Stable isotope dilution assay and HS-SPME-GCMS quantification of key aroma volatiles of Australian pineapple (Ananas comosus) cultivars.

Pineapple aroma is one of the most important sensory quality traits that influences consumer purchasing patterns. Reported in this paper is a high throughput method to quantify in a single analysis the key volatile organic compounds that contribute to the aroma of pineapple cultivars grown in Australia. The method constituted stable isotope dilution analysis in conjunction with headspace solid-phase microextraction coupled with gas-chromatography mass spectrometry. Deuterium labelled analogues of the target analytes purchased commercially were used as internal standards. Twenty-six volatile organic compounds were targeted for quantification and the resulting calibration functions of the matrix -matched validated method had determination coefficients (R2) ranging from 0.9772 to 0.9999. The method was applied to identify the key aroma volatile compounds produced by popular pineapple cultivars such as 'Aus Carnival', 'Aus Festival', 'Aus Jubilee', 'Aus Smooth (Smooth Cayenne)' and 'Aussie Gold (73-50)', grown in Queensland, Australia. Pineapple cultivars varied in its content and composition of free volatile components, which were predominantly comprised of esters, followed by terpenes, alcohols, aldehydes, and ketones.

Genotype-by-environment and QTL-by-environment interactions in sweet cherry (Prunus avium L.) for flowering date.

In sweet cherry (Prunus avium L.), flowering date is strongly dependent on the environment conditions and, therefore, is a trait of major interest for adaptation to climate change. Such trait can be influenced by genotype-by-environment interaction (G×E), that refers to differences in the response of genotypes to different environments. If not taken into account, G×E can reduce selection accuracy and overall genetic gain. However, little is known about G×E in fruit tree species. Flowering date is a highly heritable and polygenic trait for which many quantitative trait loci (QTLs) have been identified. As for the overall genetic performance, differential expression of QTLs in response to environment (QTL-by-environment interaction, QTL×E) can occur. The present study is based on the analysis of a multi-environment trial (MET) suitable for the study of G×E and QTL×E in sweet cherry. It consists of a sweet cherry F1 full-sib family (n = 121) derived from the cross between cultivars 'Regina' and 'Lapins' and planted in two copies in five locations across four European countries (France, Italy, Slovenia and Spain) covering a large range of climatic conditions. The aim of this work was to study the effect of the environment on flowering date and estimate G×E, to carry QTL detection in different environments in order to study the QTL stability across environments and to estimate QTL×E. A strong effect of the environment on flowering date and its genetic control was highlighted. Two large-effect and environment-specific QTLs with significant QTL×E were identified on linkage groups (LGs) 1 and 4. This work gives new insights into the effect of the environment on a trait of main importance in one of the most economically important fruit crops in temperate regions. Moreover, molecular markers were developed for flowering date and a strategy consisting in using specific markers for warm or cold regions was proposed to optimize marker-assisted selection (MAS) in sweet cherry breeding programs.

Review of the Aroma Chemistry of Pineapple (Ananas comosus).

Pineapple (Ananas comosus), one of the most flavorful and popular tropical fruits consumed worldwide, is known to contain many volatile organic compounds (VOCs) at varying concentrations. Much attention has been paid to understand which VOC plays a significant role in the sensory aroma notes of the fruit. Though, nearly 480 VOCs have been identified to date using different analytical techniques, only 40 compounds are reported to contribute to the unique flavor of pineapple. A consolidated database of the reported VOCs and key aroma compounds of pineapple is currently not available. This review discusses the available published data regarding the analytical methodologies, volatile profile of different varieties of pineapple at different maturities, and their characteristic aroma compounds. The output of this review is a subset of key pineapple aroma volatiles that can be targeted in analytical method development for utilization in varietal improvement or other research of pineapple.

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.

Signatures of selection in recently domesticated macadamia.

Macadamia is a high value nut crop that is recently domesticated, ideal for testing the effect of artificial selection. Here, we sequence the genome of Hawaiian cultivar 'Kau' and assemble into 794 Mb in 14 pseudo-chromosomes with 37,728 genes. Genome analysis reveals a whole-genome duplication event, occurred 46.8 million years ago. Gene expansions occurred in gene families involves in fatty acid biosynthesis. Gene duplication of MADS-Box transcription factors in proanthocyanidin biosynthesis are relevant for seed coat development. Genome re-sequencing of 112 accessions reveals the origin of Hawaiian cultivars from Mount Bauple in southeast Queensland in Australia. Selective sweeps are detected in macadamia cultivars, including genes involved in fatty acid biosynthesis, seed coat development, and heat stress response. Such strong effects of artificial selection in few generations reveals the genomic basis for 'one-step operation' for clonal crop domestication. The knowledge gained could accelerate domestication of new crops from wild species.

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.

RosBREED: bridging the chasm between discovery and application to enable DNA-informed breeding in rosaceous crops.

The Rosaceae crop family (including almond, apple, apricot, blackberry, peach, pear, plum, raspberry, rose, strawberry, sweet cherry, and sour cherry) provides vital contributions to human well-being and is economically significant across the U.S. In 2003, industry stakeholder initiatives prioritized the utilization of genomics, genetics, and breeding to develop new cultivars exhibiting both disease resistance and superior horticultural quality. However, rosaceous crop breeders lacked certain knowledge and tools to fully implement DNA-informed breeding-a "chasm" existed between existing genomics and genetic information and the application of this knowledge in breeding. The RosBREED project ("Ros" signifying a Rosaceae genomics, genetics, and breeding community initiative, and "BREED", indicating the core focus on breeding programs), addressed this challenge through a comprehensive and coordinated 10-year effort funded by the USDA-NIFA Specialty Crop Research Initiative. RosBREED was designed to enable the routine application of modern genomics and genetics technologies in U.S. rosaceous crop breeding programs, thereby enhancing their efficiency and effectiveness in delivering cultivars with producer-required disease resistances and market-essential horticultural quality. This review presents a synopsis of the approach, deliverables, and impacts of RosBREED, highlighting synergistic global collaborations and future needs. Enabling technologies and tools developed are described, including genome-wide scanning platforms and DNA diagnostic tests. Examples of DNA-informed breeding use by project participants are presented for all breeding stages, including pre-breeding for disease resistance, parental and seedling selection, and elite selection advancement. The chasm is now bridged, accelerating rosaceous crop genetic improvement.

Chromosome-Scale Assembly and Annotation of the Macadamia Genome (Macadamia integrifolia HAES 741).

Macadamia integrifolia is a representative of the large basal eudicot family Proteaceae and the main progenitor species of the Australian native nut crop macadamia. Since its commercialisation in Hawaii fewer than 100 years ago, global production has expanded rapidly. However, genomic resources are limited in comparison to other horticultural crops. The first draft assembly of M. integrifolia had good coverage of the functional gene space but its high fragmentation has restricted its use in comparative genomics and association studies. Here we have generated an improved assembly of cultivar HAES 741 (4,094 scaffolds, 745 Mb, N50 413 kb) using a combination of Illumina paired and PacBio long read sequences. Scaffolds were anchored to 14 pseudo-chromosomes using seven genetic linkage maps. This assembly has improved contiguity and coverage, with >120 Gb of additional sequence. Following annotation, 34,274 protein-coding genes were predicted, representing 90% of the expected gene content. Our results indicate that the macadamia genome is repetitive and heterozygous. The total repeat content was 55% and genome-wide heterozygosity, estimated by read mapping, was 0.98% or an average of one SNP per 102 bp. This is the first chromosome-scale genome assembly for macadamia and the Proteaceae. It is expected to be a valuable resource for breeding, gene discovery, conservation and evolutionary genomics.

Genetic Structure of Wild Germplasm of Macadamia: Species Assignment, Diversity and Phylogeographic Relationships.

Macadamia is an Australian native rainforest tree that has been domesticated and traded internationally for its premium nuts. Common cultivars rely upon a limited gene pool that has exploited only two of the four species. Introducing a more diverse germplasm will broaden the genetic base for future crop improvement and better adaptation for changing environments. This study investigated the genetic structure of 302 accessions of wild germplasm using 2872 SNP and 8415 silicoDArT markers. Structure analysis and principal coordinate analysis (PCoA) assigned the 302 accessions into four distinct groups: (i) Macadamia integrifolia, (ii) M. tetraphylla, and (iii) M. jansenii and M. ternifolia, and (iv) admixtures or hybrids. Assignment of the four species matched well with previous characterisations, except for one M. integrifolia and four M. tetraphylla accessions. Using SNP markers, 94 previously unidentified accessions were assigned into the four distinct groups. Finally, 287 accessions were identified as pure examples of one of the four species and 15 as hybrids of M. integrifolia and M. tetraphylla. The admixed accessions showed the highest genetic diversity followed by M. integrifolia, while M. ternifolia and M. jansenii accessions were the least diverse. Mantel test analysis showed a significant correlation between genetic and geographic distance for M. integrifolia (r = 0.51, p = 0.05) and a positive but not significant correlation for M. tetraphylla (r = 0.45, p = 0.06). This study provides a population genetics overview of macadamia germplasm as a background for a conservation strategy and provides directions for future macadamia breeding.

Genome-wide association studies for yield component traits in a macadamia breeding population.

BACKGROUND: Breeding for new macadamia cultivars with high nut yield is expensive in terms of time, labour and cost. Most trees set nuts after four to five years, and candidate varieties for breeding are evaluated for at least eight years for various traits. Genome-wide association studies (GWAS) are promising methods to reduce evaluation and selection cycles by identifying genetic markers linked with key traits, potentially enabling early selection through marker-assisted selection. This study used 295 progeny from 32 full-sib families and 29 parents (18 phenotyped) which were planted across four sites, with each tree genotyped for 4113 SNPs. ASReml-R was used to perform association analyses with linear mixed models including a genomic relationship matrix to account for population structure. Traits investigated were: nut weight (NW), kernel weight (KW), kernel recovery (KR), percentage of whole kernels (WK), tree trunk circumference (TC), percentage of racemes that survived from flowering through to nut set, and number of nuts per raceme. RESULTS: Seven SNPs were significantly associated with NW (at a genome-wide false discovery rate of < 0.05), and four with WK. Multiple regression, as well as mapping of markers to genome assembly scaffolds suggested that some SNPs were detecting the same QTL. There were 44 significant SNPs identified for TC although multiple regression suggested detection of 16 separate QTLs. CONCLUSIONS: These findings have important implications for macadamia breeding, and highlight the difficulties of heterozygous populations with rapid LD decay. By coupling validated marker-trait associations detected through GWAS with MAS, genetic gain could be increased by reducing the selection time for economically important nut characteristics. Genomic selection may be a more appropriate method to predict complex traits like tree size and yield.

Apple whole genome sequences: recent advances and new prospects.

In 2010, a major scientific milestone was achieved for tree fruit crops: publication of the first draft whole genome sequence (WGS) for apple (Malus domestica). This WGS, v1.0, was valuable as the initial reference for sequence information, fine mapping, gene discovery, variant discovery, and tool development. A new, high quality apple WGS, GDDH13 v1.1, was released in 2017 and now serves as the reference genome for apple. Over the past decade, these apple WGSs have had an enormous impact on our understanding of apple biological functioning, trait physiology and inheritance, leading to practical applications for improving this highly valued crop. Causal gene identities for phenotypes of fundamental and practical interest can today be discovered much more rapidly. Genome-wide polymorphisms at high genetic resolution are screened efficiently over hundreds to thousands of individuals with new insights into genetic relationships and pedigrees. High-density genetic maps are constructed efficiently and quantitative trait loci for valuable traits are readily associated with positional candidate genes and/or converted into diagnostic tests for breeders. We understand the species, geographical, and genomic origins of domesticated apple more precisely, as well as its relationship to wild relatives. The WGS has turbo-charged application of these classical research steps to crop improvement and drives innovative methods to achieve more durable, environmentally sound, productive, and consumer-desirable apple production. This review includes examples of basic and practical breakthroughs and challenges in using the apple WGSs. Recommendations for "what's next" focus on necessary upgrades to the genome sequence data pool, as well as for use of the data, to reach new frontiers in genomics-based scientific understanding of apple.

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.

Genomic heritability estimates in sweet cherry reveal non-additive genetic variance is relevant for industry-prioritized traits.

BACKGROUND: Sweet cherry is consumed widely across the world and provides substantial economic benefits in regions where it is grown. While cherry breeding has been conducted in the Pacific Northwest for over half a century, little is known about the genetic architecture of important traits. We used a genome-enabled mixed model to predict the genetic performance of 505 individuals for 32 phenological, disease response and fruit quality traits evaluated in the RosBREED sweet cherry crop data set. Genome-wide predictions were estimated using a repeated measures model for phenotypic data across 3 years, incorporating additive, dominance and epistatic variance components. Genomic relationship matrices were constructed with high-density SNP data and were used to estimate relatedness and account for incomplete replication across years. RESULTS: High broad-sense heritabilities of 0.83, 0.77, and 0.76 were observed for days to maturity, firmness, and fruit weight, respectively. Epistatic variance exceeded 40% of the total genetic variance for maturing timing, firmness and powdery mildew response. Dominance variance was the largest for fruit weight and fruit size at 34% and 27%, respectively. Omission of non-additive sources of genetic variance from the genetic model resulted in inflation of narrow-sense heritability but minimally influenced prediction accuracy of genetic values in validation. Predicted genetic rankings of individuals from single-year models were inconsistent across years, likely due to incomplete sampling of the population genetic variance. CONCLUSIONS: Predicted breeding values and genetic values revealed many high-performing individuals for use as parents and the most promising selections to advance for cultivar release consideration, respectively. This study highlights the importance of using the appropriate genetic model for calculating breeding values to avoid inflation of expected parental contribution to genetic gain. The genomic predictions obtained will enable breeders to efficiently leverage the genetic potential of North American sweet cherry germplasm by identifying high quality individuals more rapidly than with phenotypic data alone.

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.].

Modeling of genetic gain for single traits from marker-assisted seedling selection in clonally propagated crops.

Seedling selection identifies superior seedlings as candidate cultivars based on predicted genetic potential for traits of interest. Traditionally, genetic potential is determined by phenotypic evaluation. With the availability of DNA tests for some agronomically important traits, breeders have the opportunity to include DNA information in their seedling selection operations-known as marker-assisted seedling selection. A major challenge in deploying marker-assisted seedling selection in clonally propagated crops is a lack of knowledge in genetic gain achievable from alternative strategies. Existing models based on additive effects considering seed-propagated crops are not directly relevant for seedling selection of clonally propagated crops, as clonal propagation captures all genetic effects, not just additive. This study modeled genetic gain from traditional and various marker-based seedling selection strategies on a single trait basis through analytical derivation and stochastic simulation, based on a generalized seedling selection scheme of clonally propagated crops. Various trait-test scenarios with a range of broad-sense heritability and proportion of genotypic variance explained by DNA markers were simulated for two populations with different segregation patterns. Both derived and simulated results indicated that marker-based strategies tended to achieve higher genetic gain than phenotypic seedling selection for a trait where the proportion of genotypic variance explained by marker information was greater than the broad-sense heritability. Results from this study provides guidance in optimizing genetic gain from seedling selection for single traits where DNA tests providing marker information are available.

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.