Bioscience Evidence 2025, Vol.15, No.5, 237-248 http://bioscipublisher.com/index.php/be 242 2024) (Figure 2). Genomic selection (GS) uses genome-wide markers to predict breeding values and accelerate the screening speed of superior genotypes, and has been applied in disease resistance, stress resistance and quality improvement (Cao et al., 2022; Lin et al., 2022; Fang et al., 2023; Tian et al., 2025). Meanwhile, the combination of high-throughput genotyping and phenotypic techniques also enables molecular breeding to be faster and more accurate (Haidar et al., 2024). Figure 2 Multi-omics approaches for soybean molecular breeding (Adopted from Cao et al., 2022) 6.3 Genetic engineering: CRISPR/Cas9 examples, transgene approaches. Genetic engineering offers new ways to regulate the content of proteins and oils. Editing techniques such as CRISPR/Cas9 can precisely knockout or modify key genes (such as FAD2, PDHK, etc.), and new soybean varieties with high oleic acid, low linolenic acid and high protein have been obtained (Gupta and Manjaya, 2022; Rahman et al., 2022; Xu et al., 2022; Monfort et al., 2025). Transgenic methods (such as Agrobacter mediation and gene gun method) are widely used for herbicide resistance, pest resistance, stress resistance and nutritional quality improvement. Currently, more than 80% of the global planting area is transgenic soybeans (Li et al., 2017; Anderson et al., 2019; Rahman et al., 2022; Xu et al., 2022). However, transgenic and gene editing still face challenges such as low transformation efficiency, genotype dependence and regulatory issues (Gai et al., 2025). 6.4 Synthetic biology: engineering carbon flux pathways. Synthetic biology offers the possibility of simultaneously enhancing proteins and oils by modifying carbon metabolism pathways and optimizing the allocation of carbon and nitrogen. For instance, by regulating genes related to sugar transport, fatty acid synthesis and seed enrichment, the direction of carbon flow can be changed to enhance the nutritional and yield potential of seeds (Liu et al., 2020). In the future, by integrating multi-omics data and systems biology models, it is expected to promote the "design breeding" of soybean quality (Cao et al., 2022; Haidar et al., 2024; Tian et al., 2025). 7 Case Study: Functional Validation of Key Genes 7.1 Case study focus: example of a key gene such as GmWRI1a (oil regulator) or GmPDH1 (protein regulator) 7.1.1 Background: why this gene was prioritized GmSWEET10a is a gene closely related to the quality of soybean seeds. It affects oil content, protein and grain size. Whole-genome resequencing and population analysis revealed that this gene was strongly selected during the
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