Triticeae Genomics and Genetics, 2024, Vol.15, No.3, 137-151 http://cropscipublisher.com/index.php/tgg 140 content in wheat. Research on spring wheat DH populations from the IPK gene bank in Germany has identified several consistent QTLs that significantly influence anther extrusion. These include QTLs on chromosomes 4A, 2D, and 6B, which have demonstrated consistency across all years (Muqaddasi et al., 2019). Figure 1 Locations of QTLs for 13 quality traits based on RILs derived from TN18 × LM6 (Adopted from Guo et al., 2020) Image capton: The figure shows the positions of QTLs (quantitative trait loci) detected for 13 wheat quality traits in recombinant inbred lines (RILs) derived from a cross between 'Tainong 18' and 'Linmai 6'. The LOD (logarithm of odds) values for the QTL intervals are all greater than 3.0, as determined by a threshold set through 1000 permutation tests. The blue sections in the figure represent QTLs related to quality traits. This figure indicates that QTLs are widely distributed across 21 chromosomes, explaining 5.32% to 35.09% of the phenotypic variation (Adapted from Guo et al., 2020) 3.2.3 Backcross and multi-parent populations Backcross populations are created by crossing a hybrid with one of its parents, while multi-parent populations involve crosses between multiple parental lines. Kulkarni et al. (2020) identified quantitative trait loci (QTL) controlling yield and related traits from the popular rice hybrid KRH-2 using a recombinant inbred line (RIL) population. The study constructed a genetic map spanning 294.2 cM, which included 126 simple sequence repeat (SSR) markers evenly distributed across the rice genome. QTL analysis based on phenotypic and genotypic information identified a total of 22 QTLs, among which five major QTLs were found to control total grain yield, panicle weight, plant height, flag leaf width, and panicle length. These QTLs explained 20.23% to 22.76% of the phenotypic variance (Kulkarni et al., 2020). SNP genotyping validated most of the QTLs identified through SSR genotyping. The newly identified QTLs offer potential applications for improving the yield of rice hybrids. 3.3 Genotyping platforms 3.3.1 Microarrays Microarrays are used to detect thousands of SNPs simultaneously, providing a high-throughput genotyping platform. The wheat 660 K SNP array, for example, has been proven to be reliable and cost-effective for targeted genotyping and marker-assisted selection. Studies have shown that the wheat 660 K SNP array has the highest percentage of genome-specific SNPs, and its SNP density is evenly distributed, making it the best choice for targeted genotyping and marker-assisted selection in wheat genetic improvement (Sun et al., 2020). Additionally, compared to PCR markers and sequencing technologies, SNP arrays offer high throughput, high density, and cost-efficiency advantages, and they are widely used in gene locus detection and QTL mapping in wheat breeding projects. 3.3.2 Next-generation sequencing (NGS) Next-Generation Sequencing (NGS) technologies provide a comprehensive approach to genotyping by sequencing entire genomes or specific genomic regions. Research has found that Next-Generation Sequencing (NGS) technology has made significant progress in wheat genetic improvement, including mapping sequencing,
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