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

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

Trends in Fruit Quality Improvement From 15 Years of Selection in the Apple Breeding Program of Washington State University.

Washington State University's apple breeding program (WABP) was initiated in 1994 to select new apple cultivars with improved eating quality, appearance, and storability that are suitable for production in the main growing regions of the state. Fruit quality is phenotyped using various instrumental measures, such as penetrometers (texture), titrator (acidity), and refractometer (soluble solids concentration; SSC), as well as sensory assessment. The selection regime of WABP occurs in three sequential phases: phase one (P1)-single, unreplicated seedlings at one site, phase two (P2)-replicated selections at three geographically diverse sites, and phase three (P3)-highly replicated elite selections at one to two grower sites. Most of the data collection of WABP occurs in P2. Knowledge of trends/changes associated with advancing selections is essential for understanding the selection criteria and progress of WABP throughout the changing compositions of advancing and culling selections. For each post-harvest trait, P2 data from harvest years 2005 to 2019 were split across sites, and between selections and reference cultivars (e.g., Cripps Pink, Gala, and Honeycrisp). Means of instrumental crispness (Cn) and inner cortex firmness for the advancing selections increased gradually over this period and were significantly higher than those for cultivars. Means of outer cortex firmness measurements were stable for selections but significantly higher than those for cultivars. The average fruit acidity of selections increased marginally over this period and was higher than that of the cultivars. Meanwhile, the average fruit SSCs of selections and cultivars were statistically indistinguishable. These 15-year trends indicate that WABP has been selecting apples with improved eating quality and storability through increased crispness and inner cortex firmness, respectively.

Contributions of Reduced Susceptibility Alleles in Breeding Apple Cultivars with Durable Resistance to Fire Blight.

Breeding apple cultivars with durable genetic resistance is a potential long-term solution to fire blight, a devastating bacterial disease caused by Erwinia amylovora. However, phenotyping resistance/susceptibility to fire blight is challenging due to E. amylovora strain virulence, differential host × strain interactions, quantitative host resistance, environmental influences on disease, and impacts of tree vigor on susceptibility. Inheritance of resistance/susceptibility to fire blight is complex and phenotypic information alone is insufficient to guide breeding decisions targeting resistance. Several quantitative trait loci (QTLs) associated with resistance/susceptibility to fire blight have been detected throughout the apple genome. Most resistance alleles at fire blight QTLs have been identified in wild Malus germplasm with poor fruit quality, which limits their breeding utility. Several QTLs have been identified in populations derived from cultivars and reduced-susceptibility alleles have been characterized in multiple important breeding parents. Although resistance to fire blight is an attractive target for DNA-informed breeding, relatively few trait-predictive DNA tests for breeding relevant fire blight QTLs are available. Here we discuss (1) considerations and challenges associated with phenotyping resistance/susceptibility to fire blight; (2) sources of resistance that have been identified for use as parents; and (3) our perspective on short and long-term strategies to breed apple cultivars with durable resistance to fire blight with emphasis on the potential contributions of reduced susceptibility alleles to achieve this goal.

Fire blight QTL analysis in a multi-family apple population identifies a reduced-susceptibility allele in 'Honeycrisp'.

Breeding apple cultivars with resistance offers a potential solution to fire blight, a damaging bacterial disease caused by Erwinia amylovora. Most resistance alleles at quantitative trait loci (QTLs) were previously characterized in diverse Malus germplasm with poor fruit quality, which reduces breeding utility. This study utilized a pedigree-based QTL analysis approach to elucidate the genetic basis of resistance/susceptibility to fire blight from multiple genetic sources in germplasm relevant to U.S. apple breeding programs. Twenty-seven important breeding parents (IBPs) were represented by 314 offspring from 32 full-sib families, with 'Honeycrisp' being the most highly represented IBP. Analyzing resistance/susceptibility data from a two-year replicated field inoculation study and previously curated genome-wide single nucleotide polymorphism data, QTLs were consistently mapped on chromosomes (Chrs.) 6, 7, and 15. These QTLs together explained ~28% of phenotypic variation. The Chr. 6 and Chr. 15 QTLs colocalized with previously reported QTLs, while the Chr. 7 QTL is possibly novel. 'Honeycrisp' inherited a rare reduced-susceptibility allele at the Chr. 6 QTL from its grandparent 'Frostbite'. The highly resistant IBP 'Enterprise' had at least one putative reduced-susceptibility allele at all three QTLs. In general, lower susceptibility was observed for individuals with higher numbers of reduced-susceptibility alleles across QTLs. This study highlighted QTL mapping and allele characterization of resistance/susceptibility to fire blight in complex pedigree-connected apple breeding germplasm. Knowledge gained will enable more informed parental selection and development of trait-predictive DNA tests for pyramiding favorable alleles and selection of superior apple cultivars with resistance to fire blight.

A DNA test for high incidence of soft scald and soggy breakdown postharvest disorders in Malus domestica Borkh.

The 'Honeycrisp' apple, an economically important cultivar and breeding parent, is prone to soft scald and soggy breakdown postharvest physiological disorders. Phenotypic evaluation of soft scald is time consuming and costly, making it an excellent target for DNA-informed breeding. The objective of this study was to develop a DNA test for a soft scald and soggy breakdown quantitative trait locus (QTL) on linkage group two (LG2) that was characterized in a previous study. 'Honeycrisp' is homozygous for the undesirable high disorder incidence haplotype (HDI) at this QTL. In this study, sixteen single nucleotide polymorphism markers were evaluated for their associations with the HDI haplotype in a set of 132 unique cultivars and important breeding parents. A DNA test was successfully developed utilizing KASP™ (Kompetitive Allele Specific PCR) chemistry to identify the number of HDI haplotypes in individuals. This test had a 100% accuracy for detecting homozygous unfavorable HDI individuals and has an expected 88% accuracy over all three haplotype copy groups across the evaluated germplasm. This DNA test is a promising tool for minimizing the chances of selecting individuals that exhibit high incidence of soft scald postharvest disorder in 'Honeycrisp'-related germplasm. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-021-01245-w.

High-Throughput Phenotyping of Fire Blight Disease Symptoms Using Sensing Techniques in Apple.

Washington State produces about 70% of total fresh market apples in the United States. One of the primary goals of apple breeding programs is the development of new cultivars resistant to devastating diseases such as fire blight. The overall objective of this study was to investigate high-throughput phenotyping techniques to evaluate fire blight disease symptoms in apple trees. In this regard, normalized stomatal conductance data acquired using a portable photosynthetic system, image data collected using RGB and multispectral cameras, and visible-near infrared spectral reflectance acquired using a hyperspectral sensing system, were independently evaluated to estimate the progression of fire blight infection in young apple trees. Sensors with ranging complexity - from simple RGB to multispectral imaging to hyperspectral system - were evaluated to select the most accurate technique for the assessment of fire blight disease symptoms. The proximal multispectral images and visible-near infrared spectral reflectance data were collected in two field seasons (2016, 2017); while, proximal side-view RGB images and multispectral images using unmanned aerial systems were collected in 2017. The normalized stomatal conductance data was correlated with disease severity rating (r = 0.51, P < 0.05). The features extracted from RGB images (e.g., maximum length of senesced leaves, area of senesced leaves, ratio between senesced and healthy leaf area) and multispectral images (e.g., vegetation indices) also demonstrated potential in evaluation of disease rating (|r| > 0.35, P < 0.05). The average classification accuracy achieved using visible-near infrared spectral reflectance data during the classification of susceptible from symptomless groups ranged between 71 and 93% using partial least square regression and quadratic support vector machine. In addition, fire blight disease ratings were compared with normalized difference spectral indices (NDSIs) that were generated from visible-near infrared reflectance spectra. The selected spectral bands in the range 710-2,340 nm used for computing NDSIs showed consistently higher correlation with disease severity rating than data acquired from RGB and multispectral imaging sensors across multiple seasons. In summary, these specific spectral bands can be used for evaluating fire blight disease severity in apple breeding programs and potentially as early fire blight disease detection tool to assist in production systems.