A Genome-Wide Association Study of Apple Quality and Scab Resistance

Evaluation of genomic and phenomic prediction for application in apple breeding

BACKGROUND

Apple breeding schemes can be improved by using genomic prediction models to forecast the performance of breeding material. The predictive ability of these models depends on factors like trait genetic architecture, training set size, relatedness of the selected material to the training set, and the validation method used. Alternative genotyping methods such as RADseq and complementary data from near-infrared spectroscopy could help improve the cost-effectiveness of genomic prediction. However, the impact of these factors and alternative approaches on predictive ability beyond experimental populations still need to be investigated. In this study, we evaluated 137 prediction scenarios varying the described factors and alternative approaches, offering recommendations for implementing genomic selection in apple breeding.

RESULTS

Our results show that extending the training set with germplasm related to the predicted breeding material can improve average predictive ability across eleven studied traits by up to 0.08. The study emphasizes the usefulness of leave-one-family-out cross-validation, reflecting the application of genomic prediction to a new family, although it reduced average predictive ability across traits by up to 0.24 compared to 10-fold cross-validation. Similar average predictive abilities across traits indicate that imputed RADseq data could be a suitable genotyping alternative to SNP array datasets. The best-performing scenario using near-infrared spectroscopy data for phenomic prediction showed a 0.35 decrease in average predictive ability across traits compared to conventional genomic prediction, suggesting that the tested phenomic prediction approach is impractical.

CONCLUSIONS

Extending the training set using germplasm related with the target breeding material is crucial to improve the predictive ability of genomic prediction in apple. RADseq is a viable alternative to SNP array genotyping, while phenomic prediction is impractical. These findings offer valuable guidance for applying genomic selection in apple breeding, ultimately leading to the development of breeding material with improved quality.

Using Quantitative Trait Locus Mapping and Genomic Resources to Improve Breeding Precision in Peaches: Current Insights and Future Prospects

Modern breeding technologies and the development of quantitative trait locus (QTL) mapping have brought about a new era in peach breeding. This study examines the complex genetic structure that underlies the morphology of peach fruits, paying special attention to the interaction between genome editing, genomic selection, and marker-assisted selection. Breeders now have access to precise tools that enhance crop resilience, productivity, and quality, facilitated by QTL mapping, which has significantly advanced our understanding of the genetic determinants underlying essential traits such as fruit shape, size, and firmness. New technologies like CRISPR/Cas9 and genomic selection enable the development of cultivars that can withstand climate change and satisfy consumer demands with unprecedented precision in trait modification. Genotype-environment interactions remain a critical challenge for modern breeding efforts, which can be addressed through high-throughput phenotyping and multi-environment trials. This work shows how combining genome-wide association studies and machine learning can improve the synthesis of multi-omics data and result in faster breeding cycles while preserving genetic diversity. This study outlines a roadmap that prioritizes the development of superior cultivars utilizing cutting-edge methods and technologies in order to address evolving agricultural and environmental challenges.

Epistasis between genetic variations on MdMYB109 and MdHXK1 exerts a large effect on sugar content in apple fruit

Many quantitative traits are controlled by multiple genetic variations with minor effects, making it challenging to resolve the underlying genetic network and to apply functional markers in breeding. Affected by up to a hundred quantitative trait loci (QTLs), fruit-soluble sugar content is one of the most complex quantitative traits in apple (Malus sp.). Here, QTLs for apple fruit sucrose and fructose content were identified via QTL mapping and bulked-segregant analysis sequencing (BSA-seq) using a population derived from a 'Jonathan' × 'Golden Delicious' cross. Allelic variations and non-allelic interactions were validated in the candidate genes within these defined QTL regions. Three single-nucleotide polymorphisms (SNPs) (SNP -326 C/T, SNP -705 A/G, and SNP -706 G/T) in the MdMYB109 promoter region affected the binding ability of the repressive transcription factor MdWRKY33, leading to increased MdMYB109 expression. MdMYB109 bound directly to the promoter of the sucrose transporter gene MdSUT2.2 and activated its expression, raising fruit sucrose content. A SNP (SNP1060 A/G) in the hexokinase gene MdHXK1 affected the phosphorylation of the transcription factor MdbHLH3, and phosphorylated MdbHLH3 interacted with MdMYB109 to co-activate MdSUT2.2 expression and increase fruit sucrose content. Adding the joint effects of the genotype combinations at the SNP markers based on the SNPs in MdMYB109 and MdHXK1 increased the prediction accuracy of a genomics-assisted prediction (GAP) model for total soluble solid content from 0.3758 to 0.5531. These results uncovered functional variations in MdMYB109 and MdHXK1 regulating apple fruit sucrose content. The updated GAP model with improved predictability can be used efficiently in apple breeding.

Genome-wide association studies in a diverse strawberry collection unveil loci controlling agronomic and fruit quality traits

Strawberries (Fragaria sp.) are cherished for their organoleptic properties and nutritional value. However, breeding new cultivars involves the simultaneous selection of many agronomic and fruit quality traits, including fruit firmness and extended postharvest life. The strawberry germplasm collection here studied exhibited extensive phenotypic variation in 26 agronomic and fruit quality traits across three consecutive seasons. Phenotypic correlations and principal component analysis revealed relationships among traits and accessions, emphasizing the impact of plant breeding on fruit weight and firmness to the detriment of sugar or vitamin C content. Genetic diversity analysis on 124 accessions using 44,408 markers denoted a population structure divided into six subpopulations still retaining considerable diversity. Genome-wide association studies for the 26 traits unveiled 121 significant marker-trait associations distributed across 95 quantitative trait loci (QTLs). Multiple associations were detected for fruit firmness, a key breeding target, including a prominent locus on chromosome 6A. The candidate gene FaPG1, controlling fruit softening and postharvest shelf life, was identified within this QTL region. Differential expression of FaPG1 confirmed its role as the primary contributor to natural variation in fruit firmness. A kompetitive allele-specific PCR assay based on the single nucleotide polymorphism (SNP) AX-184242253, associated with the 6A QTL, predicts a substantial increase in fruit firmness, validating its utility for marker-assisted selection. In essence, this comprehensive study provides insights into the phenotypic and genetic landscape of the strawberry collection and lays a robust foundation for propelling the development of superior strawberry cultivars through precision breeding.

Upregulation of PECTATE LYASE5 by a NAC transcription factor promotes fruit softening in apple

Flesh firmness is a critical breeding trait that determines consumer selection, shelf life, and transportation. The genetic basis controlling firmness in apple (Malus × domestica Borkh.) remains to be fully elucidated. We aimed to decipher genetic variance for firmness at harvest and develop potential molecular markers for marker-assisted breeding. Maturity firmness for 439 F1 hybrids from a cross of "Cripps Pink" and "Fuji" was determined in 2016 and 2017. The phenotype segregated extensively, with a Gaussian distribution. In a combined bulked segregant analysis (BSA) and RNA-sequencing analysis, 84 differentially expressed genes were screened from the 10 quantitative trait loci regions. Interestingly, next-generation re-sequencing analysis revealed a Harbinger-like transposon element insertion upstream of the candidate gene PECTATE LYASE5 (MdPL5); the genotype was associated with flesh firmness at harvest. The presence of this transposon repressed MdPL5 expression and was closely linked to the extra-hard phenotype. MdPL5 was demonstrated to promote softening in apples and tomatoes. Subsequently, using the MdPL5 promoter as bait, MdNAC1-L was identified as a transcription activator that positively regulates ripening and softening in the developing fruit. We also demonstrated that MdNAC1-L could induce the up-regulation of MdPL5, MdPG1, and the ethylene-related genes MdACS1 and MdACO1. Our findings provide insight into TE-related genetic variation and the PL-mediated regulatory network for the firmness of apple fruit.

Genomic selection for crop improvement in fruits and vegetables: a systematic scoping review

To ensure the nutritional needs of an expanding global population, it is crucial to optimize the growing capabilities and breeding values of fruit and vegetable crops. While genomic selection, initially implemented in animal breeding, holds tremendous potential, its utilization in fruit and vegetable crops remains underexplored. In this systematic review, we reviewed 63 articles covering genomic selection and its applications across 25 different types of fruit and vegetable crops over the last decade. The traits examined were directly related to the edible parts of the crops and carried significant economic importance. Comparative analysis with WHO/FAO data identified potential economic drivers underlying the study focus of some crops and highlighted crops with potential for further genomic selection research and application. Factors affecting genomic selection accuracy in fruit and vegetable studies are discussed and suggestions made to assist in their implementation into plant breeding schemes. Genetic gain in fruits and vegetables can be improved by utilizing genomic selection to improve selection intensity, accuracy, and integration of genetic variation. However, the reduction of breeding cycle times may not be beneficial in crops with shorter life cycles such as leafy greens as compared to fruit trees. There is an urgent need to integrate genomic selection methods into ongoing breeding programs and assess the actual genomic estimated breeding values of progeny resulting from these breeding programs against the prediction models.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-024-01497-2.

Crop Landraces and Indigenous Varieties: A Valuable Source of Genes for Plant Breeding

Landraces and indigenous varieties comprise valuable sources of crop species diversity. Their utilization in plant breeding may lead to increased yield and enhanced quality traits, as well as resilience to various abiotic and biotic stresses. Recently, new approaches based on the rapid advancement of genomic technologies such as deciphering of pangenomes, multi-omics tools, marker-assisted selection (MAS), genome-wide association studies (GWAS), and CRISPR/Cas9 gene editing greatly facilitated the exploitation of landraces in modern plant breeding. In this paper, we present a comprehensive overview of the implementation of new genomic technologies and highlight their importance in pinpointing the genetic basis of desirable traits in landraces and indigenous varieties of annual, perennial herbaceous, and woody crop species cultivated in the Mediterranean region. The need for further employment of advanced -omic technologies to unravel the full potential of landraces and indigenous varieties underutilized genetic diversity is also indicated. Ultimately, the large amount of genomic data emerging from the investigation of landraces and indigenous varieties reveals their potential as a source of valuable genes and traits for breeding. The role of landraces and indigenous varieties in mitigating the ongoing risks posed by climate change in agriculture and food security is also highlighted.

Towards identification of postharvest fruit quality transcriptomic markers in Malus domestica

Gene expression is highly impacted by the environment and can be reflective of past events that affected developmental processes. It is therefore expected that gene expression can serve as a signal of a current or future phenotypic traits. In this paper we identify sets of genes, which we call Prognostic Transcriptomic Biomarkers (PTBs), that can predict firmness in Malus domestica (apple) fruits. In apples, all individuals of a cultivar are clones, and differences in fruit quality are due to the environment. The apples transcriptome responds to these differences in environment, which makes PTBs an attractive predictor of future fruit quality. PTBs have the potential to enhance supply chain efficiency, reduce crop loss, and provide higher and more consistent quality for consumers. However, several questions must be addressed. In this paper we answer the question of which of two common modeling approaches, Random Forest or ElasticNet, outperforms the other. We answer if PTBs with few genes are efficient at predicting traits. This is important because we need few genes to perform qPCR, and we answer the question if qPCR is a cost-effective assay as input for PTBs modeled using high-throughput RNA-seq. To do this, we conducted a pilot study using fruit texture in the 'Gala' variety of apples across several postharvest storage regiments. Fruit texture in 'Gala' apples is highly controllable by post-harvest treatments and is therefore a good candidate to explore the use of PTBs. We find that the RandomForest model is more consistent than an ElasticNet model and is predictive of firmness (r2 = 0.78) with as few as 15 genes. We also show that qPCR is reasonably consistent with RNA-seq in a follow up experiment. Results are promising for PTBs, yet more work is needed to ensure that PTBs are robust across various environmental conditions and storage treatments.

Advancing tree genomics to future proof next generation orchard production

The challenges facing tree orchard production in the coming years will be largely driven by changes in the climate affecting the sustainability of farming practices in specific geographical regions. Identifying key traits that enable tree crops to modify their growth to varying environmental conditions and taking advantage of new crop improvement opportunities and technologies will ensure the tree crop industry remains viable and profitable into the future. In this review article we 1) outline climate and sustainability challenges relevant to horticultural tree crop industries, 2) describe key tree crop traits targeted for improvement in agroecosystem productivity and resilience to environmental change, and 3) discuss existing and emerging genomic technologies that provide opportunities for industries to future proof the next generation of orchards.

Genome-wide association mapping in a sweet cherry germplasm collection (Prunus avium L.) reveals candidate genes for fruit quality traits

In sweet cherry (Prunus avium L.), large variability exists for various traits related to fruit quality. There is a need to discover the genetic architecture of these traits in order to enhance the efficiency of breeding strategies for consumer and producer demands. With this objective, a germplasm collection consisting of 116 sweet cherry accessions was evaluated for 23 agronomic fruit quality traits over 2-6 years, and characterized using a genotyping-by-sequencing approach. The SNP coverage collected was used to conduct a genome-wide association study using two multilocus models and three reference genomes. We identified numerous SNP-trait associations for global fruit size (weight, width, and thickness), fruit cracking, fruit firmness, and stone size, and we pinpointed several candidate genes involved in phytohormone, calcium, and cell wall metabolisms. Finally, we conducted a precise literature review focusing on the genetic architecture of fruit quality traits in sweet cherry to compare our results with potential colocalizations of marker-trait associations. This study brings new knowledge of the genetic control of important agronomic traits related to fruit quality, and to the development of marker-assisted selection strategies targeted towards the facilitation of breeding efforts.

Genomewide selection for fruit quality traits in apple: breeding insights gained from prediction and postdiction

Many fruit quality traits in apple (Malus domestica Borkh.) are controlled by multiple small-effect quantitative trait loci (QTLs). Genomewide selection (genomic selection) might be an effective breeding approach for highly quantitative traits in woody perennial crops with long generation times like apple. The goal of this study was to determine if genomewide prediction is an effective breeding approach for fruit quality traits in an apple scion breeding program. Representative apple scion breeding germplasm (n_individuals = 955), high-quality single nucleotide polymorphism (SNP) data (n_SNPs = 977), and breeding program fruit quality trait data at harvest were analyzed. Breeding parents `Honeycrisp' and `Minneiska' were highly represented. Moderate to high predictive abilities were observed for most fruit quality traits at harvest. For example, when 25% random subsets of the germplasm set were used as training sets, mean predictive abilities ranged from 0.35 to 0.54 across traits. Trait, training and test sets, family size for within family prediction, and number of SNPs per chromosome affected model predictive ability. Inclusion of large-effect QTLs as fixed effects resulted in higher predictive abilities for some traits (e.g. percent red overcolor). Postdiction (i.e. retrospective) analyses demonstrated the impact of culling threshold on selection decisions. The results of this study demonstrate that genomewide selection is a useful breeding approach for certain fruit quality traits in apple.

Marker-Assisted Selection in Breeding for Fruit Trait Improvement: A Review

Breeding fruit species is time-consuming and expensive. With few exceptions, trees are likely the worst species to work with in terms of genetics and breeding. Most are characterized by large trees, long juvenile periods, and intensive agricultural practice, and environmental variability plays an important role in the heritability evaluations of every single important trait. Although vegetative propagation allows for the production of a significant number of clonal replicates for the evaluation of environmental effects and genotype × environment interactions, the spaces required for plant cultivation and the intensity of work necessary for phenotypic surveys slow down the work of researchers. Fruit breeders are very often interested in fruit traits: size, weight, sugar and acid content, ripening time, fruit storability, and post-harvest practices, among other traits relevant to each individual species. The translation of trait loci and whole-genome sequences into diagnostic genetic markers that are effective and affordable for use by breeders, who must choose genetically superior parents and subsequently choose genetically superior individuals among their progeny, is one of the most difficult tasks still facing tree fruit geneticists. The availability of updated sequencing techniques and powerful software tools offered the opportunity to mine tens of fruit genomes to find out sequence variants potentially useful as molecular markers. This review is devoted to analysing what has been the role of molecular markers in assisting breeders in selection processes, with an emphasis on the fruit traits of the most important fruit crops for which examples of trustworthy molecular markers have been developed, such as the MDo.chr9.4 marker for red skin colour in apples, the CCD4-based marker CPRFC1, and LG3_13.146 marker for flesh colour in peaches, papayas, and cherries, respectively.

Population Structure and Association Mapping for Agronomical and Biochemical Traits of a Large Spanish Apple Germplasm

A basic knowledge of linkage disequilibrium and population structure is necessary in order to determine the genetic control and identify significant associations with agronomical and phytochemical compounds in apple (Malus × domestica Borkh). In this study, 186 apple accessions (Pop1), representing both Spanish native accessions (94) and non-Spanish cultivars (92) from the EEAD-CSIC apple core collection, were assessed using 23 SSRs markers. Four populations were considered: Pop1, Pop2, Pop3, and Pop4. The initial Pop1 was divided into 150 diploid (Pop2) and 36 triploid accessions (Pop3), while for the inter-chromosomal linkage disequilibrium and the association mapping analysis, 118 phenotype diploid accessions were considered Pop4. Thus, the average number of alleles per locus and observed heterozygosity for the overall sample set (Pop1) were 15.65 and 0.75, respectively. The population structure analysis identified two subpopulations in the diploid accessions (Pop2 and Pop4) and four in the triploids (Pop3). Regarding the Pop4, the population structure with K = 2 subpopulations segregation was in agreement with the UPGMA cluster analysis according to the genetic pairwise distances. Moreover, the accessions seemed to be segregated by their origin (Spanish/non-Spanish) in the clustering analysis. One of the two subpopulations encountered was quite-exclusively formed by non-Spanish accessions (30 out of 33). Furthermore, agronomical and basic fruit quality parameters, antioxidant traits, individual sugars, and organic acids were assessed for the association mapping analysis. A high level of biodiversity was exhibited in the phenotypic characterization of Pop4, and a total of 126 significant associations were found between the 23 SSR markers and the 21 phenotypic traits evaluated. This study also identified many new marker-locus trait associations for the first time, such as in the antioxidant traits or in sugars and organic acids, which may be useful for predictions and for a better understanding of the apple genome.

Fruit growth and development in apple: a molecular, genomics and epigenetics perspective

Fruit growth and development are physiological processes controlled by several internal and external factors. This complex regulatory mechanism comprises a series of events occurring in a chronological order over a growing season. Understanding the underlying mechanism of fruit development events, however, requires consideration of the events occurring prior to fruit development such as flowering, pollination, fertilization, and fruit set. Such events are interrelated and occur in a sequential order. Recent advances in high-throughput sequencing technology in conjunction with improved statistical and computational methods have empowered science to identify some of the major molecular components and mechanisms involved in the regulation of fruit growth and have supplied encouraging successes in associating genotypic differentiation with phenotypic observations. As a result, multiple approaches have been developed to dissect such complex regulatory machinery and understand the genetic basis controlling these processes. These methods include transcriptomic analysis, quantitative trait loci (QTLs) mapping, whole-genome approach, and epigenetics analyses. This review offers a comprehensive overview of the molecular, genomic and epigenetics perspective of apple fruit growth and development that defines the final fruit size and provides a detailed analysis of the mechanisms by which fruit growth and development are controlled. Though the main emphasis of this article is on the molecular, genomic and epigenetics aspects of fruit growth and development, we will also deliver a brief overview on events occurring prior to fruit growth.

Quantitative proteomic sequencing of F 1 hybrid populations reveals the function of sorbitol in apple resistance to Botryosphaeria dothidea

Apple ring rot, which is caused by Botryosphaeria dothidea, is one of the most devastating diseases of apple. However, the lack of a known molecular resistance mechanism limits the development of resistance breeding. Here, the 'Golden Delicious' and 'Fuji Nagafu No. 2' apple cultivars were crossed, and a population of 194 F ₁ individuals was generated. The hybrids were divided into five categories according to their differences in B. dothidea resistance during three consecutive years. Quantitative proteomic sequencing was performed to analyze the molecular mechanism of the apple response to B. dothidea infection. Hierarchical clustering and weighted gene coexpression network analysis revealed that photosynthesis was significantly correlated with the resistance of apple to B. dothidea. The level of chlorophyll fluorescence in apple functional leaves increased progressively as the level of disease resistance improved. However, the content of soluble sugar decreased with the improvement of disease resistance. Further research revealed that sorbitol, the primary photosynthetic product, played major roles in apple resistance to B. dothidea. Increasing the content of sorbitol by overexpressing MdS6PDH1 dramatically enhanced resistance of apple calli to B. dothidea by activating the expression of salicylic acid signaling pathway-related genes. However, decreasing the content of sorbitol by silencing MdS6PDH1 showed the opposite phenotype. Furthermore, exogenous sorbitol treatment partially restored the resistance of MdS6PDH1-RNAi lines to B. dothidea. Taken together, these findings reveal that sorbitol is an important metabolite that regulates the resistance of apple to B. dothidea and offer new insights into the mechanism of plant resistance to pathogens.

Phenotypic divergence between the cultivated apple (Malus domestica) and its primary wild progenitor (Malus sieversii)

An understanding of the relationship between the cultivated apple (Malus domestica) and its primary wild progenitor species (M. sieversii) not only provides an understanding of how apples have been improved in the past, but may be useful for apple improvement in the future. We measured 10 phenotypes in over 1000 unique apple accessions belonging to M. domestica and M. sieversii from Canada's Apple Biodiversity Collection. Using principal components analysis (PCA), we determined that M. domestica and M. sieversii differ significantly in phenotypic space and are nearly completely distinguishable as two separate groups. We found that M. domestica had a shorter juvenile phase than M. sieversii and that cultivated trees produced flowers and ripe fruit later than their wild progenitors. Cultivated apples were also 3.6 times heavier, 43% less acidic, and had 68% less phenolic content than wild apples. Using historical records, we found that apple breeding over the past 200 years has resulted in a trend towards apples that have higher soluble solids, are less bitter, and soften less during storage. Our results quantify the significant changes in phenotype that have taken place since apple domestication, and provide evidence that apple breeding has led to continued phenotypic divergence of the cultivated apple from its wild progenitor species.

A bulked segregant analysis tool for out-crossing species (BSATOS) and QTL-based genomics-assisted prediction of complex traits in apple

INTRODUCTION

Genomic heterozygosity, self-incompatibility, and rich-in somatic mutations hinder the molecular breeding efficiency of outcrossing plants.

OBJECTIVES

We attempted to develop an efficient integrated strategy to identify quantitative trait loci (QTLs) and trait-associated genes, to develop gene markers, and to construct genomics-assisted prediction (GAP) modes.

METHODS

A novel protocol, bulked segregant analysis tool for out-crossing species (BSATOS), is presented here, which is characterized by taking full advantage of all segregation patterns (including AB × AB markers) and haplotype information. To verify the effectiveness of the protocol in dealing with the complex traits of outbreeding species, three apple cross populations with 9,654 individuals were adopted.

RESULTS

By using BSATOS, 90, 60, and 77 significant QTLs were identified successfully and candidate genes were predicted for apple fruit weight (FW), fruit ripening date (FRD), and fruit soluble solid content (SSC), respectively. The gene-based markers were developed and genotyped for 1,396 individuals in a training population, including 145 Malus accessions and 1,251 F1 plants of the three full-sib families. GAP models were trained using marker genotype effect estimates of the training population. The prediction accuracy was 0.7658, 0.6455, and 0.3758 for FW, FRD, and SSC, respectively.

CONCLUSION

The BSATOS and GAP models provided a convenient and efficient methodology for candidate gene mining and molecular breeding in out-crossing plant species. The BSATOS pipeline can be freely downloaded from: https://github.com/maypoleflyn/BSATOS.

Variation in the promoter of the sorbitol dehydrogenase gene MdSDH2 affects binding of the transcription factor MdABI3 and alters fructose content in apple fruit

Fructose (Fru) content is a key determinant of fruit sweetness and quality. An F1 hybrid population of the apple cultivars 'Honeycrisp' × 'Qinguan' was used to investigate the quantitative trait locus (QTL) regions and genes controlling Fru content in fruit. A stable QTL on linkage group (LG) 01 in 'Honeycrisp' was detected on the single nucleotide polymorphism (SNP) genetic linkage maps. In this region, a sorbitol dehydrogenase (SDH) gene, MdSDH2, was detected and showed promoter variations and differential expression patterns between 'Honeycrisp' and 'Qinguan' fruits as well as their hybrids. A SNP variant (A/G) in the MdSDH2 promoter region (SDH2p-491) affected the binding ability of the transcription factor MdABI3, which can affect the expression of MdSDH2. Promoter sequences with an A nucleotide at SDH2p-491 had stronger binding affinity for MdABI3 than those with a G. Among 27 domesticated apple cultivars and wild relatives, this SNP (A/G) was associated with Fru content. Our results indicate that MdSDH2 can alter Fru content as the major regulatory gene and that ABA signaling might be involved in Fru content accumulation in apple fruit.

Genetic architecture and genomic predictive ability of apple quantitative traits across environments

Implementation of genomic tools is desirable to increase the efficiency of apple breeding. Recently, the multi-environment apple reference population (apple REFPOP) proved useful for rediscovering loci, estimating genomic predictive ability, and studying genotype by environment interactions (G × E). So far, only two phenological traits were investigated using the apple REFPOP, although the population may be valuable when dissecting genetic architecture and reporting predictive abilities for additional key traits in apple breeding. Here we show contrasting genetic architecture and genomic predictive abilities for 30 quantitative traits across up to six European locations using the apple REFPOP. A total of 59 stable and 277 location-specific associations were found using GWAS, 69.2% of which are novel when compared with 41 reviewed publications. Average genomic predictive abilities of 0.18-0.88 were estimated using main-effect univariate, main-effect multivariate, multi-environment univariate, and multi-environment multivariate models. The G × E accounted for up to 24% of the phenotypic variability. This most comprehensive genomic study in apple in terms of trait-environment combinations provided knowledge of trait biology and prediction models that can be readily applied for marker-assisted or genomic selection, thus facilitating increased breeding efficiency.

Combining genetic resources and elite material populations to improve the accuracy of genomic prediction in apple

Genomic selection is an attractive strategy for apple breeding that could reduce the length of breeding cycles. A possible limitation to the practical implementation of this approach lies in the creation of a training set large and diverse enough to ensure accurate predictions. In this study, we investigated the potential of combining two available populations, i.e., genetic resources and elite material, in order to obtain a large training set with a high genetic diversity. We compared the predictive ability of genomic predictions within-population, across-population or when combining both populations, and tested a model accounting for population-specific marker effects in this last case. The obtained predictive abilities were moderate to high according to the studied trait and small increases in predictive ability could be obtained for some traits when the two populations were combined into a unique training set. We also investigated the potential of such a training set to predict hybrids resulting from crosses between the two populations, with a focus on the method to design the training set and the best proportion of each population to optimize predictions. The measured predictive abilities were very similar for all the proportions, except for the extreme cases where only one of the two populations was used in the training set, in which case predictive abilities could be lower than when using both populations. Using an optimization algorithm to choose the genotypes in the training set also led to higher predictive abilities than when the genotypes were chosen at random. Our results provide guidelines to initiate breeding programs that use genomic selection when the implementation of the training set is a limitation.

Insights into the effect of human civilization on Malus evolution and domestication

The evolutionary history of the Malus genus has not been well studied. In the current study, we presented genetic evidence on the origin of the Malus genus based on genome sequencing of 297 Malus accessions, revealing the genetic relationship between wild species and cultivated apples. Our results demonstrated that North American and East Asian wild species are closer to the outgroup (pear) than Central Asian species, and hybrid species including natural (separated before the Pleistocene, about 2.5 Mya) and artificial hybrids (including ornamental trees and rootstocks) are between East and Central Asian wild species. Introgressions from M. sylvestris in cultivated apples appeared to be more extensive than those from M. sieversii, whose genetic background flowed westward across Eurasia and eastward to wild species including M. prunifolia, M. × asiatica, M. × micromalus, and M. × robust. Our results suggested that the loss of ancestral gene flow from M. sieversii in cultivated apples accompanied the movement of European traders around the world since the Age of Discovery. Natural SNP variations showed that cultivated apples had higher nucleotide diversity than wild species and more unique SNPs than other apple groups. An apple ERECTA-like gene that underwent selection during domestication on 15^th chromosome was identified as a likely major determinant of fruit length and diameter, and an NB-ARC domain-containing gene was found to strongly affect anthocyanin accumulation using a genome-wide association approach. Our results provide new insights into the origin and domestication of apples and will be useful in new breeding programmes and efforts to increase fruit crop productivity.

Genome-wide association mapping identifies novel loci underlying fire blight resistance in apple

Fire blight, caused by epiphytotic gram-negative bacteria Erwinia amylovora, is the most destructive bacterial disease of apple (Malus spp.). Genetic mechanisms of fire blight resistance have mainly been studied using traditional biparental quantitative trait loci (QTL) mapping approaches. Here, we use large-scale historic shoot and blossom fire blight data collected over multiple years and genotyping-by-sequencing (GBS) markers to identify significant marker-trait associations in a diverse set of 566 apple [Malus domestica (Suckow) Borkh.] accessions. There was large variation in fire blight resistance and susceptibility in these accessions. We identified 23 and 38 QTL significantly (p < .001) associated with shoot and blossom blight resistance, respectively. The QTL are distributed across all 17 chromosomes of apple. Four shoot blight and 19 blossom blight QTL identified in this study colocalized with previously identified QTL associated with resistance to fire blight or apple scab. Using transcriptomics data of two apple cultivars with contrasting fire blight responses, we also identified candidate genes for fire blight resistance that are differentially expressed between resistant and susceptible cultivars and located within QTL intervals for fire blight resistance. However, further experiments are needed to confirm and validate these marker-trait associations and develop diagnostic markers before use in marker-assisted breeding to develop apple cultivars with decreased fire blight susceptibility.

Apple Ripening Is Controlled by a NAC Transcription Factor

Softening is a hallmark of ripening in fleshy fruits, and has both desirable and undesirable implications for texture and postharvest stability. Accordingly, the timing and extent of pre-harvest ripening and associated textural changes following harvest are key targets for improving fruit quality through breeding. Previously, we identified a large effect locus associated with harvest date and firmness in apple (Malus domestica) using genome-wide association studies (GWAS). Here, we present additional evidence that polymorphisms in or around a transcription factor gene, NAC18.1, may cause variation in these traits. First, we confirmed our previous findings with new phenotype and genotype data from ∼800 apple accessions. In this population, we compared a genetic marker within NAC18.1 to markers targeting three other firmness-related genes currently used by breeders (ACS1, ACO1, and PG1), and found that the NAC18.1 marker was the strongest predictor of both firmness at harvest and firmness after 3 months of cold storage. By sequencing NAC18.1 across 18 accessions, we revealed two predominant haplotypes containing the single nucleotide polymorphism (SNP) previously identified using GWAS, as well as dozens of additional SNPs and indels in both the coding and promoter sequences. NAC18.1 encodes a protein that is orthogolous to the NON-RIPENING (NOR) transcription factor, a regulator of ripening in tomato (Solanum lycopersicum). We introduced both NAC18.1 transgene haplotypes into the tomato nor mutant and showed that both haplotypes complement the nor ripening deficiency. Taken together, these results indicate that polymorphisms in NAC18.1 may underlie substantial variation in apple firmness through modulation of a conserved ripening program.

Role of MdERF3 and MdERF118 natural variations in apple flesh firmness/crispness retainability and development of QTL-based genomics-assisted prediction

Retention of flesh texture attributes during cold storage is critical for the long-term maintenance of fruit quality. The genetic variations determining flesh firmness and crispness retainability are not well understood. The objectives of this study are to identify gene markers based on quantitative trait loci (QTLs) and to develop genomics-assisted prediction (GAP) models for apple flesh firmness and crispness retainability. Phenotype data of 2664 hybrids derived from three Malus domestica cultivars and a M. asiatica cultivar were collected in 2016 and 2017. The phenotype segregated considerably with high broad-sense heritability of 83.85% and 83.64% for flesh firmness and crispness retainability, respectively. Fifty-six candidate genes were predicted from the 62 QTLs identified using bulked segregant analysis and RNA-seq. The genotype effects of the markers designed on each candidate gene were estimated. The genomics-predicted values were obtained using pyramiding marker genotype effects and overall mean phenotype values. Fivefold cross-validation revealed that the prediction accuracy was 0.5541 and 0.6018 for retainability of flesh firmness and crispness, respectively. An 8-bp deletion in the MdERF3 promoter disrupted MdDOF5.3 binding, reduced MdERF3 expression, relieved the inhibition on MdPGLR3, MdPME2, and MdACO4 expression, and ultimately decreased flesh firmness and crispness retainability. A 3-bp deletion in the MdERF118 promoter decreased its expression by disrupting the binding of MdRAVL1, which increased MdPGLR3 and MdACO4 expression and reduced flesh firmness and crispness retainability. These results provide insights regarding the genetic variation network regulating flesh firmness and crispness retainability, and the GAP models can assist in apple breeding.

Tracing founder haplotypes of Japanese apple varieties: application in genomic prediction and genome-wide association study

Haplotypes provide useful information for genomics-based approaches, genomic prediction, and genome-wide association study. As a small number of superior founders have contributed largely to the breeding history of fruit trees, the information of founder haplotypes may be relevant for performing the genomics-based approaches in these plants. In this study, we proposed a method to estimate 14 haplotypes from 7 founders and automatically trace the haplotypes forward to apple parental (185 varieties) and breeding (659 F1 individuals from 16 full-sib families) populations based on 11,786 single-nucleotide polymorphisms, by combining multiple algorithms. Overall, 92% of the single-nucleotide polymorphisms information in the parental and breeding populations was characterized by the 14 founder haplotypes. The use of founder haplotype information improved the accuracy of genomic prediction in 7 traits and the resolution of genome-wide association study in 13 out of 27 fruit quality traits analyzed in this study. We also visualized the significant propagation of the founder haplotype with the largest genetic effect in genome-wide association study over the pedigree tree of the parental population. These results suggest that the information of founder haplotypes can be useful for not only genetic improvement of fruit quality traits in apples but also for understanding the selection history of founder haplotypes in the breeding program of Japanese apple varieties.

Recent Large-Scale Genotyping and Phenotyping of Plant Genetic Resources of Vegetatively Propagated Crops

Several recent national and international projects have focused on large-scale genotyping of plant genetic resources in vegetatively propagated crops like fruit and berries, potatoes and woody ornamentals. The primary goal is usually to identify true-to-type plant material, detect possible synonyms, and investigate genetic diversity and relatedness among accessions. A secondary goal may be to create sustainable databases that can be utilized in research and breeding for several years ahead. Commonly applied DNA markers (like microsatellite DNA and SNPs) and next-generation sequencing each have their pros and cons for these purposes. Methods for large-scale phenotyping have lagged behind, which is unfortunate since many commercially important traits (yield, growth habit, storability, and disease resistance) are difficult to score. Nevertheless, the analysis of gene action and development of robust DNA markers depends on environmentally controlled screening of very large sets of plant material. Although more time-consuming, co-operative projects with broad-scale data collection are likely to produce more reliable results. In this review, we will describe some of the approaches taken in genotyping and/or phenotyping projects concerning a wide variety of vegetatively propagated crops.

Genomic consequences of apple improvement

The apple (Malus domestica) is one of the world's most commercially important perennial crops and its improvement has been the focus of human effort for thousands of years. Here, we genetically characterise over 1000 apple accessions from the United States Department of Agriculture (USDA) germplasm collection using over 30,000 single-nucleotide polymorphisms (SNPs). We confirm the close genetic relationship between modern apple cultivars and their primary progenitor species, Malus sieversii from Central Asia, and find that cider apples derive more of their ancestry from the European crabapple, Malus sylvestris, than do dessert apples. We determine that most of the USDA collection is a large complex pedigree: over half of the collection is interconnected by a series of first-degree relationships. In addition, 15% of the accessions have a first-degree relationship with one of the top 8 cultivars produced in the USA. With the exception of 'Honeycrisp', the top 8 cultivars are interconnected to each other via pedigree relationships. The cultivars 'Golden Delicious' and 'Red Delicious' were found to have over 60 first-degree relatives, consistent with their repeated use by apple breeders. We detected a signature of intense selection for red skin and provide evidence that breeders also selected for increased firmness. Our results suggest that Americans are eating apples largely from a single family tree and that the apple's future improvement will benefit from increased exploitation of its tremendous natural genetic diversity.

The apple REFPOP-a reference population for genomics-assisted breeding in apple

Breeding of apple is a long-term and costly process due to the time and space requirements for screening selection candidates. Genomics-assisted breeding utilizes genomic and phenotypic information to increase the selection efficiency in breeding programs, and measurements of phenotypes in different environments can facilitate the application of the approach under various climatic conditions. Here we present an apple reference population: the apple REFPOP, a large collection formed of 534 genotypes planted in six European countries, as a unique tool to accelerate apple breeding. The population consisted of 269 accessions and 265 progeny from 27 parental combinations, representing the diversity in cultivated apple and current European breeding material, respectively. A high-density genome-wide dataset of 303,239 SNPs was produced as a combined output of two SNP arrays of different densities using marker imputation with an imputation accuracy of 0.95. Based on the genotypic data, linkage disequilibrium was low and population structure was weak. Two well-studied phenological traits of horticultural importance were measured. We found marker-trait associations in several previously identified genomic regions and maximum predictive abilities of 0.57 and 0.75 for floral emergence and harvest date, respectively. With decreasing SNP density, the detection of significant marker-trait associations varied depending on trait architecture. Regardless of the trait, 10,000 SNPs sufficed to maximize genomic prediction ability. We confirm the suitability of the apple REFPOP design for genomics-assisted breeding, especially for breeding programs using related germplasm, and emphasize the advantages of a coordinated and multinational effort for customizing apple breeding methods in the genomics era.

Quantitative trait loci-based genomics-assisted prediction for the degree of apple fruit cover color

Apple fruit cover color is an important appearance trait determining fruit quality, high degree of fruit cover color or completely red fruit skin is also the ultimate breeding goal. MdMYB1 has repeatedly been reported as a major gene controlling apple fruit cover color. There are also multiple minor-effect genes affecting degree of fruit cover color (DFC). This study was to identify genome-wide quantitative trait loci (QTLs) and to develop genomics-assisted prediction for apple DFC. The DFC phenotype data of 9,422 hybrids from five full-sib families of Malus asiatica 'Zisai Pearl', M. domestica 'Red Fuji', 'Golden Delicious', and 'Jonathan' were collected in 2014-2017. The phenotype varied considerably among hybrids with the same MdMYB1 genotype. Ten QTLs for DFC were identified using MapQTL and bulked segregant analysis via sequencing. From these QTLs, ten candidate genes were predicted, including MdMYB1 from a year-stable QTL on chromosome 9 of 'Zisai Pearl' and 'Red Fuji'. Then, kompetitive allele-specific polymerase chain reaction (KASP) markers were designed on these candidate genes and 821 randomly selected hybrids were genotyped. The genotype effects of the markers were estimated. MdMYB1-1 (represented by marker H162) exhibited a partial dominant allelic effect on MdMYB1-2 and showed non-allelic epistasis on markers H1245 and G6. Finally, a non-additive QTL-based genomics assisted prediction model was established for DFC. The Pearson's correlation coefficient between the genomic predicted value and the observed phenotype value was 0.5690. These results can be beneficial for apple genomics-assisted breeding and may provide insights for understanding the mechanism of fruit coloration.

Genomic prediction of fruit texture and training population optimization towards the application of genomic selection in apple

Texture is a complex trait and a major component of fruit quality in apple. While the major effect of MdPG1, a gene controlling firmness, has already been exploited in elite cultivars, the genetic basis of crispness remains poorly understood. To further improve fruit texture, harnessing loci with minor effects via genomic selection is therefore necessary. In this study, we measured acoustic and mechanical features in 537 genotypes to dissect the firmness and crispness components of fruit texture. Predictions of across-year phenotypic values for these components were calculated using a model calibrated with 8,294 SNP markers. The best prediction accuracies following cross-validations within the training set of 259 genotypes were obtained for the acoustic linear distance (0.64). Predictions for biparental families using the entire training set varied from low to high accuracy, depending on the family considered. While adding siblings or half-siblings into the training set did not clearly improve predictions, we performed an optimization of the training set size and composition for each validation set. This allowed us to increase prediction accuracies by 0.17 on average, with a maximal accuracy of 0.81 when predicting firmness in the 'Gala' × 'Pink Lady' family. Our results therefore identified key genetic parameters to consider when deploying genomic selection for texture in apple. In particular, we advise to rely on a large training population, with high phenotypic variability from which a 'tailored training population' can be extracted using a priori information on genetic relatedness, in order to predict a specific target population.

Genomics-assisted prediction of salt and alkali tolerances and functional marker development in apple rootstocks

Background

Saline, alkaline, and saline-alkaline stress severely affect plant growth and development. The tolerance of plants to these stressors has long been important breeding objectives, especially for woody perennials like apple. The aims of this study were to identify quantitative trait loci (QTLs) and to develop genomics-assisted prediction models for salt, alkali, and salt-alkali tolerance in apple rootstock.

Results

A total of 3258 hybrids derived from the apple rootstock cultivars ‘Baleng Crab’ (Malus robusta Rehd., tolerant) × ‘M9’ (M. pumila Mill., sensitive) were used to identify 17, 13, and two QTLs for injury indices of salt, alkali, and salt–alkali stress via bulked segregant analysis. The genotype effects of single nucleotide polymorphism (SNP) markers designed on candidate genes in each QTL interval were estimated. The genomic predicted value of an individual hybrid was calculated by adding the sum of all marker genotype effects to the mean phenotype value of the population. The prediction accuracy was 0.6569, 0.6695, and 0.5834 for injury indices of salt, alkali, and salt–alkali stress, respectively. SNP182G on MdRGLG3, which changes a leucine to an arginine at the vWFA-domain, conferred tolerance to salt, alkali, and salt-alkali stress. SNP761A on MdKCAB, affecting the Kv_beta domain that cooperated with the linked allelic variation SNP11, contributed to salt, alkali, and salt–alkali tolerance in apple rootstock.

Conclusions

The genomics-assisted prediction models can potentially be used in breeding saline, alkaline, and saline-alkaline tolerant apple rootstocks. The QTLs and the functional markers may provide insight for future studies into the genetic variation of plant abiotic stress tolerance.

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.

Analysis of sorbitol content variation in wild and cultivated apples

BACKGROUND

Sorbitol is the major sugar alcohol in apple and its accumulation in fruit is associated with fruit sweetness. However, little is known about variation in sorbitol content in fruits of apple germplasm. In this study, we investigated sorbitol content in mature fruits of 243 apple cultivars and 20 wild relatives using high-performance liquid chromatography (HPLC).

RESULTS

Sorbitol accumulation showed a significant variation in apple germplasm. Overall, cultivated fruits had significantly lower content of sorbitol than wild fruits. Fruit sorbitol concentration was significantly correlated with fruit size and acidity that are extensively domesticated traits. Hence, the variation in sorbitol accumulation between cultivated and wild fruits may be the indirect result of fruit size and acidity selection during domestication. Moreover, sorbitol content was maintained at low levels throughout fruit development, with a dramatic decrease at the middle stage. The SDH1 gene was highly expressed throughout fruit development, and its expression showed a significant correlation with fruit sorbitol concentration, suggesting its potential role in apple fruit sorbitol accumulation.

CONCLUSIONS

The finding that there is a great variation in fruit sorbitol content among apple germplasm will be helpful for genetic improvement of fruit sorbitol content in apple breeding programs. © 2019 Society of Chemical Industry.

Endogenous Auxin Content Contributes to Larger Size of Apple Fruit

Fruit size is an important economic trait that is controlled by multiple genes. However, the regulatory mechanism for fruit size remains poorly understood. A bud sport variety of "Longfeng" (LF) apple (Malus domestica) was identified and named "Grand Longfeng" (GLF). The fruit size of GLF is larger than that of LF, and both varieties are diploid. We found that the cell size in GLF fruit was larger than that of LF. Then, we compared the fruit transcriptomes of the two varieties using RNA-Seq technology. A total of 1166 differentially expressed genes (DEGs) were detected between GLF and LF fruits. The KEGG analysis revealed that the phytohormone pathway was the most enriched, in which most of the DEGs were related to auxin signaling. Moreover, the endogenous auxin levels of GLF fruit were higher than those of LF. The expressions of auxin synthetic genes, including MdTAR1 and MdYUCCA6, were higher in GLF fruit than LF. Collectively, our findings suggest that auxin plays an important role in fruit size development.

Endogenous Auxin Content Contributes to Larger Size of Apple Fruit

Fruit size is an important economic trait that is controlled by multiple genes. However, the regulatory mechanism for fruit size remains poorly understood. A bud sport variety of "Longfeng" (LF) apple (Malus domestica) was identified and named "Grand Longfeng" (GLF). The fruit size of GLF is larger than that of LF, and both varieties are diploid. We found that the cell size in GLF fruit was larger than that of LF. Then, we compared the fruit transcriptomes of the two varieties using RNA-Seq technology. A total of 1166 differentially expressed genes (DEGs) were detected between GLF and LF fruits. The KEGG analysis revealed that the phytohormone pathway was the most enriched, in which most of the DEGs were related to auxin signaling. Moreover, the endogenous auxin levels of GLF fruit were higher than those of LF. The expressions of auxin synthetic genes, including MdTAR1 and MdYUCCA6, were higher in GLF fruit than LF. Collectively, our findings suggest that auxin plays an important role in fruit size development.

Genome-wide association studies in apple reveal loci of large effect controlling apple polyphenols

Apples are a nutritious food source with significant amounts of polyphenols that contribute to human health and wellbeing, primarily as dietary antioxidants. Although numerous pre- and post-harvest factors can affect the composition of polyphenols in apples, genetics is presumed to play a major role because polyphenol concentration varies dramatically among apple cultivars. Here we investigated the genetic architecture of apple polyphenols by combining high performance liquid chromatography (HPLC) data with ~100,000 single nucleotide polymorphisms (SNPs) from two diverse apple populations. We found that polyphenols can vary in concentration by up to two orders of magnitude across cultivars, and that this dramatic variation was often predictable using genetic markers and frequently controlled by a small number of large effect genetic loci. Using GWAS, we identified candidate genes for the production of quercitrin, epicatechin, catechin, chlorogenic acid, 4-O-caffeoylquinic acid and procyanidins B1, B2, and C1. Our observation that a relatively simple genetic architecture underlies the dramatic variation of key polyphenols in apples suggests that breeders may be able to improve the nutritional value of apples through marker-assisted breeding or gene editing.

Resource allocation trade-offs and the loss of chemical defences during apple domestication

BACKGROUND AND AIMS

Most crops have been dramatically altered from their wild ancestors with the primary goal of increasing harvestable yield. A long-held hypothesis is that increased allocation to yield has reduced plant investment in defence and resulted in crops that are highly susceptible to pests. However, clear demonstrations of these trade-offs have been elusive due to the many selective pressures that occur concurrently during crop domestication.

METHODS

To provide a robust test of whether increased allocation to yield can alter plant investment in defence, this study examined fruit chemical defence traits and herbivore resistance across 52 wild and 56 domesticated genotypes of apples that vary >26-fold in fruit size. Ninety-six phenolic metabolites were quantified in apple skin, pulp and seeds, and resistance to the codling moth was assessed with a series of bioassays.

KEY RESULTS

The results show that wild apples have higher total phenolic concentrations and a higher diversity of metabolites than domesticated apples in skin, pulp and seeds. A negative phenotypic relationship between fruit size and phenolics indicates that this pattern is driven in part by allocation-based trade-offs between yield and defence. There were no clear differences in codling moth performance between wild and domesticated apples and no overall effects of total phenolic concentration on codling moth performance, but the results did show that codling moth resistance was increased in apples with higher phenolic diversity. The concentrations of a few individual compounds (primarily flavan-3-ols) also correlated with increased resistance, primarily driven by a reduction in pupal mass of female moths.

CONCLUSIONS

The negative phenotypic relationship between fruit size and phenolic content, observed across a large number of wild and domesticated genotypes, supports the hypothesis of yield-defence trade-offs in crops. However, the limited effects of phenolics on codling moth highlight the complexity of consequences that domestication has for plant-herbivore interactions. Continued studies of crop domestication can further our understanding of the multiple trade-offs involved in plant defence, while simultaneously leading to novel discoveries that can improve the sustainability of crop production.

Marker-trait associations and genomic predictions of interspecific pear (Pyrus) fruit characteristics

Interspecific pear (Pyrus spp.) hybrid populations are often used to develop novel cultivars. Pear cultivar breeding is a lengthy process because of long juvenility and the subsequent time required for reliable fruit phenotyping. Molecular techniques such as genome-wide association (GWA) and genomic selection (GS) provide an opportunity to fast-forward the development of high-value cultivars. We evaluated the genetic architecture of 10 pear fruit phenotypes (including sensory traits) and the potential of GS using genotyping-by-sequencing of 550 hybrid seedlings from nine interrelated full-sib families. Results from GWA suggested a complex polygenic nature of all 10 traits as the maximum variance explained by each marker was less than 4% of the phenotypic variance. The effect-size of SNPs for each trait suggested many genes of small effect and few of moderate effect. Some genomic regions associated with pear sensory traits were similar to those reported for apple - possibly a result of high synteny between the apple and pear genomes. The average (across nine families) GS accuracy varied from 0.32 (for crispness) to 0.62 (for sweetness), with an across-trait average of 0.42. Further efforts are needed to develop larger genotype-phenotype datasets in order to predict fruit phenotypes of untested seedlings with sufficient efficiency.

Genome-Wide Association Studies in Apple Reveal Loci for Aroma Volatiles, Sugar Composition, and Harvest Date

Understanding the genetic architecture of fruit quality traits is crucial to target breeding of apple ( L.) cultivars. We linked genotype and phenotype information by combining genotyping-by-sequencing (GBS) generated single nucleotide polymorphism (SNP) markers with fruit flavor volatile data, sugar and acid content, and historical trait data from a gene bank collection. Using gas chromatography-mass spectrometry (GC-MS) analysis of apple juice samples, we identified 49 fruit volatile organic compounds (VOCs). We found a very variable content of VOCs, especially for the esters, among 149 apple cultivars. We identified convincing associations for the acetate esters especially butyl acetate and hexyl acetate on chromosome 2 in a region of several alcohol acyl-transferases including AAT1. For sucrose content and for fructose and sucrose in percentage of total sugars, we revealed significant SNP associations. Here, we suggest a vacuolar invertase close to significant SNPs for this association as candidate gene. Harvest date was in strong SNP association with a NAC transcription factor gene and sequencing identified two haplotypes associated with harvest date. The study shows that SNP marker characterization of a gene bank collection can be successfully combined with new and historical trait data for association studies. Suggested candidate genes may contribute to an improved understanding of the genetic basis for important traits and simultaneously provide tools for targeted breeding using marker-assisted selection (MAS).

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.