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).

Autonomous differentiation of transgenic cells requiring no external hormone application: the endogenous gene expression and phytohormone behaviors.

The ectopic overexpression of developmental regulator (DR) genes has been reported to improve the transformation in recalcitrant plant species because of the promotion of cellular differentiation during cell culture processes. In other words, the external plant growth regulator (PGR) application during the tissue and cell culture process is still required in cases utilizing DR genes for plant regeneration. Here, the effect of Arabidopsis BABY BOOM (BBM) and WUSCHEL (WUS) on the differentiation of tobacco transgenic cells was examined. We found that the SRDX fusion to WUS, when co-expressed with the BBM-VP16 fusion gene, significantly influenced the induction of autonomous differentiation under PGR-free culture conditions, with similar effects in some other plant species. Furthermore, to understand the endogenous background underlying cell differentiation toward regeneration, phytohormone and RNA-seq analyses were performed using tobacco leaf explants in which transgenic cells were autonomously differentiating. The levels of active auxins, cytokinins, abscisic acid, and inactive gibberellins increased as cell differentiation proceeded toward organogenesis. Gene Ontology terms related to phytohormones and organogenesis were identified as differentially expressed genes, in addition to those related to polysaccharide and nitrate metabolism. The qRT-PCR four selected genes as DEGs supported the RNA-seq data. This differentiation induction system and the reported phytohormone and transcript profiles provide a foundation for the development of PGR-free tissue cultures of various plant species, facilitating future biotechnological breeding.

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.

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.

Allelic composition of carotenoid metabolic genes in 13 founders influences carotenoid composition in juice sac tissues of fruits among Japanese citrus breeding population.

To enrich carotenoids, especially ß-cryptoxanthin, in juice sac tissues of fruits via molecular breeding in citrus, allele mining was utilized to dissect allelic variation of carotenoid metabolic genes and identify an optimum allele on the target loci characterized by expression quantitative trait (eQTL) analysis. SNPs of target carotenoid metabolic genes in 13 founders of the Japanese citrus breeding population were explored using the SureSelect target enrichment method. An independent allele was determined based on the presence or absence of reliable SNPs, using trio analysis to confirm inheritability between parent and offspring. Among the 13 founders, there were 7 PSY alleles, 7 HYb alleles, 11 ZEP alleles, 5 NCED alleles, and 4 alleles for the eQTL that control the transcription levels of PDS and ZDS among the ancestral species, indicating that some founders acquired those alleles from them. The carotenoid composition data of 263 breeding pedigrees in juice sac tissues revealed that the phenotypic variance of carotenoid composition was similar to that in the 13 founders, whereas the mean of total carotenoid content increased. This increase in total carotenoid content correlated with the increase in either or both ß-cryptoxanthin and violaxanthin in juice sac tissues. Bayesian statistical analysis between allelic composition of target genes and carotenoid composition in 263 breeding pedigrees indicated that PSY-a and ZEP-e alleles at PSY and ZEP loci had strong positive effects on increasing the total carotenoid content, including ß-cryptoxanthin and violaxanthin, in juice sac tissues. Moreover, the pyramiding of these alleles also increased the ß-cryptoxanthin content. Interestingly, the offset interaction between the alleles with increasing and decreasing effects on carotenoid content and the epistatic interaction among carotenoid metabolic genes were observed and these interactions complexed carotenoid profiles in breeding population. These results revealed that allele composition would highly influence the carotenoid composition in citrus fruits. The allelic genotype information for the examined carotenoid metabolic genes in major citrus varieties and the trio-tagged SNPs to discriminate the optimum alleles (PSY-a and ZEP-e) from the rest would promise citrus breeders carotenoid enrichment in fruit via molecular breeding.

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.

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.

Genomics-assisted breeding in fruit trees.

Recent advancements in genomic analysis technologies have opened up new avenues to promote the efficiency of plant breeding. Novel genomics-based approaches for plant breeding and genetics research, such as genome-wide association studies (GWAS) and genomic selection (GS), are useful, especially in fruit tree breeding. The breeding of fruit trees is hindered by their long generation time, large plant size, long juvenile phase, and the necessity to wait for the physiological maturity of the plant to assess the marketable product (fruit). In this article, we describe the potential of genomics-assisted breeding, which uses these novel genomics-based approaches, to break through these barriers in conventional fruit tree breeding. We first introduce the molecular marker systems and whole-genome sequence data that are available for fruit tree breeding. Next we introduce the statistical methods for biparental linkage and quantitative trait locus (QTL) mapping as well as GWAS and GS. We then review QTL mapping, GWAS, and GS studies conducted on fruit trees. We also review novel technologies for rapid generation advancement. Finally, we note the future prospects of genomics-assisted fruit tree breeding and problems that need to be overcome in the breeding.

A simulation-based breeding design that uses whole-genome prediction in tomato.

Efficient plant breeding methods must be developed in order to increase yields and feed a growing world population, as well as to meet the demands of consumers with diverse preferences who require high-quality foods. We propose a strategy that integrates breeding simulations and phenotype prediction models using genomic information. The validity of this strategy was evaluated by the simultaneous genetic improvement of the yield and flavour of the tomato (Solanum lycopersicum), as an example. Reliable phenotype prediction models for the simulation were constructed from actual genotype and phenotype data. Our simulation predicted that selection for both yield and flavour would eventually result in morphological changes that would increase the total plant biomass and decrease the light extinction coefficient, an essential requirement for these improvements. This simulation-based genome-assisted approach to breeding will help to optimise plant breeding, not only in the tomato but also in other important agricultural crops.

Identification of SFBB-containing canonical and noncanonical SCF complexes in pollen of apple (Malus × domestica).

Gametophytic self-incompatibility (GSI) of Rosaceae, Solanaceae and Plantaginaceae is controlled by a single polymorphic S locus. The S locus contains at least two genes, S-RNase and F-box protein encoding gene SLF/SFB/SFBB that control pistil and pollen specificity, respectively. Generally, the F-box protein forms an E3 ligase complex, SCF complex with Skp1, Cullin1 (CUL1) and Rbx1, however, in Petunia inflata, SBP1 (S-RNase binding protein1) was reported to play the role of Skp1 and Rbx1, and form an SCFSLF-like complex for ubiquitination of non-self S-RNases. On the other hand, in Petunia hybrida and Petunia inflata of Solanaceae, Prunus avium and Pyrus bretschneideri of Rosaceae, SSK1 (SLF-interacting Skp1-like protein1) is considered to form the SCFSLF/SFB complex. Here, we isolated pollen-expressed apple homologs of SSK1 and CUL1, and named MdSSK1, MdCUL1A and MdCUL1B. MdSSK1 was preferentially expressed in pollen, but weakly in other organs analyzed, while, MdCUL1A and MdCUL1B were almost equally expressed in all the organs analyzed. MdSSK1 transcript abundance was significantly (>100 times) higher than that of MdSBP1. In vitro binding assays showed that MdSSK1 and MdSBP1 interacted with MdSFBB1-S9 and MdCUL1, and MdSFBB1-S9 interacted more strongly with MdSSK1 than with MdSBP1. The results suggest that both MdSSK1-containing SCFSFBB1 and MdSBP1-containing SCFSFBB1-like complexes function in pollen of apple, and the former plays a major role.

Apple S locus region represents a large cluster of related, polymorphic and pollen-specific F-box genes.

Gametophytic self-incompatibility (GSI) of Rosaceae, Solanaceae and Plantaginaceae is controlled by a complex S locus that encodes separate proteins for pistil and pollen specificities, extracellular ribonucleases (S-RNases) and F-box proteins SFB/SLF, respectively. SFB/SLFs of Prunus (subfamily Prunoideae of Rosaceae), Solanaceae and Plantaginaceae are single copy in each S haplotype, while recently identified pollen S candidates SFBBs of subfamily Maloideae of Rosaceae, apple and Japanese pear, are multiple; two and three related SFBBs were isolated from each S haplotype of apple and Japanese pear, respectively. Here, we show that apple (Malus x domestica) SFBBs constitute a gene family that is much larger than initially thought. Twenty additional SFBB-like genes/alleles were isolated by screening of a BAC library derived from S (3) S (9) genotype, and tentatively named MdFBX1-20. All but one MdFBX showed S haplotype-specific polymorphisms. All the polymorphic MdFBXs were completely linked to S-RNase in 239 segregants. In addition, FISH revealed that the monomorphic gene MdFBX11 is also located near S-RNase, and the S locus is located in a subtelomeric region of a chromosome and is not close to the centromere. All MdFBXs were specifically expressed in pollen, except for a pseudogene MdFBX4 that showed no expression in any organs analyzed. Phylogenetic analysis revealed that the closest relatives of most MdFBXs were from a different S haplotype, suggesting that proliferation of MdSFBB/FBXs predates diversification of the S haplotypes.

Pollen-expressed F-box gene family and mechanism of S-RNase-based gametophytic self-incompatibility (GSI) in Rosaceae.

Many species of Rosaceae, Solanaceae, and Plantaginaceae exhibit S-RNase-based self-incompatibility (SI) in which pistil-part specificity is controlled by S locus-encoded ribonuclease (S-RNase). Although recent findings revealed that S locus-encoded F-box protein, SLF/SFB, determines pollen-part specificity, how these pistil- and pollen-part S locus products interact in vivo and elicit the SI reaction is largely unclear. Furthermore, genetic studies suggested that pollen S function can differ among species. In Solanaceae and the rosaceous subfamily Maloideae (e.g., apple and pear), the coexistence of two different pollen S alleles in a pollen breaks down SI of the pollen, a phenomenon known as competitive interaction. However, competitive interaction seems not to occur in the subfamily Prunoideae (e.g., cherry and almond) of Rosaceae. Furthermore, the effect of the deletion of pollen S seems to vary among taxa. This review focuses on the potential differences in pollen-part function between subfamilies of Rosaceae, Maloideae, and Prunoideae, and discusses implications for the mechanistic divergence of the S-RNase-based SI.