Tree Genetics and Molecular Breeding 2024, Vol.14, No.4, 206-217 http://genbreedpublisher.com/index.php/tgmb 210 5.2 Genomic selection (GS) Genomic selection (GS) is an advanced breeding method that uses genome-wide markers to predict the genetic value of individuals, allowing for the selection of superior genotypes even before phenotypic traits are expressed. This approach is particularly beneficial for complex traits with low heritability, where traditional selection methods are less effective (Brault et al., 2021; Bharati et al., 2023). GS has shown promise in grapevine breeding by improving the predictive ability for traits such as yield, berry composition, and disease resistance (Brault et al., 2021). The integration of GS with polyploidization and omics data further enhances its potential, enabling the prediction of genotypes with desirable traits among diverse grapevine populations (Bharati et al., 2023). This method not only accelerates the breeding process but also increases the genetic gain per breeding cycle, making it a powerful tool for developing new grapevine varieties that can withstand environmental challenges and meet market demands (Gaspero and Cattonaro, 2010; Magon et al., 2023). 5.3 Gene-editing techniques Gene-editing techniques, particularly CRISPR/Cas9, have revolutionized grapevine breeding by allowing precise modifications of the genome. These techniques enable the targeted alteration of specific genes to enhance desirable traits or eliminate undesirable ones, offering a level of precision that traditional breeding methods cannot achieve (Gray et al., 2014). CRISPR/Cas9 has been used to improve traits such as disease resistance and fruit quality in grapevines, providing a rapid and efficient means of developing new cultivars (Figure 2) (Costa et al., 2019; Capriotti et al., 2020). The application of gene-editing in grapevine breeding is still in its early stages, but it holds great potential for the future. By enabling the fine-tuning of genetic traits, gene-editing can complement other genomic approaches, such as MAS and GS, to create grapevine varieties that are better suited to changing environmental conditions and consumer preferences (Butiuc-Keul and Coste, 2023; Magon et al., 2023). As the technology continues to advance, it is expected to play a crucial role in the sustainable development of the grapevine industry. 6 Case Studies 6.1 Application of genomics in breeding disease-resistant grapevine varieties The application of genomics in breeding disease-resistant grapevine varieties has revolutionized viticulture by enabling more precise and efficient selection processes. Genomic tools, such as marker-assisted selection, have been instrumental in identifying and utilizing quantitative trait loci (QTL) associated with resistance to common grapevine diseases like downy and powdery mildew. For instance, research has identified major QTLs on chromosomes 15 and 18 that are linked to resistance against these diseases, providing a genetic basis for developing resistant cultivars (Zyprian et al., 2016; Ricciardi et al., 2024). This genomic approach allows breeders to select for disease resistance at the genetic level, bypassing the limitations of traditional phenotypic selection, which can be less efficient due to the complex nature of these traits (Gaspero and Cattonaro, 2010; Zyprian et al., 2016). Moreover, the integration of genome-wide association studies (GWAS) has further enhanced the identification of novel loci associated with disease resistance. Recent studies have discovered new loci, such as Rpv36 and Rpv37 for downy mildew resistance, and Ren14 and Ren15 for powdery mildew resistance, which are rich in genes related to biotic stress response (Ricciardi et al., 2024). These advancements not only facilitate the breeding of disease-resistant varieties but also contribute to sustainable viticulture by reducing the reliance on chemical fungicides. 6.2 Developing climate-resilient grapevine cultivars The development of climate-resilient grapevine cultivars is becoming increasingly critical as climate change poses new challenges to viticulture. Genomic approaches are at the forefront of this effort, offering tools to accelerate the breeding of cultivars that can withstand extreme weather conditions (Figure 3). For example, genomic prediction methods, such as Genomic Best Linear Unbiased Predictor (GBLUP) and Least Absolute Shrinkage
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