Legume Genomics and Genetics 2024, Vol.15, No.1, 13-22 http://cropscipublisher.com/index.php/lgg 20 In alfalfa (Medicago truncatula): A study identified candidate genes associated with improved seed size and composition via GWAS. This work used two different models for genomic association prediction, including a single-locus mixed linear model and a multi-locus model. Through these analyses, researchers clearly identified quantitative trait nucleotides (QTNs) that are highly correlated with seed size and composition , providing powerful genetic markers for the improvement of seed traits (Figure 5) (Chen et al., 2021). Figure 5 Genome wide association study between alfalfa seed traits and Manhattan and QQ maps obtained from FarmCPU (Adopted from Chen et al., 2021) Image caption: A: Combination of studies on the correlation between seed size (weight, area, majellipse, minellipse); B: A combination of studies on the correlation between seed sulfur content (mg/seed) and sulfur concentration (%, w/w); C: Combination of correlation studies on seed protein content (nitrogen content (mg/seed); Nitrogen concentration (%, w/w); Carbon/nitrogen ratio (Adopted from Chen et al., 2021) These cases demonstrate the potential of GWAS technology in identifying genetic markers associated with important agronomic traits. By using these genetic markers, researchers can make more accurate breeding selections and speed up the process of improving leguminous crop varieties. These studies not only deepen our understanding of the genetic basis of crops, but also provide important tools and resources for achieving the breeding goals of high-yielding, high-resistant, and high-quality leguminous crops.
RkJQdWJsaXNoZXIy MjQ4ODYzNA==