Plant Gene and Trait 2024, Vol.15, No.2, 85-96 http://genbreedpublisher.com/index.php/pgt 91 consumer preference (Bazrkar-Khatibani et al., 2019). The use of MAS in breeding programs has also been demonstrated in the improvement of grain elemental concentrations, such as zinc and iron, which are essential for human nutrition (Nawaz et al., 2015). The application of MAS in enhancing grain quality involves the use of tightly linked DNA markers to select for multiple positive alleles. This approach has been successfully employed in the pyramiding of QTLs for seed vigor, resulting in rice varieties with strong germination and seedling establishment under various environmental conditions (Xie et al., 2014). Furthermore, the development of tools like RiceNavi, which optimizes breeding schemes based on QTL information, exemplifies the integration of genomic knowledge into practical breeding applications (Wei et al., 2021). 5.3 Future directions in breeding for superior grain quality The future of rice breeding for superior grain quality lies in the continued integration of advanced genomic tools and techniques. The development of comprehensive QTL maps and the identification of quantitative trait nucleotides (QTNs) provide a robust foundation for precision breeding (Shariatipour). Future breeding programs will benefit from the incorporation of genome-wide association studies (GWAS) and meta-QTL analyses, which offer insights into the genetic basis of complex traits and their stable expression across different environments (Selamat and Nadarajah, 2021; Shariatipour et al., 2023). One promising direction is the use of genomic selection (GS), which combines phenotypic and genotypic data to predict the breeding value of individuals. This approach can significantly accelerate the breeding cycle and improve the accuracy of selection for complex traits such as grain quality. Additionally, the integration of functional genomics and transcriptomics will enhance our understanding of the molecular mechanisms underlying grain quality traits, enabling the identification of novel candidate genes for targeted breeding (Raza et al., 2019; Mazumder et al., 2020). Another key area is the development of climate-resilient rice varieties through the identification and incorporation of QTLs associated with abiotic stress tolerance, such as drought and salinity (Solis et al., 2018; Mazumder et al., 2020). The use of advanced breeding techniques, such as CRISPR/Cas9-mediated gene editing, holds great potential for the precise modification of genes associated with grain quality, further enhancing the efficiency of breeding programs. In conclusion, the integration of QTL findings into breeding strategies, the application of MAS, and the exploration of future genomic tools will collectively drive the development of superior rice varieties with enhanced grain quality, meeting the demands of both producers and consumers. 6 Technological Innovations and Future Research 6.1 Emerging technologies in genetic mapping and their potential Recent advancements in genetic mapping technologies have significantly enhanced our ability to identify and utilize quantitative trait loci (QTLs) for rice grain quality improvement. One such technology is genotyping-by-sequencing (GBS), which has been effectively used for high-resolution QTL mapping. For instance, a study utilized GBS to construct a high-density genetic map and identified 15 QTLs associated with various grain quality traits, such as transparency and chalkiness, in rice (Jin et al., 2023). This approach allows for the precise localization of QTLs, facilitating the fine mapping and pyramiding of these loci for genetic improvement. Another promising technology is QTL-seq, which combines whole-genome resequencing with bulked segregant analysis. This method has been successfully applied to identify QTLs for traits like partial resistance to rice blast disease and seedling vigor (Takagi et al., 2013). QTL-seq offers a rapid and cost-effective means of mapping QTLs, making it a valuable tool for breeding programs. Genome-wide association studies (GWAS) have also been instrumental in identifying QTLs for grain quality traits. A GWAS conducted on a diverse panel of indica rice accessions identified 38 QTLs for traits such as grain length,
RkJQdWJsaXNoZXIy MjQ4ODYzMg==