Genome-Wide Association Study for Abscission Failure of Fruit Pericarps (Stick-Tights) in Wild Macadamia Germplasm

Macadamia pericarps that fail to abscise (‘stick-tights’) are an important trait to select against in breeding as they can harbour pests and diseases. Traditional macadamia breeding cycles are lengthy and expensive due to long juvenilities and large tree sizes. Thus, genome-wide association studies (GWAS) are an important investigative tool to identify candidate trait-linked markers to enable potential reductions in evaluation and selection cycles via marker-assisted selection (MAS) in young seedlings. This study assessed 199 wild macadamia germplasm accessions for stick-tight prevalence across two years. As the number of stick-tights per tree is limited by the number of nuts per tree, we conducted association analyses to identify SNPs linked with the number of stick-tights per tree, and examined whether such SNPs were also associated with, and thus confounded with, the number of nuts per tree. We also assessed associations with the proportion of stick-tights per total number of nuts. Thirty-two SNPs were associated with at least one of the stick-tight traits in one year (p < 0.001). Of all such SNPs, only one was associated with the number of nuts per tree (p < 0.001), indicating that most associations were not confounded with yield

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

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

Using SNP arrays to leverage historic data sets for improved prediction accuracy and estimation of GxE of fruit maturity in sweet cherry (abstract)

Publishe

Macadamia domestication in Hawai‘i

Macadamia is one of the few international food crops domesticated from the Australian flora. It was first described in Australia in 1857, but developed as a crop in Hawai’i following the First World War. Hawai’ian cultivars are responsible for the majority of the world production. This study reviews literature and archival documents to clarify the domestication pathway of this germplasm. Uncertainty about the accepted wild origin of the Jordan introduction, believed to be the main source of Hawai’ian cultivars, is highlighted. An unrecognised additional early introduction of M. integrifolia is identified, but its relevance to commercial germplasm is unknown. The Hawai’ian industry preference for M. integrifolia germplasm may have arisen because the kernels used to evaluate this species were sourced from poorly managed orchards. There is strong evidence that M. ternifolia, which produces bitter kernels, was also introduced at some stage. The advent of vegetative propagation was a major event supporting domestication. The origins of all named cultivars have been clarified and the similarity of two, Keaau and Mauka, has been highlighted. The pedigree of advanced generation selections is clarified indicating Keauhou was a common maternal parent. These results add to the heritage of the plant in both Australia and Hawai’i. In addition, knowledge of the pedigree of advanced selections can be used to improve prediction accuracy in analysis of breeding trials. Finally, improved knowledge of the domestication pathway will assist ongoing conservation and genetic improvement of the genus

Exploring opportunities for reducing complexity of genotype-by-environment interaction models

Heterogeneity in genetic effects among environments (G\ua0×\ua0E) is a common phenomenon in crop plants and can arise from heterogeneity in variance (scale effects) and/or crossover interaction. Here, a study of yield of macadamia progeny in 15 trials established at 9 locations and assessed for yield at 7\ua0years is used to explore the impact on prediction of clonal values (additive\ua0+\ua0dominance effects) from (i) scaling observations by phenotypic standard deviation of each trial, and (ii) reducing complexity of the pattern of genotype-by-environment interaction. The initial fit of an unconstrained G\ua0×\ua0E model to unscaled observations indicated significant G\ua0×\ua0E, which was supported by the fit of the same model to scaled data. Scaling observations reduced heterogeneity of genetic parameter estimates among locations. Clustering of the additive and dominance genetic-by-environment covariance matrices from the fit of G\ua0×\ua0E models to scaled observations and log-likelihood testing was used to identify reduced models where locations with apparent homogeneous genetic effects (genetic variance not significantly different, and genetic correlations not significantly different from 1) were grouped into single environments. Complexity reduction condensed the additive genetic-by-environment covariance matrix to 3 environments, and 4 environments for the dominance matrix, and the accuracy of parameters estimates increased, although accuracy of prediction as assessed by generalised heritability only improved for a few locations. On the other hand, accuracies of clonal values predicted from a main effects only G\ua0+\ua0E model were lower. Nevertheless, correlations of the averages of predicted clonal values across locations from different models were very high suggesting models are robust to parameter estimates. These results support the use of scaling by the phenotypic standard deviation to reduce heterogeneity in parameter estimates, and complexity reduction to improve accuracy of estimating parameters required to predict genetic effects