Legume Genomics and Genetics 2025, Vol.16, No.1, 44-53 http://cropscipublisher.com/index.php/lgg 44 Research Insight Open Access Key Loci Identified by GWAS for Agronomic Traits in Soybean Xiaoxi Zhou, Tianxia Guo Institute of Life Sciences, Jiyang College, Zhejiang A&F University, Zhuji, 311800, Zhejiang, China Corresponding email: tianxia.guo@jicat.org Legume Genomics and Genetics, 2025 Vol.16, No.1 doi: 10.5376/lgg.2025.16.0005 Received: 01 Jan., 2025 Accepted: 12 Feb., 2025 Published: 27 Feb., 2025 Copyright © 2025 Zhou and Guo, 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: Zhou X.X., and Guo T.X., 2025, Key loci identified by GWAS for agronomic traits in soybean, Legume Genomics and Genetics, 16(1): 44-53 (doi: 10.5376/lgg.2025.16.0005) Abstract Soybean (Glycine max [L.] Merr.) holds an important position worldwide due to its high protein and oil content, and is a key source of human consumption and animal feed. However, soybean cultivation is confronted with the challenges of climate change and the need to increase yield and stress resistance. Genome-wide association studies (GWAS) are of great value in identifying key genetic loci associated with complex agronomic traits, including yield, stress resistance, nutritional quality and disease resistance. This review summarizes the progress made in soybean genomics through GWAS and elaborates on the loci and candidate genes that affect traits such as seed composition, plant height, and root development. Integrating the findings of GWAS into molecular breeding strategies such as marker-assisted selection (MAS) and genomic selection (GS) can promote the development of high-yield and climate-adapted soybean varieties. Furthermore, the combination of GWAS with advanced genomic tools and computational methods provides insights for future research. These research findings contribute to the sustainable improvement of soybean productivity to address the urgent need for global food sec。urity under environmental challenges Keywords Soybean; GWAS; Agronomic traits; Molecular Breeding; Stress tolerance 1 Introduction When it comes to soybeans (Glycine max [L.] Merr.), this thing really feeds a lot of people. Despite its small size, it contains a considerable amount of protein and fat. It is indispensable from edible oil to feed (Sonah et al., 2015; Kim et al., 2023). In fact, in places like Southeast Asia and Africa, soybeans have long been a traditional food and are widely used in industry. However, nowadays there are more and more places around the world that need soybeans (Rani et al., 2023), and the original output alone may not be sufficient. When it comes to this, increasing production and quality becomes particularly important - although exactly how to do it still depends on the actual situation. Growing soybeans is not that simple nowadays. The weather is getting more and more unpredictable, with droughts and floods alternating, yet the global demand for soybeans is still on the rise. When it comes to solutions, the key actually lies in the soybeans themselves - such as the components in the seeds, how tall the plants can grow, and how deep the roots are (Van et al., 2017; Kim et al., 2023). If these traits are improved well, perhaps more durable and nutrient-rich soybeans can be grown. Of course, relying solely on old methods for gradual breeding is definitely not enough (Rani et al., 2023). Nowadays, molecular breeding techniques are emphasized, although they may not be so easy to operate in practice. Nowadays, there is an interesting method for conducting soybean research called genome-wide Association studies (GWAS). To put it simply, it is to find the patterns of genetic variations in a large number of soybean samples. This technology is particularly good at discovering the small details that affect the growth and yield of soybeans, such as the gene loci that determine the protein level of seeds or the development degree of root systems (Sonah et al., 2015). However, GWAS alone may not be accurate enough. Therefore, researchers often combine it with other techniques - such as genotypic sequencing (GBS) or SNP chips (Almeida-Silva et al., 2020). Although the operation is rather complicated, it can indeed help the breeding work avoid many detours.
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