Molecular Pathogens 2024, Vol.15, No.1, 40-49 http://microbescipublisher.com/index.php/mp 42 of genetic variations that are crucial for disease resistance. For instance, the re-sequencing of grapevine cultivars has led to the discovery of thousands of single nucleotide polymorphisms (SNPs), which are essential for genetic mapping and marker-assisted selection. Restriction site-associated DNA sequencing (RAD-seq) has been employed to analyze the genetic diversity of grapevine and identify genes related to disease resistance, such as those conferring resistance to white rot disease (Zhang et al., 2020). 3.2 Genotyping and SNP analysis Genotyping and SNP analysis are critical components of modern grapevine breeding programs. SNPs are the most abundant type of DNA sequence polymorphisms and provide a robust framework for genetic studies. High-density SNP arrays and genotyping-by-sequencing (GBS) methods have been used to generate extensive SNP datasets, which are then utilized in genome-wide association studies (GWAS) to link genetic markers with phenotypic traits. For example, a study using GBS identified over 76 000 SNPs in Canadian Holstein cows, demonstrating the utility of this approach for complex trait improvement (Ibeagha-Awemu et al., 2016). In grapevine, SNP genotyping has been applied to cultivar identification, genetic diversity studies, and the construction of genetic maps, thereby enhancing the efficiency of breeding programs. 3.3 Genome-wide association studies (GWAS) GWAS have become a powerful tool for identifying genetic loci associated with disease resistance in grapevine. By analyzing the association between SNPs and phenotypic traits across a large population, GWAS can pinpoint specific genomic regions that contribute to disease resistance. For instance, a high-resolution GWAS in wheat identified multiple quantitative trait loci (QTLs) associated with resistance to various diseases, providing valuable insights for breeding programs (Pang et al., 2021). Similarly, GWAS in grapevine have revealed significant SNPs linked to disease resistance, such as those associated with white rot disease (Zhang et al., 2020). The integration of GWAS with genomic selection (GS) models has further improved the predictive accuracy of breeding programs, as demonstrated by a study that combined GWAS and GS to achieve high prediction accuracies for complex traits in grapevine (Fodor et al., 2014). 4 Identification of Disease Resistance Genes 4.1 Mapping resistance loci Mapping resistance loci is a critical step in identifying and utilizing disease resistance genes in grapevine breeding programs. Various studies have employed different mapping techniques to locate these loci. For instance, a physical map of the heterozygous grapevine 'Cabernet Sauvignon' was constructed, which included 29 727 BAC clones assembled into 1 770 contigs. This map facilitated the genome-wide mapping of candidate genes for disease resistance, revealing that NBS-LRRand RLKgenes for host resistance were found in 424 contigs, with 133 of them assigned to chromosomes. A multi-tiered haplotype strategy was used to enhance phased assembly and fine-mapping of a disease resistance locus, specifically the RPV33 locus conferring resistance to grapevine downy mildew, narrowing the candidate region to only 0.46 Mb (Zou et al., 2023). Another study focused on the REN1 and REN2 loci for powdery mildew resistance, using high-resolution genetic mapping to identify candidate resistance genes (Cadle-Davidson et al., 2016). 4.2 Functional genomics approaches Functional genomics approaches are essential for understanding the roles of identified resistance genes. These approaches include transcriptome analysis, gene expression profiling, and functional validation through gene editing. For example, allele-specific RNA-seq analysis was employed to identify a cluster of three putative disease resistance RPP13-like protein 2 genes as candidates for the RPV33 locus (Zou et al., 2023). In another study, the candidate-gene approach was applied to map QTLs for disease resistance in wheat, revealing that many minor resistance QTLs may be from the action of defense response genes. Deep sequencing of putative susceptibility genes in grapevine identified Single Nucleotide Polymorphisms (SNPs) that could be used for genomic-assisted breeding and tailored gene editing approaches for resistance to biotic stresses (Pirrello et al., 2021).
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