Genomics-assisted breeding in fruit trees

Genomic prediction and genome-wide association study using combined genotypic data from different genotyping systems: application to apple fruit quality traits

With advances in next-generation sequencing technologies, various marker genotyping systems have been developed for genomics-based approaches such as genomic selection (GS) and genome-wide association study (GWAS). As new genotyping platforms are developed, data from different genotyping platforms must be combined. However, the potential use of combined data for GS and GWAS has not yet been clarified. In this study, the accuracy of genomic prediction (GP) and the detection power of GWAS increased for most fruit quality traits of apples when using combined data from different genotyping systems, Illumina Infinium single-nucleotide polymorphism array and genotyping by random amplicon sequencing-direct (GRAS-Di) systems. In addition, the GP model, which considered the inbreeding effect, further improved the accuracy of the seven fruit traits. Runs of homozygosity (ROH) islands overlapped with the significantly associated regions detected by the GWAS for several fruit traits. Breeders may have exploited these regions to select promising apples by breeders, increasing homozygosity. These results suggest that combining genotypic data from different genotyping platforms benefits the GS and GWAS of fruit quality traits in apples. Information on inbreeding could be beneficial for improving the accuracy of GS for fruit traits of apples; however, further analysis is required to elucidate the relationship between the fruit traits and inbreeding depression (e.g. decreased vigor).

Abiotic Stress Tolerance Boosted by Genetic Diversity in Plants

Plant breeding [...].

Genomic prediction of resistance to Hymenoscyphus fraxineus in common ash (Fraxinus excelsior L.) populations

The increase in introduced insect pests and pathogens due to anthropogenic environmental changes has become a major concern for tree species worldwide. Common ash (Fraxinus excelsior L.) is one of such species facing a significant threat from the invasive fungal pathogen Hymenoscyphus fraxineus. Some studies have indicated that the susceptibility of ash to the pathogen is genetically determined, providing some hope for accelerated breeding programs that are aimed at increasing the resistance of ash populations. To address this challenge, we used a genomic selection strategy to identify potential genetic markers that are associated with resistance to the pathogen causing ash dieback. Through genome-wide association studies (GWAS) of 300 common ash individuals from 30 populations across Poland (ddRAD, dataset A), we identified six significant SNP loci with a p-value ≤1 × 10-4 associated with health status. To further evaluate the effectiveness of GWAS markers in predicting health status, we considered two genomic prediction scenarios. Firstly, we conducted cross-validation on dataset A. Secondly, we trained markers on dataset A and tested them on dataset B, which involved whole-genome sequencing of 20 individuals from two populations. Genomic prediction analysis revealed that the top SNPs identified via GWAS exhibited notably higher prediction accuracies compared to randomly selected SNPs, particularly with a larger number of SNPs. Cross-validation analyses using dataset A showcased high genomic prediction accuracy, predicting tree health status with over 90% accuracy across the top SNP sets ranging from 500 to 10,000 SNPs from the GWAS datasets. However, no significant results emerged for health status when the model trained on dataset A was tested on dataset B. Our findings illuminate potential genetic markers associated with resistance to ash dieback, offering support for future breeding programs in Poland aimed at combating ash dieback and bolstering conservation efforts for this invaluable tree species.

Climate change impacts on temperate fruit and nut production: a systematic review

Temperate fruit and nut crops require distinctive cold and warm seasons to meet their physiological requirements and progress through their phenological stages. Consequently, they have been traditionally cultivated in warm temperate climate regions characterized by dry-summer and wet-winter seasons. However, fruit and nut production in these areas faces new challenging conditions due to increasingly severe and erratic weather patterns caused by climate change. This review represents an effort towards identifying the current state of knowledge, key challenges, and gaps that emerge from studies of climate change effects on fruit and nut crops produced in warm temperate climates. Following the PRISMA methodology for systematic reviews, we analyzed 403 articles published between 2000 and 2023 that met the defined eligibility criteria. A 44-fold increase in the number of publications during the last two decades reflects a growing interest in research related to both a better understanding of the effects of climate anomalies on temperate fruit and nut production and the need to find strategies that allow this industry to adapt to current and future weather conditions while reducing its environmental impacts. In an extended analysis beyond the scope of the systematic review methodology, we classified the literature into six main areas of research, including responses to environmental conditions, water management, sustainable agriculture, breeding and genetics, prediction models, and production systems. Given the rapid expansion of climate change-related literature, our analysis provides valuable information for researchers, as it can help them identify aspects that are well understood, topics that remain unexplored, and urgent questions that need to be addressed in the future.

Multiple-statistical genome-wide association analysis and genomic prediction of fruit aroma and agronomic traits in peaches

'Chinese Cling' is an important founder in peach breeding history due to the pleasant flavor. Genome-wide association studies (GWAS) combined with genomic selection are promising tools in fruit tree breeding, as there is a considerable time lapse between crossing and release of a cultivar. In this study, 242 peaches from Shanghai germplasm were genotyped with 145 456 single-nucleotide polymorphisms (SNPs). The six agronomic traits of fruit flesh color, fruit shape, fruit hairiness, flower type, pollen sterility, and soluble solids content, along with 14 key volatile odor compounds (VOCs), were recorded for multiple-statistical GWAS. Except the reported candidate genes, six novel genes were identified as associated with these traits. Thirty-nine significant SNPs were associated with eight VOCs. The putative candidate genes were confirmed for VOCs by RNA-seq, including three genes in the biosynthesis pathway found to be associated with linalool, soluble solids content, and cis-3-hexenyl acetate. Multiple-trait genomic prediction enhanced the predictive ability for γ-decalactone to 0.7415 compared with the single-trait model value of 0.1017. One PTS1-SSR marker was designed to predict the linalool content, and the favorable genotype 187/187 was confirmed, mainly existing in the 'Shanghai Shuimi' landrace. Overall, our findings will be helpful in determining peach accessions with the ideal phenotype and show the potential of multiple-trait genomic prediction to improve accuracy for highly correlated genetic traits. The diagnostic marker will be valuable for the breeder to bridge the gap between quantitative trait loci and marker-assisted selection for developing strong-aroma cultivars.

Differential gene expression associated with flower development of mango (Mangifera indica L.) varieties with different shelf-life

Mango (Mangifera indica L.) is one of the most important commercial fruit crop grown in many parts of the world. Major challenges affecting mango trade are short shelf-life, high susceptibility to chilling injury, post-harvest diseases and consumer demand for improved fruit quality. The objective of the present study was to reveal the key regulators present in bud and flower tissues during flower development stage, associated with fruit development and affect the shelf-life of the mango fruit. RNA-sequencing of contrasting genotypes having short and long shelf-life, was carried out. Comparative differential expression pathway studies of long shelf-life (Totapuri) and short shelf-life (Bombay Green) mango genotypes revealed a total of 177 highly differentially expressed genes. Out of 177 total genes, 101 genes from endoplasmic reticulum pathway and very few from gibberellins (3) and jasmonic acid (1) pathway were identified. Genes from endoplasmic reticulum pathway like hsp 90, SRC2, DFRA, CHS, BG3 and ASPG1 mainly up regulated in Bombay Green. Uniprotein B9R8D3 also shows up regulation in Bombay Green. Ethylene insensitive pathway gene EIL1 up regulated in Bombay Green. Gene CAD1 from phenylpropanoid pathway mainly up regulated in Bombay Green. A total of 4 SSRs and 227 SNPs were mined from these pathways specific to the shelf-life. Molecular studies of endoplasmic reticulum, phenylpropanoid, ethylene, polygalacturonase and hormone pathways at the time of bud and flower formation revealed key regulators that determine the shelf-life of mango fruit.

Development and Evaluation of an AxiomTM 60K SNP Array for Almond (Prunus dulcis)

A high-density single nucleotide polymorphism (SNP) array is essential to enable faster progress in plant breeding for new cultivar development. In this regard, we have developed an Axiom 60K almond SNP array by resequencing 81 almond accessions. For the validation of the array, a set of 210 accessions were genotyped and 82.8% of the SNPs were classified in the best recommended SNPs. The rate of missing data was between 0.4% and 2.7% for the almond accessions and less than 15.5% for the few peach and wild accessions, suggesting that this array can be used for peach and interspecific peach × almond genetic studies. The values of the two SNPs linked to the RMja (nematode resistance) and SK (bitterness) genes were consistent. We also genotyped 49 hybrids from an almond F2 progeny and could build a genetic map with a set of 1159 SNPs. Error rates, less than 1%, were evaluated by comparing replicates and by detection of departures from Mendelian inheritance in the F2 progeny. This almond array is commercially available and should be a cost-effective genotyping tool useful in the search for new genes and quantitative traits loci (QTL) involved in the control of agronomic traits.

Genotype-by-environment interaction and genetic dissection of heartwood color in Cryptomeria japonica based on multiple common gardens and quantitative trait loci mapping

The heartwood color of a major plantation tree Cryptomeria japonica shows high variability among clones and cultivars, and brighter heartwood has higher value in the usage of non-laminated wood such as in traditional construction, which makes heartwood color an important trait in breeding of this species. However, the genetic basis of the interactions between genetics and the environment on heartwood color has been understudied while these are necessary for effective breeding programs in multiple environmental condition. The objectives of the present study were to evaluate the effects of genetics and environments on heartwood color and how they interact in contrasting environments, and to identify genomic regions controlling heartwood color in C. japonica across multiple environments. Heartwood color in terms of L*a*b* color space and spectral reflectance was measured in common gardens established in three contrasting sites. Quantitative trait loci (QTL) that affect heartwood color were identified using previously constructed highly saturated linkage maps. Results found that heartwood color was largely genetically controlled, and genotype-by-environment interaction explained one-third of the total genetic variance of heartwood color. The effect of the environment was small compared to the effect of genetics, whereas environmental effects largely varied among heartwood color traits. QTL analysis identified a large number of QTLs with small to moderate effects (phenotypic variation explained of 6.6% on average). Some of these QTLs were stably expressed in multiple environments or had pleiotropic effects on heartwood color and moisture content. These results indicated that genetic variation in phenotypic plasticity plays an important role in regulating heartwood color and that the identified QTLs would maximize the breeding efficiency of heartwood color in C. japonica in heterogeneous environments.

Dissecting Breeders' Sense via Explainable Machine Learning Approach: Application to Fruit Peelability and Hardness in Citrus

"Genomics-assisted breeding", which utilizes genomics-based methods, e.g., genome-wide association study (GWAS) and genomic selection (GS), has been attracting attention, especially in the field of fruit breeding. Low-cost genotyping technologies that support genome-assisted breeding have already been established. However, efficient collection of large amounts of high-quality phenotypic data is essential for the success of such breeding. Most of the fruit quality traits have been sensorily and visually evaluated by professional breeders. However, the fruit morphological features that serve as the basis for such sensory and visual judgments are unclear. This makes it difficult to collect efficient phenotypic data on fruit quality traits using image analysis. In this study, we developed a method to automatically measure the morphological features of citrus fruits by the image analysis of cross-sectional images of citrus fruits. We applied explainable machine learning methods and Bayesian networks to determine the relationship between fruit morphological features and two sensorily evaluated fruit quality traits: easiness of peeling (Peeling) and fruit hardness (FruH). In each of all the methods applied in this study, the degradation area of the central core of the fruit was significantly and directly associated with both Peeling and FruH, while the seed area was significantly and directly related to FruH alone. The degradation area of albedo and the area of flavedo were also significantly and directly related to Peeling and FruH, respectively, except in one or two methods. These results suggest that an approach that combines explainable machine learning methods, Bayesian networks, and image analysis can be effective in dissecting the experienced sense of a breeder. In breeding programs, collecting fruit images and efficiently measuring and documenting fruit morphological features that are related to fruit quality traits may increase the size of data for the analysis and improvement of the accuracy of GWAS and GS on the quality traits of the citrus fruits.

Genome-Wide Association Study of Healthful Flavonoids among Diverse Mandarin Accessions

Mandarins have many unique flavonoids with documented health benefits and that help to prevent chronic human diseases. Flavonoids are difficult to measure and cannot be phenotyped without the use of specialized equipment; consequently, citrus breeders have not used flavonoid contents as selection criteria to develop cultivars with increased benefits for human health or increased tolerance to diseases. In this study, peel, pulp, and seed samples collected from many mandarin accessions and their hybrids were analyzed for the presence of selected flavonoids with documented human health benefits. A genome-wide association study (GWAS) was used to identify SNPs associated with biosynthesis of flavonoids in these mandarin accessions, and there were 420 significant SNPs were found to be associated with 28 compounds in peel, pulp, or seed samples. Four candidate genes involved in flavonoid biosynthesis were identified by enrichment analysis. SNPs that were found to be associated with compounds in pulp samples have the potential to be used as markers to select mandarins with improved phytonutrient content to benefit human health. Mandarin cultivars bred with increased flavonoid content may provide value to growers and consumers.

Perspectives and recent progress of genome-wide association studies (GWAS) in fruits

BACKGROUND

Earlier next-generation sequencing technologies are being vastly used to explore, administer, and investigate the gene space with accurate profiling of nucleotide variations in the germplasm. OVERVIEW AND PROGRESS: Recently, novel advancements in high-throughput sequencing technologies allow a genotyping-by-sequencing approach that has opened up new horizons for extensive genotyping exploiting single-nucleotide-polymorphisms (SNPs). This method acts as a bridge to support and minimize a genotype to phenotype gap allowing genetic selection at the genome-wide level, named genomic selection that could facilitate the selection of traits also in the pomology sector. In addition to this, genome-wide genotyping is a prerequisite for genome-wide association studies that have been used successfully to discover the genes, which control polygenic traits including the genetic loci, associated with the trait of interest in fruit crops.

AIMS AND PROSPECTS

This review article emphasizes the role of genome-wide approaches to unlock and explore the genetic potential along with the detection of SNPs affecting the phenotype of fruit crops and highlights the prospects of genome-wide association studies in fruits.

Inheritance of Yield Components and Morphological Traits in Avocado cv. Hass From "Criollo" "Elite Trees" via Half-Sib Seedling Rootstocks

Grafting induces precocity and maintains clonal integrity in fruit tree crops. However, the complex rootstock × scion interaction often precludes understanding how the tree phenotype is shaped, limiting the potential to select optimum rootstocks. Therefore, it is necessary to assess (1) how seedling progenies inherit trait variation from elite 'plus trees', and (2) whether such family superiority may be transferred after grafting to the clonal scion. To bridge this gap, we quantified additive genetic parameters (i.e., narrow sense heritability-h ², and genetic-estimated breeding values-GEBVs) across landraces, "criollo", "plus trees" of the super-food fruit tree crop avocado (Persea americana Mill.), and their open-pollinated (OP) half-sib seedling families. Specifically, we used a genomic best linear unbiased prediction (G-BLUP) model to merge phenotypic characterization of 17 morpho-agronomic traits with genetic screening of 13 highly polymorphic SSR markers in a diverse panel of 104 avocado "criollo" "plus trees." Estimated additive genetic parameters were validated at a 5-year-old common garden trial (i.e., provenance test), in which 22 OP half-sib seedlings from 82 elite "plus trees" served as rootstocks for the cv. Hass clone. Heritability (h ²) scores in the "criollo" "plus trees" ranged from 0.28 to 0.51. The highest h ² values were observed for ribbed petiole and adaxial veins with 0.47 (CI 95%0.2-0.8) and 0.51 (CI 0.2-0.8), respectively. The h ² scores for the agronomic traits ranged from 0.34 (CI 0.2-0.6) to 0.39 (CI 0.2-0.6) for seed weight, fruit weight, and total volume, respectively. When inspecting yield variation across 5-year-old grafted avocado cv. Hass trees with elite OP half-sib seedling rootstocks, the traits total number of fruits and fruits' weight, respectively, exhibited h ² scores of 0.36 (± 0.23) and 0.11 (± 0.09). Our results indicate that elite "criollo" "plus trees" may serve as promissory donors of seedling rootstocks for avocado cv. Hass orchards due to the inheritance of their outstanding trait values. This reinforces the feasibility to leverage natural variation from "plus trees" via OP half-sib seedling rootstock families. By jointly estimating half-sib family effects and rootstock-mediated heritability, this study promises boosting seedling rootstock breeding programs, while better discerning the consequences of grafting in fruit tree crops.

Induced Genetic Variations in Fruit Trees Using New Breeding Tools: Food Security and Climate Resilience

Fruit trees provide essential nutrients to humans by contributing to major agricultural outputs and economic growth globally. However, major constraints to sustainable agricultural productivity are the uncontrolled proliferation of the population, and biotic and abiotic stresses. Tree mutation breeding has been substantially improved using different physical and chemical mutagens. Nonetheless, tree plant breeding has certain crucial bottlenecks including a long life cycle, ploidy level, occurrence of sequence polymorphisms, nature of parthenocarpic fruit development and linkage. Genetic engineering of trees has focused on boosting quality traits such as productivity, wood quality, and resistance to biotic and abiotic stresses. Recent technological advances in genome editing provide a unique opportunity for the genetic improvement of woody plants. This review examines application of the CRISPR-Cas system to reduce disease susceptibility, alter plant architecture, enhance fruit quality, and improve yields. Examples are discussed of the contemporary CRISPR-Cas system to engineer easily scorable PDS genes, modify lignin, and to alter the flowering onset, fertility, tree architecture and certain biotic stresses.

Fruit crops in the era of genome editing: closing the regulatory gap

The conventional breeding of fruits and fruit trees has led to the improvement of consumer-driven traits such as fruit size, yield, nutritional properties, aroma and taste, as well as the introduction of agronomic properties such as disease resistance. However, even with the assistance of modern molecular approaches such as marker-assisted selection, the improvement of fruit varieties by conventional breeding takes considerable time and effort. The advent of genetic engineering led to the rapid development of new varieties by allowing the direct introduction of genes into elite lines. In this review article, we discuss three such case studies: the Arctic^® apple, the Pinkglow pineapple and the SunUp/Rainbow papaya. We consider these events in the light of global regulations for the commercialization of genetically modified organisms (GMOs), focusing on the differences between product-related systems (the USA/Canada comparative safety assessment) and process-related systems (the EU "precautionary principle" model). More recently, genome editing has provided an efficient way to introduce precise mutations in plants, including fruits and fruit trees, replicating conventional breeding outcomes without the extensive backcrossing and selection typically necessary to introgress new traits. Some jurisdictions have reacted by amending the regulations governing GMOs to provide exemptions for crops that would be indistinguishable from conventional varieties based on product comparison. This has revealed the deficiencies of current process-related regulatory frameworks, particularly in the EU, which now stands against the rest of the world as a unique example of inflexible and dogmatic governance based on political expediency and activism rather than rigorous scientific evidence.

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

Background

Improving yield prediction and selection efficiency is critical for tree breeding. This is vital for macadamia trees with the time from crossing to production of new cultivars being almost a quarter of a century. Genomic selection (GS) is a useful tool in plant breeding, particularly with perennial trees, contributing to an increased rate of genetic gain and reducing the length of the breeding cycle. We investigated the potential of using GS methods to increase genetic gain and accelerate selection efficiency in the Australian macadamia breeding program with comparison to traditional breeding methods. This study evaluated the prediction accuracy of GS in a macadamia breeding population of 295 full-sib progeny from 32 families (29 parents, reciprocals combined), along with a subset of parents. Historical yield data for tree ages 5 to 8years were used in the study, along with a set of 4113 SNP markers. The traits of focus were average nut yield from tree ages 5 to 8years and yield stability, measured as the standard deviation of yield over these 4 years. GBLUP GS models were used to obtain genomic estimated breeding values for each genotype, with a five-fold cross-validation method and two techniques: prediction across related populations and prediction across unrelated populations.

Results

Narrow-sense heritability of yield and yield stability was low (h²=0.30 and 0.04, respectively). Prediction accuracy for yield was 0.57 for predictions across related populations and 0.14 when predicted across unrelated populations. Accuracy of prediction of yield stability was high (r=0.79) for predictions across related populations. Predicted genetic gain of yield using GS in related populations was 474g/year, more than double that of traditional breeding methods (226g/year), due to the halving of generation length from 8 to 4years.

Conclusions

The results of this study indicate that the incorporation of GS for yield into the Australian macadamia breeding program may accelerate genetic gain due to reduction in generation length, though the cost of genotyping appears to be a constraint at present.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07694-z.

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.

Inheritance of Rootstock Effects in Avocado (Persea americana Mill.) cv. Hass

Grafting is typically utilized to merge adapted seedling rootstocks with highly productive clonal scions. This process implies the interaction of multiple genomes to produce a unique tree phenotype. However, the interconnection of both genotypes obscures individual contributions to phenotypic variation (rootstock-mediated heritability), hampering tree breeding. Therefore, our goal was to quantify the inheritance of seedling rootstock effects on scion traits using avocado (Persea americana Mill.) cv. Hass as a model fruit tree. We characterized 240 diverse rootstocks from 8 avocado cv. Hass orchards with similar management in three regions of the province of Antioquia, northwest Andes of Colombia, using 13 microsatellite markers simple sequence repeats (SSRs). Parallel to this, we recorded 20 phenotypic traits (including morphological, biomass/reproductive, and fruit yield and quality traits) in the scions for 3 years (2015-2017). Relatedness among rootstocks was inferred through the genetic markers and inputted in a "genetic prediction" model to calculate narrow-sense heritabilities (h 2) on scion traits. We used three different randomization tests to highlight traits with consistently significant heritability estimates. This strategy allowed us to capture five traits with significant heritability values that ranged from 0.33 to 0.45 and model fits (r) that oscillated between 0.58 and 0.73 across orchards. The results showed significance in the rootstock effects for four complex harvest and quality traits (i.e., total number of fruits, number of fruits with exportation quality, and number of fruits discarded because of low weight or thrips damage), whereas the only morphological trait that had a significant heritability value was overall trunk height (an emergent property of the rootstock-scion interaction). These findings suggest the inheritance of rootstock effects, beyond root phenotype, on a surprisingly wide spectrum of scion traits in "Hass" avocado. They also reinforce the utility of polymorphic SSRs for relatedness reconstruction and genetic prediction of complex traits. This research is, up to date, the most cohesive evidence of narrow-sense inheritance of rootstock effects in a tropical fruit tree crop. Ultimately, our work highlights the importance of considering the rootstock-scion interaction to broaden the genetic basis of fruit tree breeding programs while enhancing our understanding of the consequences of grafting.

Genome-wide association studies of fruit quality traits in jujube germplasm collections using genotyping-by-sequencing

Chinese jujube (Ziziphus jujuba Mill.) is an important fruit crop and harbors many highly diverse traits of potential economic importance. Fruit size, stone size, and fruit cracking have an important influence on the commercial value of jujube. This study is the first to conduct a genome-wide association study (GWAS) on 180 accessions of jujube and focuses on locating single-nucleotide polymorphisms (SNPs) associated with nine important fruit quality traits. Genotyping was performed using genotyping-by-sequencing and 4651 high-quality SNPs were identified. A genetic diversity analysis revealed the presence of three distinct groups, and rapid linkage disequilibrium decay was observed in this jujube population. Using a mixed linear model, a total of 45 significant SNP-trait associations were detected, among which 33 SNPs had associations with fruit size-related traits, nine were associated with stone size-related traits, and three with fruit cracking-related traits. In total, 21 candidate genes involved in cell expansion, abiotic stress responses, hormone signaling, and growth development were identified from the genome sequences of jujube. These results are useful as basic data for GWAS of other jujube traits, and these significant SNP loci and candidate genes should aid marker-assisted breeding and genomic selection of improved jujube cultivars.

Genomic predictions and genome-wide association studies based on RAD-seq of quality-related metabolites for the genomics-assisted breeding of tea plants

Effectively using genomic information greatly accelerates conventional breeding and applying it to long-lived crops promotes the conversion to genomic breeding. Because tea plants are bred using conventional methods, we evaluated the potential of genomic predictions (GPs) and genome-wide association studies (GWASs) for the genetic breeding of tea quality-related metabolites using genome-wide single nucleotide polymorphisms (SNPs) detected from restriction site-associated DNA sequencing of 150 tea accessions. The present GP, based on genome-wide SNPs, and six models produced moderate prediction accuracy values (r) for the levels of most catechins, represented by ( -)-epigallocatechin gallate (r = 0.32-0.41) and caffeine (r = 0.44-0.51), but low r values for free amino acids and chlorophylls. Integrated analysis of GWAS and GP detected potential candidate genes for each metabolite using 80-160 top-ranked SNPs that resulted in the maximum cumulative prediction value. Applying GPs and GWASs to tea accession traits will contribute to genomics-assisted tea breeding.

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

Background

Breeding for new macadamia cultivars with high nut yield is expensive in terms of time, labour and cost. Most trees set nuts after four to five years, and candidate varieties for breeding are evaluated for at least eight years for various traits. Genome-wide association studies (GWAS) are promising methods to reduce evaluation and selection cycles by identifying genetic markers linked with key traits, potentially enabling early selection through marker-assisted selection. This study used 295 progeny from 32 full-sib families and 29 parents (18 phenotyped) which were planted across four sites, with each tree genotyped for 4113 SNPs. ASReml-R was used to perform association analyses with linear mixed models including a genomic relationship matrix to account for population structure. Traits investigated were: nut weight (NW), kernel weight (KW), kernel recovery (KR), percentage of whole kernels (WK), tree trunk circumference (TC), percentage of racemes that survived from flowering through to nut set, and number of nuts per raceme.

Results

Seven SNPs were significantly associated with NW (at a genome-wide false discovery rate of < 0.05), and four with WK. Multiple regression, as well as mapping of markers to genome assembly scaffolds suggested that some SNPs were detecting the same QTL. There were 44 significant SNPs identified for TC although multiple regression suggested detection of 16 separate QTLs.

Conclusions

These findings have important implications for macadamia breeding, and highlight the difficulties of heterozygous populations with rapid LD decay. By coupling validated marker-trait associations detected through GWAS with MAS, genetic gain could be increased by reducing the selection time for economically important nut characteristics. Genomic selection may be a more appropriate method to predict complex traits like tree size and yield.

Citrus Taste Modification Potentials by Genetic Engineering

Citrus fruits are mainly consumed as fresh fruit and processed juice products. They serve as nutritional and a tasty diet in our daily life. However, the formidable bitterness and delayed bitterness significantly impact the citrus industry attributable to the two major bitter compounds naringin and limonin. The extremely sour and acidic also negatively affects the sensory quality of citrus products. Citrus breeding programs have developed different strategies to improve citrus quality and a wealth of studies have aimed to uncover the genetic and biochemical basis of citrus flavor. In this minireview, we outline the major genes characterized to be involved in pathways shaping the sweet, bitter, or sour taste in citrus, and discuss briefly about the possible approaches to modify citrus taste by genetic engineering.

QTL analysis of resistance to bacterial wilt caused by Ralstonia solanacearum in potato

Ralstonia solanacearum causes bacterial wilt, a soil-borne disease and one of the most important maladies of potato and other Solanaceae crops. We analyzed the resistance of a potato clone to bacterial wilt by quantitative trait locus (QTL) analysis. A resistant diploid potato clone 10-03-30 was crossed with a susceptible diploid clone F₁-1 to generate a diploid, two-way pseudo-testcross F₁ population comprised of 94 genotypes. Dense linkage maps, containing 4,139 single nucleotide polymorphism markers with an average distance of 0.6 and 0.3 cM between markers, were constructed for both parents. The resistance level was evaluated by in vitro inoculation test with R. solanacearum (phylotype I/biovar 4/race 1). Five QTLs (qBWR-1 to -5) were identified on potato chromosomes 1, 3, 7, 10, and 11, and they explained 9.3-18.4% of the phenotypic variance. The resistant parent had resistant alleles in qBWR-2, qBWR-3, and qBWR-4 and susceptible alleles in qBWR-1 and qBWR-5. Accumulation of the resistant alleles in all five QTLs increased the level of resistance compared with that of the resistant parent. This is the first study to identify novel QTLs for bacterial wilt resistance in potato by using genome-wide markers.

The role of genetics in mainstreaming the production of new and orphan crops to diversify food systems and support human nutrition

Especially in low-income nations, new and orphan crops provide important opportunities to improve diet quality and the sustainability of food production, being rich in nutrients, capable of fitting into multiple niches in production systems, and relatively adapted to low-input conditions. The evolving space for these crops in production systems presents particular genetic improvement requirements that extensive gene pools are able to accommodate. Particular needs for genetic development identified in part with plant breeders relate to three areas of fundamental importance for addressing food production and human demographic trends and associated challenges, namely: facilitating integration into production systems; improving the processability of crop products; and reducing farm labour requirements. Here, we relate diverse involved target genes and crop development techniques. These techniques include transgressive methods that involve defining exemplar crop models for effective new and orphan crop improvement pathways. Research on new and orphan crops not only supports the genetic improvement of these crops, but they serve as important models for understanding crop evolutionary processes more broadly, guiding further major crop evolution. The bridging position of orphan crops between new and major crops provides unique opportunities for investigating genetic approaches for de novo domestications and major crop 'rewildings'.

Single-step genomic prediction of fruit-quality traits using phenotypic records of non-genotyped relatives in citrus

The potential of genomic selection (GS) is currently being evaluated for fruit breeding. GS models are usually constructed based on information from both the genotype and phenotype of population. However, information from phenotyped but non-genotyped relatives can also be used to construct GS models, and this additional information can improve their accuracy. In the present study, we evaluated the utility of single-step genomic best linear unbiased prediction (ssGBLUP) in citrus breeding, which is a genomic prediction method that combines the kinship information from genotyped and non-genotyped relatives into a single relationship matrix for a mixed model to apply GS. Fruit weight, sugar content, and acid content of 1,935 citrus individuals, of which 483 had genotype data of 2,354 genome-wide single nucleotide polymorphisms, were evaluated from 2009–2012. The prediction accuracy of ssGBLUP for genotyped individuals was similar to or higher than that of usual genomic best linear unbiased prediction method using only genotyped individuals, especially for sugar content. Therefore, ssGBLUP could yield higher accuracy in genotyped individuals by adding information from non-genotyped relatives. The prediction accuracy of ssGBLUP for non-genotyped individuals was also slightly higher than that of conventional best linear unbiased prediction method using pedigree information. This indicates that ssGBLUP can enhance prediction accuracy of breeding values for non-genotyped individuals using genomic information of genotyped relatives. These results demonstrate the potential of ssGBLUP for fruit breeding, including citrus.

Transcriptome analysis and annotation: SNPs identified from single copy annotated unigenes of three polyploid blueberry crops

Blueberry is a kind of new rising popular perennial fruit with high healthful quality. It is of utmost importance to develop new blueberry varieties for different climatic zones to satisfy the demand of people in the world. Molecular marker assisted breeding is believed to be an ideal method for the development of new blueberry varieties for its shorter breeding cycle than the conventional breeding. Simple sequence repeats (SSRs) and single nucleotide polymorphisms (SNPs) markers are widely used molecular tools for marker assisted breeding, which could be detected at large scale by the transcriptome sequencing. Here, we sequenced the leaves transcriptome of 19 rabbiteye (Vaccinium ashei Reade), 13 southern highbush (Vaccinium. corymbosum L × native southern Vaccinium Spp) and 22 cultivars of northern highbush blueberry (Vaccinium corymbosum L) by using next generation sequencing technologies. A total of 80.825 Gb clean data with an average of about 12.525 million reads per cultivar were obtained. We assembled 58,968, 55,973 and 53,887 unigenes by using the clean data from rabbiteye, southern highbush and northern highbush blueberry cultivars, respectively. Among these unigenes, 3599, 3495 and 3513 unigenes were detected as candidate resistance genes in three blueberry crops. Moreover, we identified more than 8756, 9020, and 9198 SSR markers from these unigenes, and 7665, 4861, 13,063 SNPs from the annotated single copy unigenes, respectively. The results will be helpful for the molecular genetics and association analysis of blueberry and the basic molecular information of pest and disease resistance of blueberry, and would also offer huge number of molecular tools for the marker assisted breeding to produce blueberry cultivars with different adaptive characteristics.

Facing Climate Change: Biotechnology of Iconic Mediterranean Woody Crops

The Mediterranean basin is especially sensitive to the adverse outcomes of climate change and especially to variations in rainfall patterns and the incidence of extremely high temperatures. These two concurring adverse environmental conditions will surely have a detrimental effect on crop performance and productivity that will be particularly severe on woody crops such as citrus, olive and grapevine that define the backbone of traditional Mediterranean agriculture. These woody species have been traditionally selected for traits such as improved fruit yield and quality or alteration in harvesting periods, leaving out traits related to plant field performance. This is currently a crucial aspect due to the progressive and imminent effects of global climate change. Although complete genome sequence exists for sweet orange (Citrus sinensis) and clementine (Citrus clementina), olive tree (Olea europaea) and grapevine (Vitis vinifera), the development of biotechnological tools to improve stress tolerance still relies on the study of the available genetic resources including interspecific hybrids, naturally occurring (or induced) polyploids and wild relatives under field conditions. To this respect, post-genomic era studies including transcriptomics, metabolomics and proteomics provide a wide and unbiased view of plant physiology and biochemistry under adverse environmental conditions that, along with high-throughput phenotyping, could contribute to the characterization of plant genotypes exhibiting physiological and/or genetic traits that are correlated to abiotic stress tolerance. The ultimate goal of precision agriculture is to improve crop productivity, in terms of yield and quality, making a sustainable use of land and water resources under adverse environmental conditions using all available biotechnological tools and high-throughput phenotyping. This review focuses on the current state-of-the-art of biotechnological tools such as high throughput -omics and phenotyping on grapevine, citrus and olive and their contribution to plant breeding programs.

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.

Genome-wide association study and genomic prediction using parental and breeding populations of Japanese pear (Pyrus pyrifolia Nakai)

Breeding of fruit trees is hindered by their large size and long juvenile period. Genome-wide association study (GWAS) and genomic selection (GS) are promising methods for circumventing this hindrance, but preparing new large datasets for these methods may not always be practical. Here, we evaluated the potential of breeding populations evaluated routinely in breeding programs for GWAS and GS. We used a pear parental population of 86 varieties and breeding populations of 765 trees from 16 full-sib families, which were phenotyped for 18 traits and genotyped for 1,506 single nucleotide polymorphisms (SNPs). The power of GWAS and accuracy of genomic prediction were improved when we combined data from the breeding populations and the parental population. The accuracy of genomic prediction was improved further when full-sib data of the target family were available. The results suggest that phenotype data collected in breeding programs can be beneficial for GWAS and GS when they are combined with genome-wide marker data. The potential of GWAS and GS will be further extended if we can build a system for routine collection of the phenotype and marker genotype data for breeding populations.

The genome sequence of sweet cherry (Prunus avium) for use in genomics-assisted breeding

We determined the genome sequence of sweet cherry (Prunus avium) using next-generation sequencing technology. The total length of the assembled sequences was 272.4 Mb, consisting of 10,148 scaffold sequences with an N50 length of 219.6 kb. The sequences covered 77.8% of the 352.9 Mb sweet cherry genome, as estimated by k-mer analysis, and included >96.0% of the core eukaryotic genes. We predicted 43,349 complete and partial protein-encoding genes. A high-density consensus map with 2,382 loci was constructed using double-digest restriction site–associated DNA sequencing. Comparing the genetic maps of sweet cherry and peach revealed high synteny between the two genomes; thus the scaffolds were integrated into pseudomolecules using map- and synteny-based strategies. Whole-genome resequencing of six modern cultivars found 1,016,866 SNPs and 162,402 insertions/deletions, out of which 0.7% were deleterious. The sequence variants, as well as simple sequence repeats, can be used as DNA markers. The genomic information helps us to identify agronomically important genes and will accelerate genetic studies and breeding programs for sweet cherries. Further information on the genomic sequences and DNA markers is available in DBcherry (http://cherry.kazusa.or.jp (8 May 2017, date last accessed)).

Virtual Plants Need Water Too: Functional-Structural Root System Models in the Context of Drought Tolerance Breeding

Developing a sustainable agricultural model is one of the great challenges of the coming years. The agricultural practices inherited from the Green Revolution of the 1960s show their limits today, and new paradigms need to be explored to counter rising issues such as the multiplication of climate-change related drought episodes. Two such new paradigms are the use of functional-structural plant models to complement and rationalize breeding approaches and a renewed focus on root systems as untapped sources of plant amelioration. Since the late 1980s, numerous functional and structural models of root systems were developed and used to investigate the properties of root systems in soil or lab-conditions. In this review, we focus on the conception and use of such root models in the broader context of research on root-driven drought tolerance, on the basis of root system architecture (RSA) phenotyping. Such models result from the integration of architectural, physiological and environmental data. Here, we consider the different phenotyping techniques allowing for root architectural and physiological study and their limits. We discuss how QTL and breeding studies support the manipulation of RSA as a way to improve drought resistance. We then go over the integration of the generated data within architectural models, how those architectural models can be coupled with functional hydraulic models, and how functional parameters can be measured to feed those models. We then consider the assessment and validation of those hydraulic models through confrontation of simulations to experimentations. Finally, we discuss the up and coming challenges facing root systems functional-structural modeling approaches in the context of breeding.

Crop Breeding Chips and Genotyping Platforms: Progress, Challenges, and Perspectives

There is a rapidly rising trend in the development and application of molecular marker assays for gene mapping and discovery in field crops and trees. Thus far, more than 50 SNP arrays and 15 different types of genotyping-by-sequencing (GBS) platforms have been developed in over 25 crop species and perennial trees. However, much less effort has been made on developing ultra-high-throughput and cost-effective genotyping platforms for applied breeding programs. In this review, we discuss the scientific bottlenecks in existing SNP arrays and GBS technologies and the strategies to develop targeted platforms for crop molecular breeding. We propose that future practical breeding platforms should adopt automated genotyping technologies, either array or sequencing based, target functional polymorphisms underpinning economic traits, and provide desirable prediction accuracy for quantitative traits, with universal applications under wide genetic backgrounds in crops. The development of such platforms faces serious challenges at both the technological level due to cost ineffectiveness, and the knowledge level due to large genotype-phenotype gaps in crop plants. It is expected that such genotyping platforms will be achieved in the next ten years in major crops in consideration of (a) rapid development in gene discovery of important traits, (b) deepened understanding of quantitative traits through new analytical models and population designs, (c) integration of multi-layer -omics data leading to identification of genes and pathways responsible for important breeding traits, and (d) improvement in cost effectiveness of large-scale genotyping. Crop breeding chips and genotyping platforms will provide unprecedented opportunities to accelerate the development of cultivars with desired yield potential, quality, and enhanced adaptation to mitigate the effects of climate change.

Genome-wide association study identifies a major gene for beech bark disease resistance in American beech (Fagus grandifolia Ehrh.)

BACKGROUND

The American Beech tree (Fagus grandifolia Ehrh.), native to eastern North America, is ecologically important and provides high quality wood products. This species is susceptible to beech bark disease (BBD) and is facing high rates of mortality in North America. The disease occurs from an interaction between the woolly beech scale insect (Cryptococcus fagisuga), one of two species of the fungus Neonectria (N. faginata or N. ditissima), and American Beech trees.

METHODS

In this case-control genome-wide association study (GWAS), we tested 16 K high quality SNPs using the Affymetrix Axiom 1.5 K - 50 K assay to genotype an association population of 514 individuals. We also conducted linkage analysis in a full-sib family of 115 individuals. Fisher's exact test and logistic regression tests were performed to test associations between SNPs and phenotypes.

RESULTS

Association tests revealed four highly significant SNPs on chromosome (Chr) 5 for a single gene (Mt), which encodes a mRNA for metallothionein-like protein (metal ion binding) in Fagus sylvatica. Metallothioneins represent Cys-rich metal chelators able to coordinate metal atoms and may play an important role in the resistance mechanisms against beech scale insect.

CONCLUSION

The GWAS study has identified a single locus of major effect contributing to beech bark disease resistance. Knowledge of this genetic locus contributing to resistance might be used in applied breeding, conservation and restoration programs.

Genome-wide association study and genomic prediction in citrus: Potential of genomics-assisted breeding for fruit quality traits

Novel genomics-based approaches such as genome-wide association studies (GWAS) and genomic selection (GS) are expected to be useful in fruit tree breeding, which requires much time from the cross to the release of a cultivar because of the long generation time. In this study, a citrus parental population (111 varieties) and a breeding population (676 individuals from 35 full-sib families) were genotyped for 1,841 single nucleotide polymorphisms (SNPs) and phenotyped for 17 fruit quality traits. GWAS power and prediction accuracy were increased by combining the parental and breeding populations. A multi-kernel model considering both additive and dominance effects improved prediction accuracy for acidity and juiciness, implying that the effects of both types are important for these traits. Genomic best linear unbiased prediction (GBLUP) with linear ridge kernel regression (RR) was more robust and accurate than GBLUP with non-linear Gaussian kernel regression (GAUSS) in the tails of the phenotypic distribution. The results of this study suggest that both GWAS and GS are effective for genetic improvement of citrus fruit traits. Furthermore, the data collected from breeding populations are beneficial for increasing the detection power of GWAS and the prediction accuracy of GS.

Genome-enabled predictions for fruit weight and quality from repeated records in European peach progenies

Background

Highly polygenic traits such as fruit weight, sugar content and acidity strongly influence the agroeconomic value of peach varieties. Genomic Selection (GS) can accelerate peach yield and quality gain if predictions show higher levels of accuracy compared to phenotypic selection. The available IPSC 9K SNP array V1 allows standardized and highly reliable genotyping, preparing the ground for GS in peach.

Results

A repeatability model (multiple records per individual plant) for genome-enabled predictions in eleven European peach populations is presented. The analysis included 1147 individuals derived from both commercial and non-commercial peach or peach-related accessions. Considered traits were average fruit weight (FW), sugar content (SC) and titratable acidity (TA). Plants were genotyped with the 9K IPSC array, grown in three countries (France, Italy, Spain) and phenotyped for 3–5 years. An analysis of imputation accuracy of missing genotypic data was conducted using the software Beagle, showing that two of the eleven populations were highly sensitive to increasing levels of missing data. The regression model produced, for each trait and each population, estimates of heritability (FW:0.35, SC:0.48, TA:0.53, on average) and repeatability (FW:0.56, SC:0.63, TA:0.62, on average). Predictive ability was estimated in a five-fold cross validation scheme within population as the correlation of true and predicted phenotypes. Results differed by populations and traits, but predictive abilities were in general high (FW:0.60, SC:0.72, TA:0.65, on average).

Conclusions

This study assessed the feasibility of Genomic Selection in peach for highly polygenic traits linked to yield and fruit quality. The accuracy of imputing missing genotypes was as high as 96%, and the genomic predictive ability was on average 0.65, but could be as high as 0.84 for fruit weight or 0.83 for titratable acidity. The estimated repeatability may prove very useful in the management of the typical long cycles involved in peach productions. All together, these results are very promising for the application of genomic selection to peach breeding programmes.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3781-8) contains supplementary material, which is available to authorized users.

New Strategies and Tools in Quantitative Genetics: How to Go from the Phenotype to the Genotype

Quantitative genetics has a long history in plants: It has been used to study specific biological processes, identify the factors important for trait evolution, and breed new crop varieties. These classical approaches to quantitative trait locus mapping have naturally improved with technology. In this review, we show how quantitative genetics has evolved recently in plants and how new developments in phenotyping, population generation, sequencing, gene manipulation, and statistics are rejuvenating both the classical linkage mapping approaches (for example, through nested association mapping) as well as the more recently developed genome-wide association studies. These strategies are complementary in most instances, and indeed, one is often used to confirm the results of the other. Despite significant advances, an emerging trend is that the outcome and efficiency of the different approaches depend greatly on the genetic architecture of the trait in the genetic material under study.

Enhanced Expression of Serotonin Receptor 5-Hydroxytryptamine 2C is Associated with Increased Feather Damage in Dongxiang Blue-Shelled Layers

The gene encoding the serotonin receptor 5-hydroxytraptamine 2C (HTR2C) has been implicated in behavioral phenotypes in a number of species. In previous studies, a mutation in the chicken HTR2C gene was found to be associated with feather condition, thereby suggesting a relationship between the gene and receiving feather pecking activity. The present study analyzed the chicken HTR2C gene at both the genomic make-up and expression level in Dongxiang blue-shelled layer. A significant association between the single nucleotide polymorphism (SNP) rs13640917 (C/T) and feather condition was confirmed in the Chinese local layer. Enhanced HTR2C gene expression (151.1-fold) that was associated with high feather damage indicated that the right cerebrum might be the critical region for HTR2C to participate in the regulation of receiving feather pecking behavior.

Virus-Induced Flowering: An Application of Reproductive Biology to Benefit Plant Research and Breeding

Virus-induced flowering combines fundamental research in reproductive biology with efficient tools for manipulating gene expression in nonmodel systems to accelerate discovery and breeding.