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

Boosting grapevine breeding for climate-smart viticulture: from genetic resources to predictive genomics

The multifaceted nature of climate change is increasing the urgency to select resilient grapevine varieties, or generate new, fitter cultivars, to withstand a multitude of new challenging conditions. The attainment of this goal is hindered by the limiting pace of traditional breeding approaches, which require decades to result in new selections. On the other hand, marker-assisted breeding has proved useful when it comes to traits governed by one or few genes with great effects on the phenotype, but its efficacy is still restricted for complex traits controlled by many loci. On these premises, innovative strategies are emerging which could help guide selection, taking advantage of the genetic diversity within the Vitis genus in its entirety. Multiple germplasm collections are also available as a source of genetic material for the introgression of alleles of interest via adapted and pioneering transformation protocols, which present themselves as promising tools for future applications on a notably recalcitrant species such as grapevine. Genome editing intersects both these strategies, not only by being an alternative to obtain focused changes in a relatively rapid way, but also by supporting a fine-tuning of new genotypes developed with other methods. A review on the state of the art concerning the available genetic resources and the possibilities of use of innovative techniques in aid of selection is presented here to support the production of climate-smart grapevine genotypes.

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.

Genetic diversity, population structure, and genome-wide association analysis of ginkgo cultivars

Ginkgo biloba is an economically valuable tree worldwide. The species has nearly become extinct during the Quaternary, which has likely resulted in reduction of its genetic variability. The genetic variability is now conserved in few natural populations in China and a number of cultivars that are, however, derived from a few ancient trees, helping the species survive in China through medieval times. Despite the recent interest in ginkgo, however, detailed knowledge of its genetic diversity, conserved in cultivated trees and cultivars, has remained poor. This limits efficient conservation of its diversity as well as efficient use of the existing germplasm resources. Here we performed genotyping-by-sequencing (GBS) on 102 cultivated germplasms of ginkgo collected to explore their genetic structure, kinship, and inbreeding prediction. For the first time in ginkgo, a genome-wide association analysis study (GWAS) was used to attempt gene mapping of seed traits. The results showed that most of the germplasms did not show any obvious genetic relationship. The size of the ginkgo germplasm population expanded significantly around 1500 years ago during the Sui and Tang dynasties. Classification of seed cultivars based on a phylogenetic perspective does not support the current classification criteria based on phenotype. Twenty-four candidate genes were localized after performing GWAS on the seed traits. Overall, this study reveals the genetic basis of ginkgo seed traits and provides insights into its cultivation history. These findings will facilitate the conservation and utilization of the domesticated germplasms of this living fossil plant.

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.

QTL Analysis and CAPS Marker Development Linked with Russet in Pear (Pyrus spp.)

The fruit skin types of pear (Pyrus spp.) are divided into russet, smooth, and intermediate. One of the important traits in pear breeding programs is russet on pear fruit skin because it affects the commercial value. In the present study, a high-density genetic linkage map of ‘Whangkeumbae’ (smooth) × ‘Minibae’ (russet) was constructed. In addition, quantitative trait loci (QTL) analysis was performed to identify russet related QTL and develop a cleaved amplified polymorphism sequence (CAPS) marker. Together with SNPs derived from Axiom Pear 70K Genotyping Array and genotyping-by-sequencing derived SNPs and SSRs generated in previous study, an integrated genetic linkage map of ‘Whangkeumbae’ × ‘Minibae’ was constructed. A total of 1263 markers were anchored in 17 linkage groups (LGs) with a total genetic distance of 1894.02 cM and an average marker density of 1.48 cM. The chromosome coverage of ‘Whangkeumbae’ × ‘Minibae’ map was improved because the SNPs derived from Axiom Pear 70K Genotyping Array were anchored. QTL analysis was performed using previous russet phenotype data evaluated with russet coverage and Hunter a. As a result of QTL analysis, russet coverage- and Hunter a-related QTLs were identified in LG8 of the ‘Whangkeumbae’ × ‘Minibae’ map, and SNPs located in the QTL region were heterozygous in the ‘Minibae’. Although the russet coverage- and Hunter a-related QTLs were commonly detected in LG8, the logarithm of odds values of SNPs in the QTL region were higher in QTL related to russet coverage than to Hunter a. The CAPS marker (CBp08ca01) was developed using an array SNP located in the russet coverage related QTL, and the genotype of CBp08ca01 showed a 1:1 ratio in ‘Whangkeumbae’ × ‘Minibae’ (χ2 = 0.65, p > 0.05). ‘Whangkeumbae’ and ‘Minibae’ were thought to have rr and Rr genotypes, respectively, and the genetic factors controlling the russet formation might be located in chromosome 8. The CBp08ca01 was able to select F1 individuals with less than 30% russet coverage. Thus, it will be a useful tool for marker-assisted selection in pears.

Breeding and genetics of disease resistance in temperate fruit trees: challenges and new opportunities

Climate change, large monocultures of disease-susceptible cultivars, overuse of pesticides, and the emergence of new pathogens or pathogenic strains causing economic losses are all major threats to our environment, health, food, and nutritional supply. Temperate tree fruit crops belonging to the Rosaceae family are the most economically important and widely grown fruit crops. These long-lived crops are under attack from many different pathogens, incurring major economic losses. Multiple chemical sprays to control various diseases annually is a common practice, resulting in significant input costs, as well as environmental and health concerns. Breeding for disease resistance has been undertaken primarily in pome fruit crops (apples and pears) for a few fungal and bacterial diseases, and to a lesser extent in some stone fruit crops. These breeding efforts have taken multiple decades due to the biological constraints and complex genetics of these tree fruit crops. Over the past couple of decades, major advances have been made in genetic and physical mapping, genomics, biotechnology, genome sequencing, and phenomics, along with accumulation of large germplasm collections in repositories. These valuable resources offer opportunities to make significant advances in greatly reducing the time needed to either develop new cultivars or modify existing economic cultivars for enhanced resistance to multiple diseases. This review will cover current knowledge, challenges, and opportunities in breeding for disease resistance in temperate tree fruit crops.

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

INTRODUCTION

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSION

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

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.

Genetic characterization of carrot root shape and size using genome-wide association analysis and genomic-estimated breeding values

The principal phenotypic determinants of market class in carrot-the size and shape of the root-are under primarily additive, but also highly polygenic, genetic control. The size and shape of carrot roots are the primary determinants not only of yield, but also market class. These quantitative phenotypes have historically been challenging to objectively evaluate, and thus subjective visual assessment of market class remains the primary method by which selection for these traits is performed. However, advancements in digital image analysis have recently made possible the high-throughput quantification of size and shape attributes. It is therefore now feasible to utilize modern methods of genetic analysis to investigate the genetic control of root morphology. To this end, this study utilized both genome wide association analysis (GWAS) and genomic-estimated breeding values (GEBVs) and demonstrated that the components of market class are highly polygenic traits, likely under the influence of many small effect QTL. Relatively large proportions of additive genetic variance for many of the component phenotypes support high predictive ability of GEBVs; average prediction ability across underlying market class traits was 0.67. GWAS identified multiple QTL for four of the phenotypes which compose market class: length, aspect ratio, maximum width, and root fill, a previously uncharacterized trait which represents the size-independent portion of carrot root shape. By combining digital image analysis with GWAS and GEBVs, this study represents a novel advance in our understanding of the genetic control of market class in carrot. The immediate practical utility and viability of genomic selection for carrot market class is also described, and concrete guidelines for the design of training populations are provided.

Multicriteria Model of Support for the Selection of Pear Varieties in Raising Orchards in the Semberija Region (Bosnia and Herzegovina)

Bosnia and Herzegovina (abbreviated BiH) has great potential for fruit production. BiH has over 1.5 million hectares of agricultural land. In addition, there are excellent climatic conditions for growing fruit. However, although there is a long tradition of fruit production in BiH, this production must be improved. This paper provides guidance on making decisions in fruit growing when there are multiple criteria. All criteria are divided into two groups: economic and technical criteria. The economic criteria are further divided into three subcriteria, namely: marketing costs, orchard construction costs and processing and transport costs. Technical criteria are divided into four subcriteria, namely: fruit, variety resistance, production characteristics and processing and transport. According to these, a multicriteria decision-making model based on linguistic values was created. In order to take advantage of these values, a fuzzy approach was applied. Using this approach, decision-making process is easier because decision making is tailored to human thinking. For the example of raising a new orchard in the area of Semberija, an evaluation of seven different varieties of pears was performed. This problem is solved by applying the method of multicriteria analysis (MCDA). To solve this research problem, the MABAC (Multi-attributive border approximation area comparison) method was used. Using the fuzzy MABAC method, the obtained results show that the Šampionka variety has the best indicators among observed varieties. In addition, the Konferans variety achieved good results, and these two varieties are the first choice for raising a new orchard of pears. The paper validates the results and performs sensitivity analysis. The contribution of this research is to develop a new model of decision making by using a new methodology that facilitates decision making on variety selection. This model and methodology provide a flexible way of making decisions in fruit growing.

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.

Pear genetics: Recent advances, new prospects, and a roadmap for the future

Pear, belonging to the genus Pyrus, is one of the most economically important temperate fruit crops. Pyrus is an important genus of the Rosaceae family, subfamily Maloideae, and has at least 22 different species with over 5000 accessions maintained or identified worldwide. With the release of draft whole-genome sequences for Pyrus, opportunities for pursuing studies on the evolution, domestication, and molecular breeding of pear, as well as for conducting comparative genomics analyses within the Rosaceae family, have been greatly expanded. In this review, we highlight key advances in pear genetics, genomics, and breeding driven by the availability of whole-genome sequences, including whole-genome resequencing efforts, pear domestication, and evolution. We cover updates on new resources for undertaking gene identification and molecular breeding, as well as for pursuing functional validation of genes associated with desirable economic traits. We also explore future directions for "pear-omics".

Genome-Wide Association Analyses Track Genomic Regions for Resistance to Ascochyta rabiei in Australian Chickpea Breeding Germplasm

Ascochyta blight (AB), caused by a necrotrophic fungus, Ascochyta rabiei (syn. Phoma rabiei) has the potential to destroy the chickpea industry worldwide, due to limited sources of genetic resistance in the cultivated gene pool, high evolutionary potential of the pathogen and challenges with integrated disease management. Therefore, the deployment of stable genetic resistance in new cultivars could provide an effective disease control strategy. To investigate the genetic basis of AB resistance, genotyping-by-sequencing based DArTseq-single nucleotide polymorphism (SNP) marker data along with phenotypic data of 251 advanced breeding lines and chickpea cultivars were used to perform genome-wide association (GWAS) analysis. Host resistance was evaluated seven weeks after sowing using two highly aggressive single spore isolates (F17191-1 and TR9571) of A. rabiei. GWAS analyses based on single-locus and multi-locus mixed models and haplotyping trend regression identified twenty-six genomic regions on Ca1, Ca4, and Ca6 that showed significant association with resistance to AB. Two haplotype blocks (HB) on chromosome Ca1; HB5 (992178-1108145 bp), and HB8 (1886221-1976301 bp) were associated with resistance against both isolates. Nine HB on the chromosome, Ca4, spanning a large genomic region (14.9-56.6 Mbp) were also associated with resistance, confirming the role of this chromosome in providing resistance to AB. Furthermore, trait-marker associations in two F₃ derived populations for resistance to TR9571 isolate at the seedling stage under glasshouse conditions were also validated. Eighty-nine significantly associated SNPs were located within candidate genes, including genes encoding for serine/threonine-protein kinase, Myb protein, quinone oxidoreductase, and calmodulin-binding protein all of which are implicated in disease resistance. Taken together, this study identifies valuable sources of genetic resistance, SNP markers and candidate genes underlying genomic regions associated with AB resistance which may enable chickpea breeding programs to make genetic gains via marker-assisted/genomic selection strategies.

Genomic Approaches for Improvement of Tropical Fruits: Fruit Quality, Shelf Life and Nutrient Content

The breeding of tropical fruit trees for improving fruit traits is complicated, due to the long juvenile phase, generation cycle, parthenocarpy, polyploidy, polyembryony, heterozygosity and biotic and abiotic factors, as well as a lack of good genomic resources. Many molecular techniques have recently evolved to assist and hasten conventional breeding efforts. Molecular markers linked to fruit development and fruit quality traits such as fruit shape, size, texture, aroma, peel and pulp colour were identified in tropical fruit crops, facilitating Marker-assisted breeding (MAB). An increase in the availability of genome sequences of tropical fruits further aided in the discovery of SNP variants/Indels, QTLs and genes that can ascertain the genetic determinants of fruit characters. Through multi-omics approaches such as genomics, transcriptomics, metabolomics and proteomics, the identification and quantification of transcripts, including non-coding RNAs, involved in sugar metabolism, fruit development and ripening, shelf life, and the biotic and abiotic stress that impacts fruit quality were made possible. Utilizing genomic assisted breeding methods such as genome wide association (GWAS), genomic selection (GS) and genetic modifications using CRISPR/Cas9 and transgenics has paved the way to studying gene function and developing cultivars with desirable fruit traits by overcoming long breeding cycles. Such comprehensive multi-omics approaches related to fruit characters in tropical fruits and their applications in breeding strategies and crop improvement are reviewed, discussed and presented here.

Genome-wide association study of individual sugar content in fruit of Japanese pear (Pyrus spp.)

BACKGROUND

Understanding mechanisms of sugar accumulation and composition is essential to determining fruit quality and maintaining a desirable balance of sugars in plant storage organs. The major sugars in mature Rosaceae fruits are sucrose, fructose, glucose, and sorbitol. Among these, sucrose and fructose have high sweetness, whereas glucose and sorbitol have low sweetness. Japanese pear has extensive variation in individual sugar contents in mature fruit. Increasing total sugar content and that of individual high-sweetness sugars is a major target of breeding programs. The objective of this study was to identify quantitative trait loci (QTLs) associated with fruit traits including individual sugar accumulation, to infer the candidate genes underlying the QTLs, and to assess the potential of genomic selection for breeding pear fruit traits.

RESULTS

We evaluated 10 fruit traits and conducted genome-wide association studies (GWAS) for 106 cultivars and 17 breeding populations (1112 F1 individuals) using 3484 tag single-nucleotide polymorphisms (SNPs). By implementing a mixed linear model and a Bayesian multiple-QTL model in GWAS, 56 SNPs associated with fruit traits were identified. In particular, a SNP located close to acid invertase gene PPAIV3 on chromosome 7 and a newly identified SNP on chromosome 11 had quite large effects on accumulation of sucrose and glucose, respectively. We used 'Golden Delicious' doubled haploid 13 (GDDH13), an apple reference genome, to infer the candidate genes for the identified SNPs. In the region flanking the SNP on chromosome 11, there is a tandem repeat of early responsive to dehydration (ERD6)-like sugar transporter genes that might play a role in the phenotypes observed.

CONCLUSIONS

SNPs associated with individual sugar accumulation were newly identified at several loci, and candidate genes underlying QTLs were inferred using advanced apple genome information. The candidate genes for the QTLs are conserved across Pyrinae genomes, which will be useful for further fruit quality studies in Rosaceae. The accuracies of genomic selection for sucrose, fructose, and glucose with genomic best linear unbiased prediction (GBLUP) were relatively high (0.67-0.75), suggesting that it would be possible to select individuals having high-sweetness fruit with high sucrose and fructose contents and low glucose content.

High resolution mapping and candidate gene identification of downy mildew race 16 resistance in spinach

Background

Downy mildew, the most devastating disease of spinach (Spinacia oleracea L.), is caused by the oomycete Peronospora effusa [=P. farinosa f. sp. spinaciae]. The P. effusa shows race specificities to the resistant host and comprises 19 reported races and many novel isolates. Sixteen new P. effusa races were identified during the past three decades, and the new pathogen races are continually overcoming the genetic resistances used in commercial cultivars. A spinach breeding population derived from the cross between cultivars Whale and Lazio was inoculated with P. effusa race 16 in an environment-controlled facility; disease response was recorded and genotyped using genotyping by sequencing (GBS). The main objective of this study was to identify resistance-associated single nucleotide polymorphism (SNP) markers from the cultivar Whale against the P. effusa race 16.

Results

Association analysis conducted using GBS markers identified six significant SNPs (S3_658,306, S3_692697, S3_1050601, S3_1227787, S3_1227802, S3_1231197). The downy mildew resistance locus from cultivar Whale was mapped to a 0.57 Mb region on chromosome 3, including four disease resistance candidate genes (Spo12736, Spo12784, Spo12908, and Spo12821) within 2.69–11.28 Kb of the peak SNP.

Conclusions

Genomewide association analysis approach was used to map the P. effusa race 16 resistance loci and identify associated SNP markers and the candidate genes. The results from this study could be valuable in understanding the genetic basis of downy mildew resistance, and the SNP marker will be useful in spinach breeding to select resistant lines.

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.

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.

The Genetic Basis of Tomato Aroma

Tomato (Solanum lycopersicum L.) aroma is determined by the interaction of volatile compounds (VOCs) released by the tomato fruits with receptors in the nose, leading to a sensorial impression, such as "sweet", "smoky", or "fruity" aroma. Of the more than 400 VOCs released by tomato fruits, 21 have been reported as main contributors to the perceived tomato aroma. These VOCs can be grouped in five clusters, according to their biosynthetic origins. In the last decades, a vast array of scientific studies has investigated the genetic component of tomato aroma in modern tomato cultivars and their relatives. In this paper we aim to collect, compare, integrate and summarize the available literature on flavour-related QTLs in tomato. Three hundred and 5ifty nine (359) QTLs associated with tomato fruit VOCs were physically mapped on the genome and investigated for the presence of potential candidate genes. This review makes it possible to (i) pinpoint potential donors described in literature for specific traits, (ii) highlight important QTL regions by combining information from different populations, and (iii) pinpoint potential candidate genes. This overview aims to be a valuable resource for researchers aiming to elucidate the genetics underlying tomato flavour and for breeders who aim to improve tomato aroma.

Single Nucleotide Polymorphism Detection for Peach Gummosis Disease Resistance by Genome-Wide Association Study

Peach gummosis is one of the most widespread and destructive diseases. It causes growth stunting, yield loss, branch, trunk, and tree death, and is becoming a restrictive factor in healthy and sustainable development of peach production. Although a locus has been identified based on bi-parental quantitative trait locus (QTL) mapping, selection of gummosis-resistant cultivars remains challenging due to the lack of resistant parents and of the complexity of an inducing factor. In this study, an integrated approach of genome-wide association study (GWAS) and comparative transcriptome was used to elucidate the genetic architecture associated with the disease using 195 accessions and 145,456 genome-wide single nucleotide polymorphisms (SNPs). The broad-sense and narrow-sense heritabilities were estimated using 2-year phenotypic data and genotypic data, which gave high values of 70 and 73%, respectively. Evaluation of population structure by neighbor-joining and principal components analysis (PCA) clustered all accessions into three major groups and six subgroups, mainly according to fruit shape, hairy vs. glabrous fruit skin, pedigree, geographic origin, and domestication history. Five SNPs were found to be significantly associated with gummosis disease resistance, of which SNPrs285957, located on chromosome6 across 28 Mb, was detected by both the BLINK and the FarmCPU model. Six candidate genes flanked by or harboring the significant SNPs, previously implicated in biotic stress tolerance, were significantly associated with this resistance. Two highly resistant accessions were identified with low disease severity, which could be potential sources of resistance genes for breeding. Our results provide a fresh insight into the genetic control of peach gummosis disease.

Genome Wide Association Studies in Multiple Spinach Breeding Populations Refine Downy Mildew Race 13 Resistance Genes

Downy mildew, caused by the oomycete Peronospora effusa, is the most economically important disease on spinach. Fourteen new races of P. effusa have been identified in the last three decades. The frequent emergence of new races of P. effusa continually overcome the genetic resistance to the pathogen. The objectives of this research were to more clearly map the downy mildew resistance locus RPF1 in spinach, to identify single nucleotide polymorphism (SNP) markers associated with the resistance, and to refine the candidate genes responsible for the resistance. Progeny from populations generated from crosses of cultivars resistant (due to RPF1) to race 13 of P. effusa (Swan, T-Bird, Squirrel, and Tonga) with race 13 susceptible cultivars (Whale and Polka) were inoculated and the downy mildew disease response determined. Association analysis was performed in TASSEL, GAPIT, PLINK, and GENESIS programs using SNP markers identified from genotyping by sequencing (GBS). Association analysis mapped the race 13 resistance loci (RPF1) to positions 0.39, 0.69, 0.94-0.98, and 1.2 Mb of chromosome 3. The associated SNPs were within 1-7 kb of the disease resistance genes Spo12784, Spo12719, Spo12905, and Spo12821, and 11-18 Kb from Spo12903. This study extended our understanding of the genetic basis of downy mildew resistance in spinach and provided the most promising candidate genes Spo12784 and Spo12903 near the RPF1 locus, to pursue functional validation. The SNP markers may be used to select for the resistant lines to improve genetic resistance against the downy mildew pathogen and in developing durably resistant 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.

Turbocharging introgression breeding of perennial fruit crops: a case study on apple

The allelic diversity of primitive germplasm of fruit crops provides a useful resource for introgressing novel genes to meet consumer preferences and environmental challenges. Pre-breeding facilitates the identification of novel genetic variation in the primitive germplasm and expedite its utilisation in cultivar breeding programmes. Several generations of pre-breeding could be required to minimise linkage drag from the donor parent and to maximise the genomic content of the recipient parent. In this study we investigated the potential of genomic selection (GS) as a tool for rapid background selection of parents for the successive generation. A diverse set of 274 accessions was genotyped using random-tag genotyping-by-sequencing, and phenotyped for eight fruit quality traits. The relationship between 'own phenotypes' of 274 accessions and their general combining ability (GCA) was also examined. Trait heritability influenced the strength of correspondence between own phenotype and the GCA. The average (across eight traits) accuracy of predicting own phenotype was 0.70, and the correlations between genomic-predicted own phenotype and GCA were similar to the observed correlations. Our results suggest that genome-assisted parental selection (GAPS) is a credible alternative to phenotypic parental selection, so could help reduce the generation interval to allow faster accumulation of favourable alleles from donor and recipient parents.

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.

Potential of Genome-Wide Association Studies and Genomic Selection to Improve Productivity and Quality of Commercial Timber Species in Tropical Rainforest, a Case Study of Shorea platyclados

Shorea platyclados (Dark Red Meranti) is a commercially important timber tree species in Southeast Asia. However, its stocks have dramatically declined due, inter alia, to excessive logging, insufficient natural regeneration and a slow recovery rate. Thus, there is a need to promote enrichment planting and develop effective technique to support its rehabilitation and improve timber production through implementation of Genome-Wide Association Studies (GWAS) and Genomic Selection (GS). To assist such efforts, plant materials were collected from a half-sib progeny population in Sari Bumi Kusuma forest concession, Kalimantan, Indonesia. Using 5900 markers in sequences obtained from 356 individuals, we detected high linkage disequilibrium (LD) extending up to >145 kb, suggesting that associations between phenotypic traits and markers in LD can be more easily and feasibly detected with GWAS than with analysis of quantitative trait loci (QTLs). However, the detection power of GWAS seems low, since few single nucleotide polymorphisms linked to any focal traits were detected with a stringent false discovery rate, indicating that the species’ phenotypic traits are mostly under polygenic quantitative control. Furthermore, Machine Learning provided higher prediction accuracies than Bayesian methods. We also found that stem diameter, branch diameter ratio and wood density were more predictable than height, clear bole, branch angle and wood stiffness traits. Our study suggests that GS has potential for improving the productivity and quality of S. platyclados, and our genomic heritability estimates may improve the selection of traits to target in future breeding of this species.

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.

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

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

Genetic Mapping of the Incompatibility Locus in Olive and Development of a Linked Sequence-Tagged Site Marker

The genetic control of self-incompatibility (SI) has been recently disclosed in olive. Inter-varietal crossing confirmed the presence of only two incompatibility groups (G1 and G2), suggesting a simple Mendelian inheritance of the trait. A double digest restriction associated DNA (ddRAD) sequencing of a biparental population segregating for incompatibility groups has been performed and high-density linkage maps were constructed in order to map the SI locus and identify gene candidates and linked markers. The progeny consisted of a full-sib family of 229 individuals derived from the cross 'Leccino' (G1) × 'Dolce Agogia' (G2) varieties, segregating 1:1 (G1:G2), in accordance with a diallelic self-incompatibility (DSI) model. A total of 16,743 single nucleotide polymorphisms was identified, 7,006 in the female parent 'Leccino' and 9,737 in the male parent 'Dolce Agogia.' Each parental map consisted of 23 linkage groups and showed an unusual large size (5,680 cM in 'Leccino' and 3,538 cM in 'Dolce Agogia'). Recombination was decreased across all linkage groups in pollen mother cells of 'Dolce Agogia,' the parent with higher heterozygosity, compared to megaspore mother cells of 'Leccino,' in a context of a species that showed exceptionally high recombination rates. A subset of 109 adult plants was assigned to either incompatibility group by a stigma test and the diallelic self-incompatibility (DSI) locus was mapped to an interval of 5.4 cM on linkage group 18. This region spanned a size of approximately 300 Kb in the olive genome assembly. We developed a sequence-tagged site marker in the DSI locus and identified five haplotypes in 57 cultivars with known incompatibility group assignment. A combination of two single-nucleotide polymorphisms (SNPs) was sufficient to predict G1 or G2 phenotypes in olive cultivars, enabling early marker-assisted selection of compatible genotypes and allowing for a rapid screening of inter-compatibility among cultivars in order to guarantee effective fertilization and increase olive production. The construction of high-density linkage maps has led to the development of the first functional marker in olive and provided positional candidate genes in the SI locus.