Legume Genomics and Genetics 2025, Vol.16, No.1, 44-53 http://cropscipublisher.com/index.php/lgg 46 identified (Yoosefzadeh-Najafabadi et al., 2021). However, to be honest, knowing which genes are useful is only the first step. How to truly apply these discoveries to breeding practice might be the tough nut to crack next. Figure 1 Investigation of plant and agronomic traits of transgenic lines (Adopted from Sun et al., 2022) Image caption: *: p-value ≤ 0.05; **: p-value ≤ 0.01; (A) Plant height and root length of G16, G18, G26 and CK; (B) The number of branches, nodes, pods and seeds in the transgenic lines and non-transgenic plants; (C) The phenotype of GmNFYB17 after harvest; (D) Comparison of seed size among GmNFYB17 lines and CK; (E) The 100-seed weight of the transgenic lines and non-transgenic plants; (F) The diameter of transgenic and non-transgenic seeds (Adopted from Sun et al., 2022) 3 Methodology of GWAS in Soybean 3.1 Overview of GWAS and its relevance to soybean research When it comes to the study of soybean genes, GWAS has really been of great help nowadays. In essence, this technology involves identifying genetic differences among various soybean varieties to see which gene segments can affect the actual planting performance. For instance, some genes control when soybeans mature, while others are linked to the strength of disease resistance (Contreras-Soto et al., 2017). Interestingly, the same method can also be used to study yielt-related traits (Copley et al., 2018), which is much better than blind hybridization breeding in the past. In fact, as early as 2015, studies proved that GWAS could accurately locate the gene regions that control important agronomic traits of soybeans (Sonah et al., 2015). However, to be honest, although technology has advanced now, merely relying on GWAS to locate genes is not enough to truly cultivate ideal varieties. The subsequent verification work is what really requires effort. 3.2 GWAS workflow When it comes to conducting GWAS research on soybeans, choosing the right population type is crucial. Take the diversity group for example. This method of studying various genotypes together (Sonah et al., 2015) can indeed
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