Metabolomic Selection for Enhanced Fruit Flavor

Colantonio, Vincent; Ferrão, Luís Felipe Ventorim; Tieman, Denise M.; Bliznyuk, Nikolay; Sims, Charles A.; Klee, Harry J.; Muñoz, Patricio; Resende, M. D. V. de

doi:10.1101/2020.09.17.302802

Cited by 8 publications

(19 citation statements)

References 38 publications

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“…Indeed, multiple studies in blueberry reported that fruit quality (FQ) traits, including size (FW), total soluble solid content (TSS), titratable acidity (TA), and texture influence consumer preferences 1 – 4 , 9 – 13 . In particular, consumers cited flavor and sweetness as positive characteristics, and TSS and TA as the most and least important characteristics associated with overall consumer preferences for blueberries, respectively 4 , 14 . In fact, the balance between sugars and acids is determinant factor for berry taste.…”

Section: Introductionmentioning

confidence: 99%

“…In fact, the balance between sugars and acids is determinant factor for berry taste. Sweet berries do not necessarily have high sugar content, instead they may retain lower level of acids, which results in the higher the sugar/organic acid ratio 4 , 13 , 14 .…”

Section: Introductionmentioning

confidence: 99%

“…As a result, blueberries available on the market represent a blend of multiple cultivars, and the variation for FQ traits makes the consumer experience inconsistent across multiple purchases. In turn, this can affect consumer re-purchasing frequency and overall consumption 4 , 7 , 8 , 14 . Developing strategies that can increase the blueberry production that meet consumer preferences will be critical for sustaining the consumption growth.…”

Section: Introductionmentioning

confidence: 99%

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High-density linkage map construction and identification of loci regulating fruit quality traits in blueberry

et al. 2021

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Fruit quality traits play a significant role in consumer preferences and consumption in blueberry (Vaccinium corymbosum L). The objectives of this study were to construct a high-density linkage map and to identify the underlying genetic basis of fruit quality traits in blueberry. A total of 287 F1 individuals derived from a cross between two southern highbush blueberry cultivars, ‘Reveille’ and ‘Arlen’, were phenotyped over three years (2016–2018) for fruit quality-related traits, including titratable acidity, pH, total soluble solids, and fruit weight. A high-density linkage map was constructed using 17k single nucleotide polymorphisms markers. The linkage map spanned a total of 1397 cM with an average inter-loci distance of 0.08 cM. The quantitative trait loci interval mapping based on the hidden Markov model identified 18 loci for fruit quality traits, including seven loci for fruit weight, three loci for titratable acidity, five loci for pH, and three loci for total soluble solids. Ten of these loci were detected in more than one year. These loci explained phenotypic variance ranging from 7 to 28% for titratable acidity and total soluble solid, and 8–13% for pH. However, the loci identified for fruit weight did not explain more than 10% of the phenotypic variance. We also reported the association between fruit quality traits and metabolites detected by Proton nuclear magnetic resonance analysis directly responsible for these fruit quality traits. Organic acids, citric acid, and quinic acid were significantly (P < 0.05) and positively correlated with titratable acidity. Sugar molecules showed a strong and positive correlation with total soluble solids. Overall, the study dissected the genetic basis of fruit quality traits and established an association between these fruit quality traits and metabolites.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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High-density linkage map construction and identification of loci regulating fruit quality traits in blueberry

et al. 2021

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“…The UF blueberry breeding program has included new traits for routine phenotyping to meet the current demand from different marketable demands in recent years. For example, the use of volatiles for flavor-assisted selection has shown the ability to predict sensory perceptions by explaining 55% of the variation in overall liking scores (Colantonio et al, 2020 ). Given the high costs to perform sensory panels, we are incorporating metabolomics in the breeding pipeline to predict flavor ratings for many genotypes at Stage III (Gilbert et al, 2015 ; Colantonio et al, 2020 ; Ferrão et al, 2020 ).…”

Section: Resultsmentioning

confidence: 99%

Genomic Selection in an Outcrossing Autotetraploid Fruit Crop: Lessons From Blueberry Breeding

et al. 2021

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Blueberry (Vaccinium corymbosum and hybrids) is a specialty crop with expanding production and consumption worldwide. The blueberry breeding program at the University of Florida (UF) has greatly contributed to expanding production areas by developing low-chilling cultivars better adapted to subtropical and Mediterranean climates of the globe. The breeding program has historically focused on recurrent phenotypic selection. As an autopolyploid, outcrossing, perennial, long juvenile phase crop, blueberry breeding cycles are costly and time consuming, which results in low genetic gains per unit of time. Motivated by applying molecular markers for a more accurate selection in the early stages of breeding, we performed pioneering genomic selection studies and optimization for its implementation in the blueberry breeding program. We have also addressed some complexities of sequence-based genotyping and model parametrization for an autopolyploid crop, providing empirical contributions that can be extended to other polyploid species. We herein revisited some of our previous genomic selection studies and showed for the first time its application in an independent validation set. In this paper, our contribution is three-fold: (i) summarize previous results on the relevance of model parametrizations, such as diploid or polyploid methods, and inclusion of dominance effects; (ii) assess the importance of sequence depth of coverage and genotype dosage calling steps; (iii) demonstrate the real impact of genomic selection on leveraging breeding decisions by using an independent validation set. Altogether, we propose a strategy for using genomic selection in blueberry, with the potential to be applied to other polyploid species of a similar background.

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“…In recent years, the UF blueberry breeding program has included new traits for routine phenotyping to meet the current demand from different marketable demands. For example, the use of volatiles for flavor-assisted selection has shown the ability to predict sensory perceptions, and thus, metabolomics have been incorporated in the breeding pipeline to assess flavor ratings for a large number of genotypes (Gilbert et al , 2014; Colantonio et al , 2020; FerrÃo et al , 2020). Similarly, we want to incorporate nutraceutical compounds to leverage blueberry health benefits and shelf-life related traits so berries can withstand long periods of storage or shipment.…”

Section: Resultsmentioning

confidence: 99%

Genomic prediction in an outcrossing and autotetraploid fruit crop: lessons from blueberry breeding

Ferrão

Amadeu

Benevenuto

et al. 2021

Preprint

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Blueberry (Vaccinium corymbosum and hybrids) is a specialty crop, with expanding production and consumption worldwide. The blueberry breeding program at the University of Florida (UF) has greatly contributed to the expansion of production areas by developing low-chilling cultivars better adapted to subtropical and Mediterranean climates of the globe. The breeding program has historically focused on phenotypic recurrent selection. As an autopolyploid, outcrossing, perennial, long juvenile phase crop, blueberrys breeding cycles are costly and time-consuming, which results in low genetic gains per unit of time. Motivated by the application of molecular markers for a more accurate selection in early stages of breeding, we performed pioneering genomic prediction studies and optimization for implementation in the blueberry breeding program. We have also addressed some complexities of sequence-based genotyping and model parametrization for an autopolyploid crop, providing empirical contributions that can be extended to other polyploid species. We herein revisited some of our previous genomic prediction studies and described the current achievements in the crop. In this paper, our contribution for genomic prediction in an autotetraploid crop is three-fold: i) summarize previous results on the relevance of model parametrizations, such as diploid or polyploid methods, and inclusion of dominance effects; ii) assess the importance of sequence depth of coverage and genotype dosage calling steps; iii) demonstrate the real impact of genomic selection on leveraging breeding decisions by using an independent validation set. Altogether, we propose a strategy for the use of genomic selection in blueberry, with potential to be applied to other polyploid species of a similar background.

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Metabolomic Selection for Enhanced Fruit Flavor

Cited by 8 publications

References 38 publications

High-density linkage map construction and identification of loci regulating fruit quality traits in blueberry

High-density linkage map construction and identification of loci regulating fruit quality traits in blueberry

Genomic Selection in an Outcrossing Autotetraploid Fruit Crop: Lessons From Blueberry Breeding

Genomic prediction in an outcrossing and autotetraploid fruit crop: lessons from blueberry breeding

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