ORIGINAL RESEARCH article
Front. Plant Sci.
Sec. Plant Abiotic Stress
This article is part of the Research TopicAbiotic Challenges and Symbiotic Dynamics in Agricultural EcosystemsView all articles
Decoding the Saline-Alkaline Tolerance Nexus in Soybean: A Dual-method Evaluation Model Coupled with Co-expression Networks Identifies Core Regulatory Genes
Provisionally accepted- 1High Latitude Crops Institute to Shanxi Academy, Shanxi Agricultural University, Datong, China
- 2Shanxi Agricultural University, Jinzhong, China
- 3Maize Research Institute, Shanxi Agricultural University, Xinzhou, China
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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. 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 co-expression network analysis (WGCNA) determined the gene modules related to physiological traits. 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.
Keywords: Saline-alkali, Soybean, Ranking model, WGCNA, candidate gene
Received: 05 Sep 2025; Accepted: 31 Oct 2025.
Copyright: © 2025 Fei, 雄辉, Mengjiao, Aijing and Baolong. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Xing  Baolong, ghsxingbaolong@163.com
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