Genome to Phenome Mapping in Apple Using Historical Data

The potential of red-fleshed apples for cider production

Cider quality is influenced by numerous factors relating to the apples used during production. While extensive research has been done to explore the phenolic content, sensory quality, and storage stability of various apple products, the domain of fermented apple products, such as ciders, remains underrepresented. Red-fleshed apples (RFAs) have naturally high concentrations of phenolic compounds, which indicate their potential in the production of novel cider products. However, a knowledge gap remains regarding the application of RFAs in cider production and how their physicochemical and sensory properties are changed during processing. This review is the first to comprehensively investigate whether and to what extent apple categories (dessert, cider, and RFAs) differ regarding their physicochemical and sensory properties from harvest throughout cider processing. Furthermore, it highlights the importance of a holistic understanding of apple characteristics, encompassing both traditional and RFA varieties in the context of cider production. The findings offer valuable insights for stakeholders aiming to enhance product quality, providing a foundation for future studies on optimizing processing methods for a diverse and appealing range of ciders.

Autosuppression of MdNAC18.1 endowed by a 61-bp promoter fragment duplication delays maturity date in apple

Maturity date considerably influences fruit marketing period and commercial value and it is of particular importance in apple due to its association with fruit firmness that determines storage and shelf life, but the underlying mechanism remains unclear. In this study, we report a 61-bp fragment duplication in the MdNAC18.1 promoter that underpins maturity date variation in apple. MdNAC18.1 is the crucial major gene for maturity date and was found to regulate fruit ripening by activating transcription of ethylene biosynthetic genes and ripening-related transcription factors, including the MdNAC18.1 homologue MdNAC72 and the main regulator of JA signalling MdMYC2. Interestingly, MdNAC18.1 was capable of binding to the promoter itself containing an additional NAC recognition site that arose from the 61-bp duplication to repress its own expression, but could not bind to its own promoter without the 61-bp duplication. Thus, the MdNAC18.1 allele with autosuppression function produces a phenotype of delayed maturity date and slower softening of fruit compared to that without autoregulation function. Our results demonstrate an autosuppression module that regulates the overall tempo of fruit ripening through fine-tuning ethylene biosynthesis.

Integrative multi-environmental genomic prediction in apple

Genomic prediction for multiple environments can aid the selection of genotypes suited to specific soil and climate conditions. Methodological advances allow effective integration of phenotypic, genomic (additive, nonadditive), and large-scale environmental (enviromic) data into multi-environmental genomic prediction models. These models can also account for genotype-by-environment interaction, utilize alternative relationship matrices (kernels), or substitute statistical approaches with deep learning. However, the application of multi-environmental genomic prediction in apple remained limited, likely due to the challenge of building multi-environmental datasets and structurally complex models. Here, we applied efficient statistical and deep learning models for multi-environmental genomic prediction of eleven apple traits with contrasting genetic architectures by integrating genomic- and enviromic-based model components. Incorporating genotype-by-environment interaction effects into statistical models improved predictive ability by up to 0.08 for nine traits compared to the benchmark model. This outcome, based on Gaussian and Deep kernels, shows these alternatives can effectively substitute the standard genomic best linear unbiased predictor (G-BLUP). Including nonadditive and enviromic-based effects resulted in a predictive ability very similar to the benchmark model. The deep learning approach achieved the highest predictive ability for three traits with oligogenic genetic architectures, outperforming the benchmark by up to 0.10. Our results demonstrate that the tested statistical models capture genotype-by-environment interactions particularly well, and the deep learning models efficiently integrate data from diverse sources. This study will foster the adoption of multi-environmental genomic prediction to select apple cultivars adapted to diverse environmental conditions, providing an opportunity to address climate change impacts.

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.

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.

Natural variation in MdNAC5 contributes to fruit firmness and ripening divergence in apple

Fruit firmness is an important trait for characterizing the quality and value of apple. It also serves as an indicator of fruit maturity, as it is a complex trait regulated by multiple genes. Resequencing techniques can be employed to elucidate variations in such complex fruit traits. Here, the whole genomes of 294 F 1 hybrids of 'Fuji' and 'Cripp's Pink' were resequenced, and a high-density binmap was constructed using 5014 bin markers with a total map distance of 2213.23 cM and an average map distance of 0.44 cM. Quantitative trait loci (QTLs) of traits related to fruit were mapped, and an A-T allele variant identified in the coding region of MdNAC5 was found to potentially regulate fruit firmness and ripening. The overexpression of MdNAC5 A resulted in higher production of methionine and 1-aminocyclopropanecarboxylic acid compared to MdNAC5 T , leading to reduced fruit firmness and accelerated ripening in apples and tomatoes. Furthermore, the activities of MdNAC5 A and MdNAC5 T were enhanced through their differential binding to the promoter regions of MdACS1 and MdERF3. Spatial variations in MdNAC5 A and MdNAC5 T caused changes in MdACS1 expression following their interaction with MdERF3. Ultimately, utilizing different MdNAC5 alleles offers a strategy to manipulate fruit firmness in apple breeding.

An InDel variant in the promoter of the NAC transcription factor MdNAC18.1 plays a major role in apple fruit ripening

A complex regulatory network governs fruit ripening, but natural variations and functional differentiation of fruit ripening genes remain largely unknown. Utilizing a genome-wide association study (GWAS), we identified the NAC family transcription factor MdNAC18.1, whose expression is closely associated with fruit ripening in apple (Malus × domestica Borkh.). MdNAC18.1 activated the transcription of genes related to fruit softening (Polygalacturonase, PG) and ethylene biosynthesis (1-aminocyclopropane-1-carboxylic acid synthase, ACS), thereby promoting fruit ripening of apple and tomato (Solanum lycopersicum). There were two single-nucleotide polymorphisms (SNP-1,545 and SNP-2,002) and a 58-bp insertion-deletion (InDel-58) in the promoter region of MdNAC18.1. Among these, InDel-58 serves as the main effector in activating the expression of MdNAC18.1 and driving fruit ripening. InDel-58 determines the binding affinity of the class D MADS-box protein AGAMOUS-LIKE 11 (MdAGL11), a negative regulator of fruit ripening. The InDel-58 deletion in the early-ripening genotype reduces the inhibitory effect of MdAGL11 on MdNAC18.1. Moreover, MdNAC18.1 and its homologous genes originated from a common ancestor across 61 angiosperms, with functional diversification attributed to tandem replications that occurred in basal angiosperms. In summary, our study revealed how a set of natural variations influence fruit ripening and explored the functional diversification of MdNAC18.1 during evolution.

MdNAC5: a key regulator of fructose accumulation in apple fruit

The sweetness of apple fruit is a key factor in the improvement of apple varieties, with fructose being the sweetest of the soluble sugars, playing a crucial role in determining the overall sweetness of the apple. Therefore, uncovering the key genes controlling fructose accumulation and deciphering the regulatory mechanisms of fructose are vitally important for the improvement of apple varieties. In this study, through BSA-seq and transcriptome analysis of the 'Changfu 2' × 'Golden Delicious' F1 hybrid population, MdNAC5 was identified as a key regulatory gene for fructose content. MdNAC5 was shown to significantly influence fructose accumulation in both apples and tomatoes. Furthermore, we conducted a detailed identification of sugar transporters and metabolic enzymes in apples, discovering that MdNAC5 can enhance fructose accumulation in vacuoles and the conversion of sucrose to fructose by binding to and activating the promoters of the vacuolar sugar transporter MdTST2 and the neutral invertase MdNINV6. Additionally, MdNAC5 regulated the MdEIN3.4-MdSWEET15a module, strengthening the unloading of sucrose in the phloem of the fruit. Our results reveal a new mechanism by which MdNAC5 regulates fructose accumulation in apples and provide theoretical foundations for improving apple sweetness through genetic modification.

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.

Why we thrive beneath a northern sky - genomic signals of selection in apple for adaptation to northern Sweden

Good understanding of the genomic regions underlying adaptation of apple to boreal climates is needed to facilitate efficient breeding of locally adapted apple cultivars. Proper infrastructure for phenotyping and evaluation is essential for identification of traits responsible for adaptation, and dissection of their genetic composition. However, such infrastructure is costly and currently not available for the boreal zone of northern Sweden. Therefore, we used historical pomological data on climate adaptation of 59 apple cultivars and whole genome sequencing to identify genomic regions that have undergone historical selection among apple cultivars recommended for cultivation in northern Sweden. We found the apple collection to be composed of two ancestral groups that are largely concordant with the grouping into 'hardy' and 'not hardy' cultivars based on the pomological literature. Using a number of genome-wide scans for signals of selection, we obtained strong evidence of positive selection at a genomic region around 29 MbHFTH1 of chromosome 1 among apple cultivars in the 'hardy' group. Using phased genotypic data from the 20 K apple Infinium® SNP array, we identified haplotypes associated with the two cultivar groups and traced transmission of these haplotypes through the pedigrees of some apple cultivars. This demonstrates that historical data from pomological literature can be analyzed by population genomic approaches as a step towards revealing the genomic control of a key property for a horticultural niche market. Such knowledge is needed to facilitate efficient breeding strategies for development of locally adapted apple cultivars in the future. The current study illustrates the response to a very strong selective pressure imposed on tree crops by climatic factors, and the importance of genetic research on this topic and feasibility of breeding efforts in the light of the ongoing climate change.

Genome-wide association studies reveal novel loci controlling tuber flesh color and oxidative browning in Dioscorea alata

BACKGROUND

Consumers' preferences for food crops are guided by quality attributes. This study aimed at deciphering the genetic basis of quality traits, especially tuber flesh color (FC) and oxidative browning (OB) in Dioscorea alata, based on the genome-wide association studies (GWAS) approach. The D. alata panel was planted at two locations in Guadeloupe. At harvest, the FC was scored visually as white, cream, or purple on longitudinally sliced mature tubers. The OB was scored visually as the presence or absence of browning after 15 min of exposure of the sliced samples to ambient air.

RESULTS

Phenotypic characterization for FC and OB of a diverse panel of D. alata genotypes highlighted significant variation within the panel and across two locations. The genotypes within the panel displayed a weak structure and could be classified into three subpopulations. GWAS identified 14 and 4 significant associations for tuber FC and OB, respectively, with phenotypic variance, explained values ranging from 7.18% to 18.04%. Allele segregation analysis at the significantly associated loci highlighted the favorable alleles for the desired traits, i.e., white FC and no OB. A total of 24 putative candidate genes were identified around the significant signals. A comparative analysis with previously reported quantitative trait loci indicated that numerous genomic regions control these traits in D. alata.

CONCLUSION

Our study provides important insights into the genetic control of tuber FC and OB in D. alata. The major and stable loci can be further utilized to improve selection in breeding programs for developing new cultivars with enhanced tuber quality. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Genomic region and origin for selected traits during differentiation of small-fruit cultivars in Japanese apricot (Prunus mume)

The Japanese apricot (Prunus mume) is a popular fruit tree in Japan. However, the genetic factors associated with fruit trait variations are poorly understood. In this study, we investigated nine fruit-associated traits, including harvesting time, fruit diameter, fruit shape, fruit weight, stone (endocarp) weight, ratio of stone weight to fruit weight, and rate of fruit gumming, using 110 Japanese apricot accessions over four years. A genome-wide association study (GWAS) was performed for these traits and strong signals were detected on chromosome 6 for harvesting time and fruit diameters. These peaks were shown to undergo strong artificial selection during the differentiation of small-fruit cultivars. The genomic region defined by the GWAS and XP-nSL analyses harbored several candidate genes associated with plant hormone regulation. Furthermore, the alleles of small-fruit cultivars in this region were shown to have genetic proximity to some Chinese cultivars of P. mume. These results indicate that the small-fruit trait originated in China; after being introduced into Japan, it was preferred and selected by the Japanese people, resulting in the differentiation of small-fruit cultivars.

Linking New Alleles at the Oscillator Loci to Flowering and Expansion of Asian Rice

The central oscillator is believed to be the key mechanism by which plants adapt to new environments. However, impacts from hybridization, the natural environment, and human selection have rarely been assessed on the oscillator of a crop. Here, from clearly identified alleles at oscillator loci (OsCCA1/LHY, OsPRR95, OsPRR37, OsPRR59, and OsPRR1) in ten diverse genomes of Oryza sativa, additional accessions, and functional analysis, we show that rice's oscillator was rebuilt primarily by new alleles from recombining parental sequences and subsequent 5' or/and coding mutations. New alleles may exhibit altered transcript levels from that of a parental allele and are transcribed variably among genetic backgrounds and natural environments in RIL lines. Plants carrying more expressed OsCCA1_a and less transcribed OsPRR1_e flower early in the paddy field. 5' mutations are instrumental in varied transcription, as shown by EMSA tests on one deletion at the 5' region of highly transcribed OsPRR1_a. Compared to relatively balanced mutations at oscillator loci of Arabidopsis thaliana, 5' mutations of OsPRR37 (and OsCCA1 to a less degree) were under negative selection while those of OsPRR1 alleles were under strong positive selection. Together, range expansion of Asian rice can be elucidated by human selection on OsPRR1 alleles via local flowering time-yield relationships.

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.

Whole-genome re-sequencing, diversity analysis, and stress-resistance analysis of 77 grape rootstock genotypes

INTRODUCTION

Grape rootstocks play critical role in the development of the grape industry over the globe for their higher adaptability to various environments, and the evaluation of their genetic diversity among grape genotypes is necessary to the conservation and utility of genotypes.

METHODS

To analyze the genetic diversity of grape rootstocks for a better understanding multiple resistance traits, whole-genome re-sequencing of 77 common grape rootstock germplasms was conducted in the present study.

RESULTS

About 645 billion genome sequencing data were generated from the 77 grape rootstocks at an average depth of ~15.5×, based on which the phylogenic clusters were generated and the domestication of grapevine rootstocks was explored. The results indicated that the 77 rootstocks originated from five ancestral components. Through phylogenetic, principal components, and identity-by-descent (IBD) analyses, these 77 grape rootstocks were assembled into ten groups. It is noticed that the wild resources of V. amurensis and V. davidii, originating from China and being generally considered to have stronger resistance against biotic and abiotic stresses, were sub-divided from the other populations. Further analysis indicated that a high level of linkage disequilibrium was found among the 77 rootstock genotypes, and a total of 2,805,889 single nucleotide polymorphisms (SNPs) were excavated, GWAS analysis among the grape rootstocks located 631, 13, 9, 2, 810, and 44 SNP loci that were responsible to resistances to phylloxera, root-knot nematodes, salt, drought, cold and waterlogging traits.

DISCUSSION

This study generated a significant amount of genomic data from grape rootstocks, thus providing a theoretical basis for further research on the resistance mechanism of grape rootstocks and the breeding of resistant varieties. These findings also reveal that China originated V. amurensis and V. davidii could broaden the genetic background of grapevine rootstocks and be important germplasm used in breeding high stress-resistant grapevine rootstocks.

An apple somatic mutation of delayed fruit maturation date is primarily caused by a retrotransposon insertion-associated large deletion

Somatic mutations may alter important traits in tree fruits, such as fruit color, size and maturation date. Autumn Gala (AGala), a somatic mutation from apple cultivar Gala, matures 4 weeks later than Gala. To understand the mechanisms underlying the delayed maturation, RNA-seq analyses were conducted with fruit sampled at 13 (Gala) and 16 (AGala) time-points during their growth and development. Weighted gene co-expression network analysis (WGCNA) of 23 372 differentially expressed genes resulted in 25 WGCNA modules. Of these, modules 1 (r = -0.98, P = 2E-21) and 2 (r = -0.52, P = 0.004), which were suppressed in AGala, were correlated with fruit maturation date. Surprisingly, 77 of the 152 member genes in module 1 were harbored in a 2.8-Mb genomic region on chromosome 6 that was deleted and replaced by a 10.7-kb gypsy-like retrotransposon (Gy-36) from chromosome 7 in AGala. Among the 77 member genes, MdACT7 was the most suppressed (by 10.5-fold) in AGala due to a disruptive 2.5-kb insertion in coding sequence. Moreover, MdACT7 is the exclusive apple counterpart of Arabidopsis ACT7 known of essential roles in plant development, and the functional allele MdACT7, which was lost to the deletion in AGala, was associated with early fruit maturation in 268 apple accessions. Overexpressing alleles MdACT7 and Mdact7 in an Arabidopsis act7 line showed that MdACT7 largely rescued its stunted growth and delayed initial flowering while Mdact7 did not. Therefore, the 2.8-Mb hemizygous deletion is largely genetically causal for fruit maturation delay in AGala, and the total loss of MdACT7 might have contributed to the phenotype.

Research Progress on Genetic Basis of Fruit Quality Traits in Apple (Malus × domestica)

Identifying the genetic variation characteristics of phenotypic traits is important for fruit tree breeding. During the long-term evolution of fruit trees, gene recombination and natural mutation have resulted in a high degree of heterozygosity. Apple (Malus × domestica Borkh.) shows strong ecological adaptability and is widely cultivated, and is among the most economically important fruit crops worldwide. However, the high level of heterozygosity and large genome of apple, in combination with its perennial life history and long juvenile phase, complicate investigation of the genetic basis of fruit quality traits. With continuing augmentation in the apple genomic resources available, in recent years important progress has been achieved in research on the genetic variation of fruit quality traits. This review focuses on summarizing recent genetic studies on apple fruit quality traits, including appearance, flavor, nutritional, ripening, and storage qualities. In addition, we discuss the mapping of quantitative trait loci, screening of molecular markers, and mining of major genes associated with fruit quality traits. The overall aim of this review is to provide valuable insights into the mechanisms of genetic variation and molecular breeding of important fruit quality traits in apple.

Target of rapamycin (TOR) regulates the response to low nitrogen stress via autophagy and hormone pathways in Malus hupehensis

Target of rapamycin (TOR) is a highly conserved master regulator in eukaryotes; it regulates cell proliferation and growth by integrating different signals. However, little is known about the function of TOR in perennial woody plants. Different concentrations of AZD8055 (an inhibitor of TOR) were used in this study to investigate the role of TOR in the response to low nitrogen (N) stress in the wild apple species Malus hupehensis. Low N stress inhibited the growth of M. hupehensis plants, and 1 μM AZD alleviated this effect. Plants supplied with 1 μM AZD had higher photosynthetic capacity, which promoted the accumulation of biomass, as well as higher contents of N and anthocyanins and lower content of starch. Exogenous application of 1 μM AZD also promoted the development of the root system. Plants supplied with at least 5 μM AZD displayed early leaf senescence. RNA-seq analysis indicated that TOR altered the expression of genes related to the low N stress response, such as genes involved in photosystem, starch metabolism, autophagy, and hormone metabolism. Further analysis revealed altered autophagy in plants supplied with AZD under low N stress; the metabolism of plant hormones also changed following AZD supplementation. In sum, our findings revealed that appropriate inhibition of TOR activated autophagy and jasmonic acid signaling in M. hupehensis, which allowed plants to cope with low N stress. Severe TOR inhibition resulted in the excessive accumulation of salicylic acid, which probably led to programmed cell death in M. hupehensis.

Recent status of Genotyping by Sequencing (GBS) Technology in cucumber (Cucumis sativus L.): a review

Current and advanced breeding tools are being used to improve economically important horticultural crops to meet the consumers' needs and preferences. Genotyping-by-sequencing (GBS) is an extremely useful tool in the investigation and analysis of the genetic diversity of different cultivars. Based on a broad range of genetic backgrounds like single nucleotide polymorphism (SNPs), GBS is known as a novel technique to facilitate the detection of quantitative trait loci (QTL) regions robustly linked with interested traits compared to genome-wide association study (GWAS) and QTL. GBS has gained popularity among breeders in recent years and it is also employed in cucumber breeding programs. Cucumbers (C. sativus L.) are monoecious, gynoecious and some of them are parthenocarpic species. Cucumber is one of the most economical and essential crops in the Cucurbitaceae family. For time immemorial, cucumber has been produced and consumed all over the world like other cucurbits. To a large extent, cultivated cucurbits are beneficial to human health for providing necessary minerals and fibers.Therefore, this review portrays the current status of advances made by using GBS and its combination with other tools in various studies of cucumber such as the use of GBS and single nucleotide polymorphism (SNP) markers, GBS and GWAS, also with QTL and marker-assisted selection (MAS) are applied to display and detect explicit genetic architecture complex traits in crops and chromosome rearrangements.Cucumber breeding programs have undoubtedly benefited from genotyping-by-sequencing. Using the GBS method, research discovered lots of new candidate genes that control various traits including spine color, fruit stalk-end color, and disease resistance in cucumber lines.

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.

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.

New insights into flowering date in Prunus: fine mapping of a major QTL in sweet cherry

Flowering date is an important trait in Prunus fruit species, especially for their adaptation in a global warming context. Numerous quantitative trait loci (QTLs) have been identified and a major one was previously located on LG4. The objectives of this study were to fine-map this QTL in sweet cherry, to identify robust candidate genes by using the new sweet cherry genome sequence of the cultivar 'Regina' and to define markers usable in marker-assisted selection (MAS). We performed QTL analyses on two populations derived from crosses using cultivars 'Regina' and 'Garnet' as parents. The first one (n = 117) was phenotyped over ten years, while the second one (n = 1386) was evaluated during three years. Kompetitive allele specific PCR (KASP) markers located within the QTL region on LG4 were developed and mapped within this region, consisting in the first fine mapping in sweet cherry. The QTL interval was narrowed from 380 kb to 68 kb and candidate genes were identified by using the genome sequence of 'Regina'. Their expression was analyzed from bud dormancy period to flowering in cultivars 'Regina' and 'Garnet'. Several genes, such as PavBOI-E3, PavSR45a and PavSAUR71, were differentially expressed in these two cultivars and could be then considered as promising candidate genes. Two KASP markers were validated using a population derived from a cross between cultivars 'Regina' and 'Lapins' and two collections, including landraces and modern cultivars. Thanks to the high synteny within the Prunus genus, these results give new insights into the control of flowering date in Prunus species and pave the way for the development of molecular breeding strategies.

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.

Chromosome-level genome assemblies of five Prunus species and genome-wide association studies for key agronomic traits in peach

Prunus species include many important perennial fruit crops, such as peach, plum, apricot, and related wild species. Here, we report de novo genome assemblies for five species, including the cultivated species peach (Prunus persica), plum (Prunus salicina), and apricot (Prunus armeniaca), and the wild peach species Tibetan peach (Prunus mira) and Chinese wild peach (Prunus davidiana). The genomes ranged from 240 to 276 Mb in size, with contig N50 values of 2.27-8.30 Mb and 25,333-27,826 protein-coding gene models. As the phylogenetic tree shows, plum diverged from its common ancestor with peach, wild peach species, and apricot ~7 million years ago (MYA). We analyzed whole-genome resequencing data of 417 peach accessions, called 3,749,618 high-quality SNPs, 577,154 small indels, 31,800 deletions, duplications, and inversions, and 32,338 insertions, and performed a structural variant-based genome-wide association study (GWAS) of key agricultural traits. From our GWAS data, we identified a locus associated with a fruit shape corresponding to the OVATE transcription factor, where a large inversion event correlates with higher OVATE expression in flat-shaped accessions. Furthermore, a GWAS revealed a NAC transcription factor associated with fruit developmental timing that is linked to a tandem repeat variant and elevated NAC expression in early-ripening accessions. We also identified a locus encoding microRNA172d, where insertion of a transposable element into its promoter was found in double-flower accessions. Thus, our efforts have suggested roles for OVATE, a NAC transcription factor, and microRNA172d in fruit shape, fruit development period, and floral morphology, respectively, that can be connected to traits in other crops, thereby demonstrating the importance of parallel evolution in the diversification of several commercially important domesticated species. In general, these genomic resources will facilitate functional genomics, evolutionary research, and agronomic improvement of these five and other Prunus species. We believe that structural variant-based GWASs can also be used in other plants, animal species, and humans and be combined with deep sequencing GWASs to precisely identify candidate genes and genetic architecture components.

The NAC transcription factor FaRIF controls fruit ripening in strawberry

In contrast to climacteric fruits such as tomato, the knowledge on key regulatory genes controlling the ripening of strawberry, a nonclimacteric fruit, is still limited. NAC transcription factors (TFs) mediate different developmental processes in plants. Here, we identified and characterized Ripening Inducing Factor (FaRIF), a NAC TF that is highly expressed and induced in strawberry receptacles during ripening. Functional analyses based on stable transgenic lines aimed at silencing FaRIF by RNA interference, either from a constitutive promoter or the ripe receptacle-specific EXP2 promoter, as well as overexpression lines showed that FaRIF controls critical ripening-related processes such as fruit softening and pigment and sugar accumulation. Physiological, metabolome, and transcriptome analyses of receptacles of FaRIF-silenced and overexpression lines point to FaRIF as a key regulator of strawberry fruit ripening from early developmental stages, controlling abscisic acid biosynthesis and signaling, cell-wall degradation, and modification, the phenylpropanoid pathway, volatiles production, and the balance of the aerobic/anaerobic metabolism. FaRIF is therefore a target to be modified/edited to control the quality of strawberry fruits.

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.

Genome-Wide Association Study Reveals Genomic Region Associated with Mite-Recruitment Phenotypes in the Domesticated Grapevine (Vitis vinifera)

Indirect defenses are plant phenotypes that reduce damage by attracting natural enemies of plant pests and pathogens to leaves. Despite their economic and ecological importance, few studies have investigated the genetic underpinnings of indirect defense phenotypes. Here, we present a genome-wide association study of five phenotypes previously determined to increase populations of beneficial (fungivorous and predacious) mites on grape leaves (genus Vitis): leaf bristles, leaf hairs, and the size, density, and depth of leaf domatia. Using a common garden genetic panel of 399 V. vinifera cultivars, we tested for genetic associations of these phenotypes using previously obtained genotyping data from the Vitis9kSNP array. We found one single nucleotide polymorphism (SNP) significantly associated with domatia density. This SNP (Chr5:1160194) is near two genes of interest: Importin Alpha Isoform 1 (VIT_205s0077g01440), involved in downy mildew resistance, and GATA Transcription Factor 8 (VIT_205s0077g01450), involved in leaf shape development. Our findings are among the first to examine the genomic regions associated with ecologically important plant traits that facilitate interactions with beneficial mites, and suggest promising candidate genes for breeding and genetic editing to increase naturally occurring predator-based defenses in grapevines.

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.

Research progress of fruit color development in apple (Malus domestica Borkh.)

Apple (Malus domestica Borkh.) is one of the most widely produced and economically important fruits in temperate regions. Fruit color development in apple is a major focus for both breeders and researchers as consumers associate brightly colored red apples with ripeness and a good flavor. In recent years, great progress has been made in the research of apple fruit color development, but its development mechanism has not been systematic dissected from the aspects of genetics, transcription or environmental factors. Here, we summarize research on the coloration of apple fruit, including the development of important genomic databases to identify important genomic regions and genes, genetic and transcriptional factors that regulate pigment accumulation, environmental factors that affect anthocyanin synthesis, and the current breeding progress of red-skinned and red-fleshed apples. We describe key transcription factors, such as MYB, bHLH, and WD40, which are involved in the regulation of anthocyanin synthesis and fruit color development in apple. We also discuss the regulation of apple color by external environmental factors such as light, temperature, and water. The aim of this review is to provide insights into the molecular mechanisms underlying anthocyanin biosynthesis in apple. This information will provide significant guidance for the breeding of high-quality red-skinned and red-fleshed apple varieties.

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.

Physicochemical quality and metabolomics comparison of the green food apple and conventional apple in China

The Green Food apple production has increased rapidly in China recently, due to its sustainability and high-quality compared to the conventional apple. The aim of this study was evaluating and comparing physicochemical quality as well as metabolomics of the apples grown in green certified and conventional production systems. The results of physicochemical properties indicated that Green Food apples showed significant superiorities than conventional ones at soluble solids content, firmness and titratable acidity. While, in the vitamin C content comparison, there was no significant difference. Compounds, including several phenolic compounds and fatty acids, were revealed by the untargeted metabolomics as differential markers between apples grown in the two production systems, and could serve as the potential markers for differentiating these two types of apples. Overall, these results of this study could encourage the Green Food apples consumption, promote its production, and will benefit the development of Green Food production and the cleaner agricultural production in China.

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.

Multiple-population QTL mapping of maturity and fruit-quality traits reveals LG4 region as a breeding target in sweet cherry (Prunus avium L.)

Sweet cherry maturity date and fruit quality are relevant traits for its marketability, transport, and consumer acceptance. In this work, sweet cherry fruit development time, maturity date, and commercial fruit-quality traits (size, weight, firmness, soluble solid content, and titratable acidity) were investigated to improve the knowledge of their genetic control, and to identify alleles of breeding interest. Six sweet cherry populations segregating for these traits were used for QTL analyses. These populations descend from cross- and self-pollinations of local Spanish sweet cherries 'Ambrunés' and 'Cristobalina', and breed cultivars ('Brooks', 'Lambert', or 'Vic'). The six populations (n = 411), previously genotyped with RosBREED Cherry 6 K SNP array, were phenotyped for 2 years. QTL analyses were conducted using a multifamily approach implemented by FlexQTL™. Fruit development time, soluble solid content, and titratable acidity QTLs are first reported in sweet cherry in this work. Significant QTLs were detected for all the traits. Eighteen were more stable as they were detected for 2 years. Of these, nine are first reported in this work. The major QTLs for fruit development time, maturity date, firmness, and soluble solid content were identified on the same narrow region of linkage group 4. These traits also showed significant positive correlation (long fruit development time associated with late maturity, high firmness, and high SSC). NAC transcription factor genes identified on this LG4 region may be candidate genes for the regulation of these traits in sweet cherry, as previously described in syntenic regions of other Rosaceae species. Haplotypes of breeding interest on this LG4 genomic region were identified and will be useful for sweet cherry breeding from this and related plant material.

Review of the Impact of Apple Fruit Ripening, Texture and Chemical Contents on Genetically Determined Susceptibility to Storage Rots

Fungal storage rots like blue mould, grey mould, bull's eye rot, bitter rot and brown rot destroy large amounts of the harvested apple crop around the world. Application of fungicides is nowadays severely restricted in many countries and production systems, and these problems are therefore likely to increase. Considerable variation among apple cultivars in resistance/susceptibility has been reported, suggesting that efficient defence mechanisms can be selected for and used in plant breeding. These are, however, likely to vary between pathogens, since some fungi are mainly wound-mediated while others attack through lenticels or by infecting blossoms. Since mature fruits are considerably more susceptible than immature fruits, mechanisms involving fruit-ripening processes are likely to play an important role. Significant associations have been detected between the susceptibility to rots in harvested fruit and various fruit maturation-related traits like ripening time, fruit firmness at harvest and rate of fruit softening during storage, as well as fruit biochemical contents like acidity, sugars and polyphenols. Some sources of resistance to blue mould have been described, but more research is needed on the development of spore inoculation methods that produce reproducible data and can be used for large screenings, especially for lenticel-infecting fungi.

Multi-dimensional machine learning approaches for fruit shape phenotyping in strawberry

BACKGROUND

Shape is a critical element of the visual appeal of strawberry fruit and is influenced by both genetic and non-genetic determinants. Current fruit phenotyping approaches for external characteristics in strawberry often rely on the human eye to make categorical assessments. However, fruit shape is an inherently multi-dimensional, continuously variable trait and not adequately described by a single categorical or quantitative feature. Morphometric approaches enable the study of complex, multi-dimensional forms but are often abstract and difficult to interpret. In this study, we developed a mathematical approach for transforming fruit shape classifications from digital images onto an ordinal scale called the Principal Progression of k Clusters (PPKC). We use these human-recognizable shape categories to select quantitative features extracted from multiple morphometric analyses that are best fit for genetic dissection and analysis.

RESULTS

We transformed images of strawberry fruit into human-recognizable categories using unsupervised machine learning, discovered 4 principal shape categories, and inferred progression using PPKC. We extracted 68 quantitative features from digital images of strawberries using a suite of morphometric analyses and multivariate statistical approaches. These analyses defined informative feature sets that effectively captured quantitative differences between shape classes. Classification accuracy ranged from 68% to 99% for the newly created phenotypic variables for describing a shape.

CONCLUSIONS

Our results demonstrated that strawberry fruit shapes could be robustly quantified, accurately classified, and empirically ordered using image analyses, machine learning, and PPKC. We generated a dictionary of quantitative traits for studying and predicting shape classes and identifying genetic factors underlying phenotypic variability for fruit shape in strawberry. The methods and approaches that we applied in strawberry should apply to other fruits, vegetables, and specialty crops.

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.

A Genomic Variation Map Provides Insights into the Genetic Basis of Spring Chinese Cabbage (Brassica rapa ssp. pekinensis) Selection

Chinese cabbage is the most consumed leafy crop in East Asian countries. However, premature bolting induced by continuous low temperatures severely decreases the yield and quality of the Chinese cabbage, and therefore restricts its planting season and geographic distribution. In the past 40 years, spring Chinese cabbage with strong winterness has been selected to meet the market demand. Here, we report a genome variation map of Chinese cabbage generated from the resequencing data of 194 geographically diverse accessions of three ecotypes. In-depth analyses of the selection sweeps and genome-wide patterns revealed that spring Chinese cabbage was selected from a specific population of autumn Chinese cabbage around the area of Shandong peninsula in northern China. We identified 23 genomic loci that underwent intensive selection, and further demonstrated by gene expression and haplotype analyses that the incorporation of elite alleles of VERNALISATION INSENTIVE 3.1 (BrVIN3.1) and FLOWER LOCUS C 1 (BrFLC1) is a determinant genetic source of variation during selection. Moreover, we showed that the quantitative response of BrVIN3.1 to cold due to the sequence variations in the cis elements of the BrVIN3.1 promoter significantly contributes to bolting-time variation in Chinese cabbage. Collectively, our study provides valuable insights into the genetic basis of spring Chinese cabbage selection and will facilitate the breeding of bolting-resistant varieties by molecular-marker-assisted selection, transgenic or gene editing approaches.

Genetic analysis of a major international collection of cultivated apple varieties reveals previously unknown historic heteroploid and inbred relationships

Domesticated apple (Malus x domestica Borkh.) is a major global crop and the genetic diversity held within the pool of cultivated varieties is important for the development of future cultivars. The aim of this study was to investigate the diversity held within the domesticated form, through the analysis of a major international germplasm collection of cultivated varieties, the UK National Fruit Collection, consisting of over 2,000 selections of named cultivars and seedling varieties. We utilised Diversity Array Technology (DArT) markers to assess the genetic diversity within the collection. Clustering attempts, using the software STRUCTURE revealed that the accessions formed a complex and historically admixed group for which clear clustering was challenging. Comparison of accessions using the Jaccard similarity coefficient allowed us to identify clonal and duplicate material as well as revealing pairs and groups that appeared more closely related than a standard parent-offspring or full-sibling relations. From further investigation, we were able to propose a number of new pedigrees, which revealed that some historically important cultivars were more closely related than previously documented and that some of them were partially inbred. We were also able to elucidate a number of parent-offspring relationships that had resulted in a number of important polyploid cultivars. This included reuniting polyploid cultivars that in some cases dated as far back as the 18th century, with diploid parents that potentially date back as far as the 13th century.

Population structure, relatedness and ploidy levels in an apple gene bank revealed through genotyping-by-sequencing

In recent years, new genome-wide marker systems have provided highly informative alternatives to low density marker systems for evaluating plant populations. To date, most apple germplasm collections have been genotyped using low-density markers such as simple sequence repeats (SSRs), whereas only a few have been explored using high-density genome-wide marker information. We explored the genetic diversity of the Pometum gene bank collection (University of Copenhagen, Denmark) of 349 apple accessions using over 15,000 genome-wide single nucleotide polymorphisms (SNPs) and 15 SSR markers, in order to compare the strength of the two approaches for describing population structure. We found that 119 accessions shared a putative clonal relationship with at least one other accession in the collection, resulting in the identification of 272 (78%) unique accessions. Of these unique accessions, over half (52%) share a first-degree relationship with at least one other accession. There is therefore a high degree of clonal and family relatedness in the Danish apple gene bank. We find significant genetic differentiation between Malus domestica and its supposed primary wild ancestor, M. sieversii, as well as between accessions of Danish origin and all others. Using the GBS approach allowed us to estimate ploidy levels, which were in accordance with flow cytometry results. Overall, we found strong concordance between analyses based on the genome-wide SNPs and the 15 SSR loci. However, we argue that GBS is superior to traditional SSR approaches because it allows detection of a much more detailed population structure and can be further exploited in genome-wide association studies (GWAS). Finally, we compare GBS with SSR for the purpose of identifying clones and pedigree relations in a diverse apple gene bank and discuss the advantages and constraints of the two approaches.

Apple fruit acidity is genetically diversified by natural variations in three hierarchical epistatic genes: MdSAUR37, MdPP2CH and MdALMTII

Many efforts have been made to map quantitative trait loci (QTLs) to facilitate practical marker-assisted selection (MAS) in plants. In the present study, using MapQTL and BSA-seq (bulk segregant analysis using next generation sequencing) with two independent pedigree-based populations, we identified four major genome-wide QTLs responsible for apple fruit acidity. Candidate genes were screened in major QTL regions, and three functional gene markers, including a non-synonymous A/G single-nucleotide polymorphism (SNP) in the coding region of MdPP2CH, a 36-bp insertion in the promoter of MdSAUR37 and a previously reported SNP in MdALMTII, were validated to influence the malate content of apple fruits. In addition, MdPP2CH inactivated three vacuolar H⁺ -ATPases (MdVHA-A3, MdVHA-B2 and MdVHA-D2) and one aluminium-activated malate transporter (MdALMTII) via dephosphorylation and negatively influenced fruit malate accumulation. The dephosphotase activity of MdPP2CH was suppressed by MdSAUR37, which implied a higher hierarchy of genetic interaction. Therefore, the MdSAUR37/MdPP2CH/MdALMTII chain cascaded hierarchical epistatic genetic effects to precisely determine apple fruit malate content. An A/G SNP (-1010) on the MdMYB44 promoter region from a major QTL (qtl08.1) was closely associated with fruit malate content. The predicted phenotype values (PPVs) were estimated using the tentative genotype values of the gene markers, and the PPVs were significantly correlated with the observed phenotype values. Our findings provide an insight into plant genome-based selection in apples and will aid in conducting research to understand the fundamental physiological basis of quantitative genetics.

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

The apple ( × Borkh.) is an economically and culturally important crop grown worldwide. Growers of this long-lived perennial must produce fruit of adequate quality while also combatting abiotic and biotic stress. Traditional apple breeding can take up to 20 yr from initial cross to commercial release, but genomics-assisted breeding can help accelerate this process. To advance genomics-assisted breeding in apple, we performed genome-wide association studies (GWAS) and genomic prediction in a collection of 172 apple accessions by linking over 55,000 single nucleotide polymorphisms (SNPs) with 10 phenotypes collected over 2 yr. Genome-wide association studies revealed several known loci for skin color, harvest date and firmness at harvest. Several significant GWAS associations were detected for resistance to a major fungal pathogen, apple scab ( [Cke.] Wint.), but we demonstrate that these hits likely represent a single ancestral source. Using genomic prediction, we show that most phenotypes are sufficiently predictable using genome-wide SNPs to be candidates for genomic selection. Finally, we detect a signal for firmness retention after storage on chromosome 10 and show that it may not stem from variation in , a gene repeatedly identified in bi-parental mapping studies and widely believed to underlie a major QTL for firmness on chromosome 10. We provide evidence that this major QTL is more likely due to variation in a neighboring ethylene response factor (ERF) gene. The present study showcases the superior mapping resolution of GWAS compared to bi-parental linkage mapping by identifying a novel candidate gene underlying a well-studied, major QTL involved in apple firmness.

An integrated approach for increasing breeding efficiency in apple and peach in Europe

Despite the availability of whole genome sequences of apple and peach, there has been a considerable gap between genomics and breeding. To bridge the gap, the European Union funded the FruitBreedomics project (March 2011 to August 2015) involving 28 research institutes and private companies. Three complementary approaches were pursued: (i) tool and software development, (ii) deciphering genetic control of main horticultural traits taking into account allelic diversity and (iii) developing plant materials, tools and methodologies for breeders. Decisive breakthroughs were made including the making available of ready-to-go DNA diagnostic tests for Marker Assisted Breeding, development of new, dense SNP arrays in apple and peach, new phenotypic methods for some complex traits, software for gene/QTL discovery on breeding germplasm via Pedigree Based Analysis (PBA). This resulted in the discovery of highly predictive molecular markers for traits of horticultural interest via PBA and via Genome Wide Association Studies (GWAS) on several European genebank collections. FruitBreedomics also developed pre-breeding plant materials in which multiple sources of resistance were pyramided and software that can support breeders in their selection activities. Through FruitBreedomics, significant progresses were made in the field of apple and peach breeding, genetics, genomics and bioinformatics of which advantage will be made by breeders, germplasm curators and scientists. A major part of the data collected during the project has been stored in the FruitBreedomics database and has been made available to the public. This review covers the scientific discoveries made in this major endeavour, and perspective in the apple and peach breeding and genomics in Europe and beyond.

Morphometrics Reveals Complex and Heritable Apple Leaf Shapes

Apple (Malus spp.) is a widely grown and valuable fruit crop. Leaf shape is important for flowering in apple and may also be an early indicator for other agriculturally valuable traits. We examined 9,000 leaves from 869 unique apple accessions using linear measurements and comprehensive morphometric techniques. We identified allometric variation as the result of differing length-to-width aspect ratios between accessions and species of apple. The allometric variation was due to variation in the width of the leaf blade, not the length. Aspect ratio was highly correlated with the first principal component (PC1) of morphometric variation quantified using elliptical Fourier descriptors (EFDs) and persistent homology (PH). While the primary source of variation was aspect ratio, subsequent PCs corresponded to complex shape variation not captured by linear measurements. After linking the morphometric information with over 122,000 genome-wide single nucleotide polymorphisms (SNPs), we found high SNP heritability values even at later PCs, indicating that comprehensive morphometrics can capture complex, heritable phenotypes. Thus, techniques such as EFDs and PH are capturing heritable biological variation that would be missed using linear measurements alone.