Xiaofei Tang , Yongguo Xue , Dan Cao , Xiaoyan Luan , Qi Liu , Zifei Zhu , Xinlei Liu

Soybean Research Institute, Heilongjiang Academy of Agricultural Science, Harbin, 150086, China
Author    Correspondence author
Legume Genomics and Genetics, 2024, Vol. 15, No. 6   doi: 10.5376/lgg.2024.15.0028
Received: 07 Nov., 2024    Accepted: 08 Dec., 2024    Published: 20 Dec., 2024

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.

Tang X.F., Xue Y.G., Cao D., Luan X.Y., Liu Q., Zhu Z.F., and Liu X.L., 2024, Marker-assisted selection strategies for drought tolerance in soybean and future perspectives, Legume Genomics and Genetics, 15(6): 291-302 (doi: 10.5376/lgg.2024.15.0028)

Soybean is a crucial crop for global food security, yet its growth and yield are highly susceptible to drought stress. This study reviews the application of marker-assisted selection (MAS) in breeding drought-tolerant soybean varieties, summarizing the identification and utilization of quantitative trait loci (QTL) and key candidate genes associated with drought tolerance. MAS enables the precise selection of drought tolerance traits using molecular markers, significantly shortening breeding cycles and enhancing the efficiency of drought-resistant variety development. The study finds that drought tolerance, a complex trait controlled by multiple genes and significantly affected by environmental factors, requires the integration of genomic selection and high-throughput genotyping technologies to improve MAS accuracy and applicability. The paper discusses potential future directions, including the integration of climate-resilient agricultural practices and emerging technologies in MAS, offering comprehensive theoretical and practical guidance for advancing drought-tolerant soybean breeding.

Marker-assisted selection; Drought tolerance; Soybean breeding; Quantitative trait loci; Genomic selection