Legume Genomics and Genetics 2025, Vol.16, No.1, 23-32 http://cropscipublisher.com/index.php/lgg 23 Research Insight Open Access Deciphering the Genetic Interactions That Control Soybean Agronomic Traits Shiying Yu Biotechnology Research Center, Cuixi Academy of Biotechnology, Zhuji, 311800, Zhejiang, China Corresponding email: shiying.yu@cuixi.org Legume Genomics and Genetics, 2025 Vol.16, No.1 doi: 10.5376/lgg.2025.16.0003 Received: 05 Dec., 2024 Accepted: 15 Jan., 2025 Published: 31 Jan., 2025 Copyright © 2025 Yu, This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Yu S.Y., 2025, Deciphering the genetic interactions that control soybean agronomic traits, Legume Genomics and Genetics, 16(1): 23-32 (doi: 10.5376/lgg.2025.16.0003) Abstract Soybeans are a crop of global significance, highly valued for their diverse applications in food, feed and industrial products. The productivity of soybeans is determined by complex agronomic traits, including yield, drought resistance, disease resistance and quality. Understanding the genetic interactions that regulate these traits is crucial for promoting soybean breeding programs. This study explored the genetic basis of these agronomic traits, with a focus on Mendelian genetics, quantitative trait loci (QTLs), and epigenetic interactions. Meanwhile, molecular mechanisms such as gene regulatory networks, transcription factors, and environmental interactions were studied, and these factors jointly affect trait expression. Through the advancements in genomics, high-throughput sequencing technology and bioinformatics platforms, an in-depth analysis of genetic interactions has been conducted. A case study on yield improvement demonstrated the identification and functional verification of cooperative gene interactions, highlighting their practical application in the cultivation of high-yield soybean varieties. Although there are still challenges in decoding polygenic traits and translating genetic insights into practice, this study highlights the potential of integrating multi-omics data and genome editing tools in enhancing the stress resistance and productivity of soybeans. This research provides a foundation for future soybean breeding innovation to meet global agricultural demands. Keywords Soybean; Genetic interactions; Agronomic traits; Genomics; Breeding strategies 1 Introduction When it comes to soybeans (Glycine max [L.] Merr.), although they may seem ordinary, you might not know how important they are. Whether it is making tofu or extracting oil, it is indispensable (Diers et al., 2018; Almeida-Silva et al., 2020). But then again, the demand for soybeans is increasing now (He et al., 2019) Not only humans eat it, but also animal feed is used, and it is widely used even in industry. Of course, the soybeans grown in different places vary quite a lot. So now everyone is trying to cultivate better varieties (Li et al., 2023; Rani et al., 2023b). In fact, perhaps no one paid attention to it in the early years, but the protein and fat content of soybeans is indeed astonishingly high, which is why it is so popular. When it comes to soybean yield, it's not just about how many pods are produced. You see, things like plant height, whether the root system grows well, and even the weight of each bean are directly related to how many soybeans can be harvested in the end (Rani et al., 2023a). Of course, these manifestations are not solely determined by genes. The location and weather conditions are also particularly important. Let's take flowering time as an example. The difference between early and late flowering can be significant, as well as the time it takes from planting to harvesting, including what we often refer to as "hundred grain weight", all of which secretly affect yield (Rahama et al., 2022). Many people may not have noticed, but the root system underground is actually crucial, especially in times of drought or poor soil conditions. Good root growth is necessary to absorb sufficient nutrients (Kim et al., 2023b). Those engaged in soybean breeding all know that merely looking at surface traits is not enough. The manifestations grown in the ground are actually the result of various genes "fighting" behind them-some genes cooperate with each other, while others undermine each other (Rani et al., 2023b). Nowadays, with advanced technology, detection methods like GWAS, combined with SNP chip technology, can help us identify those gene markers that control important traits (Kim et al., 2023a). However, to be honest, the performance of the same
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