Grapevines are challenged by a range of diseases and pests, causing economic losses and requiring often costly approaches to mitigate damage. Public interest in reducing the use of chemicals is a related challenge, along with climate change. Yet, the Vitis gene pool provides vast resources for the development of genetic resistance in rootstock and scion cultivars. Traditional breeding approaches have made great strides in the development of adaptive traits, and recent access to ‘omic technologies has further facilitated the identification of useful loci along with rapid trait introgression from wild species. Moreover, marker technologies are now used to stack multiple genes for the same trait into a single genotype, a heretofore barely accessible technology. Genomic technologies are also impacting germplasm characterization, and thereby facilitating “Breeding by Design” approaches. Genetic transformation and gene-editing technologies are also applicable for both cultivar improvement as well as functional studies of genes. The landscape for acceptance of new resistant cultivars is complex and with wine grapes, subject to high degrees of regulation especially in the European Union. With rootstocks, as well as table/raisin grapes, gaining acceptance in the marketplace for new cultivars developed through either traditional or marker-assisted approaches is routine. Yet even in the highly regulated EU environment, the adoption of new wine cultivars of interspecific origins is beginning to take place in both traditional wine growing regions as well as non-traditional regions nearby.
Genomic Designing for Biotic Stress Resistant Grapevine / S. Vezzulli, D. Gramaje, J. Tello, G. Gambino, P. Bettinelli, C. Pirrello, A. Schwandner, P. Barba, E. Angelini, G. Anfora, V. Mazzoni, A. Pozzebon, J. Emilio Palomares-Rius, M. Pilar Martínez-Diz, S.L. Toffolatti, G. DE LORENZIS, E. De Paoli, I. Perrone, E. D’Incà, S. Zenoni, J. Wilmink, T. Lacombe, M. Crespan, M. Andrew Walker, L. Bavaresco, M. De la Fuente, A. Fennell, G. Battista Tornielli, A. Forneck, J. Ibáñez, L. Hausmann, A.B.I. Reisch - In: Genomic Designing for Biotic Stress Resistant Fruit Crops / [a cura di] C. Kole. - [s.l] : Springer, 2022. - ISBN 978-3-030-91801-9. - pp. 87-255 [10.1007/978-3-030-91802-6_4]
Genomic Designing for Biotic Stress Resistant Grapevine
S.L. Toffolatti;G. DE LORENZIS;
2022
Abstract
Grapevines are challenged by a range of diseases and pests, causing economic losses and requiring often costly approaches to mitigate damage. Public interest in reducing the use of chemicals is a related challenge, along with climate change. Yet, the Vitis gene pool provides vast resources for the development of genetic resistance in rootstock and scion cultivars. Traditional breeding approaches have made great strides in the development of adaptive traits, and recent access to ‘omic technologies has further facilitated the identification of useful loci along with rapid trait introgression from wild species. Moreover, marker technologies are now used to stack multiple genes for the same trait into a single genotype, a heretofore barely accessible technology. Genomic technologies are also impacting germplasm characterization, and thereby facilitating “Breeding by Design” approaches. Genetic transformation and gene-editing technologies are also applicable for both cultivar improvement as well as functional studies of genes. The landscape for acceptance of new resistant cultivars is complex and with wine grapes, subject to high degrees of regulation especially in the European Union. With rootstocks, as well as table/raisin grapes, gaining acceptance in the marketplace for new cultivars developed through either traditional or marker-assisted approaches is routine. Yet even in the highly regulated EU environment, the adoption of new wine cultivars of interspecific origins is beginning to take place in both traditional wine growing regions as well as non-traditional regions nearby.File | Dimensione | Formato | |
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2021-06-01_Springer_GDSRC_Chapter_Grapevine.pdf
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978-3-030-91802-6_4.pdf
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