Plant Gene and Trait 2024, Vol.15, No.5, 230-242 http://genbreedpublisher.com/index.php/pgt 233 combined linkage mapping with GWAS to identify QTLs governing rice grain shape and weight, highlighting the co-detection of several QTLs on chromosomes 3, 5, and 12 (Kang et al., 2020). Wang et al. (2023) performed GWAS on 137 indica rice accessions, identifying 195 significant SNP-trait associations and revealing six key QTLs linked to grain quality traits. Figure 1 Kinship matrix, marker density, PCA, heritability, and genome selection results (Adopted from Kabange et al., 2023) Image caption: (A) heat map showing the relatedness or the level of co-ancestry of the population, (B) density map of SNP Chip DNA markers, (C) principal component analysis (PCA), (D) narrow sense heritability of grain length, (E) grain width, (F) grain thickness, (G) grain length-to-width ratio, (H) thousand-grain weight, and (I, J) results of the genome selection analysis that predict the genomic estimated breeding value (GEBV) of individuals in the RIL population in the reference group (Ref) and the inference group (Inf) (Adopted from Kabange et al., 2023) 4.2 QTL mapping QTL mapping is a method used to identify regions of the genome that are associated with quantitative traits (Chen et al., 2016). This approach involves crossing two parent lines with contrasting traits and analyzing the progeny to identify genetic markers linked to the traits of interest. By correlating these traits with molecular markers, QTLs are identified, which pinpoint regions of the genome contributing to the variation in traits. For example, a study using recombinant inbred lines (RILs) derived from a cross between two Iranian rice cultivars identified seven QTLs associated with grain appearance and quality traits on chromosomes 1, 6, 9, and 12 (Bazrkar-Khatibani et al., 2019). Another study focused on fine mapping a major QTL, qGL1.3, for grain length and weight, narrowing it down to a 350 kb region on chromosome 1 (Zhou et al., 2019). Additionally, QTL-seq, a rapid mapping technique using whole-genome resequencing of DNA from bulked populations, has been successfully applied to identify QTLs for traits such as seedling vigor and resistance to rice blast disease (Takagi et al., 2013). Advanced techniques like high-density SNP arrays and next-generation sequencing have improved the resolution of QTL mapping, enabling more precise identification of candidate genes involved in rice trait development (Huang et al., 2010).
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