Decoding the saline-alkaline tolerance nexus in soybean: a dual-method evaluation model coupled with co-expression networks identifies core regulatory genes.

Introduction: Soybean (Glycine max) growth is severely restricted by the high salt content in saline-alkali soils, resulting in substantial declines in both yield and quality. Enhancing soybean's tolerance to saline-alkali stress holds significant economic and ecological importance. However, current research on the regulatory mechanisms of soybean's response to such stress, especially when integrating physiological traits with transcriptomic analyses, remains inadequate. Methods and Results: In this study, seven physiological indicators of soybean cultivars showed significant differences between saline-alkali and normal conditions, and there were correlations among their rates of change. The salt tolerance rankings obtained by principal component analysis combined with the membership function value method were verified to be reliable by the technique for order preference by similarity to an ideal solution (TOPSIS). Transcriptome analysis identified 4,582 differentially expressed genes (DEGs), 39 of which were differentially expressed in all tissues and varieties. Weighted gene coexpression network analysis (WGCNA) determined the gene modules related to physiological traits. Discussion: Through comprehensive analysis, 13 core candidate genes were found, providing a basis for elucidating the molecular mechanisms of soybean's adaptation to saline-alkali conditions.