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. 2026 Mar 6;26:669. doi: 10.1186/s12870-026-08425-w

Transcriptome analysis revealed the mechanism of exogenous silicon alleviating allelopathic inhibition of cinnamic acid on soybean seedlings

Xiaohuan Yang 1,#, Zhichao Sun 1,#, Yaping Song 1, Ailian Lu 1, Fei Wu 2, Minghao Chen 1, Xinghai Shi 1, Jun Ren 1, Xiuzhen Qin 1, Jinhu Ma 3,✉
PMCID: PMC13078096  PMID: 41787283

Abstract

Background

Soybean (Glycine max (Linn.) Merr.) is one of the important grain crops in China and a significant oilseed and high-protein dual-purpose crop both in China and worldwide. During soybean cultivation, continuous cropping obstacles are often encountered, which impede the growth and development of the crop and significantly reduce its yield and quality. Enhancing soybean’s resistance to autotoxicity has become an important research direction. Exogenous silicon (Si) plays a crucial role in the stress resistance regulation of crops, but the mechanism by which it alleviates autotoxicity remains unclear.

Results

We used soybean seeds (“ Zhonghuang 13 “) to assess how exogenous silicon (20 mM) affected the growth, photosynthetic characteristics, and activities of antioxidant enzymes and flavonoid-related enzymes of soybean seedlings under 4 mM Cinnamic acid(CA)-induced autotoxicity. The results showed that 4 mM CA induced autotoxicity could significantly reduce stem weight, stem fresh weight, root dry weight, root fresh weight, plant height and nodule number of soybean seedlings. Exogenous silicon can significantly improve these indexes of soybean seedlings under CA stress, and can also improve the net photosynthetic rate, transpiration rate, stomatal conductance and intercellular CO2 concentration of soybean seedlings under CA stress, and alleviate the inhibition of antioxidase activity induced by CA. In addition, exogenous silicon can reduce the flavonoid-related enzyme activity of soybean seedlings under CA stress, thus reducing the formation of lignin and alleviating the influence on root nodules. Through transcriptome analysis, it was found that under cinnamic acid stress, a total of 9235 differentially expressed genes (DEGs) were responsive to exogenous silicon and involved in a variety of metabolic pathways and biosynthesis, including phenylpropanoid metabolism, hydrogen peroxide metabolism, nitrogen metabolism, nodulation process, plant hormone signal transduction, isoflavone biosynthesis, etc. These major metabolic and biosynthetic pathways may be the potential mechanisms by which exogenous silicon alleviates cinnamic acid stress on soybean seedlings. In addition, some members of the transcription factor family, such as AP2/ERF, C2H2, MYB, NAC, bHLH, and WRKY, may also contribute to exogenous silicon reducing cinnamic acid stress tolerance in soybean plants. This study has far-reaching significance to overcome the obstacle.

Conclusions

In conclusion, the phenotypic, physiological and transcriptomic results demonstrated that the autotoxic substance cinnamic acid significantly inhibited the growth of soybeans. Exogenous sodium silicate could enhance the plant’s resistance to cinnamic acid stress by regulating the activities of antioxidant enzymes and phenylpropanoid pathway-related enzymes, as well as the expression of genes related to auxin, plant hormone signal transduction and phenylpropanoid synthesis, thereby alleviating the damage.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12870-026-08425-w.

Keywords: Soybean, Si, Autotoxicity, Nodulation, Transcriptome analysis

Background

Autotoxicity is a form of plant allelopathy [1], is widely distributed in legumes [2, 3], Cucurbit family [4], and Umbelliferae. Autotoxic substances are released into the environment from various plant parts of the crop through secretion, volatilization, rain leaching and decomposition of plant residues [5]. In continuous cultivation systems, these compounds can directly or indirectly inhibit the growth of the crop itself or its close relatives [6, 7].

Soybeans (Glycine max (Linn.) Merr.) are one of the important grain crops in China, with global production exceeding 300 million tons [8]. Compared to cereal crops such as maize, rice, and wheat, soybeans produce seeds rich in proteins and oil, making them exceptionally nutritious [9]. However, limited arable area has led to continuous cropping obstacles in soybean. In northern China, continuous cropping accounts for 70%-80% of soybeans cultivation area, seriously affecting the yield formation [10].

Salvador et al. pointed out that the content of secondary metabolites in the soil is generally between 0.01 and 0.1 mM. When their concentration reaches 10 mM, it will have an impact on the growth of crops [11]. Cinnamic acid (CA) is one of the secondary metabolites and is a well-established chemical antagonist that has been extensively studied for its effects on the growth of leguminous plants. Research has shown that CA accumulates in the above-ground tissues of leguminous crops, the extract of the culture medium base, and the root exudates, and its accumulation is an important factor contributing to the yield reduction in consecutive soybean plantings [12]. Cinnamic acid inhibits the secretion of flavonoids in crops [13], affects the phenylalanine metabolic pathway, and plays a significant role in the formation of root nodules [14]. In this pathway, PAL, C4H, and 4CL play key regulatory roles [15]. Cinnamic acid also causes premature lignification of the cell wall, increases the activity of indole-3-acetic acid oxidase (IAA) and the cinnamate-4-hydroxylase (C4H), and inhibits the growth of the roots of leguminous plants [16, 17]. Current agricultural practices indicate that traditional methods are inefficient in overcoming the yield reduction caused by consecutive soybean plantings, and long-term rotation becomes increasingly unfeasible under the existing planting patterns. Therefore, new methods are urgently needed to address the yield reduction caused by consecutive soybean plantings and increase production.

Silicon (Si) is an environmentally friendly element, highly favored for its non-corrosive and non-polluting properties. It can be used in crop cultivation and does not produce harmful residues, making it an ideal fertilizer for achieving ecological sustainable agriculture [18]. Studies have indicated [19] that, organic silicon may play a crucial role in the structure and remodeling of plant cell walls, influencing plant growth and resistance to biological and abiotic stresses. Silicon can also increase the tolerance of crops to biological and abiotic stresses [20, 21]. According to the research of Lu et al. [22], exogenous silicon significantly improved the water status of cucumber leaves under calcification stress, promoted the absorption of mineral elements, and alleviated the inhibition of enzymes related to nitrogen metabolism caused by calcification. Ahmed et al. discovered that silicon can alleviate the toxicity of cadmium to rapeseed (Brassica napus L.) by regulating the oxidative stress metabolism process within the cells and reducing the transfer of cadmium [23].

Although extensive studies have reported the effects of CA stress on crop growth and the role of Si in alleviating abiotic plant stress. It is still unknown whether exogenous silicon affects the perception and absorption of cinnamic acid by crops, or whether it inhibits the self-toxic effect caused by CA through genetic regulation. In this study, CA was used to simulate soybean autotoxic stress, applying exogenous Si to alleviate CA-induced stress during early seedling growth. It seems that Si achieves detoxification by regulating related genes, thereby eliminating the inhibitory effect of cinnamic acid on the secretion of flavonoids. Through transcriptomic analysis, we explore the underlying physiological and molecular mechanisms, providing theoretical basis for soybean cultivation practices.

Materials and methods

Cultivation of the plant material

Soybean (Glycine max (L.)) “Zhonghuang 13’’ was purchased from Fenghong Seed Industry in Shandong, China. Seeds were sterilized with 5% sodium hypochlorite solution for 15 min, and planted in pots. Seedings was grown at 25℃ with an 18/6 h light/dark photoperiod, and 500 µmol m− 2 s− 1 light intensity. Low-nitrogen nutrient solution (60 mL) was applied every 3 d.

Rhizobium cilture

The USDA110 rhizobacteria were cultured using the YMA medium (The formula for 1 L of YMA medium is Mannitol 10.0 g, Yeast Extract 3.0 g, Agar 15.0 g, NaCl 0.05 g, MgSO4.7H2O 0.2 g, KH2PO4 0.25 g, K2HPO4 0.25 g). The rhizobacteria were inoculated onto solid culture medium plates. After 3 days of cultivation at 28 ℃, single colonies were picked and inoculated into liquid medium. The liquid medium was shaken and cultivated to prepare a bacterial suspension. The inoculation could be performed when the OD600 value reached 0.16–0.2.

Rhizobium inoculation

When the first true leaf fully unfolded, plants were inoculated with 30 mL of USDA110 bacterial suspension (OD600 = 0.16–0.2) along the root system. Greenhouse cultivation, with regular observations of the formation of nodules during the process.

Experimental design

In the preliminary experiments conducted, it was found that when the concentration of CA reached 4 mM, it would have a significant negative impact on various physiological indicators of soybeans. Herein, the first fully unfolded true leaf of the soybean seedling were divided into three treatment groups: control group (CK), CA stress group (4mM CA), and CA stress combined with sodium silicate treatment group (4 mM CA + 20 mM Si)(sodium silicate is added to the nutrient solution.). Plants were cultivated in the greenhouse of Shanxi Agricultural University. Five uniform seeds were planted in each pot (7 cm diameter × 7.5 cm height) containing 80 g vermiculite and 80 mL water. Pots were maintained at 25℃ for 2 d, with light provided after the seedling emergence. After cotyledons expansion, seedlings were thinned to one seedling per pot. During the cultivation period, apply a low-nitrogen nutrient solution(pH 6.5) once every 3 days (30 g/L Ca(NO3)2, 100 g/L CaCl2·2H2O, 100 g/L KHPO4, 150 g/L NaHPO4·12H2O, 120 g/L MgSO4·7H2O, 50 g/L Fe, diluted 1:1000 from the stock solution). Each application is 60 mL.

After 14 days of treatment, various physiological indicators of the seedlings were measured. Soybean root samples for transcriptome sequencing were taken at 2 d and 7 d after treatment, immediately frozen in liquid nitrogen and stored at -80℃. Each treatment included three biological replicates. During cultivation, the low nitrogen nutrient solution (60 mL) was applied once.

Phenotypic determination

Representative seedlings from each treatment were scanned for imaging. Seedling height was measured using a ruler. The seedlings were then dried at 80℃ until reaching a constant weight, after which an electronic balance was used to measure both the dry weight of the seedings and their root nodules.(The nodules were separated before dyring.)

Physiological index determination

Phenylalaninase ammonia-lyase (PAL) activity, cinnamate-4-hydroxylase (C4H) activity, 4-coumaric acid CoA ligase (4CL) activity, chalketone synthetase (CHS) activity, shikimic acid/quinic acid hydroxycinnamyl transferase (HCT) activity, lignin and total flavonoids content (TFC) were determination using commercial assay kits from Beijing Baoruyi Biotechnology Co., Ltd. After treated for 14 days, the samples were taken from the elongation zone and meristematic zone of the root tissue, with at least three replicate samples for each experiment.

Enzyme solution extraction followed the method of Gong et al. [24]with modifications. Superoxide dismutase (SOD) activity was determined by the nitroblue tetrazolium (NBT) method [24]. Peroxidase (POD) and catalase (CAT) activities were determined according to Yang et al. [25]. Malondialdehyde (MDA) content was determined by thiobarbituric acid method [26]. All samples were cryogenically frozen in liquid nitrogen with three technical repeats per treatment.

Superoxide (O2−) content was determined according to Elstner et al. [27]. Plant material (0.2 g) was homogenated in phosphate buffer on ice, centrifuged at 10,000 r·min− 1 for 10 min at 4℃,and the supernatant was collected. The supernatant (2 mL) was mixed with 1.5 mL phosphate buffer and 0.5 mL of hydroxylamine hydrochloride, incubated at 25℃ for 20 min, then combined with 2 mL of p-aminobenzenesulfonic acid and 2 mL α-naphthylamine. Samples were incubated in a water bath at 30℃ for 30 min, absorbance was measured at 530 nm.

Hydrogen peroxide (H2O2) content was determined according to Patterson et al. [28]. Plant material (0.2 g) was homogenized with 4 mL 0.1% trichloroacetic acid (TCA) on ice, centrifuged at 3000 r·min− 1 for 20 min at 4℃. The supernatant (2 mL) was mixed with 2 mL potassium iodide solution, kept in darkness for 10 min, and absorbance was measured at 390 nm.

Photosynthetic characteristics

The fourth pair of true leaves starting from the base from different treatments were selected for were measured for photosynthetic measurements under natural light using an LI-6800 portable photosynthesizer (LI-COR Corporation, USA). For each assay, at least 3 biological replicates were performed. The photosynthetically active radiation (PAR) was set at 500 µmol·m− 2·s− 1 with 50% relative humidity (RH). Net photosynthetic rate (Pn, µmol·m− 2·s− 1), stomatal conductance (Gsw, mol·m− 2·s− 1), transpiration rate (Tr, mmol H2O·m− 2·s− 1) and intercellular CO2 concentration (Ci, µmol CO2·mol− 1) were measured between 9:00 and 11:00 AM. For chlorophyll fluorescence measurements, leaves from the same position were dark-adapted for 3 h, then, analyzed using a pulse-modulated fluorometer (Imaging-PAMm series, Walz, Germany).

Transcriptome analysis

In this study, transcriptome sequencing is performed using paired-end sequencing. Roots samples from plants treated with CA and CA + Si were taken for 2 d and 7 d, respectively, with three biological replicates per treatment. RNA extraction, library construction, sequencing, and data processing were performed by Myv Metabolic Biotechnology (Wuhan, China). Raw reads were quality-filtered using FastQ for quality control. Reads containing adapters, reads with more than 10% N content, and sequences with an average quality score below Q20 were removed. All subsequent analyses were based on high-quality clean date. Correlation network analysis was performed using the WGCNA package in R to identify gene clusters with highly correlated expression profiles. Map clean reads were mapped to soybeans (Glycine max (L.)) on the reference genome (https://ftp.ncbi.nlm.nih.gov/genomes/all/GCA/014/282/085/GCA_014282085.1_WHFS_GmZH13_1.0/). Expression levels for each transcript were calculated using the FPKM (Fragments Per Kilobase of transcript per Million fragments mapped) method. The DESeq2 software package (version 1.10.1) was used to analyze the differential expression between the sample groups. Differentially expressed genes (DEGs) were identified using the criteria of |log2Fold Change| ≥ 1, and FDR < 0.05. DEGs were functionally annotated using the GO (Gene Ontology, http://geneontology.org/) database and KEGG (Kyoto Encyclopedia of Genes and Genomes, https://www.genome.jp/kegg) database to identify significantly enriched biological processes and metabolic pathways.

Real-time quantitative PCR

Twelve DEGs were randomly selected for qRT-PCR validation of Illumina sequencing results. Gene sequences were obtains from the transcriptome data and specific primers were designed using Primer Premier 5 software (Table S1). Samples were identical to those used for transcriptome analysis, including 2 d and 7 d samples from CK, CA, and CA + Si treatments, with three biological replicates per treatment. Total RNA was extracted using MiniBEST kit (Takara, Shiga, Japan), and complementary DNA (cDNA) was synthesized using Supe Mix reverse transcription kit (Genesand Biotech, Beijing, China). Quantitative PCR was performed using the Master Mix kit (Sangon Biotech, Shanghai, China) on the CFX 96TM real-time PCR system (Bio-Rad, California, USA). All procedures were carried out according to the manufacturer’s instructions. Detailed qRT-PCR reaction conditions are provided in the supplementary material (Table S2). Gm-actin and GmCPY2 were used as reference genes, and relative expression levels were calculated using the 2−ΔΔCt method.

Statistical analysis

Data on the physiological and transcriptomic are the results of the mean ± standard error of three biological replicates and three technical replicates.Data analysis was performed using Excel 2022 (Microsoft, Redmond, WA, USA) and SPSS23.0 software (SPSS Inc., Chicago, IL, USA). One-way analysis of variance (ANOVA) followed by; Duncan’s mAultiple range test (p < 0.05) was performed using SPSS23.0 [29].

Results

Effects of exogenous sodium silicate on growth phenotype of soybean seedlings under cinnamic acid stress

We first investigated the effects of Si treatment on plant growth under CA stress. As shown in Fig. 1, CA stress significantly reduced the biomass of soybean seedlings. Compared with the control group, aboveground dry weight (Fig. 1C), underground dry weight (Fig. 1E), plant height (Fig. 1F), nodule number (Fig. 1G) and nodule dry weight(Fig. 1I) of seedlings decreased by 40.09%, 37.02%, 29.79%, 61.62% and 53.75%, respectively, with all differences being statistically significant (p < 0.05). Application of Si significantly mitigated the negative effects of CA stress. Under CA stress, soybean seedlings treated with Si showed significant increases in aboveground dry weight (38.42%, Fig. 1C), underground dry weight (36.33%, Fig. 1E), plant height (32.04%, Fig. 1F), nodule number (105%, Fig. 1G) and nodule dry weight (62.39%, Fig. 1I) compared to plants subjected to CA stress alone.

Fig. 1.

Fig. 1

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Effects of exogenous Si on early seedling growth of soybean under CA stress. A: Representative images of plant phenotypes. Scale bars, 5 cm. B-I, Aboveground fresh weight (B), aboveground dry weigh (C), underground fresh weight (D), underground dry weight (E), plant height (F), nodule number (G), nodule fresh weight (H), nodule dry weight (I) were determined. Data are represent as means ± SDs (n = 3, seedlings per treatment, measured on the 14th day after treatment). Different * denote statistically significant differences between treatments according to Duncan’s test (p < 0.05)

Effects of exogenous sodium silicate on physiology of soybean seedlings under cinnamic acid stress

Subsequently, we analyzed antioxidant enzyme activities, oxidative stress markers, and key enzymes involved in phenylpropanoid metabolism. After treated for 14 days, the samples were taken from the elongation zone and meristematic zone of the root tissue, with at least three replicate samples for each experiment. Compared with CA treatment, the CA + Si treatment significantly reduced oxidative stress markers, with MDA content, O2− production, and H2O2 levels decreasing by 40.95%, 52.30%, and 41.20%, respectively (Fig. 2A-C). Correspondingly, antioxidant enzyme activities were increased, with SOD, POD and CAT activities increasing by 107.83%, 47.90% and 119.08%, respectively (Fig. 2D-F).

Fig. 2.

Fig. 2

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Effects of exogenous Si on physiology of soybean seedlings under CA stress. 5-day-old soybean seedlings were treated with control solution (CK), 4 mmol·L-1 CA, or 4 mmol·L-1 CA plus 20 mmol·L-1 sodium silicate (CA + Si) for 7 d. The determination of the concentrations of malondialdehyde (A), oxygen concentration (B), hydrogen peroxide concentration (C), superoxide dismutase activity (D), peroxidase activity (E), and peroxidase activity (F) in the Leaf, as well as the activities of phenylalanine ammonia-lyase (G), 4-phenylcoumaric acid coenzyme A ligase activity (H), 4-phenylcoumaric acid coenzyme A ligase activity (I), chalcone synthase activity (J), hydroxycinnamic acid transferase activity (K), lignin content (L), and total flavonoid content (M) in the Root. Data are presented as means ± SD. Data are represent as means ± SDs (n = 3 seedlings per treatment, measured on the 14th day after treatment). Different * denote statistically significant differences between treatments according to Duncan’s test (ns: not significant, P ≤ 0.05*, P ≤ 0.01**, P ≤ 0.001***)

As shown in Fig. 2G-K, CA stress significantly altered the activities of key enzymes in soybean roots, with PAL, 4CL, C4H and HCT activities being increased by 29.87%, 16.96%, 19.95% and 18.31%, respectively, compared to control conditions. In contrast, CHS activity was markedly decreased by 42.05% under CA stress. When exogenous Si was applied under CA stress, PAL, 4CL, C4H and HCT activities decreased by 18.46%, 11.77%, 14.18% and 13.02%, respectively, while CHS activity increased by 58.03%. Compared to CA treatment alone, CA + Si treatment significantly increased TFC by 16.70%, and decreased lignin content by 40.03% (Fig. 2L-M).

Si improved photosynthetic efficiency and chlorophyll fluorescence parameters in soybean seedlings under CA stress

As shown in Fig. 3, CA significantly inhibited photosynthesis of soybean seedling leaves compared to the control treatment. Si supplementation under CA stress significantly increased photosynthetic parameters. Specifically, Si addition increased Pn by 81.96%, Gs by 106.41% and Tr by 164.29% compared to CA treatment alone. Concurrently, Ci significantly decreased by 31% in Si-supplemented plants compared to those under CA stress alone (Fig. 3A-D).

Fig. 3.

Fig. 3

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Si improved photosynthetic efficiency and chlorophyll fluorescence parameters in soybean seedlings under CA stress. A-K, net photosynthetic rate (Pn) (A), stomatal conductance (Gs) (B), transpirationrate (Tr) (C), intereellular CO2 concentration (Ci) (D), non-photochemical quenching coefficient (qN) (E), The photochemical quenching coefficient (qP) (F), basal fluorescence (Fo) (G), Maximumfluorescence after dark adaptation (Fm) (H), maximum quantum yield of the PSⅡ (I), (Fv/Fm), quantum yield of the regulatory energy dissipation at the PSⅡ [Y(NPQ)] (J). representative images showing the chlorophyll fluorescence parameters (K). Data are represent as means ± SDs (n = 3 seedlings per treatment, measured on the 14th day after treatment)

Chlorophyll fluorescence parameters serve as sensitive intrinsic indicators that reveal plant photosynthetic effciency and physiological status under varying environment conditions [30]. As shown in Fig. 3E-K, CA treament significantly inhibited fluorescence parameters compared to the control treatment. Addition of exogenous Si to CA-stressed plants significantly increased Fv/Fm, Fm and qP by 12.79%, 17.24% and 38.26%, respectively, compared to CA treatment alone. In contrast, Si supplementation significantly reduced Y(NPQ), qN and Fo by 109.31%, 34.57%, and 19.87%, compared to CA treatment alone.

Transcriptomic analysis

To investigate transcriptional responses under different treatments, DEGs were identified and analyzed. Volcano plot analysis of DEGs revealed substantial transcriptional reprogramming across treatments. Compared with control, CA treatment after 2 d identified 3,532 DEGs, comprising 1,437 upregulated and 2,059 downregulated genes. This pattern persisted after 7 d, where CA treatment relative to control resulted in 1,933 DEGs, with 616 upregulated and 1,317 downregulated genes. Meanwhile, comparison of CA + Si with CA treatment after 2 d showed 2,504 DEGs, with 1,832 upregulated and 672 downregulated genes. Similarly, after 7 d, comparison of CA + Si with CA treatment revealed 1,266 DEGs, with 754 upregulated and 512 downregulated genes. Compared with control, CA stress significantly altered the transcriptional profile, predominantly driving gene downregulation. In contrast, CA + Si reversed this pattern when compared with CA treatment alone, resulting in significant upregulation of many differentially expressed genes (Fig. 4E).

Fig. 4.

Fig. 4

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Differential transcriptome analysis of soybean plant under different treatments. (A: control vs. CA 2d; B: CA vs. CASi 2d; C: control vs. CA 7d; D: CA vs. CASi 7d), Volcano plots showing distribution of the DEGs in different treatments, with red dots representing significantly up-regulated genes and green dots representing significantly down-regulated genes across different treatment comparisons. E: Bar graph quantifying the number of up-regulated and down-regulated genes in each treatments comparison

GO enrichment analysis of differentially expressed genes

After performing GO enrichment analysis on the four treatments (CA 2d, CA + Si 2d, CA 7d, CA + Si 7d), it was found that the differentially expressed genes were mainly enriched in biological processes, such as “metabolic process”, “cell process”, “stimulation response”, etc. (Figs. 5A-D).

Fig. 5.

Fig. 5

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GO enrichment analysis of DEGs under CA treatment and CA + Si treatment. A, control 2 d vs. CA 2 d. B, CA 2 d vs. CA + Si 2 d. C, control 7 d vs. CA 7 d. D, CA 7 d vs. CA + Si 7 d. The top 15 GO terms (p < 0.01) are categorized into Biological Process (BP, blue), Cellular Component (CC, orange), and Molecular Function (MF, red)

GO enrichment analysis of differentially expressed genes between different treatments

When CA subjected soybeans to stress for 2 days, the gene differences were mainly enriched in phenylpropanoid metabolic process, phenylpropanoid biosynthetic process, and secondary metabolic biosynthetic process. This indicates that the accumulation of CA can affect the phenylpropanoid metabolic pathway in soybeans, thereby influencing nodulation. When adding exogenous silicon to resist CA stress 2d, the gene differences were mainly enriched in enzyme inhibitor activity, phenylpropanoid metabolic process. Exogenous silicon not only promotes the accumulation of flavonoids, but also enhances the antioxidant capacity of soybeans.

When CA subjected soybeans to stress for 7 days, the gene differences were mainly enriched in response to decreased oxygen levels, long-term CA stress has impaired the antioxidant function of soybeans. Interestingly, the continuous application of exogenous silicon led to the enrichment of genetic differences in genes related to photosynthesis.(Supplementary Table S3).

This analysis precisely demonstrates that exogenous silicon plays a significant role in influencing the production of flavonoids, enhancing the antioxidant capacity of soybeans, and protecting their photosynthetic structure (Fig. 6).

Fig. 6.

Fig. 6

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GO enrichment analysis of differentially treated genes. A: control 2 d vs. CA 2 d; B: CA 2 d vs. CA + Si-2 d; C: control 7 d vs. CA 7 d; D: CA 7 d vs. CA + Si 7 d. The size of each dot indicates the count of DEGs enriched in that term, while the color represents the Q-value significance level

KEGG enrichment analysis of differentially expressed genes

Enrichment analysis was performed to identify the major differential biological pathways associated with DEGs in soybean seedlings, with results summarized in Supplementary Table S4-S5.

KEGG enrichment analysis identified the top 20 significant enriched pathways across the three different treatments after 2 d and 7 d (Fig. 7, Supplement Table S6-S7). Several metabolic pathways were significantly enriched, including photosynthesis and photosynthetic antenna proteins (ko00196), phenylpropanoid biosynthesis (ko00940), ribosome biogenesis (ko03010), starch and sucrose metabolism (ko00500), an amino sugar, nucleotide sugar metabolism (ko00520). At 2 d treatment, the phenylpropane biosynthesis pathway (ko00940), isoflavone biosynthesis pathway (ko00943), MAPK signaling pathway-plant (ko04016), plant hormone signaling (ko04075), plant-pathogen interaction (ko04626) and secondary metabolite biosynthesis (ko01110) were simultaneously enriched across all treatments. After 7 d treatment, the phenylpropanoid biosynthesis pathway (ko00940), photosynthesis (ko00195) and carotenoid biosynthesis (ko00906) were significantly enriched across all three treatments.

Fig. 7.

Fig. 7

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KEGG enrichment analysis of differentially treated genes. A: control 2 d vs. CA 2 d; B: CA 2 d vs. CA + Si 2 d; C: control 7 d vs. CA 7 d; D: CA 7 d vs. CA + Si 7 d. The size of each dot indicates the count of DEGs enriched in that term, while the color represents the Q-value significance level

This indicates that the biosynthesis of phenylpropanoids is crucial for soybeans’ response to CA stress and for the alleviation of CA stress by exogenous silicon. This also confirms our inference that cinnamic acid inhibits the secretion of flavonoids, thereby affecting the phenylpropanoid metabolic pathway and ultimately influencing soybean nodulation.

Regulation of plant hormone signaling and phenylpropanoid biosynthesis by exogenous Si in soybean

Gene expression was conducted for both plant hormone signaling pathways and phenylpropanoid metabolic pathways after 2 d and 7 d of soybean growth. According to gene expression heatmap (Fig. 8A) and supplemental table S6-S7, CA stress significantly impacted phenylpropanoid biosynthesis gene expression. After 2 d CA stress, 59.1% (52/88) of phenylpropanoid biosynthesis DEGs were downregulated, while aftre 7 d CA stress, 33.3% (11/33) were downregulated. Key enzymes including phenylalanine ammonolyase (PAL) (JHK84_029037, JHK84_056629), hydroxycinnamoyl transferase (HCT) (JHK84_049899, JHK84_046630, JHK84_049884), cinnamoyl-CoA reductase (CCR) (JHK84_049383, novel.14583), coumarate-5-hydroxylase (F5H) (JHK84_045416) and peroxidases (JHK84_053528, JHK84_049360, JHK84_042697, JHK84_031762) were significantly downregulated by CA treatment. Si application demonstrated remarkable alleviate effects, causeing 67.3% (33/52) of the downregulated genes after 2 d and 36.4% (4/11) after 7 d to exhibit opposite expression patterns compared to CA. Additionally, 75.7% (53/70) of genes were upregulated after 2 d and 65.4% (17/26) after 7 d following Si treatment.

Fig. 8.

Fig. 8

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A: Gene expression heatmap; B: Phenylpropanoid biosynthesis gene correlation network; C: Correlation network of plant hormone signaling genes

Plant hormone signaling similarly affected by CA stress, with 63.5% (94/148) of hormone signal transduction-related DEGs being downregulated after 2 d CA stress. Critical regulatory genes including DELLA gene (JHK84_027084, JHK84_037967 and JHK84_046138), xylan transferase (TCH4) (JHK84_036193, JHK84_046669 and JHK84_036192), gibberellin receptor (GID1) The expression of JHK84_033611 and JHK84_027613, MYC2 (JHK84_030274 and JHK84_041795) and GH3 (JHK84_034106) were significantly downregulated by CA stress. Exogenous Si application reversed the expression pattern of 59.5% (56/94) of these downregulated genes.

To elucidate the gene regulatory network underlying soybean responses to CA stress in the presence of Si (Si + CA), gene correlation networks were mapped using FPKM values between plant hormone signal transduction and phenylpropane biosynthesis pathways. In phenylpropanoid biosynthesis, six key genes (JHK84_049358, JHK84_031762, JHK84_041203, JHK84_029037, JHK84_056629 and JHK84_049884) were identified as central regulators of the Si-mediated CA stress response (Fig. 8B). These genes encode peroxidase, PAL and HCT enzymes that function synergistically in the phenylpropanoid biosynthesis pathway to regulate lignin, flavonoids and phenols compound synthesis, thereby influencing plant growth, development, disease resistance and stress resistance. In plant hormone signal transduction networks, four key genes (JHK84_036193, JHK84_040593, JHK84_034106 and JHK84_046138) were identified as critical mediators key genes in the response of Si alleviate CA stress (Fig. 8C). These genes encode TCH4, protein phosphatase 2 C (PP2C), GH3 and DELLA which play essential roles in cell wall modification, cell elongation, abscisic acid signaling pathways, auxin and gibberellin regulatory pathways. These proteins play a key role in plant hormone signal transduction, coordinating plant growth and development and stress response through a complex regulatory network.

Transcription factor analysis of differentially expressed genes

Transcription factors (TFs) serve as upstream regulators that control gene expression in plant metabolic pathways and play crucial roles in plant stress tolerance responses [31]. In this study, we identified key TF mediating Si to alleviate the effects of CA stress effects in soybeans through differential expression analysis after 2 d and 7 d of treatment (Supplement Table 8; Fig. 9). After 2 d of treatment, 371 TF were identified between control and CA treatment. These TFs were classified into multiple families, with, six major families accounting for 55.26% of the total response: AP2/ERF (51), C2H2 (25), MYB (62), WRKY (22), bHLH (19) and NAC (29).

Fig. 9.

Fig. 9

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Transcription factor family distribution and expression patterns in soybean response to CA stress and Si treatment. A: control 2 d vs. CA 2 d; B: CA 2 d vs. CA + Si 2 d; C: control 7 d vs. CA 7 d; D: CA 7 d vs. CA + Si 7 d

Combined with GO enrichment analysis, we speculate that the MYB families mainly regulate the phenylpropanoid metabolic and synthetic pathways. The downregulation of AP2/ERF family genes is mainly related to antioxidant properties. The upregulation of WRKY family genes is associated with the photosynthetic biological process.

qRT-PCR validation of soybean DEGs treated with sodium silicate under cinnamic acid stress

To validate the reliability and accuracy of our RNA-seq data, twelve DEGs were randomly selected for quantitative real-time PCR (qRT-PCR) analysis. And correlation analysis and quality metrics of RNA-seq data is presented in the supplementary material (Table 9. Fig. 1). The qRT-PCR results demonstrated strong concordance with the RNA-Seq expression patterns, showing consistent up-regulation and down-regulation trends across all tested genes (Fig. 10). The relevant information of the twelve genes (such as gene functions and primer design) is provided in the supplementary material (Table 1). The consistency confirms the reliability and accuracy of our RNA-Seq results and confirms the transcriptional changes of soybeans under CA stress and sodium silicate treatment.

Fig. 10.

Fig. 10

Open in a new tab

Expression levels of 12 randomly selected DEGs under different treatments. The gene expression level detected by RNA-seq and qRT-PCR was presented on the left and right Y-axis, re-spectively. The column and red line represent the respective results of RNA-seq and RT-qPCR

Discussion

Cinnamic acid, as a prominent autotoxic substance, significantly affect the growth and development of many crops, including legumes [32], melons, maize. Si has emerged as a crucial element in plant stress response, demonstrating active roles in regulating plant growth and development while improving photosynthetic efficiency [33, 34]. At present, Si application has become an effective foliar strategy to improve plant productivity and stress resistance [35, 36]. In this study, we employed an integrated approach combining phenotypic, physiological and transcriptomic analyses to elucidate the mechanisms by which exogenous Si alleviates CA’s allelopathic inhibition on soybean seedlings.

Cinnamic acid inhibits root growth and nodulation, but exogenous silicon alleviates this inhibition

The root system, as the main organ interacting with toxic substances in the soil, is particularly susceptible to the influence of allelochemicals [37]. Although CA originates from the exudates of crop roots, excessive accumulation of CA can transform it into a potent allelochemical, inhibiting the secretion of flavonoids and inhibiting nodulation, thereby significantly affecting root growth [38]. Our research results indicate that CA directly affects the dry weight, fresh root weight, and number of nodules of soybeans [39].

Silicon plays a crucial role in inducing nodule formation, which is essential for biological nitrogen fixation and plant growth (especially in leguminous plants). Studies have shown that using silicon fertilizer significantly increases the number and morphology of nodules in soybeans [40–42]. Our research confirms that under CA stress conditions, adding exogenous silicon to the nutrient solution significantly improves the root growth of soybean seedlings.

Effects of exogenous silicon on photosynthetic characteristics of soybean seedlings

Photosynthesis provides the necessary substances and energy for the growth, development and yield formation of plants. Pn, Tr, Gs and Ci are important indicators of photosynthesis [43]. Chlorophyll fluorescence parameters reflect the quantum efficiency regulation of photosynthesis and the ability of plants to effectively utilize light energy. Many studies have shown that high concentrations of CA can inhibit the photosynthetic characteristics of plants and reduce the Pn, Tr and Gs of treated plants. The chlorophyll fluorescence parameters Fv/Fm, ΦPSII and qP also significantly decrease, indicating that CA stress significantly damages the photosynthetic system [42, 44, 45]. Our research also discovered this phenomenon.

There are reports in the literature indicating that silicon can alleviate some stresses by protecting photosynthetic structures, improving water use efficiency, protecting photosynthetic mechanisms from damage caused by reactive oxygen species (ROS), through gene regulation, and by interacting with other physiological processes [46]. Applying exogenous silicon, we found that the net photosynthetic rate, stomatal conductance, transpiration rate and intercellular carbon dioxide concentration of soybean seedlings were all increased, indicating that exogenous silicon elements can effectively alleviate the damage of calcium stress to the photosynthetic system. This is consistent with the research results of Ma, Liang and others [45, 47].

Changes of antioxidant enzyme activity under exogenous silicon

Reactive oxygen species (ROS) are inevitable by-products during aerobic metabolism in plant cells. Plants have evolved complex enzymatic and non-enzymatic mechanisms to remove excess ROS. However, under stress conditions, the balance between the generation and clearance of ROS within the cells is disrupted, leading to oxidative stress [48]. Oxidative stress can damage cellular proteins and biological membranes, impair the antioxidant system, and affect the main metabolic activities of plants. Silicon can enhance the tolerance of plants to oxidative stress by increasing the activity of antioxidant enzymes, reducing the production of ROS, and inhibiting lipid peroxidation. It also alleviates the damage caused by oxidative stress [49]. Previous studies have shown that CA stress can cause oxidative damage in various crops. The application of exogenous silicon can significantly enhance the antioxidant defense mechanism of plants [50]. Our experimental results indicate that CA stress leads to oxidative stress and membrane lipid peroxidation in the roots and leaves of soybean seedlings, while exogenous silicon activates the activity of antioxidant enzymes in soybeans and enhances the ability to clear ROS. This suggests that exogenous silicon participates in regulating the antioxidant enzyme system of soybeans under CA stress and enhances the tolerance of soybeans to CA.

Biosynthesis of flavonoids and their role in nodulation

Flavonoids are secondary metabolites with antioxidant properties that relate to adaptive responses under various abiotic stresses. Flavonoids are the first known signal involved in establishing rhizobia-legume symbiosis and play crucial roles in chemical communication between plant roots and symbionts such as nitrogen-fixing rhizobia [51, 52]. In this study, soybean, as a leguminous crop sensitive to autotoxicity, showed significantly inhibited soybean growth and reduced the numbers of root nodule under CA stress. Compared to CA stress alone, soybean treated with exogenous Si showed significantly increased root nodules and notable root morphology changes. CA induced increased activities of key flavonoid synthesis pathway enzymes such as PAL, 4CL and C4H leading to increased phenolic compounds accumulation (tannins, lignin, etc.) in plants. Exogenous Si addition may upregulate PAL and HCT genes to decrease PAL, 4CL and C4H activities in soybean roots, resulting in decreased lignin content, normal cell wall and root growth, increased root flavonoid released and increased root nodulation. These results indicate that Si participate in flavonoid biosynthesis, thereby improving plant nodulation processes and stress resistance.

Transcriptome analysis revealed the mechanism of alleviating allelopathic inhibition of cinnamic acid on soybean seedlings by exogenous silicon

Our transcriptome analysis revealed the complex molecular mechanism by which exogenous silicon alleviates the effects of CA stress on soybean seedlings.

By combining GO enrichment analysis and KEGG analysis, we inferred that, under silicon treatment, the upregulation of genes encoding such as PAL and HCT in the phenylpropanoid biosynthesis pathway can enhance the synthesis of lignin, flavonoids, and phenolic compounds. This compensates for the growth inhibition and reduced number of nodules in soybeans under CA stress [53]. The upregulation of enzymes such as peroxidase provides a basis for the enhancement of soybean antioxidant capacity. Similarly, the regulation of genes involved in plant hormone signaling (including DELLA proteins, GID1, and MYC2 transcription factors) highlights the role of silicon in finely regulating hormone stress responses [54]. The identification of key transcription factors such as MYB, AP2/ERF, and WRKY (which have been proven to be crucial for plant stress responses) further confirms the protective effect of Si. These transcription factors are likely to coordinate the construction of a complex regulatory network, thereby enhancing the plant’s ability to resist stress caused by CA [55].

Based on the comprehensive analysis of GO enrichment, KEGG analysis, and transcriptome analysis, we hypothesize that the underlying molecular mechanism by which exogenous silicon alleviates CA stress might be as follows. The auto-toxic stress of CA only affects the phenylpropanoid biosynthesis pathway in the first 2 days, influencing the production of nodulation-related substances in soybeans. Then, from the 3rd day onwards, it affects the generation of reactive oxygen species. These all impose stress on the photosynthetic system of soybeans, affecting their photosynthetic efficiency and the activity of antioxidant enzymes. After the soybeans were treated for 2 days, CA directly affected the phenylpropanoid biosynthesis pathway of the soybeans, causing PAL, 4CL, CH4, etc. to accumulate in the roots of the soybeans, resulting in a decrease in the number of soybean nodules. After the soybeans were treated for 7 days, the long-term stress also affected the generation of reactive oxygen species, which was highly detrimental to the protection of the photosynthetic structure. The photosynthetic mechanism was damaged by the ROS. After adding exogenous silicon, the early expression of genes such as PAL and HCT increased, resulting in a reduction in the accumulation of phenolic substances like PAL, 4CL, and C4H, and an increase in the number of nodules. In addition, the genes of the AP2/ERF family were downregulated, enhancing the antioxidant capacity of the crop. The WRKY family genes were upregulated, improving the photosynthetic efficiency of soybeans. Of course, the alleviation effect of exogenous silicon on CA stress is not limited to these aspects. In the future, we will analyze the underlying molecular mechanisms one by one.

Conclusion

Our study demonstrates that CA-induced autotoxic stress affects the growth of soybean seedlings. Exogenous application of Si effectively counteracts these negative effects through complex molecular mechanisms. Transcriptome analysis revealed that under continuous cropping self-poisoning stress, exogenous silicon application can influence changes in various metabolic pathways and biosynthetic processes in soybeans, including phenylpropanoid metabolism, nitrogen metabolism, plant hormone signal transduction, isoflavone biosynthesis, hydrogen peroxide metabolism, and nodulation processes, etc. Key transcription factor families such as AP2/ERF, C2H2, MYB, NAC, bHLH, and WRKY play a crucial role in mediating the tolerance of soybeans to continuous cropping self-poisoning stress. Therefore, strategic use of silicon in agricultural production systems may overcome the self-poisoning stress generated by various crop continuous cropping.

Supplementary Information

Supplementary Material 1. (56.6KB, xlsx)
Supplementary Material 2. (59.5KB, xlsx)
Supplementary Material 3. (248KB, docx)
Supplementary Material 4. (176.3KB, docx)

Acknowledgements

Thanks to the College of Agriculture of Shanxi Agricultural University for providing the greenhouse planting land and rhizobium strains. We also thank Shandong Fenghong Seed Industry for providing the soybean seeds.We would like to express our gratitude for the support provided by the Central Government’s Project for Guiding Local Science and Technology Development in Shanxi Province (YDZJSX2024D039).

Abbreviations

CA

Cinnamic acid

PAL

Phenylalaninammo-nialyase

C4H

Cinnamate-4-hydroxylase

4CL

4-coumaric acid CoA ligase

CHS

Chalketone synthetase

HCT

Shikimic acid/quinic acid hydroxycinnamyl transferase

TFC

Lignin and total flavonoids content

SOD

Superoxide dismutase

NBT

Nitroblue tetrazolium

POD

Peroxidase

CAT

Catalase

MDA

Malondialdehyde

O2−

Superoxide

H2O2

Hydrogen peroxide

TCA

Trichloroacetic acid

Authors’ contributions

Zhichao Sun and Xiaohuan Yang : Conceptualization, Methodology, Data Curation, Writing - Original Draft, Writing - Review & Editing, Visualization, Investigation. Yaping Song : Methodology, Writing - Review & Editing, Visualization, Investigation. Ailian Lu: Writing - Review & Editing, Visualization, Validation. Fei Wu : Writing - Review & Editing, Validation. Minghao Chen : Writing - Review & Editing, Validation. Xinghai Shi : Writing - Review & Editing. Jun Ren : Writing - Review & Editing. Xiuzhen Qin : Writing - Review & Editing. Jinhu Ma : Funding acquisition, Writing - Review & Editing.

Funding

This research is supported by the project of the central government guiding local science and technology development fund in Shanxi Province (YDZJSX2024D039).

Data availability

The datasets generated and/or analyzed during the current study are available in the NCBI SRA repository, with accession number PRJNA1293669 (https://www.ncbi.nlm.nih.gov/bioproject/1293669). All data generated or analyzed during this study are included within the article and its additional files.

Declarations

Ethics approval and consent to participate

The seeds of Zhonghuang 13 used in this study were provided by Shandong Fenghong Seed Industry Co., Ltd. The sample collection complies with relevant institutional, national, and international guidelines and legislation. All the plant materials in this paper comply with relevant institutional, national, and international guidelines and legislation.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Xiaohuan Yang and Zhichao Sun contributed equally to this work and shared first authorship

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material 1. (56.6KB, xlsx)
Supplementary Material 2. (59.5KB, xlsx)
Supplementary Material 3. (248KB, docx)
Supplementary Material 4. (176.3KB, docx)

Data Availability Statement

The datasets generated and/or analyzed during the current study are available in the NCBI SRA repository, with accession number PRJNA1293669 (https://www.ncbi.nlm.nih.gov/bioproject/1293669). All data generated or analyzed during this study are included within the article and its additional files.

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