Plant Gene and Trait 2024, Vol.15, No.2, 85-96 http://genbreedpublisher.com/index.php/pgt 86 This study is to explore the genetic basis of rice grain quality traits through QTL mapping and assess their practical applications in rice breeding. By integrating high-density genetic maps, advanced genotyping techniques, and comprehensive phenotypic evaluations, this study aims to identify and validate QTLs associated with key grain quality traits. Furthermore, the study seeks to understand the molecular mechanisms underlying these traits and develop molecular markers for MAS. Ultimately, the goal is to enhance rice grain quality, thereby improving its market value, consumer acceptance, and nutritional benefits. This research will contribute to the development of high-quality rice varieties that meet diverse consumer preferences and address global food security challenges. 2 Understanding Quantitative Trait Loci (QTLs) 2.1 Definition and basics of QTLs in genetic research Quantitative Trait Loci (QTLs) are regions of the genome that are associated with specific quantitative traits, which are typically influenced by multiple genes and environmental factors. These traits can include various phenotypic characteristics such as grain size, yield, and quality in crops like rice. The identification and mapping of QTLs are crucial for understanding the genetic basis of these complex traits and for facilitating marker-assisted selection (MAS) in breeding programs (Takagi et al., 2013; Yun et al., 2014). QTLs are identified through statistical analysis that correlates genetic markers with phenotypic variation in a population. This process involves creating a genetic linkage map, which is a representation of the order and relative distances between markers on the chromosomes. By analyzing the co-segregation of markers and traits in a mapping population, researchers can pinpoint the genomic regions that contribute to the trait of interest (Yun et al., 2014; Kinoshita et al., 2017). 2.2 Methods for identifying QTLs related to rice grain quality Several methods are employed to identify QTLs associated with rice grain quality. Traditional QTL mapping involves crossing two parent lines with contrasting traits to produce a mapping population, such as recombinant inbred lines (RILs) or doubled haploid (DH) lines. These populations are then genotyped using molecular markers, and phenotypic data are collected for the traits of interest. Statistical methods, such as interval mapping and composite interval mapping, are used to detect QTLs by analyzing the association between markers and phenotypic variation (Figure 1) (Yun et al., 2014; Kinoshita et al., 2017). Advanced techniques like QTL-seq have been developed to expedite the QTL identification process. QTL-seq involves whole-genome resequencing of DNA from two bulked populations that exhibit extreme phenotypes for the trait of interest. This method allows for rapid and precise identification of QTLs by comparing the allele frequencies between the two bulks. Additionally, meta-QTL analysis, which combines data from multiple studies, can identify stable QTLs across different genetic backgrounds and environments, enhancing the reliability of QTLs for breeding applications (Selamat and Nadarajah, 2021). 2.3 Impact of QTLs on rice phenotypes and grain characteristics QTLs have a significant impact on various rice phenotypes and grain characteristics. For instance, QTLs associated with grain weight, length, and width have been identified, which are crucial determinants of overall grain yield and quality. Fine-mapping of these QTLs has revealed specific genomic regions and candidate genes that control these traits, providing valuable targets for genetic improvement (Zhang et al., 2020a). QTLs also influence the nutritional quality of rice grains. For example, QTLs associated with the concentrations of essential elements like zinc (Zn), iron (Fe), and phosphorus (P) have been mapped, offering insights into the genetic basis of nutrient accumulation in rice grains (Nawaz et al., 2015). Furthermore, QTLs related to grain protein and amylose content have been identified, which are important for determining the eating and cooking quality of rice (Yun et al., 2014; Kinoshita et al., 2017). The identification and characterization of QTLs enable breeders to develop rice varieties with enhanced grain quality through marker-assisted selection. By incorporating favorable alleles at key QTLs, it is possible to improve traits such as grain size, nutritional content, and stress tolerance, ultimately leading to higher-yielding
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