Dandan Huang

Hainan Institute of Biotechnology, Haikou, 570206, Hainan, China
Author    Correspondence author
Legume Genomics and Genetics, 2025, Vol. 16, No. 1   
Received: 22 Nov., 2024    Accepted: 03 Jan., 2025    Published: 18 Jan., 2025

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.

Genome wide association studies (GWAS), as a powerful genomic tool, have been widely used to analyze the genetic basis of drought resistance traits in soybean. By mining quantitative trait loci (QTLs) related to drought resistance, they provide important molecular markers for drought resistance breeding. This study introduces the application of GWAS in the research of drought resistance traits in soybeans, with a focus on analyzing the mapping of drought resistance QTLs, the mining of candidate genes, and their application in drought resistance breeding. At the same time, combining GWAS with other molecular breeding techniques such as marker assisted selection (MAS) and genome selection (GS), we have promoted the improvement of drought resistance traits and explored the potential of gene editing technology in enhancing soybean drought resistance. Research has found that GWAS has made significant progress in the study of soybean drought resistance, identifying multiple key QTLs that affect root development, water use efficiency (WUE), and metabolic pathways, and revealing the impact of gene environment interactions on drought resistance traits. Through gene functional analysis, candidate genes for drought resistance and their regulatory networks have been identified, providing a new direction for molecular breeding of drought resistant traits. GWAS has demonstrated strong potential in the study of drought resistant traits in soybeans, not only revealing complex genetic regulatory networks, but also providing valuable molecular tools for drought resistant breeding. In the future, by integrating new technologies such as big data, machine learning, and gene editing, precision breeding of drought resistant traits will be further optimized and promoted, providing more adaptable varieties for global soybean production.

Soybean; Drought resistance; Genome-wide association study (GWAS); Genomic selection; Gene editing