Molecular Plant Breeding 2024, Vol.15, No.5, 308-316 http://genbreedpublisher.com/index.php/mpb 315 The findings from systematic QTL analysis have several implications for future research and breeding programs. First, the continuous discovery and validation of QTLs will provide a robust genetic foundation for developing high-yielding and high-quality rice varieties. Future research should focus on fine-mapping and cloning additional QTLs, as well as understanding their molecular mechanisms. Second, the integration of QTL analysis with other genomic tools, such as genome-wide association studies (GWAS) and genomic selection, will further enhance the efficiency of breeding programs. Finally, breeding programs should adopt a holistic approach that considers both yield and quality traits, ensuring that new rice varieties meet the demands of both farmers and consumers. The use of advanced breeding techniques, such as marker-assisted selection and genomic selection, will be instrumental in achieving these goals. Acknowledgments The author extends sincere appreciation to the two anonymous peer reviewers for their valuable insights and constructive feedback, which contributed to the academic rigor of this work. Conflict of Interest Disclosure The author affirms that this research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest. References Aloryi K., Okpala N., Amo A., Bello S., Akaba S., and Tian X., 2022, A meta-quantitative trait loci analysis identified consensus genomic regions and candidate genes associated with grain yield in rice, Frontiers in Plant Science, 13: 1035851. https://doi.org/10.3389/fpls.2022.1035851 Bai X., Wu B., and Xing Y., 2012, Yield-related QTLs and their applications in rice genetic improvement, Journal of Integrative Plant Biology, 54(5): 300-311. https://doi.org/10.1111/j.1744-7909.2012.01117.x Bernier J., Kumar A., Venuprasad R., Spaner D., Verulkar S., Mandal N., Sinha P., Peeraju P., Dongre P., Mahto R., and Atlin G., 2009, Characterization of the effect of a QTL for drought resistance in rice, qtl12.1, over a range of environments in the Philippines and eastern India, Euphytica, 166: 207-217. https://doi.org/10.1007/s10681-008-9826-y Francia E., Tacconi G., Crosatti C., Barabaschi D., Bulgarelli D., Dall’Aglio E., and Vale G., 2005, Marker assisted selection in crop plants, Plant Cell, Tissue and Organ Culture, 82: 317-342. https://doi.org/10.1007/s11240-005-2387-z Gao F., Zeng L., Qiu L., Lu X., Ren L., Wu X., Su X., Gao Y., and Ren G., 2016, QTL mapping of grain appearance quality traits and grain weight using a recombinant inbred population in rice (Oryza sativa L.), Journal of Integrative Agriculture, 15(8): 1693-1702. https://doi.org/10.1016/S2095-3119(15)61259-X Guo L., and Ye G., 2014, Use of major quantitative trait loci to improve grain yield of rice, Rice Science, 21(2): 65-82. https://doi.org/10.1016/S1672-6308(13)60174-2 Huang W.Z., and Hong Z.M., 2024, Marker-assisted selection in cassava: from theory to practice, Plant Gene and Trait, 15(1): 33-43. https://doi.org/10.5376/pgt.2024.15.0005 Ishimaru K., Yano M., Aoki N., Ono K., Hirose T., Lin S., Monna L., Sasaki T., and Ohsugi R., 2001, Toward the mapping of physiological and agronomic characters on a rice function map: QTL analysis and comparison between QTLs and expressed sequence tags, Theoretical and Applied Genetics, 102: 793-800. https://doi.org/10.1007/s001220000467 Jena K., and Mackill D., 2008, Molecular markers and their use in marker-assisted selection in rice, Crop Science, 48(4): 1266-1276. https://doi.org/10.2135/CROPSCI2008.02.0082 Jiang C., 2024, Genetic mechanisms of crop disease resistance: new advances in GWAS, Plant Gene and Trait, 15(1): 15-22. https://doi.org/10.5376/pgt.2024.15.0003 Kulkarni S., Balachandran S., Ulaganathan K., Balakrishnan D., Praveen M., Prasad A., Fiyaz R., Senguttuvel P., Sinha P., Kale R., Rekha G., Kousik M., Harika G., Anila M., Punniakoti E., Dilip T., Hajira S., Pranathi K., Das M., Shaik M., Chaitra K., Rao P., Gangurde S., Pandey M., and Sundaram R., 2020, Molecular mapping of QTLs for yield related traits in recombinant inbred line (RIL) population derived from the popular rice hybrid KRH-2 and their validation through SNP genotyping, Scientific Reports, 10: 1695. https://doi.org/10.1038/s41598-020-70637-3 Li X., Yan W., Agrama H., Jia L., Shen X., Jackson A., Moldenhauer K., Yeater K., McClung A., and Wu D., 2011, Mapping QTLs for improving grain yield using the USDA rice mini-core collection, Planta, 234: 347-361. https://doi.org/10.1007/s00425-011-1405-0
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