Molecular Pathogens 2024, Vol.15, No.5, 219-226 http://microbescipublisher.com/index.php/mp 221 resistance, as demonstrated in various crops, including wheat and strawberries (Cockerton et al., 2021). By leveraging large datasets of genomic and phenotypic information, GS can accelerate the breeding cycle and increase genetic gains. In strawberries, GS can be used to improve complex traits such as disease resistance, yield, and fruit quality by selecting the best-performing individuals based on their genomic profiles (Crossa et al., 2017). This method holds great promise for developing robust, disease-resistant strawberry varieties that can thrive under diverse environmental conditions. Figure 1 Schematic diagram of plant breeding using molecular markers (Adopted from Jeon et al., 2023) 4 Applications of Biotechnology in Enhancing Disease Resistance 4.1 Gene mapping for disease resistance 4.1.1 Identification of disease resistance genes Gene mapping has become a pivotal tool in identifying disease resistance genes in strawberries. A study on octoploid strawberries identified a major locus, FaRPc2, on linkage group 7D, which is significantly associated with resistance to crown rot disease caused by Phytophthora cactorum. This locus contains multiple resistance alleles, making it a prime target for breeding programs aimed at enhancing disease resistance (Mangandi et al., 2017). Additionally, advances in plant genome sequencing have facilitated the discovery of novel resistance (R) genes, which can be leveraged to control diseases caused by various pathogens (Pandolfi et al., 2017). 4.1.2 Utilization of gene mapping in breeding The utilization of gene mapping in breeding programs allows for the precise selection of desirable traits. By employing quantitative trait locus (QTL) analyses in multiparental populations, breeders can increase the power of QTL detection and estimate allele effects across diverse genetic backgrounds. This approach has been successfully applied to improve resistance to diseases like crown rot in strawberries, thereby accelerating genetic gains and enhancing the efficiency of breeding programs (Yin and Qiu, 2019). Predictive breeding techniques, which combine phenotypic data with genomic information, have shown promise in developing cultivars with increased resistance to diseases such as verticillium wilt (Taliansky et al., 2019). 4.2 RNA interference (RNAi) in disease control 4.2.1 Mechanism and benefits of RNAi RNA interference (RNAi) is a gene regulatory mechanism that involves the silencing of specific genes through the action of small interfering RNAs (siRNAs) or microRNAs (miRNAs). This process can effectively down-regulate gene expression without affecting other genes, making it a precise tool for crop improvement. RNAi has been widely used to develop resistance against various pathogens, including viruses, bacteria, fungi, and nematodes, by targeting and silencing genes essential for pathogen survival or virulence (Kamthan et al., 2015). The benefits of
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