! ! Legume Genomics and Genetics 2025, Vol.16, No.1, 1-10 http://cropscipublisher.com/index.php/lgg! ! 1! Systematic Review Open Access Mining Key Agronomic Traits through GWAS and Integrating Breeding Strategies for Soybean Chunxia Wu, Qishan Chen Modern Agricultural Research Center, Cuixi Academy of Biotechnology, Zhuji, 311800, Zhejiang, China Corresponding email: qishan.chen@cuixi.org Legume Genomics and Genetics, 2025 Vol.16, No.1 doi: 10.5376/lgg.2025.16.0001 Received: 11 Nov., 2024 Accepted: 21 Dec., 2024 Published: 05 Jan., 2025 Copyright © 2025 Wu and Chen, 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: Wu C.X., and Chen Q.S., 2025, Mining key agronomic traits through GWAS and integrating breeding strategies for soybean, Legume Genomics and Genetics, 16(1): 1-10 (doi: 10.5376/lgg.2025.16.0001) Abstract Soybean (Glycine max) is a very important crop and is cultivated in many places around the world. It is rich in protein and oil and is a common and important part of agriculture and food production. With the continuous progress of genomic research, scientists have also found more ways to improve soybeans. Among them, GWAS (Genome-wide Association Study) is a commonly used technique that can be employed to identify the locations of genes related to agronomic traits. This study introduces the basic concepts and main methods of GWAS, such as how to conduct genotyping, how to collect phenotypic data, and common statistical analysis approaches. All these contents are closely related to soybean research. Nowadays, GWAS has been used to discover many genes related to soybean yield, disease resistance and stress tolerance. These discoveries have provided many references for breeding and also accelerated the progress of breeding. However, there are also many challenges in the practical application of GWAS. For instance, there are significant differences in genetic background among different soybean varieties, and their phenotypes are also easily influenced by the environment. In addition, the interaction between genes (superiorality) also makes the analysis more complex. This study also takes the disease resistance of soybeans as an example, focusing on introducing the achievements of GWAS in improving disease-resistant varieties, especially its application in genetically modified soybeans and the benefits it brings. Looking to the future, there are still many areas where GWAS can be improved. For instance, multiple omics data can be combined, more powerful computing tools can be used, and the technology for trait collection can also be improved. All these practices will make GWAS more useful in soybean research. GWAS plays a very important role in soybean breeding. This research has laid a foundation for future genetic studies and provided technical support for the screening and improvement of high-quality soybean varieties. Keywords Soybean; Genome-wide association studies; Crop improvement; Genetic loci; Breeding programs 1 Introduction Soybean (Glycine max L.) is a major crop that is grown all over the world. Because it is rich in both protein and vegetable oil, it is widely used in many places. Soybeans are an important source of feed for livestock and aquaculture. They are also often used to extract oil and can be processed into various foods. Many people consume them in their daily diet. Soybeans were first grown in China and East Asia and have now spread all over the world. At present, the soybeans produced by countries in the Western Hemisphere account for 80% to 85% of the global total output (Anderson et al., 2019). Because soybeans have strong adaptability and high returns, researchers and farmers in many countries are striving to improve the varieties. Nowadays, soybeans have become one of the oil crops with the largest planting area in the world. In recent years, genomics has developed rapidly, and scientists have gained more and more understanding of the genes of soybeans. Techniques such as genome-wide association analysis (GWAS) have helped researchers identify many gene loci related to agronomic traits (Jiang, 2024). For instance, the appearance of soybean roots, the high yield, and the proportion of protein and oil in seeds are all related to certain specific genes (Kim et al., 2023a; Rani et al., 2023). These studies have identified many SNP (single nucleotide polymorphism) markers and some potential candidate genes. This information is very useful for subsequent precision breeding. Now, the research team is combining these genomic data with traditional breeding methods, hoping to breed new drought-tolerant and high-yield soybean varieties more quickly (Almeida-Silva et al., 2020).
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