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Casorzo G, Ferrão LF, Adunola P, Tavares Flores E, Azevedo C, Amadeu R, Munoz PR. Understanding the genetic basis of blueberry postharvest traits to define better breeding strategies. G3 (BETHESDA, MD.) 2024; 14:jkae163. [PMID: 39052988 PMCID: PMC11373639 DOI: 10.1093/g3journal/jkae163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 01/23/2024] [Accepted: 07/09/2024] [Indexed: 07/27/2024]
Abstract
Blueberry (Vaccinium spp.) is among the most-consumed soft fruit and has been recognized as an important source of health-promoting compounds. Highly perishable and susceptible to rapid spoilage due to fruit softening and decay during postharvest storage, modern breeding programs are looking to maximize the quality and extend the market life of fresh blueberries. However, it is uncertain how genetically controlled postharvest quality traits are in blueberries. This study aimed to investigate the prediction ability and the genetic basis of the main fruit quality traits affected during blueberry postharvest to create breeding strategies for developing cultivars with an extended shelf life. To achieve this goal, we carried out target genotyping in a breeding population of 588 individuals and evaluated several fruit quality traits after 1 day, 1 week, 3 weeks, and 7 weeks of postharvest storage at 1°C. Using longitudinal genome-based methods, we estimated genetic parameters and predicted unobserved phenotypes. Our results showed large diversity, moderate heritability, and consistent predictive accuracies along the postharvest storage for most of the traits. Regarding the fruit quality, firmness showed the largest variation during postharvest storage, with a surprising number of genotypes maintaining or increasing their firmness, even after 7 weeks of cold storage. Our results suggest that we can effectively improve the blueberry postharvest quality through breeding and use genomic prediction to maximize the genetic gains in the long term. We also emphasize the potential of using longitudinal genomic prediction models to predict the fruit quality at extended postharvest periods by integrating known phenotypic data from harvest.
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Affiliation(s)
- Gonzalo Casorzo
- Horticultural Sciences Department, University of Florida, Gainesville, FL 32608, USA
| | - Luis Felipe Ferrão
- Horticultural Sciences Department, University of Florida, Gainesville, FL 32608, USA
| | - Paul Adunola
- Horticultural Sciences Department, University of Florida, Gainesville, FL 32608, USA
| | | | - Camila Azevedo
- Department of Statistics, Federal University of Viçosa, Viçosa 36570, Brazil
| | - Rodrigo Amadeu
- Horticultural Sciences Department, University of Florida, Gainesville, FL 32608, USA
- Bayer US-Crop Science, Chesterfield, MO 63017, USA
| | - Patricio R Munoz
- Horticultural Sciences Department, University of Florida, Gainesville, FL 32608, USA
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Lee AMJ, Foong MYM, Song BK, Chew FT. Genomic selection for crop improvement in fruits and vegetables: a systematic scoping review. MOLECULAR BREEDING : NEW STRATEGIES IN PLANT IMPROVEMENT 2024; 44:60. [PMID: 39267903 PMCID: PMC11391014 DOI: 10.1007/s11032-024-01497-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/08/2024] [Accepted: 09/01/2024] [Indexed: 09/15/2024]
Abstract
To ensure the nutritional needs of an expanding global population, it is crucial to optimize the growing capabilities and breeding values of fruit and vegetable crops. While genomic selection, initially implemented in animal breeding, holds tremendous potential, its utilization in fruit and vegetable crops remains underexplored. In this systematic review, we reviewed 63 articles covering genomic selection and its applications across 25 different types of fruit and vegetable crops over the last decade. The traits examined were directly related to the edible parts of the crops and carried significant economic importance. Comparative analysis with WHO/FAO data identified potential economic drivers underlying the study focus of some crops and highlighted crops with potential for further genomic selection research and application. Factors affecting genomic selection accuracy in fruit and vegetable studies are discussed and suggestions made to assist in their implementation into plant breeding schemes. Genetic gain in fruits and vegetables can be improved by utilizing genomic selection to improve selection intensity, accuracy, and integration of genetic variation. However, the reduction of breeding cycle times may not be beneficial in crops with shorter life cycles such as leafy greens as compared to fruit trees. There is an urgent need to integrate genomic selection methods into ongoing breeding programs and assess the actual genomic estimated breeding values of progeny resulting from these breeding programs against the prediction models. Supplementary Information The online version contains supplementary material available at 10.1007/s11032-024-01497-2.
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Affiliation(s)
- Adrian Ming Jern Lee
- Department of Biological Sciences, National University of Singapore, 14 Science Drive 4, Singapore, 117543 Republic of Singapore
- NUS Agritech Centre, National University of Singapore, 85 Science Park Dr, #01-03, Singapore, 118258 Republic of Singapore
| | - Melissa Yuin Mern Foong
- School of Science, Monash University Malaysia, Bandar Sunway, 47500 Subang Jaya, Selangor Darul Ehsan Malaysia
| | - Beng Kah Song
- School of Science, Monash University Malaysia, Bandar Sunway, 47500 Subang Jaya, Selangor Darul Ehsan Malaysia
| | - Fook Tim Chew
- Department of Biological Sciences, National University of Singapore, 14 Science Drive 4, Singapore, 117543 Republic of Singapore
- NUS Agritech Centre, National University of Singapore, 85 Science Park Dr, #01-03, Singapore, 118258 Republic of Singapore
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Cao X, Su Y, Zhao T, Zhang Y, Cheng B, Xie K, Yu M, Allan A, Klee H, Chen K, Guan X, Zhang Y, Zhang B. Multi-omics analysis unravels chemical roadmap and genetic basis for peach fruit aroma improvement. Cell Rep 2024; 43:114623. [PMID: 39146179 DOI: 10.1016/j.celrep.2024.114623] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2024] [Revised: 07/15/2024] [Accepted: 07/29/2024] [Indexed: 08/17/2024] Open
Abstract
Selection of fruits with enhanced health benefits and superior flavor is an important aspect of peach breeding. Understanding the genetic interplay between appearance and flavor chemicals remains a major challenge. We identify the most important volatiles contributing to consumer preferences for peach, thus establishing priorities for improving flavor quality. We quantify volatiles of a peach population consisting of 184 accessions and demonstrate major reductions in the important flavor volatiles linalool and Z-3-hexenyl acetate in red-fleshed accessions. We identify 474 functional gene regulatory networks (GRNs), among which GRN05 plays a crucial role in controlling both red flesh and volatile content through the NAM/ATAF1/2/CUC (NAC) transcription factor PpBL. Overexpressing PpBL results in reduced expression of PpNAC1, a positive regulator for Z-3-hexenyl acetate and linalool synthesis. Additionally, we identify haplotypes for three tandem PpAATs that are significantly correlated with reduced gene expression and ester content. We develop genetic resources for improvement of fruit quality.
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Affiliation(s)
- Xiangmei Cao
- Laboratory of Fruit Quality Biology/Zhejiang Key Laboratory of Horticultural Crop Quality Improvement, Zhejiang University, Zijingang Campus, Hangzhou 310058, China
| | - Yike Su
- Laboratory of Fruit Quality Biology/Zhejiang Key Laboratory of Horticultural Crop Quality Improvement, Zhejiang University, Zijingang Campus, Hangzhou 310058, China
| | - Ting Zhao
- Zhejiang Provincial Key Laboratory of Crop Genetic Resources, The Advanced Seed Institute, Plant Precision Breeding Academy, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 300058, China
| | - Yuanyuan Zhang
- Institute of Pomology, Jiangsu Academy of Agricultural Sciences/Jiangsu Key Laboratory of Horticultural Crop Genetic Improvement, Nanjing, Jiangsu 210014, China
| | - Bo Cheng
- Laboratory of Fruit Quality Biology/Zhejiang Key Laboratory of Horticultural Crop Quality Improvement, Zhejiang University, Zijingang Campus, Hangzhou 310058, China
| | - Kaili Xie
- Laboratory of Fruit Quality Biology/Zhejiang Key Laboratory of Horticultural Crop Quality Improvement, Zhejiang University, Zijingang Campus, Hangzhou 310058, China
| | - Mingliang Yu
- Institute of Pomology, Jiangsu Academy of Agricultural Sciences/Jiangsu Key Laboratory of Horticultural Crop Genetic Improvement, Nanjing, Jiangsu 210014, China
| | - Andrew Allan
- The New Zealand Institute for Plant & Food Research Limited (Plant & Food Research) Mt Albert, Auckland Mail Centre, Private Bag 92169, Auckland 1142, New Zealand
| | - Harry Klee
- Laboratory of Fruit Quality Biology/Zhejiang Key Laboratory of Horticultural Crop Quality Improvement, Zhejiang University, Zijingang Campus, Hangzhou 310058, China
| | - Kunsong Chen
- Laboratory of Fruit Quality Biology/Zhejiang Key Laboratory of Horticultural Crop Quality Improvement, Zhejiang University, Zijingang Campus, Hangzhou 310058, China
| | - Xueying Guan
- Zhejiang Provincial Key Laboratory of Crop Genetic Resources, The Advanced Seed Institute, Plant Precision Breeding Academy, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 300058, China
| | - Yuyan Zhang
- Institute of Pomology, Jiangsu Academy of Agricultural Sciences/Jiangsu Key Laboratory of Horticultural Crop Genetic Improvement, Nanjing, Jiangsu 210014, China.
| | - Bo Zhang
- Laboratory of Fruit Quality Biology/Zhejiang Key Laboratory of Horticultural Crop Quality Improvement, Zhejiang University, Zijingang Campus, Hangzhou 310058, China; Hainan Institute of Zhejiang University, Sanya, Hainan 572000, China.
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Magon G, De Rosa V, Martina M, Falchi R, Acquadro A, Barcaccia G, Portis E, Vannozzi A, De Paoli E. Boosting grapevine breeding for climate-smart viticulture: from genetic resources to predictive genomics. FRONTIERS IN PLANT SCIENCE 2023; 14:1293186. [PMID: 38148866 PMCID: PMC10750425 DOI: 10.3389/fpls.2023.1293186] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 11/27/2023] [Indexed: 12/28/2023]
Abstract
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.
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Affiliation(s)
- Gabriele Magon
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), Laboratory of Plant Genetics and Breeding, University of Padova, Agripolis, Viale dell’Università 16, Legnaro, Italy
| | - Valeria De Rosa
- Department of Agricultural, Food, Environmental and Animal Sciences (DI4A), University of Udine, Via delle Scienze, 206, Udine, Italy
| | - Matteo Martina
- Department of Agricultural, Forest and Food Sciences (DISAFA), Plant Genetics, University of Torino, Largo P. Braccini 2, Grugliasco, Italy
| | - Rachele Falchi
- Department of Agricultural, Food, Environmental and Animal Sciences (DI4A), University of Udine, Via delle Scienze, 206, Udine, Italy
| | - Alberto Acquadro
- Department of Agricultural, Forest and Food Sciences (DISAFA), Plant Genetics, University of Torino, Largo P. Braccini 2, Grugliasco, Italy
| | - Gianni Barcaccia
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), Laboratory of Plant Genetics and Breeding, University of Padova, Agripolis, Viale dell’Università 16, Legnaro, Italy
| | - Ezio Portis
- Department of Agricultural, Forest and Food Sciences (DISAFA), Plant Genetics, University of Torino, Largo P. Braccini 2, Grugliasco, Italy
| | - Alessandro Vannozzi
- Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), Laboratory of Plant Genetics and Breeding, University of Padova, Agripolis, Viale dell’Università 16, Legnaro, Italy
| | - Emanuele De Paoli
- Department of Agricultural, Food, Environmental and Animal Sciences (DI4A), University of Udine, Via delle Scienze, 206, Udine, Italy
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