Rice Genomics and Genetics 2024, Vol.15, No.4, 164-177 http://cropscipublisher.com/index.php/rgg 169 accurately. For example, a study using GS in rice identified multiple QTLs for root system architecture and agronomic traits, demonstrating the effectiveness of this approach in enhancing yield-related traits (Sharma et al., 2021). Moreover, integrating GS with machine learning models such as Bayesian networks has shown to improve prediction accuracies for complex traits like yield (Sharma et al., 2021). 4.2 Stress resistance and tolerance Abiotic stress, including drought and salinity, poses significant challenges to rice production. The identification of QTLs and genes associated with abiotic stress tolerance is essential for developing resilient rice varieties. The introgression lines developed from various Oryza species have shown traits such as drought resistance and aerobic adaptation, which are critical for improving rice performance under stress conditions (Zhang et al., 2022). These genetic resources provide a foundation for breeding programs aimed at enhancing abiotic stress tolerance in rice. Several genes associated with abiotic stress responses have been identified. For instance, the Oryza coarctata genome revealed genes involved in salinity and submergence stress responses (Bansal et al., 2020). Additionally, studies have shown that genetic variations in heterotrimeric G proteins play a significant role in the regulation of key agronomic traits under varying climatic conditions. Biotic stresses, such as diseases and pests, also impact rice yield and quality. The genetic analysis of interspecific backcross populations has revealed QTLs linked to biotic stress resistance. For instance, Oryza glaberrima has been identified as a valuable source of genes for resistance to various biotic stresses, which can be introgressed into Oryza sativa cultivars to enhance their resilience (Bharamappanavara et al., 2023). Additionally, the introgression library includes lines with blast resistance, highlighting the potential of wild species in providing durable resistance to biotic stresses (Zhang et al., 2022). 4.3 Nutritional and quality traits Improving the nutritional quality of rice is a key objective in rice breeding. The genetic diversity present in wild and relative species offers opportunities to enhance nutrient biosynthesis pathways. The introgression lines developed from multiple Oryza species include traits related to nutrient biosynthesis, which can be harnessed to improve the nutritional profile of rice (Zhang et al., 2022). These genetic resources are invaluable for breeding programs focused on enhancing the nutritional quality of rice. Grain quality and processing traits are important determinants of rice marketability and consumer preference. The identification of QTLs associated with grain quality traits, such as grain length and width, has been facilitated by the development of introgression libraries. For example, novel allelic variations related to grain length and width have been identified in the introgression lines, providing valuable resources for improving grain quality (Zhang et al., 2022). These findings highlight the potential of utilizing genetic diversity from wild and relative species to enhance grain quality and processing traits in rice. 5 Genomic Tools and Technologies for Oryza Improvement 5.1 Genome editing and CRISPR/Cas systems The advent of CRISPR/Cas systems has revolutionized the field of functional genomics in rice (Oryza sativa L.). One notable tool is the CRISPR applicable functional redundancy inspector (CAFRI-Rice), which addresses the challenge of functional redundancy in the rice genome. This tool utilizes a phylogenetic heatmap to estimate the similarity between protein sequences and expression patterns, thereby identifying genes with potential functional redundancy. CAFRI-Rice has successfully predicted functional redundancy in 7 075 genes and demonstrated its utility in overcoming redundancy in root-preferred genes through loss-of-function analyses (Figure 3) (Hong et al., 2020). This approach not only accelerates functional genomic studies in rice but also holds potential for application in other plant species. The research of Hong et al. (2020) validated functional redundancy and dominance in rice using the CAFRI-Rice model. Figure 3 (a) shows the functional dominance of RUPO and MATL genes in anther/pollen, with the uniqueness of the MTD1 gene also being confirmed. Figure 3 (b) demonstrates the high functional redundancy of
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