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Article

Integrated Multi-Omics Analysis Revealed the Synergistic Regulatory Mechanisms of Salt Tolerance in Soybean (Kefeng 1)

by
Yuan Yuan
1,
Lihua Zhu
1,
Biting Cao
1,
Jiaqi You
1,
Haijian Zhi
2,
Kai Li
2,
Weihong Gu
1,
Hongjuan Yang
1 and
Chaohan Li
1,*
1
Shanghai Key Laboratory of Protected Horticultural Technology, Protected Horticultural Research Institute, Shanghai Academy of Agricultural Sciences, Shanghai 201106, China
2
Soybean Research Institute & MARA National Center for Soybean Improvement & MARA Key Laboratory of Biology and Genetic Improvement of Soybean & State Innovation Platform for Integrated Production and Education in Soybean Bio-Breeding & State Key Laboratory for Crop Genetics and Germplasm Enhancement and Utilization & Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing 210095, China
*
Author to whom correspondence should be addressed.
Plants 2026, 15(4), 555; https://doi.org/10.3390/plants15040555
Submission received: 3 January 2026 / Revised: 30 January 2026 / Accepted: 3 February 2026 / Published: 10 February 2026
(This article belongs to the Special Issue Plant Challenges in Response to Salt and Water Stress, 2nd Edition)
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Abstract

Soil salinisation has become one of the major abiotic stresses limiting crop growth in the world. To enhance soybean productivity on saline lands, understanding its salt-stress response and underlying mechanisms is necessary. In this study, the salt-tolerant soybean Kefeng 1 and the salt-sensitive soybean Qihuang 1 were used to elucidate the synergistic regulatory networks underlying soybean salt tolerance. After 12 days of 150 mM NaCl treatment, both varieties were subjected to phenotypic evaluation, physiological measurements, and integrated transcriptomic and metabolomic analysis. The results showed that the salt tolerance in Kefeng 1 primarily originated from its root. Under salt stress, Kefeng 1 maintained Na+/K+ ion homeostasis by up-regulating Cation/H+ Exchanger 15 (CHX15) and Cation Exchanger 3 (CAX3), and down-regulating Cyclic Nucleotide-Gated Channel 13 (CNGC13). Furthermore, Kefeng 1 stabilised auxin (IAA) homeostasis by inhibiting IAA biosynthesis and regulating concentrations through PIN-FORMED 3 (PIN3)-mediated efflux. It also scavenged reactive oxygen species (ROS) by employing enhanced enzymatic antioxidant systems, specifically aldo-keto reductase 1 (AKR1), glutathione S-transferase (GST), and catalase (CAT), alongside non-enzymatic antioxidants like the isoflavone genistein. Gene–metabolite correlation network analysis identified Glyma.09G117900 (PIN3) and Glyma.19G244200 (AKR1) as two hub genes. These two genes were specifically up-regulated in Kefeng 1 root under NaCl stress, and the proteins they encoded played important roles in salt tolerance in Kefeng 1 root as described above. Accordingly, these two genes were identified as candidate genes for salt tolerance in Kefeng 1. This study offered a theoretical framework and genetic resources for developing salt-tolerant soybean cultivars.

1. Introduction

Global soil salinisation has become a major environmental stressor threatening food security. Statistics show that approximately 1.125 billion hectares of land worldwide are affected by salinity [1]. The Food and Agriculture Organization (FAO) of the United Nations estimates that over 800 million hectares of arable land are under salinity stress. This accounts for about 6% of the world’s total arable land [2]. Climate change and inappropriate irrigation methods exacerbate this issue. It is predicted that by 2050, half of the world’s arable land will degrade into sodium-rich soil. This could lead to a 30% loss of arable land within the next 25 years, posing a severe challenge to food production [2].
As an important oil and protein crop, soybean is usually susceptible to salt stress throughout its growing period [3]. Salt stress induces osmotic and ionic imbalances, which inhibit soybean growth, root nodule formation, and seed quality and yield [4]. Osmotic stress hinders the absorption of soil water and nutrients by the root. Ion homeostasis disorder leads to intracellular Na+ accumulation, K+ loss, and elevated levels of the second messenger Ca2+ [5,6]. In addition, salt stress can induce oxidative stress. This leads to the release of reactive oxygen species (ROS), which causes cell damage and metabolic disorders [2,7].
To mitigate salt stress, plants have evolved multiple defensive strategies. At the ion regulation level, the Salt-Overly Sensitive (SOS) complex activated by Ca2+ signalling, SOS3-SOS2, drives the plasma-membrane-localised SOS1 to expel excess intracellular Na+ [8]. Simultaneously, the vacuole-membrane-localised Na+/H+ antiporter (NHX) transports Na+ into the vacuole to reduce cytotoxicity [9]. Combined with the regulation of K+ uptake by Arabidopsis K+ Transporter 1 (AKT1) and High-affinity K+ Transporter 1 (HKT1), these measures jointly maintain the intracellular Na+/K+ ratio balance [10,11]. At the signal transduction level, high concentrations of Ca2+ activate Calcium-Dependent Protein Kinase (CDPK) and Mitogen-Activated Protein Kinase (MAPK) pathways [5,12,13]. These pathways, together with a multi-hormone crosstalk network centred on abscisic acid (ABA) and encompassing ethylene, salicylic acid (SA), jasmonic acid (JA), and brassinosteroids (BR), enable the precise regulation of downstream salt-tolerance-related genes [2,5,13]. In terms of root development, plants can also adjust their root system architecture (RSA) through phenotypic plasticity [14]. Root tips achieve salt-avoidance growth through auxin (IAA) redistribution and PIN-FORMED (PIN) protein regulation [14]. Under mild salt stress, lateral root development is promoted via the SOS3 pathway to expand the absorption area [14]. Under severe salt stress, lateral root growth is inhibited via the ABA pathway to optimise energy allocation [14]. Furthermore, plants reduce cell water potential by synthesising compatible solutes, such as proline, betaine, and soluble sugars, to promote water uptake [5,15]. They also employ enzymatic antioxidant systems (e.g., superoxide dismutase, SOD) and non-enzymatic antioxidant systems (e.g., flavonoids) to scavenge oxidative damage caused by ROS [2,5,7].
High-throughput sequencing technologies, including genomics, transcriptomics, and metabolomics, have become important tools for systematically elucidating plant salt-tolerance mechanisms. These technologies enable efficient identification of key genes, differentially expressed metabolites, and their regulatory networks. In this study, salt-tolerant soybean Kefeng 1 and salt-sensitive soybean Qihuang 1 were used as materials. The salt-tolerance mechanism in Kefeng 1 was explored through phenotypic, physiological index, and multi-omics combined analysis. The results showed that Kefeng 1 achieved salt tolerance primarily through its roots by integrating ion homeostasis, auxin-mediated growth regulation, and ROS scavenging. Two genes, Glyma.09G117900 (PIN3) and Glyma.19G244200 (AKR1), were identified as key candidates for driving these processes through auxin efflux and antioxidant defence.

2. Results

2.1. Plant Phenotypic Characteristics

After 12 days of 150 mM NaCl stress, the salt-sensitive soybean Qihuang 1 exhibited wrinkling and yellowing of its true leaves. In contrast, the salt-tolerant soybean Kefeng 1 displayed no obvious phenotypic changes in its true leaves (Figure 1A). After rehydration, damage to Qihuang 1 was irreversible, while Kefeng 1 maintained normal growth (Figure 1B). Statistical analysis showed that the root length of Kefeng 1 was significantly longer than that of Qihuang 1 after salt stress. No significant differences were found in plant height, node number, leaf width and leaf length between the two varieties under salt stress (Table 1). This suggested that the salt tolerance in Kefeng 1 might originate from its roots.

2.2. Na+ and K+ Content and Na+/K+ Ratio

The Na+/K+ ratio is a key indicator of plant salt tolerance [16]. An excessively high Na+/K+ ratio disrupts ion homeostasis and inhibits plant growth [17,18]. Figure 2A reveals that Na+ content in both the roots and leaves of the salt-treated groups (KN and QN) were significantly higher than those in their respective control groups (KC and QC). Notably, the Na+ content in KN root was significantly lower than that in QN root (p = 0.012). In KC and QC, Na+/K+ ratios in roots and leaves remained below 0.5. Under salt stress, the leaf Na+/K+ ratios in KN and QN increased to approximately 0.5. However, the root Na+/K+ ratios in KN and QN exceeded 1. Consistently, the Na+/K+ ratio in KN root was significantly lower than that in QN root (p = 0.012). These suggested that Kefeng 1 maintained superior ionic homeostasis under salt in its roots.

2.3. SOD, POD and CAT Activity

The activities of CAT, POD and SOD were measured in the roots and leaves of KN, KC, QN and QC. CAT and POD activities exhibited tissue variation, showing distinct activity levels between roots and leaves. CAT activity in the leaves of Kefeng 1 and Qihuang 1 was significantly higher than that in their roots, while POD activity displayed the opposite trend (Figure 2B). In the leaves, enzyme activities changed in response to stress. Compared with their respective KC and QC values, CAT activity in KN and QN leaves decreased, SOD activity increased, and POD activity showed no significant change (Figure 2B). In the roots, enzyme activities displayed variety-specific responses to stress. Compared with their respective KC and QC values, CAT activity increased in KN root but decreased in QN root, while SOD and POD activity decreased in both KN and QN roots (Figure 2B). It was observed that the reduction in SOD and POD activity was greater in QN root than that in KN root. This meant that compared with Qihuang 1, Kefeng 1 maintained more stable SOD and POD activities and enhanced CAT activity in its root.
Both phenotypic and physiological measurements results indicated that the superior salt tolerance in Kefeng 1 was associated with its root. Therefore, subsequent studies focused exclusively on the roots of the four experimental groups (KC, KN, QC, and QN).

2.4. Transcriptome Analysis

The roots of KC, KN, QC and QN were subjected to RNA sequencing. A total of 36,271,106–63,133,192 raw reads were generated. After filtering, 36,266,030–63,120,178 high-quality clean reads were obtained. Clean reads were mapped to the soybean reference genome Williams 82 (Glycine_max_v6.0). This yielded a mapping rate over 98.33%, indicating the reliability and completeness of the sequencing data (Table 2).
To validate the reliability of the transcriptomic data, qRT-PCR was performed on 11 selected genes. The results demonstrated that all 11 genes exhibited similar expression trends between qRT-PCR and RNA-seq datasets, thereby confirming the accuracy and reliability of the transcriptomic data (Figure S1).
DEGs were screened using thresholds of |log2FoldChange| ≥ 2 and padj < 0.05. A total of 3860 DEGs were identified in KNr vs. KCr (Kefeng 1 salt-treatment root vs. control root), and 4930 DEGs were detected in QNr vs. QCr (Qihuang 1 salt-treatment root vs. control root). To explore inter-varietal transcriptional differences, the two sets of DEGs were further compared. Genes with consistent up-regulation or down-regulation across both comparisons were excluded by applying a secondary threshold of |log2FoldChange| ≥ 1. This analysis identified 1183 candidate genes, including 418 DEGs unique to KNr vs. KCr, 735 DEGs unique to QNr vs. QCr, and 30 DEGs shared between the two comparisons (Table S2). Venn diagram and volcano plot analysis (Figure 3A,B) revealed three observations: QN vs. QC had a greater number of down-regulated genes than that in KNr vs. KCr, the gene with the highest up-regulation fold change was identified in KNr vs. KCr, and the gene with the lowest down-regulation fold change was found in QNr vs. QCr.
To elucidate the salt-tolerance mechanism in Kefeng 1, the 418 DEGs unique to KNr vs. KCr DEGs and the 30 shared DEGs with opposite expression trends between two comparisons were selected for heatmap and cluster analysis. Sample clustering showed that KNr was distinct from the KCr, QCr, and QNr groups, suggesting that gene expression patterns in KNr were different from those in other three groups (Figure 3C). Based on their expression profiles, these 448 genes were grouped into four clusters (Figure 3D). Genes in clusters 2, 3, and 4 displayed KNr-specific expression patterns. This suggested that these genes were related to the salt-tolerance response in Kefeng 1. After excluding cluster 1, 432 core DEGs were identified for further study.
The 432 core DEGs showed significant Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment in six pathways associated with root development and stress tolerance (p < 0.05, Figure 3E), including plant hormone signal transduction, flavonoid biosynthesis, glycosphingolipid biosynthesis (lacto and neolacto series), cutin/suberin/wax biosynthesis, zeatin biosynthesis, and diterpenoid biosynthesis. The plant hormone signal transduction pathway contained the largest number of enriched DEGs, primarily IAA-related genes. Heatmap analysis showed that AUX/IAA (Glyma.10G031900) and GH3 genes (Glyma.01G190600, Glyma.12G197800) were up-regulated in KNr vs. KCr (Figure 3F). These genes repressed IAA signalling. Conversely, SAUR (Glyma.09g222200, Glyma.09g222300, Glyma.17G046200) and AUX/LAX genes (Glyma.04g004800), which promoted IAA biosynthesis and transport, were down-regulated in KNr vs. KCr (Figure 3F). The zeatin and diterpenoid biosynthesis pathways corresponded to cytokinin (CK) and GA metabolic processes, respectively. The GA catabolic gene GA2ox4 (Glyma.07g236100) was up-regulated in KNr vs. KCr, while the biosynthetic gene GA3ox1 (Glyma.03g33800) was down-regulated (Figure 3F). Similarly, the CK catabolic gene CKX6 (Glyma.17g054600) was up-regulated in KNr vs. KCr, whereas the biosynthetic gene IPT3 (Glyma.03g151800) was down-regulated (Figure 3F). Furthermore, genes associated with cell wall reinforcement and flavonoid biosynthesis, including FAR2 (Glyma.02g69100), CCoAOMT (Glyma.08g030400), and CYP450 (Glyma.17g077700), were up-regulated (Figure 3F). Collectively, these findings suggested that Kefeng 1 might achieve salt tolerance by reducing IAA, GA, and CK levels while simultaneously enhancing cell wall protection and antioxidant capacity.

2.5. Plant Hormone Content

The total content of IAA and ABA in roots of KC, KN, QC, and QN were determined via LC-MS/MS. As shown in Table 3, IAA content was higher in KNr and QNr than that in KCr and QCr, while no significant difference in ABA content was observed among the four groups. Notably, the IAA content in QNr was four times higher than that in KNr. These results implied that salt stress induced IAA accumulation in both varieties, but Kefeng 1 maintained better IAA homeostasis than Qihuang 1 in its roots. This finding was consistent with the transcriptomic analysis results.

2.6. Metabolomics Analysis

Metabolites in root samples from KC, KN, QC, and QN were identified using LC-MS. A total of 1946 metabolites were obtained. Principal component analysis (PCA, Figure 4A) revealed that principal component (PC) 1 and PC2 contributed 18.9% and 18.1% in cationic metabolites and 22.6% and 20% in anionic metabolites, respectively. Three biological replicates in the same sample cluster closely together in Figure 4A. This indicates that the signal detection was stable and the data was reliable. Figure 4A also shows that the four groups exhibited clear separation in both cationic and anionic metabolite profiles. This points to significant differences in metabolites among KNr, KCr, QCr, and QNr.
DAMs were screened using thresholds of VIP > 1, |log2FoldChange| ≥ 1, and p < 0.05. A total of 399 DAMs were identified in KNr vs. KCr, and 311 DAMs were detected in QNr vs. QCr. To explore inter-varietal metabolites differences, the two sets of DAMs were further compared. Metabolites consistently up-accumulated or down-accumulated across both comparisons were excluded with a secondary threshold of |log2FoldChange| ≥ 1. A total of 351 DAMs were yielded. Of these, 331 DAMs were unique to KN vs. KC and 63 DAMs were unique to QN vs. QC, with 43 DAMs shared between them (Table S3). Unlike the transcriptomic results, both the total number of DAMs and the number of down-accumulated DAMs were higher in KNr vs. KCr than that in QNr vs. QCr (Figure 4B).
A total of 288 unique DAMs from KNr vs. KCr and 43 shared DAMs with opposing expression trends between two comparisons were selected for heatmap and cluster analysis. The results (Figure 4C) showed that KN and QN clustered closely, as did KC and QC. This indicated that salt stress was the main factor driving differences in metabolites. It also suggested that the two varieties exhibited distinct metabolic responses to salt stress. Cluster analysis grouped 331 DAMs into five clusters (Figure 4D). Metabolites in clusters 1, 2, and 5 showed significantly different accumulation patterns in KNr compared with the other three groups. This meant that these metabolites were associated with the salt-tolerance response in Kefeng 1. After excluding clusters 3 and 4, 238 core DAMs were retained for further study.
A total of 238 core DAMs were classified into 10 categories based on chemical taxonomy of metabolites (Figure 4E, Table S3): phenylpropanoids and polyketides (56), organic heterocyclic compounds (41), lipids and lipid-like molecules (37), organic acids and derivatives (30), benzene and substituted derivatives (24), alkaloids and derivatives (13), organic nitrogen compounds (12), organic oxygen compounds (10), nucleosides, nucleotides, and analogues (3), and other compounds (24). Within the phenylpropanoids and polyketides, the number of flavonoids was the highest, accounting for 69.64% (39 compounds). Although isoflavonoids did not constitute the largest subclass of flavonoids in 238 core DAMs, they represented the majority of up-accumulated flavonoids (Figure 4F). Specifically, 57.1% of isoflavonoids exhibited increased accumulation in KNr vs. KCr, whereas the proportion of up-accumulated flavone DAMs was only 25% (Figure 4F). Furthermore, the accumulation levels of these up-accumulated isoflavonoids were among the highest of all flavonoids in KNr (Figure 4F). This implied that the isoflavonoid biosynthesis pathway in Kefeng 1 root was significantly activated under salt stress. Notably, the amino acids and their derivatives exhibited lower accumulation in KNr than that in the other three groups, with the exception of homoglutathione (MP14921) (Figure 4F). These changes in amino acid metabolism potentially reflected energy metabolism reprogramming under salt stress.
Among the top 20 KEGG-enriched pathways of 238 DAMs (Figure 4G), the biosynthesis of various plant secondary metabolites ranked first with the lowest p-value, indicating that Kefeng 1 responded to salt stress by enhancing the biosynthesis of secondary metabolites in its root. The subsequent three pathways in the top 20 were all related to tryptophan, including tryptophan metabolism, indole alkaloid biosynthesis, and aminoacyl-tRNA biosynthesis. This suggested that tryptophan played an important role in Kefeng 1’s salt-tolerance response. The fifth enriched pathway was isoflavonoid biosynthesis, further supporting the conclusion that the isoflavonoid biosynthesis pathway in Kefeng 1 root was activated under salt stress.

2.7. Combined Transcriptome and Metabolome Analysis

A total of 432 core DEGs and 238 core DAMs were enriched in 34 and 43 KEGG pathways, respectively. Among these, 13 pathways were co-enriched at both the transcriptional and metabolic levels (Figure 5A). These co-enriched pathways were classified into three primary categories (Table S4): secondary-metabolism- and defence-associated pathways, amino-acid- and sulphur-metabolism-related pathways, and primary-metabolism- and transport-related pathways. Amino-acid-related pathways were the most numerous, followed by flavonoid-related pathways. Notably, the ABC transporter pathway contained the highest number of enriched DAMs. These findings suggested that amino acids, flavonoids, and ABC transporters played important roles in the salt-tolerance response in Kefeng 1 root.
Canonical correlation analysis (CCorA) was performed to investigate associations between all transcriptome and metabolome datasets. The loading plot revealed that the angles between the loading vectors representing each principal component in the transcriptome and metabolome were all less than 90° (Figure 5B). This indicated a strong positive correlation and a synergistic regulatory trend between the two omics datasets across these principal component dimensions. For the same sample, transcriptomic and metabolomic scores were closely in the ordination plot (Figure 5C), indicating similar variation trends between the transcriptome and metabolome within the same sample.
Pearson and Spearman correlation coefficients were calculated for the 432 core DEGs and 238 core DAMs (p < 0.05). A gene–metabolite correlation network was constructed using the top 100 highly correlated pairs, all of which exhibited absolute correlation coefficients exceeding 0.993 (Figure 5D, Table S5). This implied extremely strong and significant correlations between these DEGs and DAMs. These 100 pairs involved 20 DEGs and 49 DAMs. Within the gene set, only Glyma.12g092300 was down-regulated in KNr vs. KCr, while the others were significantly up-regulated. These genes cover many stress-related processes, including defence responses, substance transport, and signal transduction. It is worth noting that Glyma.09G117900 (PIN3) and Glyma.19G244200 (AKR1) exhibited extremely high connectivity, correlating with 19 and 18 DAMs, respectively (Figure 5D). This meant that they were hub genes, which played critical regulatory roles in the network. Furthermore, their expression was specifically up-regulated in Kefeng 1 root under salt stress (Figure S1). Therefore, Glyma.09G117900 and Glyma.19G244200 were identified as candidate salt-tolerance genes in Kefeng 1.

3. Discussion

3.1. Root Length Response to Salt Stress in Kefeng 1

RSA responses to salt stress are species-specific and dose-dependent [19]. In Arabidopsis thaliana [20], barley [21], wheat [22], and maize [23], salinity levels up to 150 mM NaCl reduced the rate of taproot elongation. Conversely, moderate salinity (25–100 mM NaCl) promoted taproot growth in cotton seedlings [24]. Populus euphratica similarly exhibited increased root length at 200 mM NaCl, while growth was inhibited at 400 mM NaCl [25]. In this study, after 12 days of 150 mM NaCl treatment, the root length of the salt-tolerant soybean Kefeng 1 was significantly longer than that of the salt-sensitive Qihuang 1 and both their control groups (Table 1). These results suggested that Kefeng 1 possessed a higher salt-tolerance threshold, enabling it to maintain a growth advantage under saline conditions.

3.2. Ion Homeostasis Effects on Salt Tolerance in Kefeng 1

In high-salt environments, the surge in intracellular Na+ concentration leads to severe ion toxicity. To maintain cytoplasmic ion homeostasis, plants usually inhibit Na+ influx and enhance the antiporter-mediated Na+ efflux [26]. Among the 432 core DEGs identified in this study, three genes were closely associated with ion homeostasis (Table S2): Glyma.06G154201 (CHX15), Glyma.18G200500 (CAX3), and Glyma.16G025400 (CNGC13). CHX belongs to the cation/H+ antiporter family (CPA2) [27], which regulates intracellular ion composition and pH via K+/Na+ and H+ exchange [28,29]. CAX functions as an H+-dependent transporter of Ca2+ and other metal ions [30]. Overexpression of CAX3 in Arabidopsis had been shown to increase Ca2+ levels and activate antioxidant enzymes [31]. Cyclic nucleotide-gated channels (CNGCs) are non-specific cation channels that are involved in the uptake of ions such as Na+, K+, and Ca2+ [32]. According to the transcriptome data, CHX15 and CAX3 were up-regulated in KNr vs. KCr, whereas CNGC13 was down-regulated. And no significant differences in the expression of these genes were detected in QNr vs. QCr. These findings suggested that under 150 mM NaCl stress, Kefeng 1 maintained Na+ and K+ homeostasis through the up-regulation of CHX15 and CAX3 compared to Qihuang 1, thereby optimising Ca2+-mediated signalling and antioxidant systems. Simultaneously, the inhibition of CNGC13 served to restrict non-selective Na+ influx at the point of entry. This coordinated regulation suggested that Kefeng 1 possessed more efficient Na+ exclusion or vacuolar sequestration mechanisms, which might have alleviated the inhibition of root cell expansion and division caused by Na+ toxicity [33]. This spatial regulation potentially explained the sustained primary root elongation in Kefeng 1, whereas Qihuang 1 might have entered growth arrest differentiation due to ion imbalance.
SOS and NHX genes are widely recognised as pivotal for maintaining cellular Na+ homeostasis. However, in this study, no differential expression of SOS genes was detected in the transcriptomic data of either Kefeng 1 or Qihuang 1, suggesting that both varieties might have bypassed the SOS pathway after 12 days of salt stress. In contrast, HKT genes were significantly up-regulated in both genotypes, indicating their potential dominance in ion regulation during this period. Furthermore, most NHX genes exhibited no significant change or were even down-regulated. Notably, although one NHX gene (Glyma.08G092000) only showed up-regulation in Kefeng 1, it was excluded from the core DEG list as its expression level fell below the pre-defined statistical threshold. These results suggested that after 12 days of 150 mM NaCl stress, neither variety relied primarily on the SOS pathway to maintain ionic homeostasis.

3.3. Auxin Homeostasis Effects on Salt Tolerance in Kefeng 1

The IAA content (Table 2) demonstrated that salt stress induced IAA accumulation in roots of both Kefeng 1 and Qihuang 1. However, Kefeng 1 exhibited stronger homeostatic regulatory capacity, maintaining IAA content only one-fourth of that in Qihuang 1 (Table 2). In plants, IAA biosynthesis predominantly proceeds via the tryptophan (Trp)-dependent pathway [34]. Metabolomic KEGG pathway enrichment analysis revealed that tryptophan metabolism played a pivotal role in the salt-tolerance response of Kefeng 1 (Figure 4G). Notably, tryptophan serves as both a core precursor for IAA and a starting point for the biosynthesis of various defence substances [35]. β-tryptophan synthase (TSB) catalyses the condensation of indole and serine to produce tryptophan (Figure 6A) [36]. Subsequently, members of the tryptophan aminotransferase of Arabidopsis 1 (TAA1) family convert tryptophan into indole-3-pyruvate (IPA), which is finally converted into IAA by YUCCA (YUC)-family proteins [37,38]. After KEGG analysis, five amino-acid-related pathways are co-enriched among 432 core DEGs and 238 core DAMs. These amino-acid-related pathways involved five DEGs and seven DAMs. Two DEGs, Glyma.11G003500 (TSB2) and Glyma.02G037600 (TAA1), were directly related to tryptophan and IAA biosynthesis. Both genes were significantly up-regulated in KNr vs. KCr. And no significant differences in the expression of these two genes were detected in QNr vs. QCr. It was interesting that tryptophan accumulation was reduced in KNr vs. KCr, whereas it showed a slight increase in QNr vs. QCr. Furthermore, the intermediate IPA was not detected in DAMs (Table S4). This suggested that, unlike Qihuang 1, while Kefeng 1 enhanced its tryptophan biosynthetic potential under salt stress, the resulting products were rapidly consumed or diverted into downstream non-IAA biosynthetic pathways.
Regarding IAA signalling and transport, previous studies have identified Aux/IAA, GH3, and SAUR as key auxin-responsive genes. Aux/IAA proteins negatively regulate IAA signalling by dimerising with auxin response factors (ARFs) in the nucleus, thereby inhibiting the ARF-mediated transcription of downstream genes [34,39,40,41]. GH3 family proteins regulate free-IAA levels by catalysing its conjugation to amino acids [34,42,43]. The functions of SAUR family members are species-specific and diverse, primarily regulating root development via modulation of cell elongation [44,45,46]. Intercellular polar IAA transport further relies on three protein families: AUX1/LAX (influx), PIN (efflux), and ABCB/PGP (bidirectional transport) [34,47,48,49,50]. In this study, eight of the nine DEGs enriched in plant hormone signal transduction pathways were associated with the IAA pathway, including Aux/IAA, Aux/LAX, GH3, and SAURs (Figure 3). In KNr vs. KCr, Aux/IAA and GH3 were up-regulated, while Aux/LAX and SAURs were down-regulated. In contrast, these genes showed no significant differences in QNr vs. QCr, or exhibited expression trends in QNr vs. QCr entirely opposite to those observed in the KNr vs. KCr comparison. Notably, one of the two hub genes identified within the gene–metabolite correlation network was Glyma.09G117900, which encoded the IAA efflux protein PIN3. This gene was only up-regulated in KNr vs. KCr and associated with 19 DAMs (Figure S1). Collectively, these expression patterns indicated that Kefeng 1 maintained stable cytoplasmic IAA level and potentially re-established the required auxin gradients in the root by synergistically inhibiting signalling responses and promoting IAA efflux (Figure 6A). This regulatory capacity might have enabled Kefeng 1 to exhibit “salt-avoidance growth”, allowing the plant to escape high-salinity zones by adjusting its growth direction or maintaining continuous elongation. This potentially represented another key factor contributing to the longer primary roots observed in Kefeng 1 compared to Qihuang 1.
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Figure 6. Auxin (IAA) and isoflavone biosynthetic pathways (within the pathway diagram, embedded heatmaps use geometric symbols to represent expression patterns or accumulation patterns. QCr: Qihuang 1 root cultured with 1/2 Hoagland’s solution; QNr: Qihuang 1 root cultured with 1/2 Hoagland’s solution supplemented with 150 mM NaCl; KCr: Kefeng 1 root cultured with 1/2 Hoagland’s solution; KNr: Kefeng 1 root cultured with 1/2 Hoagland’s solution supplemented with 150 mM NaCl). (A) Molecular model of cellular auxin signalling pathways (modified from Naser & Shani, 2016 [34]). (TBS, β-tryptophan synthase; TAA, tryptophan aminotransferase of Arabidopsis; IPA, indole-3-pyruvate; YUC, YUCCA flavin monooxygenases; AUX/LAX, auxin-resistant 1/like-aux1; ARFs, auxin response factors; SCF-TIR1/AFB, SKP1-CUL1-F-box protein complex; PIN, PIN-FORMED; AUX/IAA, auxin/indole-3-acetic acid; GH3, grette hagen 3). (B) Isoflavone biosynthetic pathway (modified from Uchida, K. et al., 2020 [51]). (4CL, 4-coumarate-CoA ligase; CHR, chalcone reductase; CHS: chalcone synthase; CH: chalcone isomerase; IFS: isoflavone synthase; HID: 2-hydroxyisoflavone dehydratase; F6H: flavonoid 6-hydroxylase; OMT: O-methyltransferase; IF7GT, isoflavone 7-O-glucosyltransferase; IF7MaT, isoflavone 7-O-glucoside 6″-O-malonyltransfrease; ICHG, isoflavone-conjugate-hydrolysing beta-glucosidase).
Figure 6. Auxin (IAA) and isoflavone biosynthetic pathways (within the pathway diagram, embedded heatmaps use geometric symbols to represent expression patterns or accumulation patterns. QCr: Qihuang 1 root cultured with 1/2 Hoagland’s solution; QNr: Qihuang 1 root cultured with 1/2 Hoagland’s solution supplemented with 150 mM NaCl; KCr: Kefeng 1 root cultured with 1/2 Hoagland’s solution; KNr: Kefeng 1 root cultured with 1/2 Hoagland’s solution supplemented with 150 mM NaCl). (A) Molecular model of cellular auxin signalling pathways (modified from Naser & Shani, 2016 [34]). (TBS, β-tryptophan synthase; TAA, tryptophan aminotransferase of Arabidopsis; IPA, indole-3-pyruvate; YUC, YUCCA flavin monooxygenases; AUX/LAX, auxin-resistant 1/like-aux1; ARFs, auxin response factors; SCF-TIR1/AFB, SKP1-CUL1-F-box protein complex; PIN, PIN-FORMED; AUX/IAA, auxin/indole-3-acetic acid; GH3, grette hagen 3). (B) Isoflavone biosynthetic pathway (modified from Uchida, K. et al., 2020 [51]). (4CL, 4-coumarate-CoA ligase; CHR, chalcone reductase; CHS: chalcone synthase; CH: chalcone isomerase; IFS: isoflavone synthase; HID: 2-hydroxyisoflavone dehydratase; F6H: flavonoid 6-hydroxylase; OMT: O-methyltransferase; IF7GT, isoflavone 7-O-glucosyltransferase; IF7MaT, isoflavone 7-O-glucoside 6″-O-malonyltransfrease; ICHG, isoflavone-conjugate-hydrolysing beta-glucosidase).
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3.4. ROS Scavenging System Effects on Salt Tolerance in Kefeng 1

Abiotic stresses trigger the accumulation of ROS in plants, including H2O2, 1O2, O2−·, and ·OH [52]. These highly reactive molecules can cause oxidative damage, disrupting normal plant physiological metabolism [52]. To mitigate these effects, plants employ the synergistic action of enzymatic and non-enzymatic antioxidant systems.
Figure 2A shows that under salt stress, Kefeng 1 root maintained greater stability in SOD and POD activities relative to Qihuang 1, while also exhibiting enhanced CAT activity.
The other of the two hub genes identified within the gene–metabolite correlation network was Glyma.19G244200, which encoded an aldo/keto reductase (AKR1) (Figure 5B). This gene was only up-regulated in KNr vs. KCr and associated with 18 DAMs (Figure 5B and Figure S1). AKRs are NAD(P)H-dependent oxidoreductases involved in diverse biological processes [53]. Usually, AKRs catalyse the reduction of carbonyl-containing compounds, such as ketones and aldehydes, into their corresponding alcohols via an NADPH-dependent mechanism [53,54]. This process effectively reduces the accumulation of toxic metabolic byproducts. Additionally, Glyma.05G161300, which encoded a glutathione S-transferase (GST), was also found in the gene–metabolite correlation network and was specifically up-regulated in KNs vs. KCs (Figure 5B, Table S2). GSTs are important detoxification enzymes highly inducible under various stress conditions [55]. They mainly catalyse the covalent conjugation of reduced glutathione (GSH) to harmful electrophilic substrates [55,56,57]. This results in soluble conjugates that facilitate free-radical scavenging and the maintenance of cellular homeostasis. Notably, GSH level is extremely low in soybean; instead, homoglutathione (hGSH) typically fulfils analogous physiological functions [58]. In this study, hGSH was the only amino acid derivative of 238 core DAMs to show increased accumulation in KNs vs. KCs (Figure 4F), whereas no such accumulation occurred in QNs vs. QCs. This aligned with the specifically up-regulated expression of GST in KNr vs. KCr and confirmed the activation of this detoxification pathway in Kefeng 1 under salt stress, a response that was absent in Qihuang 1.
Non-enzymatic antioxidants in plants primarily include flavonoids, α-tocopherol, ascorbic acid, glutathione, and carotenoids [59]. This study found that salt stress significantly activated the isoflavonoid biosynthetic pathway in Kefeng 1 root. As a subclass of flavonoids, isoflavonoids are predominantly found in legumes and play a critical role in combating stress-induced ROS. Their involvement in various abiotic stress responses has been documented in previous studies [60,61,62]. As secondary metabolites, isoflavonoids are derived from the phenylpropanoid pathway. Chalcone synthase (CHS) first catalyses the synthesis of naringenin chalcone, and also catalyses isoliquiritigenin with chalcone reductase (CHR) [63]. Then, naringenin chalcone and isoliquiritigenin are converted by chalcone isomerase (CHI) into naringenin and liquiritigenin [63,64]. Subsequently, enzymes such as isoflavone synthase (IFS) [65,66] and 2-hydroxyisoflavone dehydratase (HID) [67] facilitate the production of isoflavone aglycones, including genistein and daidzein [68]. Glycitein aglycone is synthesised from liquiritigenin by flavonoid 6-hydroxylase (F6H, a member of the cytochrome P450 family) [69,70], IFS, HID, and O-methyltransferase (OMT) [51]. These aglycones are further modified by glycosyltransferases and malonyltransferases to form glycosides and malonyl glycosides [71,72]. Regarding transport, isoflavone aglycones can be directly exported to the apoplast via ABC transporters [73]. In contrast, malonyl glucosides are sequestered in the vacuole by MATE proteins, later released into the intercellular space through ABC transporters, and finally hydrolysed back into aglycones by β-glucosidase (ICHG) [73]. Transcriptomic analysis revealed that, compared to Qihuang 1, key isoflavonoid biosynthetic genes, including IFS, HID, and F6H, were significantly up-regulated in KNr vs. KCr (Figure 6B). Correspondingly, metabolomic data showed a reduction in liquiritigenin and a significant increase in genistein and glycitein levels in KNr vs. KCr, while malonylgenistin content decreased (Figure 6B). In contrast, while a reduction in liquiritigenin was also observed in QNr vs. QCr, the levels of genistein and glycitein in QNr remained unchanged relative to QCr. Given that genistein, daidzein, and glycitein are known ROS scavengers, and that genistein possesses the strongest antioxidant and growth-promoting properties [74], it was therefore speculated that Kefeng 1 preferentially allocates metabolic resources toward isoflavone aglycone biosynthesis, especially genistein, to facilitate ROS scavenging under salt stress. Furthermore, the specific increased accumulation of other antioxidants in KNr vs. KCr, such as resveratrol, cis-resveratrol, and phloridzin (Table S3), likely worked synergistically with isoflavonoids to maintain cellular redox homeostasis in Kefeng 1.
In summary, compared to Qihuang 1, both the enzymatic and non-enzymatic antioxidant systems were more robustly activated in Kefeng 1 to facilitate ROS scavenging. Given that ROS and peroxidases triggered the cross-linking of phenolic compounds and glycoproteins within cell walls, leading to wall hardening [75], the reduction in ROS might have mitigated this process. This mitigation might stabilise root physiology in Kefeng 1, underpinning the plant’s overall salt tolerance.
Notably, while the accumulation of isoflavonoids, such as genistein, enhanced salt-stress resilience in Kefeng 1, these compounds were also associated with increased bitterness and astringency in soy-based products. Future breeding programmes required a balance between salt-tolerant breeding and seed palatability.
Another point to note was that the ABC transport pathway was co-enriched at both the transcriptional and metabolic levels. It contained an ABCB/PGP protein-encoding gene, Glyma.13G119000 (GmABCB7) [76]. This gene was only up-regulated in KNr vs. KCr and also identified in the gene–metabolite correlation network. All above, these suggested that GmABCB7 contributes to salt tolerance in Kefeng 1. ABCB/PGP transporters are a subfamily of ABC transporters responsible for polar auxin transport and the translocation of certain secondary metabolites (e.g., trans-resveratrol) [50,77]. However, their function in soybean was unclear. Therefore, GmABCB7 may coordinate with PIN3 to regulate IAA homeostasis. Alternatively, it may participate in the transport of flavonoids, such as trans-resveratrol or genistein.

4. Materials and Methods

4.1. Plant Material, Growth Conditions and Stress Treatment

Seeds of Kefeng 1 and Qihuang 1 were planted in vermiculite substrate. They were cultured in an artificial climate incubator. The growth conditions were maintained at a photoperiod of 16 h light (26 °C) and 8 h dark (22 °C), with illumination provided by LED lamps at a light intensity of 30,000 lux. Stress treatment was initiated immediately after the true leaves fully unfolded. The control group was irrigated with 1/2 Hoagland’s solution. The reagents for Hoagland’s solution formulation were purchased from Sinopharm Chemical Reagent Co., Ltd. (Shanghai, China). The treatment group was irrigated with 1/2 Hoagland’s solution containing 150 mM NaCl (Sinopharm, Shanghai, China). The control group of Kefeng 1 was recorded as KC. The treatment group of Kefeng 1 was recorded as KN. The control group of Qihuang 1 was recorded as QC. The treatment group of Qihuang 1 was recorded as QN. Roots and leaves of these four groups were collected after 12 days of treatment, as this time point marked the onset of significant phenotypic divergence between the two varieties. Samples were snap-frozen in liquid nitrogen and stored at −80 °C (DW-86L626, Haier Biomedical, Qingdao, China). Kefeng 1 and Qihuang 1 were provided by the National Center for Soybean Improvement, Nanjing, China.
The plants were irrigated using a bottom-watering method: the pots were placed in large containers filled with the treatment solution for 2 h daily, after which they were transferred to dry trays. For the rehydration assay, irrigation was suspended after 10 days of salt treatment. After 2 days, the plants were re-watered with 1/2 Hoagland’s solution. Phenotypic observations were then recorded after an additional 2-day recovery period.

4.2. Assessment of Phenotypic Traits

To evaluate the growth performance of Kefeng 1 and Qihuang 1 under control (KC, QC) and salt-stress (KN, QN) conditions, several phenotypic traits were measured. Plant height and root length were defined as the vertical lengths of the aerial part and the underground portion, respectively. The number of nodes was determined by counting upward from the true leaf node. Leaf width and leaf length were measured at the widest and longest points of the first fully expanded trifoliate leaf.

4.3. Determination of Na+ and K+ Content

The total content of Na+ and K+ in roots and leaves of KC, KN, QC, and QN were determined by microwave digestion–ICP-MS. Ground sample was dried at 105 °C to a constant weight. Then, 0.1 g (accurately to 0.0001 g, PTX-FA210, Huazhi Scientific and Technological Co., Ltd., Fujian, China) of the dried sample was transferred into a polytetrafluoroethylene microwave digestion vessel. Samples were moistened with distilled water and mixed with 5 mL of 65% nitric acid (HNO3, Merck-Millipore, Burlington, MA, USA). After standing for 1 h, 1 mL of 30% hydrogen peroxide (H2O2, Sinopharm, Shanghai, China) was added and mixed thoroughly. The digestion vessel was then sealed and placed in a microwave digester (TANK, Shanghai Sineo Microwave Chemistry Technology Co., Ltd., Shanghai, China) for digestion. After digestion, the sample was transferred to an acid-removing apparatus (TK 24, Shanghai Sineo Microwave Chemistry Technology Co., Ltd., Shanghai, China). Once the residual liquid volume was reduced to the size of a soybean seed, it was then diluted to a final volume of 50 mL with distilled water and filtered through a 0.22 μm membrane. Na+ and K+ content were determined using Inductively Coupled Plasma Mass Spectrometry (ICP-MS, NexION 1000G, PerkinElmer, Waltham, MA, USA). The element content (mg/kg dry weight) was calculated as
C o n t e n t = C × V W
where C is the element content in the solution (μg/L), V is the extraction volume (L), and W is the sample mass (g).

4.4. Determination of SOD, POD and CAT Activity

The activities of SOD (EC 1.15.1.1), peroxidase (POD, EC 1.11.1.7), and catalase (CAT, EC 1.11.1.6) in roots and leaves of KC, KN, QC, and QN were determined via Enzyme-Linked Immunosorbent Assay (ELISA). The ELISA kits were purchased from Shanghai Enzyme-linked Biotechnology Co., Ltd. (Shanghai, China). Absorbance was measured using a microplate reader (Infinite 200 Pro M Nano, Tecan Group Ltd., Männedorf, Switzerland). The specific procedures were strictly performed according to the kit instructions.

4.5. Transcriptome

Root samples from KC, KN, QC, and QN were sent to Personalbio (Shanghai) Co., Ltd. (Shanghai, China) for RNA-seq. Total RNA was extracted using TRIzol reagent (Orileaf, Shanghai, China). RNA purity and integrity were assessed using NanoDrop 2000 (Thermo Fisher Scientific, Wilmington, DE, USA) and Agilent 2100 (Agilent Technologies, Santa Clara, CA, USA) equipment, respectively. High-quality RNA was used for library construction with the NEBNext Ultra II kit (New England Biolabs Inc., Ipswich, MA, USA). RNA sequencing was performed on the NovaSeq platform (Illumina, San Diego, CA, USA) in paired-end 150 bp (PE150) mode. Raw data were processed using FastP software (0.22.0, Open-source, Shenzhen, China/Global) to obtain clean reads. These clean reads were aligned with the soybean reference genome (https://phytozome-next.jgi.doe.gov/info/Gmax_Wm82_a6_v1 (23 April 2025)) using Hisat2 software (v2.1.0, Johns Hopkins University, Baltimore, MD, USA). Gene read counts were quantified by HTSeq (v0.9.1, European Molecular Biology Laboratory, Heidelberg, Germany), and expression levels were normalised as FPKM and TPM.
A volcano plot was constructed based on the results of differential expression analysis using GenesCloud platform (Personalbio, Shanghai, China, https://www.genescloud.cn/chart/MultipleVolcano (13 October 2025)). Agglomerate hierarchical clustering heatmap analysis was performed using GenesCloud platform (https://www.genescloud.cn/chart/HeatMap (13 October 2025)) on the union of differentially expressed genes (DEGs) across all comparison groups. To identify patterns, both genes and samples were clustered using Euclidean distance and the Complete Linkage method. Trend analysis was conducted to categorise DEGs into distinct clusters based on the similarity of their expression profiles (https://www.genescloud.cn/chart/TrendAnalysis (13 October 2025)). The similarities of expression profiles were defined by agglomerative hierarchical clustering. KEGG pathway enrichment analysis was carried out using GenesCloud platform (https://www.genescloud.cn/chart/KEGGenrich (13 October 2025)).

4.6. qRT-PCR

Total RNA was extracted from the roots of Kefeng 1 and Qihuang 1 under both control and salt-stress conditions. Quantitative real-time PCR (qRT-PCR) was performed using the Hieff® qPCR SYBR Green Master Mix (Low Rox Plus) (Yeasen Biotechnology (Shanghai) Co., Ltd., Shanghai, China). Each gene was validated with three biological replicates. Gene IDs and primer sequences were provided in Table S1.

4.7. Determination of IAA and ABA Content

The total content of IAA and ABA in roots of KC, KN, QC, and QN were determined via Liquid Chromatography–Tandem Mass Spectrometry (LC-MS/MS). First, 0.5 g of sample was homogenised in acetonitrile (Fisher Scientific, Waltham, MA, USA) (1:4, w/v). Then, 0.25 mL homogenate was mixed with 25 mL of purified water. After vortexing, homogenate was centrifuged at 503.1× g (4 °C) for 10 min (5430R, Eppendorf, Hamburg, Germany). The supernatant was loaded onto an SPE column, which was pre-activated with 5 mL methanol (Fisher Scientific, Waltham, MA, USA) and 10 mL purified water. After eluting twice with 5 mL of methanol, the eluate was concentrated under nitrogen flow and reconstituted to 1 mL. Following ultrasonication (5 min), vortexing (10 min), and high-speed centrifugation (12,577.5× g, 10 min; 5430R, Eppendorf, Hamburg, Germany), the final supernatant was analysed under LC-MS/MS (ExionLC AD MP HPLC coupled with a QTRAP 6500+ MS/MS system, AB Sciex, Framingham, MA, USA). The hormone contents were calculated based on external calibration curves using (S)-(+)-abscisic acid (99.73% purity) and indole-3-acetic acid (99.94% purity) standards (MedChemExpress LCC, Monmouth Junction, NJ, USA).

4.8. Metabolomics

Root samples from KC, KN, QC, and QN were sent to Personalbio (Shanghai) Co., Ltd. for metabolite detection. Samples were extracted using a pre-cooled methanol–acetonitrile–water solution (2:2:1, Fisher Scientific, Waltham, MA, USA). Mass spectrometry data were acquired in both positive and negative electrospray ionisation (ESI) modes using a Thermo Orbitrap Exploris 120(Thermo Fisher Scientific, Waltham, MA, USA) controlled by Xcalibur software (v4.7, Thermo Fisher Scientific), operating in data-dependent acquisition (DDA) mode. Instrument stability was monitored throughout the run using quality control (QC) samples. Raw data were processed in MS-DIAL soft (version 4.9.221218, RIKEN Center for Sustainable Resource Science, Yokohama, Japan) for peak extraction and normalisation. Metabolites were identified against database PSNGM (Personalbio, Shanghai, China). PSNGM included a self-built library, mzCloud, LIPIDMAPS, HMDB, MoNA, NIST_2020, and AI-predicted MS/MS spectral libraries.
Principal component analysis (PCA) was performed via multivariate statistical analysis using the Ropls package in R. For the union of differentially accumulated metabolites (DAMs), agglomerate hierarchical clustering heatmaps were generated using GenesCloud platform (https://www.genescloud.cn/chart/HeatMap (13 October 2025)). Similarly to the transcriptomic approach, metabolites and samples were clustered based on abundance levels using Euclidean distance and the Complete Linkage method. Trend analysis further divided these DAMs into specific clusters according to their expression patterns (https://www.genescloud.cn/chart/TrendAnalysis (13 October 2025)). KEGG pathway enrichment analysis was conducted using Metware Cloud (Metware Biotechnology Co., Ltd., Wuhan, Chinad; https://cloud.metware.cn/#/tools/detail?id=201 (13 October 2025)).

5. Conclusions

In summary, compared to the salt-sensitive soybean Qihuang 1, salt-tolerant soybean Kefeng 1 exhibited superior salt tolerance, primarily manifested in its root. Kefeng 1 achieved salt tolerance through a multi-faceted and synergistic regulatory network (Figure 7). (1) Ion homeostasis regulation: Kefeng 1 mitigated root ion toxicity through down-regulating CNGC13 to restrict Na+ influx and concurrently up-regulating transporter genes including CHX15 and CAX3 to maintain Na+/K+ homeostasis and Ca2+ transport. (2) Remodelling of auxin homeostasis: Through the synergistic up-regulation of Aux/IAA and GH3, which suppressed IAA signalling and biological activity, alongside PIN3-mediated IAA efflux, Kefeng 1 remodelled its auxin metabolic balance, thereby averting salt-induced hormonal perturbations. (3) Enhanced antioxidant defence: The enzymatic antioxidant system was bolstered by the up-regulation of AKR1 and GST genes and increased CAT activity. Simultaneously, the activation of the isoflavonoid biosynthetic pathway prioritised the synthesis of antioxidant aglycones, such as genistein. These aglycones, acting in concert with other non-enzymatic antioxidants, efficiently scavenged ROS. In addition, Glyma.09G117900 (PIN3) and Glyma.19G244200 (AKR1) were identified as primary candidate genes for salt tolerance in this study. Their pivotal role was highlighted by their high connectivity in the gene–metabolite correlation network and their specific up-regulation in the salt-tolerant soybean Kefeng 1 under salt stress (Figure 5B and Figure S1). These findings provided a theoretical foundation and genetic resources for the molecular breeding of salt-tolerant soybean cultivars.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/plants15040555/s1. Figure S1: Validation of transcriptomic data by qRT-PCR analysis for 11 selected genes; Table S1: The qRT-PCR primers of 11 genes; Table S2: The information of 439 core differentially expressed genes; Table S3: The information of 238 core differentially accumulated metabolites; Table S4: Co-enriched KEGG pathways for 432 core DEGs and 238 core DAMs; Table S5: The top 100 highly correlated gene–metabolite pairs derived from 432 core DEGs and 238 core DAMs.

Author Contributions

C.L., H.Z., K.L. and W.G. conceived the study. Y.Y. and C.L. designed and performed the experiments. L.Z., B.C. and J.Y. did the preliminary data analysis. Y.Y. analysed the data and wrote the manuscript. C.L., H.Z., K.L. and W.G. revised the manuscript. H.Z. and K.L. provided plant materials. L.Z. and H.Y. conducted plant cultivation and salt stress treatments. All authors have read and agreed to the published version of the manuscript.

Funding

This work was financially supported by the Shanghai Sailing Program, China (23YF1439200) and the Domestic Science and Technology Cooperation Program of Shanghai, China (24010700900).

Data Availability Statement

Raw transcriptome and metabolomic data was deposited in the National Genomics Data Center (https://www.cncb.ac.cn/) under the BioProject PRJCA054798 (GSA: CRA036296, OMIX: OMUIX014067).

Conflicts of Interest

The authors declare that the research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest.

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Figure 1. Phenotypic observations of Kefeng 1 and Qihuang 1. (A) Phenotypic observations of Kefeng 1 and Qihuang 1 after 12 days of treatment (CK: 1/2 Hoagland’s solution; 150 mM NaCl: 1/2 Hoagland’s solution supplemented with 150 mM NaCl); (B) Phenotypic observations of Kefeng 1 and Qihuang 1 after rehydration (Red-boxed area: phenotypic differences in true leaves between Kefeng 1 and Qihuang 1.).
Figure 1. Phenotypic observations of Kefeng 1 and Qihuang 1. (A) Phenotypic observations of Kefeng 1 and Qihuang 1 after 12 days of treatment (CK: 1/2 Hoagland’s solution; 150 mM NaCl: 1/2 Hoagland’s solution supplemented with 150 mM NaCl); (B) Phenotypic observations of Kefeng 1 and Qihuang 1 after rehydration (Red-boxed area: phenotypic differences in true leaves between Kefeng 1 and Qihuang 1.).
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Figure 2. Na+ and K+ content, Na+/K+ ratio, and antioxidant enzyme activities in Kefeng 1 and Qihuang 1 after 12 days of treatment (QL: Qihuang 1 leaves; KL: Kefeng 1 leaves; QR: Qihuang 1 roots; KR: Kefeng 1 roots; CK: 1/2 Hoagland’s solution; 150 mM NaCl: 1/2 Hoagland’s solution supplemented with 150 mM NaCl). (A) Na+ and K+ content and Na+/K+ ratio; (B) Activities of catalase (CAT), superoxide dismutase (SOD), and peroxidase (POD). (Different lowercase letters indicate significant differences at p < 0.05).
Figure 2. Na+ and K+ content, Na+/K+ ratio, and antioxidant enzyme activities in Kefeng 1 and Qihuang 1 after 12 days of treatment (QL: Qihuang 1 leaves; KL: Kefeng 1 leaves; QR: Qihuang 1 roots; KR: Kefeng 1 roots; CK: 1/2 Hoagland’s solution; 150 mM NaCl: 1/2 Hoagland’s solution supplemented with 150 mM NaCl). (A) Na+ and K+ content and Na+/K+ ratio; (B) Activities of catalase (CAT), superoxide dismutase (SOD), and peroxidase (POD). (Different lowercase letters indicate significant differences at p < 0.05).
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Figure 3. Transcriptome data of Kefeng 1 and Qihuang 1 after 12 days of treatment (QCr: Qihuang 1 root cultured with 1/2 Hoagland’s solution; QNr: Qihuang 1 root cultured with 1/2 Hoagland’s solution supplemented with150 mM NaCl; KCr: Kefeng 1 root cultured with 1/2 Hoagland’s solution; KNr: Kefeng 1 root cultured with 1/2 Hoagland’s solution supplemented with 150 mM NaCl). (A) Volcano plot of differentially expressed genes (DEGs); (B) Venn diagram of DEGs (red arrows: up-regulated genes; blue arrows: down-regulated genes; matching dashed arrows indicate identical gene sets; pink area: number of genes uniquely expressed in KNr vs KCr; dark pink area: shared genes between KNr vs KCr and QNr vs QCr that originated from the KNr vs KCr group; light teal area: number of genes uniquely expressed in QNr vs QCr; dark teal area: shared genes between the two groups that originated from the QNr vs QCr group); (C) Heatmap of 432 core DEGs; (D) The expression trend of 432 core DEGs (the light-colored background lines: the expression patterns of individual genes within each cluster; the blue central line: the mean expression level of all genes within the cluster across the samples); (E) Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of 432 core DEGs; (F) Heatmap of DEGs from enriched KEGG pathways.
Figure 3. Transcriptome data of Kefeng 1 and Qihuang 1 after 12 days of treatment (QCr: Qihuang 1 root cultured with 1/2 Hoagland’s solution; QNr: Qihuang 1 root cultured with 1/2 Hoagland’s solution supplemented with150 mM NaCl; KCr: Kefeng 1 root cultured with 1/2 Hoagland’s solution; KNr: Kefeng 1 root cultured with 1/2 Hoagland’s solution supplemented with 150 mM NaCl). (A) Volcano plot of differentially expressed genes (DEGs); (B) Venn diagram of DEGs (red arrows: up-regulated genes; blue arrows: down-regulated genes; matching dashed arrows indicate identical gene sets; pink area: number of genes uniquely expressed in KNr vs KCr; dark pink area: shared genes between KNr vs KCr and QNr vs QCr that originated from the KNr vs KCr group; light teal area: number of genes uniquely expressed in QNr vs QCr; dark teal area: shared genes between the two groups that originated from the QNr vs QCr group); (C) Heatmap of 432 core DEGs; (D) The expression trend of 432 core DEGs (the light-colored background lines: the expression patterns of individual genes within each cluster; the blue central line: the mean expression level of all genes within the cluster across the samples); (E) Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of 432 core DEGs; (F) Heatmap of DEGs from enriched KEGG pathways.
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Figure 4. Metabolomic analysis of Kefeng 1 and Qihuang 1 after 12 days of treatment (QCr: Qihuang 1 root cultured with 1/2 Hoagland’s solution; QNr: Qihuang 1 root cultured with 1/2 Hoagland’s solution supplemented with 150 mM NaCl; KCr: Kefeng 1 root cultured with 1/2 Hoagland’s solution; KNr: Kefeng 1 root cultured with 1/2 Hoagland’s solution supplemented with 150 mM NaCl). (A) Principal component analysis (PC: principal component); (B) Venn diagram of differentially accumulated metabolites (DAMs; red arrows: up-regulated genes; blue arrows: down-regulated genes; matching dashed arrows indicate identical gene sets; light yellow area: number of DAMs uniquely identified in KNr vs KCr; dark yellow area: shared DAMs between KNr vs KCr and QNr vs QCr within the KNr vs KCr group; light blue area: number of DAMs uniquely identified in QNr vs QCr; dark blue area: shared DAMs between KNr vs KCr and QNr vs QCr within the QNr vs QCr group); (C) Heatmap of 238 core DAMs; (D) The accumulation trend of 238 core DAMs (the light-colored background lines: the abundance patterns of individual metabolites within each cluster; the blue central line: the mean abundance level of all metabolites within the cluster across the samples); (E) Chemical taxonomy of 238 core DAMs; (F) Heatmap of DAMs from flavonoids and amino acid and amino acid derivatives; (G) KEGG pathway enrichment analysis of 238 core DAMs.
Figure 4. Metabolomic analysis of Kefeng 1 and Qihuang 1 after 12 days of treatment (QCr: Qihuang 1 root cultured with 1/2 Hoagland’s solution; QNr: Qihuang 1 root cultured with 1/2 Hoagland’s solution supplemented with 150 mM NaCl; KCr: Kefeng 1 root cultured with 1/2 Hoagland’s solution; KNr: Kefeng 1 root cultured with 1/2 Hoagland’s solution supplemented with 150 mM NaCl). (A) Principal component analysis (PC: principal component); (B) Venn diagram of differentially accumulated metabolites (DAMs; red arrows: up-regulated genes; blue arrows: down-regulated genes; matching dashed arrows indicate identical gene sets; light yellow area: number of DAMs uniquely identified in KNr vs KCr; dark yellow area: shared DAMs between KNr vs KCr and QNr vs QCr within the KNr vs KCr group; light blue area: number of DAMs uniquely identified in QNr vs QCr; dark blue area: shared DAMs between KNr vs KCr and QNr vs QCr within the QNr vs QCr group); (C) Heatmap of 238 core DAMs; (D) The accumulation trend of 238 core DAMs (the light-colored background lines: the abundance patterns of individual metabolites within each cluster; the blue central line: the mean abundance level of all metabolites within the cluster across the samples); (E) Chemical taxonomy of 238 core DAMs; (F) Heatmap of DAMs from flavonoids and amino acid and amino acid derivatives; (G) KEGG pathway enrichment analysis of 238 core DAMs.
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Figure 5. Combined transcriptome and metabolome analysis. (A) Co-enriched KEGG pathways for 432 core DEGs and 238 core DAMs; (B) Canonical correlation analysis of all transcriptome and metabolomic data (PC: principal component); (C) Ordination plot analysis of all transcriptome and metabolomic data (QCr: Qihuang 1 root cultured with 1/2 Hoagland’s solution; QNr: Qihuang 1 root cultured with 1/2 Hoagland’s solution supplemented with 150 mM NaCl; KCr: Kefeng 1 root cultured with 1/2 Hoagland’s solution; KNr: Kefeng 1 root cultured with 1/2 Hoagland’s solution supplemented with 150 mM NaCl); (D) Gene–metabolite correlation network of the top 100 highly correlated gene–metabolite pairs derived from 432 core DEGs and 238 core DAMs (orange lines: positive correlation; blue lines: negative correlation; triangle: metabolite; circle: gene; the size of the circles: the number of associated metabolites).
Figure 5. Combined transcriptome and metabolome analysis. (A) Co-enriched KEGG pathways for 432 core DEGs and 238 core DAMs; (B) Canonical correlation analysis of all transcriptome and metabolomic data (PC: principal component); (C) Ordination plot analysis of all transcriptome and metabolomic data (QCr: Qihuang 1 root cultured with 1/2 Hoagland’s solution; QNr: Qihuang 1 root cultured with 1/2 Hoagland’s solution supplemented with 150 mM NaCl; KCr: Kefeng 1 root cultured with 1/2 Hoagland’s solution; KNr: Kefeng 1 root cultured with 1/2 Hoagland’s solution supplemented with 150 mM NaCl); (D) Gene–metabolite correlation network of the top 100 highly correlated gene–metabolite pairs derived from 432 core DEGs and 238 core DAMs (orange lines: positive correlation; blue lines: negative correlation; triangle: metabolite; circle: gene; the size of the circles: the number of associated metabolites).
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Figure 7. A molecular model for salt tolerance mechanisms in Kefeng 1. (ROS, reactive oxygen species; IAA: auxin; GH3, gretchen hagen 3; AUX/IAA, auxin/indole-3-acetic acid; PIN, PIN-FORMED; ABC transporter, ATP-binding cassette transporter; CAX, cation/H+ exchanger; CHX, cation/H+ exchanger; ARK, aldo/keto reductase; GST, glutathione S-transferase; CAT, catalase; SOD, superoxide dismutase; POD, peroxidase).
Figure 7. A molecular model for salt tolerance mechanisms in Kefeng 1. (ROS, reactive oxygen species; IAA: auxin; GH3, gretchen hagen 3; AUX/IAA, auxin/indole-3-acetic acid; PIN, PIN-FORMED; ABC transporter, ATP-binding cassette transporter; CAX, cation/H+ exchanger; CHX, cation/H+ exchanger; ARK, aldo/keto reductase; GST, glutathione S-transferase; CAT, catalase; SOD, superoxide dismutase; POD, peroxidase).
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Table 1. Phenotypic statistics for Kefeng 1 and Qihuang 1.
Table 1. Phenotypic statistics for Kefeng 1 and Qihuang 1.
VarietyPlant Height/cmNumber of NodesLeaf Width/cmLeaf Length/cmRoot Length/cm
Qihuang 117.49 a ± 4.983.94 a ± 0.503.69 a ± 0.566.00 a ± 0.9812.2 a ± 0.61
Kefeng 117.13 a ± 2.524.07 a ± 0.194.31 a ± 0.196.01 a ± 0.5313.07 a ± 0.81
Qihaung 19.16 b ± 2.552.86 b ± 0.852.90 b ± 0.194.34 b ± 0.5711.9 a ± 1.14
Kefeng 17.11 b ± 1.253.06 b ± 0.172.97 b ± 0.263.62 b± 0.3522.2 b ± 2.76
Note: Different lowercase letters indicated significant differences at p < 0.05.
Table 2. Statistical summary of Kefeng 1 and Qihuang 1 after RNA resequencing.
Table 2. Statistical summary of Kefeng 1 and Qihuang 1 after RNA resequencing.
SampleRaw Reads No.Clean Reads No.Total_MappedMapped Ratio
QC_137,931,29237,923,87437,435,32398.71%
QC_243,596,62043,587,66643,020,92398.70%
QC_349,110,99449,100,94448,458,32098.69%
QN_146,338,53446,331,91645,569,24198.35%
QN_236,271,10636,266,03035,733,22398.53%
QN_345,365,92245,359,48044,707,33398.56%
KC_144,697,69044,690,49844,047,10398.56%
KC_263,130,19263,120,17862,157,45098.47%
KC_343,709,42243,702,46243,089,98898.60%
KN_141,933,15641,926,36041,227,50498.33%
KN_249,294,77849,287,11648,507,51698.42%
KN_347,871,61047,864,03247,110,09798.42%
Table 3. The content of auxin (IAA) and abscisic acid (ABA).
Table 3. The content of auxin (IAA) and abscisic acid (ABA).
SampleContent (ng/g, FW)
IAAABA
QC0.415 ± 0.01 a3.39 ± 0.68 a
QN7.26 ± 0.33 b2.54 ± 0.06 a
KC0.338 ± 0.02 a2.40 ± 0.07 a
KN1.81 ± 0.04 c2.34 ± 0.14 a
Note: Different lowercase letters indicate significant differences at p < 0.05. FW: fresh weight.
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Yuan, Y.; Zhu, L.; Cao, B.; You, J.; Zhi, H.; Li, K.; Gu, W.; Yang, H.; Li, C. Integrated Multi-Omics Analysis Revealed the Synergistic Regulatory Mechanisms of Salt Tolerance in Soybean (Kefeng 1). Plants 2026, 15, 555. https://doi.org/10.3390/plants15040555

AMA Style

Yuan Y, Zhu L, Cao B, You J, Zhi H, Li K, Gu W, Yang H, Li C. Integrated Multi-Omics Analysis Revealed the Synergistic Regulatory Mechanisms of Salt Tolerance in Soybean (Kefeng 1). Plants. 2026; 15(4):555. https://doi.org/10.3390/plants15040555

Chicago/Turabian Style

Yuan, Yuan, Lihua Zhu, Biting Cao, Jiaqi You, Haijian Zhi, Kai Li, Weihong Gu, Hongjuan Yang, and Chaohan Li. 2026. "Integrated Multi-Omics Analysis Revealed the Synergistic Regulatory Mechanisms of Salt Tolerance in Soybean (Kefeng 1)" Plants 15, no. 4: 555. https://doi.org/10.3390/plants15040555

APA Style

Yuan, Y., Zhu, L., Cao, B., You, J., Zhi, H., Li, K., Gu, W., Yang, H., & Li, C. (2026). Integrated Multi-Omics Analysis Revealed the Synergistic Regulatory Mechanisms of Salt Tolerance in Soybean (Kefeng 1). Plants, 15(4), 555. https://doi.org/10.3390/plants15040555

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