographic origins of crops is important for the conservation and utilization of novel genetic variation. Even so, the origins of many food crops remain elusive. The tree nut crop macadamia has a remarkable domestication history, from subtropical rain forests in Australia through Hawaii to global cultivation all within the last century. The industry is based primarily on Macadamia integrifolia and M. integrifolia-M. tetraphylla hybrid cultivars with Hawaiian cultivars the main contributors to world production. Sequence data from the chloroplast genome assembled using a genome skimming strategy was used to determine population structure among remnant populations of the main progenitor species, M. integrifolia. Phylogenetic analysis of a 506 bp chloroplast SNP alignment from 64 wild and cultivated accessions identified phylogeographic structure and deep divergences between clades providing evidence for historical barriers to seed dispersal. High levels of variation were detected among wild accessions. Most Hawaiian cultivars, however, shared a single chlorotype that was also present at two wild sites at Mooloo and Mt Bauple from the northernmost distribution of the species in south-east Queensland. Our results provide evidence for a maternal genetic bottleneck during early macadamia domestication, and pinpoint the likely source of seed used to develop the Hawaiian cultivars. The extensive variability and structuring of M. integrifolia chloroplast genomic variation detected in this study suggests much unexploited genetic diversity is available for improvement of this recently domesticated crop.

Prediction of genetic value for sweet cherry fruit maturity among environments using a 6K SNP array.

The timing of fruit maturity is an important trait in sweet cherry production and breeding. Phenotypic variation for phenology of fruit maturity in sweet cherry appears to be under strong genetic control, but that control might be complicated by phenotypic instability across environments. Although such genotype-by-environment interaction (G × E) is a common phenomenon in crop plants, knowledge about it is lacking for fruit maturity timing and other sweet cherry traits. In this study, 1673 genome-wide SNP markers were used to estimate genomic relationships among 597 weakly pedigree-connected individuals evaluated over two seasons at three locations in Europe and one location in the USA, thus sampling eight 'environments'. The combined dataset enabled a single meta-analysis to investigate the environmental stability of genomic predictions. Linkage disequilibrium among marker loci declined rapidly with physical distance, and ordination of the relationship matrix suggested no strong structure among germplasm. The most parsimonious G × E model allowed heterogeneous genetic variance and pairwise covariances among environments. Narrow-sense genomic heritability was very high (0.60-0.83), as was accuracy of predicted breeding values (>0.62). Average correlation of additive effects among environments was high (0.96) and breeding values were highly correlated across locations. Results indicated that genomic models can be used in cherry to accurately predict date of fruit maturity for untested individuals in new environments. Limited G × E for this trait indicated that phenotypes of individuals will be stable across similar environments. Equivalent analyses for other sweet cherry traits, for which multiple years of data are commonly available among breeders and cultivar testers, would be informative for predicting performance of elite selections and cultivars in new environments.

Correction to "Whole genome shotgun sequences for microsatellite discovery and application in cultivated and wild Macadamia (Proteaceae)".

[This corrects the article DOI: 10.3732/apps.1300089.].

Cost and accuracy of advanced breeding trial designs in apple.

Trialing advanced candidates in tree fruit crops is expensive due to the long-term nature of the planting and labor-intensive evaluations required to make selection decisions. How closely the trait evaluations approximate the true trait value needs balancing with the cost of the program. Designs of field trials of advanced apple candidates in which reduced number of locations, the number of years and the number of harvests per year were modeled to investigate the effect on the cost and accuracy in an operational breeding program. The aim was to find designs that would allow evaluation of the most additional candidates while sacrificing the least accuracy. Critical percentage difference, response to selection, and correlated response were used to examine changes in accuracy of trait evaluations. For the quality traits evaluated, accuracy and response to selection were not substantially reduced for most trial designs. Risk management influences the decision to change trial design, and some designs had greater risk associated with them. Balancing cost and accuracy with risk yields valuable insight into advanced breeding trial design. The methods outlined in this analysis would be well suited to other horticultural crop breeding programs.

Whole genome shotgun sequences for microsatellite discovery and application in cultivated and wild Macadamia (Proteaceae).

PREMISE OF THE STUDY: Next-generation sequencing (NGS) data are widely used for single-nucleotide polymorphism discovery and genetic marker development in species with limited available genome information. We developed microsatellite primers for the Proteaceae nut crop species Macadamia integrifolia and assessed cross-species transferability in all congeners to investigate genetic identification of cultivars and gene flow. • METHODS AND RESULTS: Primers were designed from both raw and assembled Illumina NGS paired-end reads. The final 12 microsatellite markers selected were polymorphic among wild individuals of all four Macadamia species-M. integrifolia, M. tetraphylla, M. ternifolia, and M. jansenii-and in commercial macadamia cultivars including hybrids. • CONCLUSIONS: We demonstrate the utility of raw and assembled Illumina NGS reads from total genomic DNA for the rapid development of microsatellites in Macadamia. These primers will facilitate future studies of population structure, hybridization, parentage, and cultivar identification in cultivated and wild Macadamia populations.

THE RELATIONSHIP BETWEEN CROSS SUCCESS AND SPATIAL PROXIMITY OF EUCALYPTUS GLOBULUS SSP. GLOBULUS PARENTS.

The genetic structure of Eucalyptus globulus forest was examined using progeny vigor as an indirect measure of parental relatedness. Seven trees were crossed with pollen from trees: 0 m (seifing); 21 m (nearest flowering neighbors), 250 m, 500 m, 1 km, 10 km, and 100 km away from the female. Only selfing depressed seed set. Growth of the 21 m progenies was intermediate to selfing and the longer distance pollinations, suggesting tight family clusters occur due to limited seed dispersal. Under this structure biparental inbreeding may be common, however, the cumulative impact of inbreeding seems negligible as relatedness did not appear to decline with distance between mates beyond 50 m.

POSTDISPERSAL SELECTION FOLLOWING MIXED MATING IN EUCALYPTUS REGNANS.

Eucalyptus regnans is a mass flowering, tall forest tree of southeastern Australia with a mixed mating system. A field trial containing randomized single tree plots of self, outcross, and naturally open-pollinated (OP) progenies of 13 parents from two natural populations was surveyed over 15 yr. Inbreeding depression in survival at 15 years was 67% for selfs, one of the highest levels reported for a tree species, and differed little between populations. OP progenies were intermediate and the difference in fitness among the three cross types indicated that at planting, 59% were derived from outcrossing. However, with selection against the inbred progenies, this increased to 83% by 15 yr of age. Most selection against selfs occurred after four years, coincident with canopy closure and the apparent onset of intense competition.