Molecular Pathogens, 2025, Vol.16, No.2, 45-52 http://microbescipublisher.com/index.php/mp 48 Recently, many studies have used SNP genetic maps to find QTLs related to some rice diseases, such as bacterial ear blight, leaf strip disease and brown strip disease. Some studies have also found important regions related to resistance to ramen disease on chromosomes 2, 4, 5, 7 and 9 through high-precision methods (Neelam et al., 2021). Later, the researchers further integrated these QTLs using meta-analysis methods, thus finding multiple candidate genes related to disease resistance (Kumar and Nadarajah, 2020). 4.3 Transcriptomic and proteomic insights into disease resistance In addition to QTL, we are now using transcriptomics and proteomics to study how rice fights diseases. These methods can help verify whether candidate genes in QTL work, and can also tell us which genes in rice are changing before and after bacterial infection (Fang et al., 2023). Through this analysis, researchers have a clearer understanding of how rice fights bacteria and can also find key disease-resistant genes and signaling pathways that can be used in breeding (Liu et al., 2021; Akohoue and Miedaner, 2022). Combining these molecular data with genomic information will help to more accurately carry out disease-resistant breeding. 5 Integration of Biotechnological Tools in Traditional Breeding Programs 5.1 Marker-assisted selection (MAS) for accelerated breeding Marker-assisted selection (MAS) is now a very commonly used tool in rice disease-resistant breeding. It can help us accurately add disease-resistant genes to varieties that are prone to disease, much faster than traditional methods. For example, MAS has been used to place several disease-resistant genes in a rice variety together, which can make rice more resistant to white leaf blight and blast (Ashkani et al., 2015; Chukwu et al., 2019; Sahu et al., 2022). The Tellahamsa variety bred with MAS can resist both diseases at the same time, which shows that this method is very useful (Jamaloddin et al., 2020). 5.2 Genomic selection and its role in developing resistant lines Genome selection is also a new breeding method. It uses genome-wide data to predict which varieties may be more resistant to disease, and then select them to perform well. This method can screen multiple disease-resistant genes at once, helping to cultivate rice varieties that can fight multiple diseases at the same time. Using genome selection with traditional breeding methods can also make breeding faster (Kumar et al., 2018; Tao et al., 2021). Moreover, by integrating multiple disease-resistant genes, resistance can also be longer-lasting and not easily broken by bacteria. 5.3 Use of molecular markers in breeding programs across regions In many regions, breeding projects have begun to use molecular marking technology to breed suitable local disease-resistant varieties. These markers can help us find disease-resistant genes in different genetic materials, and then transfer these genes to excellent varieties to enhance resistance. For example, some studies have used molecular markers to find new disease-resistant genes from wild rice and have been successfully introduced into cultivated rice (Ke et al., 2017). This provides new genetic resources for breeding and also allows rice varieties to be more adapted to local disease conditions. 6 Environmental and Agronomic Factors Influencing Disease Resistance 6.1 Influence of climatic conditions on disease incidence and resistance The weather has a great impact on the disease condition and resistance of rice. For example, rising temperatures can make some diseases more likely to break out. Like brown spots and bacterial seedling decay, it is more likely to occur at high temperatures around 30 °C because bacteria grow fast at this temperature (Mizobuchi et al., 2016). Therefore, to deal with these situations, we must breed rice varieties that can withstand high temperature diseases. Light also has an impact. When there are more cloudy days and less sun, rice will have a decrease in disease resistance, especially its resistance to rice blast disease becomes weak. This shows that light has a regulatory effect on the rice immune system and must also be taken into account during breeding (Liu et al., 2019). 6.2 Impact of soil health and microbiome on rice disease suppression Whether the soil is healthy and whether there are beneficial microorganisms in it will have a great impact on
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