Molecular Plant Breeding 2024, Vol.15, No.5, 308-316 http://genbreedpublisher.com/index.php/mpb 308 Review and Progress Open Access Systematic Analysis of QTLs for Rice Yield and Quality: From Mapping to Application Yumin Huang School of Life Science, Xiamen University, Xiamen, 361102, Fujian, China Corresponding email: hym@xmu.edu.cn Molecular Plant Breeding, 2024, Vol.15, No.5 doi: 10.5376/mpb.2024.15.0029 Received: 17 Sep., 2024 Accepted: 17 Oct., 2024 Published: 28 Oct., 2024 Copyright © 2024 Huang, This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Huang Y.M., 2024, Systematic analysis of QTLs for rice yield and quality: from mapping to application, Molecular Plant Breeding, 15(5): 308-316 (doi: 10.5376/mpb.2024.15.0029) Abstract Rice (Oryza sativaL.) is a major food crop crucial to global food security, and its yield and quality are the most important traits for improvement. This study examines the quantitative trait loci (QTL) associated with rice yield and quality, details their localization, mechanism, and application in breeding programs, and explores the historical development of QTL mapping techniques, from traditional two-parent hybridization to advanced methods such as genome-wide association studies (GWAS). The genetic mechanisms and regulatory pathways of key QTLS affecting yield components such as grain number, panicle length, biomass, grain size, amylose content, aroma and other quality traits were discussed. By analyzing previous studies, this study highlights the successful identification and application of these QTLS in the breeding of high-yield and high-quality rice varieties, and illustrates how QTL data can be integrated into breeding strategies through marker-assisted selection (MAS) and genomic selection (GS). The purpose of this study is to provide some scientific basis for the next research. Keywords Rice yield; Rice quality; Quantitative trait loci (QTL); Marker-assisted selection (MAS); Genomic selection (GS) 1 Introduction Rice (Oryza sativa L.) is a staple food for more than half of the world’s population, providing 60%~70% of the daily caloric intake for over two billion Asians alone (Marathi et al., 2012). The global demand for rice continues to rise due to population growth, urbanization, and changing dietary preferences. Ensuring high rice yield and quality is crucial for global food security, especially in the face of challenges such as climate change, water scarcity, and limited arable land (Sandhu and Kumar, 2017). Enhancing rice yield and quality not only addresses food shortages but also contributes to economic stability and poverty alleviation in rice-dependent regions (Miura et al., 2011). Quantitative trait loci (QTL) are genomic regions that contribute to the variation in complex traits such as yield, drought tolerance, and grain quality in rice. The identification and mapping of QTLs have revolutionized plant breeding by enabling the precise selection of desirable traits through marker-assisted selection (MAS) (Selamat and Nadarajah, 2021; Aloryi et al., 2022). QTL mapping involves the use of various genetic populations and high-throughput sequencing technologies to locate specific genomic regions associated with target traits (Miura et al., 2011). Meta-QTL analysis further refines these regions, providing stable and robust QTLs that are consistent across different genetic backgrounds and environments (Aloryi et al., 2022). This approach has been instrumental in identifying key genes and regulatory networks that control important agronomic traits, thereby facilitating the development of high-yielding and stress-tolerant rice varieties (Sandhu and Kumar, 2017). The aim of this study is to provide a comprehensive analysis of QTLS related to rice yield and quality, from their initial localization to their practical application in breeding programs. In this study, we reviewed the current status of QTL research related to rice yield and quality, highlighted the main research results in recent years, discussed the methods and techniques of QTL localization and meta-QTL analysis, and emphasized their advantages and limitations. In different studies, identify consistent genomic regions and candidate genes associated with yield and quality traits, and explore the practical application of QTL in marker-assisted selection and genetic engineering of improved rice varieties. By synthesizing the latest research and providing
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