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

Transcriptome analysis revealed the mechanism of exogenous silicon alleviating allelopathic inhibition of cinnamic acid on soybean seedlings | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Transcriptome analysis revealed the mechanism of exogenous silicon alleviating allelopathic inhibition of cinnamic acid on soybean seedlings Xiaohuan Yang, Zhichao Sun, Yaping Song, Ailian Lu, Fei Wu, Minghao Chen, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7165248/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 Mar, 2026 Read the published version in BMC Plant Biology → Version 1 posted 20 You are reading this latest preprint version 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 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 CO 2 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. Soybean Si Autotoxicity Nodulation Transcriptome analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Background Autotoxicity is a form of plant allelopathy[ 1 ], is widely distributed in legumes, Solanaceae, Cucurbit family, and Umbelliferaceae. Autotoxic substances are released into the environment from various plant parts of the crop through secretion, volatilization, rain leaching and decomposition of plant residues[ 2 ]. In continuous cultivation systems, these compounds can directly or indirectly inhibit the growth of the crop itself or its close relatives [ 3 ]. Soybeans ( Glycine max (Linn.) Merr.) are one of the important grain crops in China, with global production exceeding 300 million tons[ 4 ]. Compared to cereal crops such as maize, rice, and wheat, soybeans produce seeds rich in proteins and lipids, making them exceptionally nutritious[ 5 ]. 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[ 6 ]. Cinnamic acid (CA), a well-documented chemical allelopathic substance, has been extensively studied for its effects on crop growth. Research has shown that CA inhibit root growth, flavonoid secretion and endophytic fungal colonization of maize [ 7 ]. Flavonoids, which play an important role in root nodule in formation[ 8 ], represent a branch of phenylalanine metabolic pathway. Within this pathway, PAL, C4H and 4CL serve as key regulatory[ 9 ]. Additionally, CHS catalyzes the first and rate-limiting step in flavonoid biosynthesis, while HCT initiates the lignin synthesis pathway [ 10 , 11 ]. Cen et al. found that exogenous application of CA inhibited broad bean seed germination in a concentration-dependent manner[ 12 ]. Researchers have identified CA in above-ground tissues, culture substrate extracts and root secretions of legume crops, its accumulation represents a significant factor contributing to soybean continuous cropping obstacles. Ma et al. reported that CA accumulation during continuous cultivation of legume inhibits legume growth and ultimately affect yield[ 13 ]. Lima et al.[ 14 ]uggested that CA accumulation leads to reduced root growth and premature cell wall lignification. Salvador et al.[ 15 ] showed that exogenous CA inhibits soybean root growth while increasing IAA oxidase and Cinnamate-4 -Hydroxylase (C4H) activities. Current agricultural practices have shown traditional methods of overcoming continuous cropping barriers inefficient, and long-term rotation is becoming less feasible under existing cropping patterns. Therefore, novel approaches are urgently needed to address soybean continuous cropping obstacles and increase yield. Silicon (Si) is an environmentally friendly element due to its non-corrosive and non-polluting nature. It can be applied to crops without the risk of harmful residues, making it an ideal fertilizer for ecologically sustainable agriculture[ 16 ]. Sheng et al. [ 17 ]suggested that beyond non-covalent interactions through amorphous silica, Si can form covalent bonds with plant cell wall components such as hemicelluloses, pectin and lignin. The covalently bound organosilicon may play a crucial role in plant cell wall structure and remodeling, influencing plant growth and resistance against biotic and abiotic stresses. Rizwan et al.[ 18 ] proposed that silicon application under both drought and salt stress can improve plant growth, biomass, photosynthetic pigments and yield quality. Daniel Debona et al.[ 19 ] reported that plants with high root or stem silicon concentrations show greater resistance to pest infestation and enhanced tolerance to abiotic stresses including drought, low temperature and metal toxicity. According to Lyu et al.[ 20 ], exogenous silicon significantly improve water status in cucumber leaves under CA-induced stress, promotes mineral element absorption, and reduces the inhibition of nitrogen metabolism-related enzymes caused by CA. Although extensive studies have reported the effects of CA stress on crop growth and Si's role in alleviating abiotic plant stress, few have reported how CA specifically affects soybean seedling growth and development, whether Si can alleviate the autotoxicity of CA in soybean root secretions, or how Si influences soybean nodulation under CA stress. Therefore, this study uses CA to simulate soybean autotoxic stress, applying exogenous Si to alleviate CA-induced stress during early seedling growth. Transcriptomic analysis was used to 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. Low-nitrogen nutrient solution (60 mL) was applied every 3 d. Rhizobium Cilture The USDA110 rhizobacteria were cultured using the YMA medium (Mannitol 10.0 g, Yeast Extract 3.0 g, Agar 15.0 g, NaCl 0.05 g, MgSO 4 .7H 2 O 0.2 g, KH 2 PO 4 0.25 g, K 2 HPO 4 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 OD 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 (OD 600 = 0.16–0.2) along the root system. Greenhouse cultivation, with regular observations of the formation of nodules during the process. Experimental design Soybean seedlings were divided into three treatment groups: control group (CK), CA stress group (4mM CA), CA stress combined with sodium silicate treatment group (4 mM CA + 20 mM Si). 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. Plant morphology, root nodulation and enzyme activity were determined at 2 d, 7 d and 14 d. Biomass of seedlings was measured at 14 d of growth. Soybean root samples for transcriptome sequencing were taken at 2 d and 7 d from each treatment, immediately frozen in liquid nitrogen and stored at -80℃. Each treatment included three biological replicates. During cultivation, the low nitrogen nutrient solution (60mL) was applied once. Phenotypic determination Representative seedlings from each treatment were scanned for imaging. Seeding height was measured using a ruler. The seedings 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. Physiological index determinatio 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 determined using commercial assay kits from Beijing Baoruyi Biotechnology Co., Ltd. Enzyme solution extraction followed the method of Gong et al.[ 21 ]with modifications. Superoxide dismutase (SOD) activity was determined by the nitroblue tetrazolium (NBT) method[ 21 ]. Peroxidase (POD) and catalase (CAT) activities were determined according to Yang et al.[ 22 ]. Malondialdehyde (MDA) content was determined by thiobarbituric acid method[ 23 ]. All samples were cryogenically frozen in liquid nitrogen with three technical repeats per treatment. Superoxide (O 2 − ) content was determined according to Elstner et al.[ 24 ]. Plant material (0.2 g) was homogenated in phosphate buffer on ice, centrifuged at 10000 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 (H 2 O 2 ) content was determined according to Patterson et al. [ 25 ]. 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 Leaves from same position on plants from different treatments were selected for were measured for photosynthetic measurements under natural light using an LI-6800 portable photosynthesizer (LI-COR Corporation, USA). 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 H 2 O·m − 2 ·s − 1 ) and intercellular CO 2 concentration (Ci, µmol CO 2 ·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 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. 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. Quantitative and statistical analysis 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 multiple range test (p < 0.05) was performed using SPSS23.0. All data are presented as mean ± standard deviation (SD). 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. 1 C), underground dry weight (Fig. 1 E), plant height (Fig. 1 F), nodule number (Fig. 1 G) and nodule dry weight(Fig. 1 I) 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. 1 C), underground dry weight (36.33%, Fig. 1 E), plant height (32.04%, Fig. 1 F), nodal number (105%, Fig. 1 G) and nodal dry weight (62.39%, Fig. 1 I) compared to plants subjected to CA stress alone. 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. Compared with CA treatment, the CA + Si treatment significantly reduced oxidative stress markers, with MDA content, O 2 − production, and H 2 O 2 levels decreasing by 40.95%, 52.30%, and 41.20%, respectively (Fig. 2 A-C). Correspondingly, antioxidant enzyme activities were increased, with SOD, POD and CAT activities increasing by 107.83%, 47.90% and 119.08%, respectively (Fig. 2 D-F). As shown in Fig. 2 G-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%. Furthermore, compared to CA treatment alone, CA + Si treatment significantly increased TFC by 16.70%, and decreased lignin content by 40.03% (Fig. 2 L-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). Chlorophyll fluorescence parameters serve as sensitive intrinsic indicators that reveal plant photosynthetic effciency and physiological status under varying environment conditions[ 26 ]. 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. Figure 3 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 CO 2 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). 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. 4 E). GO enrichment analysis of differentially expressed genes Under CA treatments after 2 d DEGs were distributed across 40 subgroups,with biological processes accounting for 56.78%, cellular components accounting for 17.13% and molecular functions accounting for 26.09%. Biological process were significantly enriched in "metabolic process", "cellular process", "stimulus response", "biological regulation" and "developmental process". Cellular components showed significant enrichment in "anatomical entities of cells" and "complexes of proteins". Molecular functions were significantly enriched in "binding", "catalytic activity", "transporter activity", "transcriptional regulator activity", "molecular functional regulator activity" and "ATP-dependent activity" (Fig. 5 A). In the CA 2 d vs. CA + Si 2 d comparison, DEGs were distributed across 37 subgroups, with biological processes accounting for 56.95%, cellular components accounting for 17.18% and molecular functions accounting for 25.86%. The main categories of GO items are similar to CK and CA in 2d(Fig. 5 B). In the CA 7 d vs. control,DEGs were distributed across 37 subgroups, with biological processes accounting for 59.67%, cellular components accounting for 16.28% and molecular functions accounting for 24.05%. (Fig. 5 C). In the CA + Si 7 d vs. CA 7 d comparison, DEGs were distributed across 37 subgroups, with biological processes accounting for 55.75%, cellular components accounting for 18.30%, and molecular functions accounting for 25.95%. The classification of GO item are similar to CK and CA in 2d (Fig. 5 D). GO enrichment analysis of differentially expressed genes between different treatments To further analyze the function of DEGs in soybean nodules treated with exogenous Si, pathway analysis was conducted based on the GO database. GO enrichment analysis showed (Fig. 6 ) that exogenous Si application regulated the metabolic processes of phenylpropanoid and hydrogen peroxide after 2 d, and hypoxia response and nodulation processes after 7 d (Fig. 6 ). Compared with CA treatment alone, CA + Si treatment regulated 64 phenylpropanol metabolism genes and 50 hydrogen peroxide metabolism genes in 2 d. There were 31 hypoxia response genes and 24 nodulation process related genes after 7 d.(Supplementary Table S3) 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. In the CK vs CA comparisons after 2 d, 3,532 DEGs were annotated to 125 metabolic pathways. Among these, 1,437 upregulated DEGs were mapped to 112 metabolic pathways, while 2,095 down-regulated DEGs were mapped to 110 metabolic pathways. The pathways analysis revealed that 15 metabolic pathways contained exclusively upregulated DEGs, 13 pathways contained exclusively downregulated DEGs, and the majority (97 pathways) contained both upregulated and downregulated DEGs. In contrast, the CA vs CA + Si comparison showed 2504 DEGs annotations to 117 metabolic pathways. Of these, 1,832 upregulated DEGs were mapped to 104 metabolic pathways, and 672 downregulated DEGs were mapped to 88 metabolic pathways. Among the 117 metabolic pathways, 29 metabolic pathways with exclusively upregulated DEGs, 13 metabolic pathways with exclusively downregulated DEGs, and 75 metabolic pathways containing both upregulated and downregulated DEGs. After 7 d, the CK vs CA comparison revealed 1,933 DEGs were mapped to 106 metabolic pathways. Among these, 616 upregulated DEGs were mapped to 79 metabolic pathways, while 1,317 downregulated DEGs were mapped with 93 metabolic pathways. Of the 106 metabolic pathways, 13 contained exclusively upregulated DEGs, 27 contained exclusively downregulated DEGs, and 66 contained both upregulated and downregulated DEGs. Similarly, in the CA vs CA + Si comparison, 1,266 DEGs were mapped to 110 metabolic pathways. Among these, 754 upregulated DEGs were mapped to 97 metabolic pathways, and 512 downregulated DEGs were mapped to77 metabolic pathways. Among the 110 metabolic pathways, 33 metabolic pathways with exclusively upregulated DEGs, 13 metabolic pathways with exclusively downregulated DEGs, and 64 metabolic pathways containing both upregulated and downregulated genes. 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. To further identify the involvement of Si mediated CA stress response genes, we focused on specific pathways with upregulated DEGs in the CA vs CA + Si comparison groups at both time points. Photosynthesis-antenna proteins, nitrogen metabolism, phenylpropanoid biosynthesis, isoflavonoid biosynthesis, secondary metabolite biosynthesis and carotenoid biosynthesis were significantly enriched. The KEGG enrichment analysis revealed distinct temporal regulation patterns in response to silicon treatment. After 2 d, MAPK signaling pathways-plant, plant hormone signal transduction, plant pathogen interaction, isoflavone biosynthesis, phenylpropanoid biosynthesis, α-linolenic acid metabolism and nitrogen metabolism were upregulated, while protein processing in the endoplasmic reticulum and biotin metabolism were downregulated. After 7 d, MAPK signaling pathways-plant, nitrogen metabolism, phenylpropanoid biosynthesis, isoflavone biosynthesis, carotenoid biosynthesis and cysteine and methionine metabolism were upregulated, whereas photosynthesis and glucosinolide biosynthesis were downregulated. 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. 8 A) 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. 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. 8 B). 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. 8 C). These genes encode TCH4, protein phosphatase 2C (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[ 27 ]. In this study, we identified key TF mediatingSi 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 and 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). When comparing CA treatment alone with CA + Si treatment, 256 TF showed differential expression. The same six TF families dominated this response, accounted for 60.55% of the differentially expressed TFs: MYB (41), C2H2 (13), WRKY (21), bHLH (23), AP2/ERF (42) and NAC (15). After 7 d of treatment, the transcriptional response became more focused. Between control and CA treatments, 228 TFs were differentially expressed across 20 homologous groups. The six major TF families maintained their dominance, representing 60.98% of the total response: AP2/ERF (46), C2H2 (16), MYB (22), WRKY (22), bHLH (16) and NAC (17). The comparison between CA and CA + Si treatments revealed 112 differentially expressed TFs distributed across 20 categories. The top six TF families accounted for 58.04% of this response: MYB (16), C2H2 (4), WRKY (16), bHLH (5), AP2/ERF (22) and NAC (2). The MYB transcription factor family consist of functionally diverse proteins found in all eukaryotes, with most MYB proteins involved in regulating cellular processes and stress responses in plants[ 28 ]. After 2 d of treatment, comparison between control and CA revealed 62 MYB TFs, with 17 upregulated and 45 downregulated. In contrast, the CA vs CA + Si comparison identified 41 MYB TFs, showing a predominantly positive response with 35 upregulated and only 6 downregulated. After 7 d of treatment, the response became more focused, with 22 MYB TFs differentially expressed between CK and CA, (3 upregulated, 19 downregulated), while the CA and CA + Si comparison showed 16 MYB TFs with 10 upregulated and 6 downregulated. These results indicate that Si treatment significantly enhanced MYB gene expression, particularly during the early response phase. After 2 d of treatment, 51 AP2/ERF TFs were differentially expressed between control and CA treatments, with 28 upregulated and 23 downregulated. The addition of Si (CA vs CA + Si) resulted in 42 differentially expressed AP2/ERF TFs, maintaining a similar upregulation pattern with 26 upregulated and 16 downregulated. After 7 d of treatment, the control vs CA comparison revealed 46 AP2/ERF TFs with a shift toward downregulation (7 upregulated, 39 downregulated). However, the CA vs CA + Si comparison showed a strong positive response with 22 AP2/ERF TFs, predominantly upregulated (18 upregulated, 4 downregulated), suggesting that Si effectively counteracted the suppressive effects of prolonged CA stress.. WRKY participate in plant transcriptional reprogramming to cope with different stress environments[ 29 ]. After 2 d of treatment, 22 WRKY TFs were differentially expressed between control and CA, with 8 upregulated and 14 downregulated. Notably, the CA vs CA + Si comparison revealed 21 WRKY TFs with a positive response (20 upregulated, 1 downregulated). After 7 d of treatment, this pattern intensified, with all 22 WRKY TFs being upregulated in the control and CA comparison, while the CA and CA + Si comparison maintained high activation levels with 15 out of 16 WRKY TFs upregulated. This consistent upregulation pattern suggests that WRKY TFs play a crucial role in the stress defense mechanism activated by both CA stress and Si treatment. After 2 d of treatment, 19 bHLH TFs were differentially expressed between control and CA, showing predominantly down-regulation (4 upregulated, 15 downregulated). However, the CA vs CA + Si comparison revealed 23 bHLH TFs with a reversed pattern of mostly up-regulation (19 upregulated, 4 downregulated). After 7 d of treatment, the suppressive effect of CA became more pronounced, with 16 bHLH TFs (1 upregulated, 15 downregulated) in the control vs CA comparison. The CA vs CA + Si comparison identified only 5 bHLH TFs (3 upregulated, 2 downregulated) demonstrating the sustained protective effect of Si on bHLH gene expression. NAC are plant-specific TFs containing a highly conserved N-terminal domain, and several NAC TFs have been reported to participate in salt stress[ 30 ]. After 2 d of treatment, 29 NAC TFs were differentially expressed between control and CA, with the majority up-regulated (19 upregulated, 10 downregulated), suggesting an active stress response. The CA vs CA + Si comparison revealed 15 NAC TFs with predominantly positive regulation (11 upregulated, 4 downregulated). After 7 d of treatment, the control vs CA comparison showed 17 NAC TFs with mostly downregulation (2 upregulated, 15 downregulated), indicating a shift in the stress response over time. Remarkably, the CA vs CA + Si comparison identified only 2 NAC TFs genes, both of which were upregulated. 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. 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 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. Discussion Cinnamic acid, as a prominent autotoxic substance, significantly affecta the growth and development of many crops, including legumes[ 31 ], 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[ 32 , 33 ]. At present, Si application has become an effective foliar strategy to improve plant productivity and stress resistance. 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.Author Contributions. Cinnamic acid inhibits root growth and nodulation, but exogenous silicon alleviates this inhibition The root system, being the primary organ that interacts with soil-borne toxic substances, is particularly vulnerable to allelopathic compounds[ 34 ]. Although CA originates from crop root secretion, its excessive accumulation transforms it into a potent allelopathic substance that significantly impacts root growth[ 35 ]. Our findings demonstrate that CA directly affected soybean root dry weight, fresh root weight, and nodule number, consistent with previous studies showing that CA treatment reduces root length and dry weight in broad beans[ 36 ]. Root nodules hold special significance for leguminous crop growth and development, and CA accumulation inevitably affects nodulation in these crops. Autotoxic substances may inhibit the recognition or signaling of rhizobial nodulation factors in legumes. Additionally, these compounds may impair nodule function and activity, reducing nitrogen fixation efficiency and nitrogen supply capacity to legumes. Si plays a crucial role in inducing root nodule formation, which is essential for biological nitrogen fixation and plant growth, particularly in legumes Under salt and water stress conditions, Si significantly enhanced root nodulation and nitrogen fixation in sesame leguminous plants. Steiner et al.[ 37 ] observed a two-fold increase in soybean root nodule numbers following with Si fertilizer application. Furthermore, Tripathi et al.[ 38 ] revealed that Si application to soybean soil and leaves significantly increased both the number and size of root nodules, with significantly changes in root morphological characteristics compared with control plants[ 39 ]. Our study confirmed that exogenous Si added to nutrient solutions significantly improve root growth of soybean seedlings under CA stress. Effects of exogenous silicon on photosynthetic characteristics of soybean seedlings Photosynthesis provides essential materials and energy for plant growth, development and yield formation. Pn, Tr, Gs and Ci serve as important indicators of photosynthesis[ 40 ]. Chlorophyll fluorescence parameters reflect photosynthetic quantum efficiency regulation and the plant's ability to utilize light energy effectively. Many studies have shown that high concentrations of CA inhibit plant photosynthetic characteristics. For example, Zhang et al.[ 41 ] found that CA reduce Pn, Tr and Gs in treated plants. Yang et al.[ 39 ]reported that chlorophyll fluorescence parameters Fv/Fm, ΦPSII and qP of broad bean leaves significantly decreased under CA stress, with concurrent reductions in Pn and Gs, indicating obvious photosynthetic system damage. Similarly,Ma et al.[ 42 ]observed decreased trends in all major photosynthetic parameters in cucumber seedlings under CA treatment. This result is consistent with our research. There have been many reports on the improvement of photosynthetic characteristics of crops by exogenous Si application. Liang et al.[ 43 ] found that Si nanoparticles enhanced photosynthesis of cotton seedlings under salt and low temperature stress. Li et al.[ 44 ] found that Si significantly increased Pn in both salt-sensitive and salt-tolerant genotypes of cotton seedlings. Our results showed that exogenous Si application increased Pn, Tr, Gs and Ci in soybean seedlings under CA stress, indicating that exogenous Si effectively alleviates CA damage to photosynthetic system. Changes of antioxidant enzyme activity under exogenous silicon Reactive oxygen species (ROS) are inevitable byproducts of aerobic metabolism in plant cells. Plants have evolved complex enzymatic and non-enzymatic mechanisms to eliminate excess ROS. However, under stress conditions, the balance between intracellular ROS production and clearance becomes disrupted, resulting in oxidative stress[ 45 ]. Oxidative stress damages cellular proteins and biomembranes, impairs the antioxidant system and affects primary plant metabolic activities. Si enhances plant tolerance to oxidative stress by increasing antioxidant enzyme activities and reducing the production of ROS and lipid peroxidation. Si can enhance activities of SOD, CAT and GR, thereby alleviating the damage of oxidative stress [ 46 ]. Previous studies have shown that CA stress causes oxidative damage in various crops. Meng et al.[ 47 ] reported that CA induced oxidative stress in cucumber seedlings, and induced the enhancement of MDA, Pro, SOD and CAT activities. Zhang et al.[ 48 ] found that the autotoxic substance coumarin caused oxidative stress damage in alfalfa, accumulating large amount of H 2 O 2 , O 2 − , POD and APX. Wei et al. [ 49 ] found that exogenous Si application significantly enhanced antioxidant defense mechanisms in plants under cadmium stress. Beyond increasing POD and APX activities, exogenous Si treatment significantly increased the activities of antioxidant enzymes such as SOD, CAT, GR and GST[ 49 ]. Additionally, Si supplementation increased the contents of antioxidant substances ASA and cadmia-chelating related substances GSH, PCs and TP[ 49 ]. Our experimental results demonstrated that CA stress caused oxidative stress and membrane lipid peroxidation in the roots and leaves of soybean seedlings, while exogenous Si activated the activities of soybean antioxidant enzymes to enhance ROS removal capacity. This indicates that exogenous Si was participates in the regulating the soybean antioxidant enzyme system under CA stress and enhanced the tolerance of soybean 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[ 50 , 51 ]. 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 decreased 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 increased 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 intricate molecular mechanisms by which exogenous Si mitigates CA stress effects on soybean seedlings, particularly focusing on transcriptional regulation of genes involved in plant hormone signaling and phenylpropanoid biosynthesis pathways. The findings reveal that CA stress significantly alters the transcriptional landscape, predominantly downregulating genes associated with these pathways. However, Si application not only reverses the expression of a substantial proportion of these downregulated genes but also upregulates key stress-responsive genes. The upregulation of genes encoding enzymes such as PAL, HCT, and peroxidases in the phenylpropanoid biosynthesis pathway under Si treatment highlights Si's potential to enhance lignin, flavonoids and phenolic compounds synthesis, which are vital for plant defense mechanisms[ 52 ]. Similarly, the modulation of genes involved in plant hormone signaling, including DELLA proteins, GID1, and MYC2 transcription factors, underscores Si's role in fine-tuning hormonal stress responses[ 53 ]. The identification of key TFs such as MYB, AP2/ERF, WRKY, bHLH, and NAC, known to be pivotal in plant stress responses, further corroborates Si's protective role. These TFs likely orchestrate a complex regulatory network that enhances the plant's ability to withstand CA-induced stress[ 54 ]. The significant upregulation of WRKY TFs particular aligns with previous studies demonstrating their role in transcriptional reprogramming during stress[ 29 ]. Our comprehensive analysis demonstrates that exogenous Si mitigates CA stress in soybean seedlings through multiple coordinated mechanisms reversing the downregulation of critical genes, enhancing stress-responsive genes, modulating antioxidant enzyme activities, improving photosynthetic performance and enhancing flavonoid biosynthesis for better nodulation. This transcriptional reprogramming, mediated by key TFs and metabolic pathways, underscores Si's potential as an effective agent for improving plant stress tolerance. Conclusion Our study demonstrates that CA-induced autotoxic stress affects multiple physiological parameters in soybean seedlings, including stem, root biomassplant height, nodule number, photosynthetic capacity and antioxidant enzyme activities. Exogenous application of Si effectively counteracts these negative effects through complex molecular mechanisms. Transcriptome analysis revealed that 9,235 DEGs participate in various metabolic pathways and biosynthesis in response to exogenous Si under CA stress, including phenylpropanoid metabolism, nitrogen metabolism, plant hormone signal transduction, isoflavone biosynthesis, hydrogen peroxide metabolism and nodulation processes. Key transcription factor families including AP2/ERF, C2H2, MYB, NAC, bHLH and WRKY play crucial roles in mediating soybean toleranc to CA stress. Our results clearly indicate that Si application at appropriate concentrations is an effective strategy for alleviating autotoxic stress in soybean seedlings. These findings provide valuable insights for overcoming CA-induced autotoxic stress through the strategic use of Si in agricultural production system. 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 Declarations Supplementary Information Supplementary Table 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. 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). 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. Author details 1 College of Agriculture, Shanxi Agricultural University, Taigu, Shanxi 030801, China 2 College of Horticulture, Shanxi Agricultural University, Taigu, Shanxi 030801, China. 3 School of Innovation and Intrepreneurship, Shanxi Agricultural University, Taigu, Shanxi 030801, China. + Equal contribution and first authorship: These authors contributed equally to this work and share first authorship Publisher’sNote Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations References Kato-Noguchi H, Nakamura K, Okuda N. Involvement of an autotoxic compound in asparagus decline. J Plant Physiol. 2018;224:49–55. 10.1016/j.jplph.2018.03.005 . Yan SL, Cai B, Tang HL, Yuan Y, Ao S. Study on the allelopathic effects of different parts of bitter gourd. Journal of Agricultural Science & Technology; 2018. (1008 – 0864), 20(8). Wu B, Long Q, Gao Y, Wang Z, Shao T, Liu Y, et al. Comprehensive characterization of a time-course transcriptional response induced by autotoxins in Panax ginseng using RNA-Seq. BMC Genomics. 2015;16(1):1010. 10.1186/s12864-015-2151-7 . Liu MC, Zuo YJ, Liu YL. A new molecular identification method for soybean plants (Glycine Willd.) based on chloroplast whole genome nucleotide variation sites. Bot Res. 2024;13:124. Bellaloui N, Reddy KN, Bruns HA, Gillen AM, Mengistu A, Zobiole LH, et al. Soybean seed composition and quality: Interactions of environment, genotype, and management practices. Soybeans: Cultivation, Uses and Nutrition. New York, USA: Nova Science Publishers, Inc.; 2011. pp. 1–42. Liu X, Herbert SJ. Fifteen years of research examining cultivation of continuous soybean in northeast China: a review. Field Crops Res. 2002;79(1):1–7. Mehmood A, Hussain A, Irshad M, Hamayun M, Iqbal A, Rahman H, et al. Cinnamic acid as an inhibitor of growth, flavonoids exudation and endophytic fungus colonization in maize root. Plant Physiol Biochem. 2019;135:61–8. 10.1016/j.plaphy.2018.11.029 . Liu CW, Murray JD. The role of flavonoids in nodulation host-range specificity: an update. Plants. 2016;5(3):33. Feduraev P, Skrypnik L, Riabova A, Pungin A, Tokupova E, Maslennikov P, et al. Phenylalanine and tyrosine as exogenous precursors of wheat (Triticum aestivum L.) secondary metabolism through PAL-associated pathways. Plants. 2020;9(4):476. 10.3390/plants9040476 . Lin L, CHEN FANGJ, AI G, Y. Cloning and Bioinformatics of Chalcone Synthase Gene of Moringa oleifera. Fujian J Agricultural Sci. 2021;36(5):549–55. Nie HZ, Xue YC, Gao ZH. Research progress on hydroxylases in lignin biosynthesis. J Henan Agricultural Sci. 2008;37(4):5. Cen Z, Zheng Y, Guo Y, Yang S, Dong Y. Nitrogen fertilization in a faba bean–wheat intercropping system can alleviate the autotoxic effects in faba bean. Plants. 2023;12(6):1232. Ma L, Ma S, Chen G, Lu X, Chai Q, Li S. Mechanisms and mitigation strategies for the occurrence of continuous cropping obstacles of legumes in China. Agronomy. 2023;14(1):104. Lima RB, Salvador VH, dos Santos WD, Bubna GA, Finger-Teixeira A, Soares AR, et al. Enhanced lignin monomer production caused by cinnamic acid and its hydroxylated derivatives inhibits soybean root growth. PLoS ONE. 2013;8(12):e80542. 10.1371/journal.pone.0080542 . Salvador VH, Lima RB, dos Santos WD, Soares AR, Böhm PAF, Marchiosi R, et al. Cinnamic acid increases lignin production and inhibits soybean root growth. PLoS ONE. 2013;8(7):e69105. 10.1371/journal.pone.0069105 . Etesami H, Jeong BR. Silicon (Si): Review and future prospects on the action mechanisms in alleviating biotic and abiotic stresses in plants. Ecotoxicol Environ Saf. 2018;147:881–96. Sheng H, Chen S. Plant silicon-cell wall complexes: Identification, model of covalent bond formation and biofunction. Plant Physiol Biochem. 2020;155:13–9. 10.1016/j.plaphy.2020.07.020 . Rizwan M, Ali S, Ibrahim M, Farid M, Adrees M, Bharwana SA, et al. Mechanisms of silicon-mediated alleviation of drought and salt stress in plants: a review. Environ Sci Pollut Res. 2015;22(20):15416–31. 10.1007/s11356-015-5305-x . Debona D, Rodrigues FA, Datnoff LE. Silicon's role in abiotic and biotic plant stresses. Annu Rev Phytopathol. 2017;55:85–107. Lyu J, Jin N, Meng X, Jin L, Wang S, Xiao X, et al. Exogenous silicon alleviates the adverse effects of cinnamic acid-induced autotoxicity stress on cucumber seedling growth. Front Plant Sci. 2022;13:968514. 10.3389/fpls.2022.968514 . Gong H, Zhu X, Chen K, Wang S, Zhang C. Silicon alleviates oxidative damage of wheat plants in pots under drought. Plant Sci. 2005;169(2):313–21. 10.1016/j.plantsci.2005.02.023 . Yang Y, Liu Q, Wang GX, Wang XD, Guo JY. Germination, osmotic adjustment, and antioxidant enzyme activities of gibberellin-pretreated Picea asperata seeds under water stress. New Forest. 2010;39(2):231–43. 10.1007/s11056-009-9167-2 . Mu Y, Li Y, Zhang Y, Guo X, Song S, Huang Z, et al. A comparative study on the role of conventional, chemical, and nanopriming for better salt tolerance during seed germination of direct seeding rice. J Integr Agric. 2024;23(12):3998–4017. 10.1016/j.jia.2023.12.013 . Elstner EF, Heupel A. Formation of hydrogen peroxide by isolated cell walls from horseradish (Armoracia lapathifolia Gilib). Planta. 1976;130(2):175–80. Patterson BD, MacRae EA, Ferguson IB. Estimation of hydrogen peroxide in plant extracts using titanium (IV). Anal Biochem. 1984;139(2):487–92. Biswal B, Joshi PN, Raval MK, Biswal UC. (2011). Photosynthesis, a global sensor of environmental stress in green plants: stress signalling and adaptation. Curr Sci, 47–56. Shan X, Li Y, Jiang Y, Jiang Z, Hao W, Yuan Y. Transcriptome profile analysis of maize seedlings in response to high-salinity, drought and cold stresses by deep sequencing. Plant Mol biology Report. 2013;31(6):1485–91. 10.1007/s11105-013-0622-z . Stracke R, Werber M, Weisshaar B. The R2R3-MYB gene family in Arabidopsis thaliana. Curr Opin Plant Biol. 2001;4(5):447–56. Rushton PJ, Somssich IE, Ringler P, Shen QJ. WRKY transcription factors. Trends Plant Sci. 2010;15(5):247–58. 10.4161/psb.27700 . Mahmood K, El-Kereamy A, Kim SH, Nambara E, Rothstein SJ. ANAC032 positively regulates age-dependent and stress-induced senescence in Arabidopsis thaliana. Plant Cell Physiol. 2016;57(10):2029–46. Yang W, Guo Y, Li Y. Cinnamic acid toxicity on the structural resistance and photosynthetic physiology of faba bean Promoted the occurrence of Fusarium Wilt of faba bean, which was alleviated through wheat and faba bean intercropping[J]. Front Plant Sci. 2022;13:857780. Alamri S, Hu Y, Mukherjee S, Aftab T, Fahad S, Raza A, et al. Silicon-induced postponement of leaf senescence is accompanied by modulation of antioxidative defense and ion homeostasis in mustard (Brassica juncea) seedlings exposed to salinity and drought stress. Plant Physiol Biochem. 2020;157:47–59. Salim BBM, El-Yazied A, Salama A, Raza YAM, Osman A, H. S. Impact of silicon foliar application in enhancing antioxidants, growth, flowering and yield of squash plants under deficit irrigation condition. Annals Agricultural Sci. 2021;66(2):176–83. 10.1016/j.aoas.2021.12.003 . LIN KM, YE FM, LIN Y, LI QS. Research advances of phenolic functional mechanisms in soils and plants. Chin J Eco-Agriculture. 2010;18(5):1130–7. 10.3724/sp.j.1011.2010.01130 . Gao X, Zhang G, Hu Q, Xu S, Gong G. Y. (2013). Effects of cinnamic acid on growth and chlorophyll fluorescence parameters of Pisum sativum L. seedlings. Zhao Q, Chen L, Dong K, Dong Y, Xiao J. Cinnamic acid inhibited growth of faba bean and promoted the incidence of fusarium wilt. Plants. 2018;7(4):84. Steiner F, Zuffo AM, Bush A, Santos DMDS. Silicate fertilization potentiates the nodule formation and symbiotic nitrogen fixation in soybean1. Pesquisa Agropecuária Trop. 2018;48(3):212–21. 10.1590/1983-40632018v4851472 . Tripathi P, Na CI, Kim Y. Effect of silicon fertilizer treatment on nodule formation and yield in soybean (Glycine max L). Eur J Agron. 2021;122:126172. 10.1016/j.eja.2020.126172 . Yang W, Zhang Z, Yuan T, Li Y, Zhao Q, Dong Y. Intercropping improves faba bean photosynthesis and reduces disease caused by Fusarium commune and cinnamic acid-induced stress. BMC Plant Biol. 2024;24(1):650. 10.1186/s12870-024-05326-8 . Haider FU, Liqun C, Coulter JA, Cheema SA, Wu J, Zhang R, et al. Cadmium toxicity in plants: Impacts and remediation strategies. Ecotoxicol Environ Saf. 2021;211:111887. 10.1016/j.ecoenv.2020.111887 . Zhang Xiaoyan. Physiological and molecular mechanisms of response to autotoxicity coumarin in alfalfa (Medicago sativa L.) varieties. Gansu Agricultural University; 2022. Ma N, Chen B, Yang H. Photosynthetic fluorescence characteristics of cucumber seedlings and response of root antioxidant system to exogenous cinnamic acid. Jiangsu Agricultural Sci. 2020;48(12):113–9. Liang Y, Liu H, Fu Y, Li P, Li S, Gao Y. Regulatory effects of silicon nanoparticles on the growth and photosynthesis of cotton seedlings under salt and low-temperature dual stress. BMC Plant Biol. 2023;23(1):504. 10.1186/s12870-023-04509-z . Li L, Qi Q, Zhang H, Dong Q, Iqbal A, Gui H, Antioxidants et al. 11(8), 1520. 10.3390/antiox11081520 Zhang P, Huang H, Liu W, Zhang C. Physiological mechanisms of a wetland plant (Echinodorus osiris Rataj) to cadmium detoxification. Environ Sci Pollut Res. 2017;24(27):21859–66. 10.1007/s11356-017-9744-4 . Liang Y, Chen QIN, Liu Q, Zhang W, Ding R. Exogenous silicon (Si) increases antioxidant enzyme activity and reduces lipid peroxidation in roots of salt-stressed barley (Hordeum vulgareL). J Plant Physiol. 2003;160(10):1157–64. 10.1078/0176-1617-01065 . Meng X. The effect of exogenous silicon on cucumber seed germination and growth under cinnamic acid stress. Gansu Agricultural University; 2022. Zhang Z, Wu J, Xi Y, Zhang L, Gao Q, Wang-Pruski G. Effects of autotoxicity on seed germination, gas exchange attributes and chlorophyll fluorescence in melon seedlings. J Plant Growth Regul. 2022;41(3):993–1003. 10.1007/s00344-021-10355-w . Wei Xiaoman. The response of stem tumor mustard to cadmium stress and the physiological and biochemical mechanisms of silicon alleviating cadmium toxicity. Chongqing Three Gorges University; 2024. Abdel-Lateif K, Bogusz D, Hocher V. The role of flavonoids in the establishment of plant roots endosymbioses with arbuscular mycorrhiza fungi, rhizobia and Frankia bacteria. Plant Signal Behav. 2012;7(6):636–41. 10.4161/psb.20039 . Mollavali M, Perner H, Rohn S, Riehle P, Hanschen FS, Schwarz D. Nitrogen form and mycorrhizal inoculation amount and timing affect flavonol biosynthesis in onion (Allium cepa L). Mycorrhiza. 2018;28(1):59–70. 10.1007/s00572-017-0799-3 . Dixon RA, Achnine L, Kota P, Liu CJ, Reddy MS, Wang L. The phenylpropanoid pathway and plant defence—a genomics perspective. Mol Plant Pathol. 2002;3(5):371–90. 10.1046/j.1364-3703.2002.00131.x . Colebrook EH, Thomas SG, Phillips AL, Hedden P. The role of gibberellin signalling in plant responses to abiotic stress. J Exp Biol. 2014;217(1):67–75. 10.1242/jeb.089938 . Nakashima K, Takasaki H, Mizoi J, Shinozaki K, Yamaguchi-Shinozaki K. (2012). NAC transcription factors in plant abiotic stress responses. Biochimica et Biophysica Acta (BBA)-Gene Regulatory Mechanisms, 1819(2), 97–103. 10.1016/j.bbagrm.2011.10.005 Additional Declarations No competing interests reported. Supplementary Files Supplementaryfile.xlsx Cite Share Download PDF Status: Published Journal Publication published 06 Mar, 2026 Read the published version in BMC Plant Biology → Version 1 posted Editorial decision: Revision requested 11 Nov, 2025 Reviews received at journal 09 Nov, 2025 Reviewers agreed at journal 09 Nov, 2025 Reviewers agreed at journal 09 Nov, 2025 Reviews received at journal 07 Nov, 2025 Reviewers agreed at journal 06 Nov, 2025 Reviewers agreed at journal 06 Nov, 2025 Reviewers agreed at journal 05 Nov, 2025 Reviewers agreed at journal 04 Nov, 2025 Reviews received at journal 15 Sep, 2025 Reviewers agreed at journal 23 Aug, 2025 Reviewers agreed at journal 20 Aug, 2025 Reviewers agreed at journal 20 Aug, 2025 Reviewers agreed at journal 18 Aug, 2025 Reviewers agreed at journal 18 Aug, 2025 Reviewers invited by journal 18 Aug, 2025 Editor invited by journal 24 Jul, 2025 Editor assigned by journal 23 Jul, 2025 Submission checks completed at journal 23 Jul, 2025 First submitted to journal 19 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7165248","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":504567393,"identity":"34eb85d8-bdcd-4a58-b310-cc9c85916342","order_by":0,"name":"Xiaohuan Yang","email":"","orcid":"","institution":"Shanxi Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Xiaohuan","middleName":"","lastName":"Yang","suffix":""},{"id":504567394,"identity":"523e6fdf-88bf-4e25-87e8-03d6702e27c6","order_by":1,"name":"Zhichao Sun","email":"","orcid":"","institution":"Shanxi Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Zhichao","middleName":"","lastName":"Sun","suffix":""},{"id":504567395,"identity":"d0fb96c9-549a-49c5-b4e4-0dd3df998b41","order_by":2,"name":"Yaping Song","email":"","orcid":"","institution":"Shanxi Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Yaping","middleName":"","lastName":"Song","suffix":""},{"id":504567396,"identity":"c70d3cde-e517-456b-944d-d535102cd62f","order_by":3,"name":"Ailian Lu","email":"","orcid":"","institution":"Shanxi Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Ailian","middleName":"","lastName":"Lu","suffix":""},{"id":504567397,"identity":"3591d03c-6429-4f0e-bdbc-2ca1cb70af45","order_by":4,"name":"Fei Wu","email":"","orcid":"","institution":"Shanxi Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Fei","middleName":"","lastName":"Wu","suffix":""},{"id":504567398,"identity":"56e7eab4-a6c9-4c4c-be42-037231cbc753","order_by":5,"name":"Minghao Chen","email":"","orcid":"","institution":"Shanxi Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Minghao","middleName":"","lastName":"Chen","suffix":""},{"id":504567399,"identity":"54e4c212-7904-48e0-bcfe-8cee3533cea1","order_by":6,"name":"Xinghai Shi","email":"","orcid":"","institution":"Shanxi Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Xinghai","middleName":"","lastName":"Shi","suffix":""},{"id":504567400,"identity":"a55d9e00-b5dc-439b-b475-489b6ef39617","order_by":7,"name":"Jun Ren","email":"","orcid":"","institution":"Shanxi Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Jun","middleName":"","lastName":"Ren","suffix":""},{"id":504567401,"identity":"b8e16335-3a46-4740-ac76-ab752133c3fb","order_by":8,"name":"Xiuzhen Qin","email":"","orcid":"","institution":"Shanxi Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Xiuzhen","middleName":"","lastName":"Qin","suffix":""},{"id":504567402,"identity":"13be1e64-6054-47e3-b317-c7e013e4b38e","order_by":9,"name":"Jinhu H. Ma","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAsElEQVRIiWNgGAWjYFCCMwwHEipsePjZG4jXwnjgw5k0GcmeA0Rr4WE+OLPtsI3BDQciNeg2nj1wmLftPA/DDQbGDx9ziNBiduBcwmGec7d5GGc3MEvO3EaUljMGh3nKbvMwyxxgY+YlXgvbOR42iQQStByc0XaAh4ckLcBATuaR4DnYTKRfbpwx/pBQYWdvf7z54IePxGhhkDgAYzE2EKMeCPiJVTgKRsEoGAUjFwAAhuQ+01AHxJIAAAAASUVORK5CYII=","orcid":"","institution":"Shanxi Agricultural University","correspondingAuthor":true,"prefix":"","firstName":"Jinhu","middleName":"H.","lastName":"Ma","suffix":""}],"badges":[],"createdAt":"2025-07-19 15:08:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7165248/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7165248/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12870-026-08425-w","type":"published","date":"2026-03-06T15:57:07+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":89955758,"identity":"91414245-1a82-4027-ba04-bc1bbfbc17b7","added_by":"auto","created_at":"2025-08-26 21:45:46","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":208942,"visible":true,"origin":"","legend":"\u003cp\u003eEffects 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, 6 seedlings per treatment).\u003c/p\u003e\n\u003cp\u003eDifferent * denote statistically significant differences between treatments according to Duncan's test (p \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7165248/v1/9a5fa6ea7de53b8a744b14c1.jpg"},{"id":89955764,"identity":"77498e63-60b4-4039-a68c-24a79592fdaa","added_by":"auto","created_at":"2025-08-26 21:45:46","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":153970,"visible":true,"origin":"","legend":"\u003cp\u003eEffects 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, 6 seedlings per 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***).\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7165248/v1/710b71f5fa66e2d5dc248371.jpg"},{"id":89955782,"identity":"f7587228-d9d6-439f-a57e-124d7acd926a","added_by":"auto","created_at":"2025-08-26 21:45:47","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":146174,"visible":true,"origin":"","legend":"\u003cp\u003eSi 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 CO\u003csub\u003e2 \u003c/sub\u003econcentration (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).\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7165248/v1/8230c939526094ec62cd8992.jpg"},{"id":89956019,"identity":"be511238-8a9d-41dc-a61c-16942d473a8a","added_by":"auto","created_at":"2025-08-26 21:53:46","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":110094,"visible":true,"origin":"","legend":"\u003cp\u003eDifferential 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.\u003c/p\u003e","description":"","filename":"Picture4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7165248/v1/e3db2281fdee440d55264fe0.jpg"},{"id":89955761,"identity":"31466e1b-e65b-4012-bb03-871a7f926e48","added_by":"auto","created_at":"2025-08-26 21:45:46","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":196689,"visible":true,"origin":"","legend":"\u003cp\u003eGO 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 \u0026lt; 0.01) are categorized into Biological Process (BP, blue), Cellular Component (CC, orange), and Molecular Function (MF, red).\u003c/p\u003e","description":"","filename":"Picture5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7165248/v1/3aefd5d2efd7d66dd2e50d62.jpg"},{"id":89956028,"identity":"b4cb4559-91f8-4082-a7d1-a258dc8699ca","added_by":"auto","created_at":"2025-08-26 21:53:47","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":124201,"visible":true,"origin":"","legend":"\u003cp\u003eGO 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.\u003c/p\u003e","description":"","filename":"Picture6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7165248/v1/549ecbce5f76e4908f849c44.jpg"},{"id":89955768,"identity":"f23d72f6-2769-4c01-85be-f2fc4b570709","added_by":"auto","created_at":"2025-08-26 21:45:46","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":160992,"visible":true,"origin":"","legend":"\u003cp\u003eKEGG 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.\u003c/p\u003e","description":"","filename":"Picture7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7165248/v1/e262a72655dcd16c875725b4.jpg"},{"id":89955787,"identity":"fe6f60bd-f266-44d7-a166-b73e420e0d82","added_by":"auto","created_at":"2025-08-26 21:45:47","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":165694,"visible":true,"origin":"","legend":"\u003cp\u003eA Gene expression heatmap; B: Phenylpropanoid biosynthesis gene correlation network; C: Correlation network of plant hormone signaling genes.\u003c/p\u003e","description":"","filename":"Picture8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7165248/v1/ec4078436bf79563e17931f7.jpg"},{"id":89956027,"identity":"4f3d2113-8fc2-493c-94fc-11ba08eba266","added_by":"auto","created_at":"2025-08-26 21:53:47","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":98577,"visible":true,"origin":"","legend":"\u003cp\u003eTranscription 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.\u003c/p\u003e","description":"","filename":"Picture9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7165248/v1/a9f11c9bbc5b0004428afe96.jpg"},{"id":89955759,"identity":"bfc1fdf9-9994-4274-913d-118aa3992e69","added_by":"auto","created_at":"2025-08-26 21:45:46","extension":"jpg","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":188376,"visible":true,"origin":"","legend":"\u003cp\u003eExpression 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.\u003c/p\u003e","description":"","filename":"Picture10.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7165248/v1/1519cab981e28eef4b373273.jpg"},{"id":104250696,"identity":"47813fcc-52a3-418d-ab80-fe261cd92fd4","added_by":"auto","created_at":"2026-03-09 16:05:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2888361,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7165248/v1/5f774f58-ef74-4a63-abac-a0ac14878a81.pdf"},{"id":89956018,"identity":"89787a8d-0c77-42d2-b688-e0fadac2eebf","added_by":"auto","created_at":"2025-08-26 21:53:46","extension":"xlsx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":57926,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfile.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7165248/v1/795646d873c9b127dd6eb51f.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Transcriptome analysis revealed the mechanism of exogenous silicon alleviating allelopathic inhibition of cinnamic acid on soybean seedlings","fulltext":[{"header":"Background","content":"\u003cp\u003eAutotoxicity is a form of plant allelopathy[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], is widely distributed in legumes, Solanaceae, Cucurbit family, and Umbelliferaceae. Autotoxic substances are released into the environment from various plant parts of the crop through secretion, volatilization, rain leaching and decomposition of plant residues[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In continuous cultivation systems, these compounds can directly or indirectly inhibit the growth of the crop itself or its close relatives [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eSoybeans (\u003cem\u003eGlycine max\u003c/em\u003e (Linn.) Merr.) are one of the important grain crops in China, with global production exceeding 300\u0026nbsp;million tons[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Compared to cereal crops such as maize, rice, and wheat, soybeans produce seeds rich in proteins and lipids, making them exceptionally nutritious[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. 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[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eCinnamic acid (CA), a well-documented chemical allelopathic substance, has been extensively studied for its effects on crop growth. Research has shown that CA inhibit root growth, flavonoid secretion and endophytic fungal colonization of maize [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Flavonoids, which play an important role in root nodule in formation[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], represent a branch of phenylalanine metabolic pathway. Within this pathway, PAL, C4H and 4CL serve as key regulatory[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Additionally, CHS catalyzes the first and rate-limiting step in flavonoid biosynthesis, while HCT initiates the lignin synthesis pathway [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Cen et al. found that exogenous application of CA inhibited broad bean seed germination in a concentration-dependent manner[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Researchers have identified CA in above-ground tissues, culture substrate extracts and root secretions of legume crops, its accumulation represents a significant factor contributing to soybean continuous cropping obstacles. Ma et al. reported that CA accumulation during continuous cultivation of legume inhibits legume growth and ultimately affect yield[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Lima et al.[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]uggested that CA accumulation leads to reduced root growth and premature cell wall lignification. Salvador et al.[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] showed that exogenous CA inhibits soybean root growth while increasing IAA oxidase and Cinnamate-4 -Hydroxylase (C4H) activities. Current agricultural practices have shown traditional methods of overcoming continuous cropping barriers inefficient, and long-term rotation is becoming less feasible under existing cropping patterns. Therefore, novel approaches are urgently needed to address soybean continuous cropping obstacles and increase yield.\u003c/p\u003e\u003cp\u003eSilicon (Si) is an environmentally friendly element due to its non-corrosive and non-polluting nature. It can be applied to crops without the risk of harmful residues, making it an ideal fertilizer for ecologically sustainable agriculture[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Sheng et al. [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]suggested that beyond non-covalent interactions through amorphous silica, Si can form covalent bonds with plant cell wall components such as hemicelluloses, pectin and lignin. The covalently bound organosilicon may play a crucial role in plant cell wall structure and remodeling, influencing plant growth and resistance against biotic and abiotic stresses. Rizwan et al.[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] proposed that silicon application under both drought and salt stress can improve plant growth, biomass, photosynthetic pigments and yield quality. Daniel Debona et al.[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] reported that plants with high root or stem silicon concentrations show greater resistance to pest infestation and enhanced tolerance to abiotic stresses including drought, low temperature and metal toxicity. According to Lyu et al.[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], exogenous silicon significantly improve water status in cucumber leaves under CA-induced stress, promotes mineral element absorption, and reduces the inhibition of nitrogen metabolism-related enzymes caused by CA.\u003c/p\u003e\u003cp\u003eAlthough extensive studies have reported the effects of CA stress on crop growth and Si's role in alleviating abiotic plant stress, few have reported how CA specifically affects soybean seedling growth and development, whether Si can alleviate the autotoxicity of CA in soybean root secretions, or how Si influences soybean nodulation under CA stress. Therefore, this study uses CA to simulate soybean autotoxic stress, applying exogenous Si to alleviate CA-induced stress during early seedling growth. Transcriptomic analysis was used to explore the underlying physiological and molecular mechanisms, providing theoretical basis for soybean cultivation practices.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cb\u003eCultivation of the plant material\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSoybean (\u003cem\u003eGlycine max\u003c/em\u003e (L.)) \u0026ldquo;Zhonghuang 13\u0026rsquo;\u0026rsquo; 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. Low-nitrogen nutrient solution (60 mL) was applied every 3 d.\u003c/p\u003e\u003cp\u003e\u003cb\u003eRhizobium Cilture\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe USDA110 rhizobacteria were cultured using the YMA medium (Mannitol 10.0 g, Yeast Extract 3.0 g, Agar 15.0 g, NaCl 0.05 g, MgSO\u003csub\u003e4\u003c/sub\u003e.7H\u003csub\u003e2\u003c/sub\u003eO 0.2 g, KH\u003csub\u003e2\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e 0.25 g, K\u003csub\u003e2\u003c/sub\u003eHPO\u003csub\u003e4\u003c/sub\u003e 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 OD value reached 0.16\u0026ndash;0.2.\u003c/p\u003e\u003cp\u003e\u003cb\u003eRhizobium Inoculation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWhen the first true leaf fully unfolded, plants were inoculated with 30 ml of USDA110 bacterial suspension (OD\u003csub\u003e600\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.16\u0026ndash;0.2) along the root system. Greenhouse cultivation, with regular observations of the formation of nodules during the process.\u003c/p\u003e\u003cp\u003e\u003cb\u003eExperimental design\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSoybean seedlings were divided into three treatment groups: control group (CK), CA stress group (4mM CA), CA stress combined with sodium silicate treatment group (4 mM CA\u0026thinsp;+\u0026thinsp;20 mM Si). Plants were cultivated in the greenhouse of Shanxi Agricultural University. Five uniform seeds were planted in each pot (7 cm diameter \u0026times; 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.\u003c/p\u003e\u003cp\u003ePlant morphology, root nodulation and enzyme activity were determined at 2 d, 7 d and 14 d. Biomass of seedlings was measured at 14 d of growth. Soybean root samples for transcriptome sequencing were taken at 2 d and 7 d from each treatment, immediately frozen in liquid nitrogen and stored at -80℃. Each treatment included three biological replicates. During cultivation, the low nitrogen nutrient solution (60mL) was applied once.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePhenotypic determination\u003c/b\u003e\u003c/p\u003e\u003cp\u003eRepresentative seedlings from each treatment were scanned for imaging. Seeding height was measured using a ruler. The seedings 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.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePhysiological index determinatio\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePhenylalaninase 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 determined using commercial assay kits from Beijing Baoruyi Biotechnology Co., Ltd.\u003c/p\u003e\u003cp\u003eEnzyme solution extraction followed the method of Gong et al.[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]with modifications. Superoxide dismutase (SOD) activity was determined by the nitroblue tetrazolium (NBT) method[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Peroxidase (POD) and catalase (CAT) activities were determined according to Yang et al.[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Malondialdehyde (MDA) content was determined by thiobarbituric acid method[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. All samples were cryogenically frozen in liquid nitrogen with three technical repeats per treatment.\u003c/p\u003e\u003cp\u003eSuperoxide (O\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e) content was determined according to Elstner et al.[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Plant material (0.2 g) was homogenated in phosphate buffer on ice, centrifuged at 10000 r\u0026middot;min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e 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.\u003c/p\u003e\u003cp\u003eHydrogen peroxide (H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e) content was determined according to Patterson et al. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Plant material (0.2 g) was homogenized with 4 mL 0.1% trichloroacetic acid (TCA) on ice, centrifuged at 3000 r\u0026middot;min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e 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.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePhotosynthetic characteristics\u003c/b\u003e\u003c/p\u003e\u003cp\u003eLeaves from same position on plants from different treatments were selected for were measured for photosynthetic measurements under natural light using an LI-6800 portable photosynthesizer (LI-COR Corporation, USA). The photosynthetically active radiation (PAR) was set at 500 \u0026micro;mol\u0026middot;m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e\u0026middot;s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e with 50% relative humidity (RH). Net photosynthetic rate (Pn, \u0026micro;mol\u0026middot;m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e\u0026middot;s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), stomatal conductance (Gsw, mol\u0026middot;m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e\u0026middot;s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), transpiration rate (Tr, mmol H\u003csub\u003e2\u003c/sub\u003eO\u0026middot;m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e\u0026middot;s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and intercellular CO\u003csub\u003e2\u003c/sub\u003e concentration (Ci, \u0026micro;mol CO\u003csub\u003e2\u003c/sub\u003e\u0026middot;mol\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) 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).\u003c/p\u003e\u003cp\u003e\u003cb\u003eTranscriptome analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eRoots samples from plants treated with CA and CA\u0026thinsp;+\u0026thinsp;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. Map clean reads were mapped to soybeans (\u003cem\u003eGlycine max\u003c/em\u003e (L.)) on the reference genome (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://ftp.ncbi.nlm.nih.gov/genomes/all/GCA/014/282/085/GCA_014282085.1_WHFS_GmZH13_1.0/\u003c/span\u003e\u003cspan address=\"https://ftp.ncbi.nlm.nih.gov/genomes/all/GCA/014/282/085/GCA_014282085.1_WHFS_GmZH13_1.0/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). 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| \u0026ge; 1, and FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05. DEGs were functionally annotated using the GO (Gene Ontology, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://geneontology.org/\u003c/span\u003e\u003cspan address=\"http://geneontology.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) database and KEGG (Kyoto Encyclopedia of Genes and Genomes, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.genome.jp/kegg\u003c/span\u003e\u003cspan address=\"https://www.genome.jp/kegg\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) database to identify significantly enriched biological processes and metabolic pathways.\u003c/p\u003e\u003cp\u003e\u003cb\u003eReal-time quantitative PCR\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTwelve 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 \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Samples were identical to those used for transcriptome analysis, including 2 d and 7 d samples from CK, CA, and CA\u0026thinsp;+\u0026thinsp;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\u003csup\u003e\u0026minus;ΔΔCt\u003c/sup\u003e method.\u003c/p\u003e\u003cp\u003e\u003cb\u003eQuantitative and statistical analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eData 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\u0026rsquo;s multiple range test (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) was performed using SPSS23.0. All data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eEffects of exogenous sodium silicate on growth phenotype of soybean seedlings under cinnamic acid stress\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe first investigated the effects of Si treatment on plant growth under CA stress. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, CA stress significantly reduced the biomass of soybean seedlings. Compared with the control group, aboveground dry weight (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC), underground dry weight (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE), plant height (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF), nodule number (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eG) and nodule dry weight(Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eI) of seedlings decreased by 40.09%, 37.02%, 29.79%, 61.62% and 53.75%, respectively, with all differences being statistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;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.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC), underground dry weight (36.33%, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE), plant height (32.04%, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF), nodal number (105%, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eG) and nodal dry weight (62.39%, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eI) compared to plants subjected to CA stress alone.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eDifferent * denote statistically significant differences between treatments according to Duncan's test (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003cp\u003e\u003cb\u003eEffects of exogenous sodium silicate on physiology of soybean seedlings under cinnamic acid stress\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSubsequently, we analyzed antioxidant enzyme activities, oxidative stress markers, and key enzymes involved in phenylpropanoid metabolism. Compared with CA treatment, the CA\u0026thinsp;+\u0026thinsp;Si treatment significantly reduced oxidative stress markers, with MDA content, O\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e production, and H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e levels decreasing by 40.95%, 52.30%, and 41.20%, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA-C). Correspondingly, antioxidant enzyme activities were increased, with SOD, POD and CAT activities increasing by 107.83%, 47.90% and 119.08%, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD-F).\u003c/p\u003e\u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eG-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%. Furthermore, compared to CA treatment alone, CA\u0026thinsp;+\u0026thinsp;Si treatment significantly increased TFC by 16.70%, and decreased lignin content by 40.03% (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eL-M).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eSi improved photosynthetic efficiency and chlorophyll fluorescence parameters in soybean seedlings under CA stress\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAs shown in Fig.\u0026nbsp;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.\u0026nbsp;3A-D).\u003c/p\u003e\u003cp\u003eChlorophyll fluorescence parameters serve as sensitive intrinsic indicators that reveal plant photosynthetic effciency and physiological status under varying environment conditions[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. As shown in Fig.\u0026nbsp;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.\u003c/p\u003e\u003cp\u003e\u003cb\u003eFigure\u0026nbsp;3\u003c/b\u003e 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 CO\u003csub\u003e2\u003c/sub\u003e 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).\u003c/p\u003e\u003cp\u003e\u003cb\u003eTranscriptomic analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo 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\u0026thinsp;+\u0026thinsp;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\u0026thinsp;+\u0026thinsp;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\u0026thinsp;+\u0026thinsp;Si reversed this pattern when compared with CA treatment alone, resulting in significant upregulation of many differentially expressed genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003eE).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eGO enrichment analysis of differentially expressed genes\u003c/b\u003e\u003c/p\u003e\u003cp\u003eUnder CA treatments after 2 d DEGs were distributed across 40 subgroups,with biological processes accounting for 56.78%, cellular components accounting for 17.13% and molecular functions accounting for 26.09%. Biological process were significantly enriched in \"metabolic process\", \"cellular process\", \"stimulus response\", \"biological regulation\" and \"developmental process\". Cellular components showed significant enrichment in \"anatomical entities of cells\" and \"complexes of proteins\". Molecular functions were significantly enriched in \"binding\", \"catalytic activity\", \"transporter activity\", \"transcriptional regulator activity\", \"molecular functional regulator activity\" and \"ATP-dependent activity\" (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). In the CA 2 d vs. CA\u0026thinsp;+\u0026thinsp;Si 2 d comparison, DEGs were distributed across 37 subgroups, with biological processes accounting for 56.95%, cellular components accounting for 17.18% and molecular functions accounting for 25.86%. The main categories of GO items are similar to CK and CA in 2d(Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). In the CA 7 d vs. control,DEGs were distributed across 37 subgroups, with biological processes accounting for 59.67%, cellular components accounting for 16.28% and molecular functions accounting for 24.05%. (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). In the CA\u0026thinsp;+\u0026thinsp;Si 7 d vs. CA 7 d comparison, DEGs were distributed across 37 subgroups, with biological processes accounting for 55.75%, cellular components accounting for 18.30%, and molecular functions accounting for 25.95%. The classification of GO item are similar to CK and CA in 2d (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eD).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eGO enrichment analysis of differentially expressed genes between different treatments\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo further analyze the function of DEGs in soybean nodules treated with exogenous Si, pathway analysis was conducted based on the GO database. GO enrichment analysis showed (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e6\u003c/span\u003e) that exogenous Si application regulated the metabolic processes of phenylpropanoid and hydrogen peroxide after 2 d, and hypoxia response and nodulation processes after 7 d (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Compared with CA treatment alone, CA\u0026thinsp;+\u0026thinsp;Si treatment regulated 64 phenylpropanol metabolism genes and 50 hydrogen peroxide metabolism genes in 2 d. There were 31 hypoxia response genes and 24 nodulation process related genes after 7 d.(Supplementary Table S3)\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eKEGG enrichment analysis of differentially expressed genes\u003c/b\u003e\u003c/p\u003e\u003cp\u003eEnrichment analysis was performed to identify the major differential biological pathways associated with DEGs in soybean seedlings, with results summarized in Supplementary Table S4-S5. In the CK vs CA comparisons after 2 d, 3,532 DEGs were annotated to 125 metabolic pathways. Among these, 1,437 upregulated DEGs were mapped to 112 metabolic pathways, while 2,095 down-regulated DEGs were mapped to 110 metabolic pathways. The pathways analysis revealed that 15 metabolic pathways contained exclusively upregulated DEGs, 13 pathways contained exclusively downregulated DEGs, and the majority (97 pathways) contained both upregulated and downregulated DEGs. In contrast, the CA vs CA\u0026thinsp;+\u0026thinsp;Si comparison showed 2504 DEGs annotations to 117 metabolic pathways. Of these, 1,832 upregulated DEGs were mapped to 104 metabolic pathways, and 672 downregulated DEGs were mapped to 88 metabolic pathways. Among the 117 metabolic pathways, 29 metabolic pathways with exclusively upregulated DEGs, 13 metabolic pathways with exclusively downregulated DEGs, and 75 metabolic pathways containing both upregulated and downregulated DEGs.\u003c/p\u003e\u003cp\u003eAfter 7 d, the CK vs CA comparison revealed 1,933 DEGs were mapped to 106 metabolic pathways. Among these, 616 upregulated DEGs were mapped to 79 metabolic pathways, while 1,317 downregulated DEGs were mapped with 93 metabolic pathways. Of the 106 metabolic pathways, 13 contained exclusively upregulated DEGs, 27 contained exclusively downregulated DEGs, and 66 contained both upregulated and downregulated DEGs. Similarly, in the CA vs CA\u0026thinsp;+\u0026thinsp;Si comparison, 1,266 DEGs were mapped to 110 metabolic pathways. Among these, 754 upregulated DEGs were mapped to 97 metabolic pathways, and 512 downregulated DEGs were mapped to77 metabolic pathways. Among the 110 metabolic pathways, 33 metabolic pathways with exclusively upregulated DEGs, 13 metabolic pathways with exclusively downregulated DEGs, and 64 metabolic pathways containing both upregulated and downregulated genes.\u003c/p\u003e\u003cp\u003eKEGG enrichment analysis identified the top 20 significant enriched pathways across the three different treatments after 2 d and 7 d (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e7\u003c/span\u003e, 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.\u003c/p\u003e\u003cp\u003eTo further identify the involvement of Si mediated CA stress response genes, we focused on specific pathways with upregulated DEGs in the CA vs CA\u0026thinsp;+\u0026thinsp;Si comparison groups at both time points. Photosynthesis-antenna proteins, nitrogen metabolism, phenylpropanoid biosynthesis, isoflavonoid biosynthesis, secondary metabolite biosynthesis and carotenoid biosynthesis were significantly enriched.\u003c/p\u003e\u003cp\u003eThe KEGG enrichment analysis revealed distinct temporal regulation patterns in response to silicon treatment. After 2 d, MAPK signaling pathways-plant, plant hormone signal transduction, plant pathogen interaction, isoflavone biosynthesis, phenylpropanoid biosynthesis, α-linolenic acid metabolism and nitrogen metabolism were upregulated, while protein processing in the endoplasmic reticulum and biotin metabolism were downregulated. After 7 d, MAPK signaling pathways-plant, nitrogen metabolism, phenylpropanoid biosynthesis, isoflavone biosynthesis, carotenoid biosynthesis and cysteine and methionine metabolism were upregulated, whereas photosynthesis and glucosinolide biosynthesis were downregulated.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eRegulation of plant hormone signaling and phenylpropanoid biosynthesis by exogenous Si in soybean\u003c/b\u003e\u003c/p\u003e\u003cp\u003eGene 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.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e8\u003c/span\u003eA) 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.\u003c/p\u003e\u003cp\u003ePlant 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.\u003c/p\u003e\u003cp\u003eTo elucidate the gene regulatory network underlying soybean responses to CA stress in the presence of Si (Si\u0026thinsp;+\u0026thinsp;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.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e8\u003c/span\u003eB). 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.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e8\u003c/span\u003eC). These genes encode TCH4, protein phosphatase 2C (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.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eTranscription factor analysis of differentially expressed genes\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTranscription factors (TFs) serve as upstream regulators that control gene expression in plant metabolic pathways and play crucial roles in plant stress tolerance responses[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. In this study, we identified key TF mediatingSi to alleviate the effects of CA stress effects in soybeans through differential expression analysis after 2 d and 7 d of treatment (Supplement Table\u0026nbsp;8 and Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). 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). When comparing CA treatment alone with CA\u0026thinsp;+\u0026thinsp;Si treatment, 256 TF showed differential expression. The same six TF families dominated this response, accounted for 60.55% of the differentially expressed TFs: MYB (41), C2H2 (13), WRKY (21), bHLH (23), AP2/ERF (42) and NAC (15). After 7 d of treatment, the transcriptional response became more focused. Between control and CA treatments, 228 TFs were differentially expressed across 20 homologous groups. The six major TF families maintained their dominance, representing 60.98% of the total response: AP2/ERF (46), C2H2 (16), MYB (22), WRKY (22), bHLH (16) and NAC (17). The comparison between CA and CA\u0026thinsp;+\u0026thinsp;Si treatments revealed 112 differentially expressed TFs distributed across 20 categories. The top six TF families accounted for 58.04% of this response: MYB (16), C2H2 (4), WRKY (16), bHLH (5), AP2/ERF (22) and NAC (2). The MYB transcription factor family consist of functionally diverse proteins found in all eukaryotes, with most MYB proteins involved in regulating cellular processes and stress responses in plants[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. After 2 d of treatment, comparison between control and CA revealed 62 MYB TFs, with 17 upregulated and 45 downregulated. In contrast, the CA vs CA\u0026thinsp;+\u0026thinsp;Si comparison identified 41 MYB TFs, showing a predominantly positive response with 35 upregulated and only 6 downregulated. After 7 d of treatment, the response became more focused, with 22 MYB TFs differentially expressed between CK and CA, (3 upregulated, 19 downregulated), while the CA and CA\u0026thinsp;+\u0026thinsp;Si comparison showed 16 MYB TFs with 10 upregulated and 6 downregulated. These results indicate that Si treatment significantly enhanced MYB gene expression, particularly during the early response phase. After 2 d of treatment, 51 AP2/ERF TFs were differentially expressed between control and CA treatments, with 28 upregulated and 23 downregulated. The addition of Si (CA vs CA\u0026thinsp;+\u0026thinsp;Si) resulted in 42 differentially expressed AP2/ERF TFs, maintaining a similar upregulation pattern with 26 upregulated and 16 downregulated. After 7 d of treatment, the control vs CA comparison revealed 46 AP2/ERF TFs with a shift toward downregulation (7 upregulated, 39 downregulated). However, the CA vs CA\u0026thinsp;+\u0026thinsp;Si comparison showed a strong positive response with 22 AP2/ERF TFs, predominantly upregulated (18 upregulated, 4 downregulated), suggesting that Si effectively counteracted the suppressive effects of prolonged CA stress.. WRKY participate in plant transcriptional reprogramming to cope with different stress environments[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. After 2 d of treatment, 22 WRKY TFs were differentially expressed between control and CA, with 8 upregulated and 14 downregulated. Notably, the CA vs CA\u0026thinsp;+\u0026thinsp;Si comparison revealed 21 WRKY TFs with a positive response (20 upregulated, 1 downregulated). After 7 d of treatment, this pattern intensified, with all 22 WRKY TFs being upregulated in the control and CA comparison, while the CA and CA\u0026thinsp;+\u0026thinsp;Si comparison maintained high activation levels with 15 out of 16 WRKY TFs upregulated. This consistent upregulation pattern suggests that WRKY TFs play a crucial role in the stress defense mechanism activated by both CA stress and Si treatment. After 2 d of treatment, 19 bHLH TFs were differentially expressed between control and CA, showing predominantly down-regulation (4 upregulated, 15 downregulated). However, the CA vs CA\u0026thinsp;+\u0026thinsp;Si comparison revealed 23 bHLH TFs with a reversed pattern of mostly up-regulation (19 upregulated, 4 downregulated). After 7 d of treatment, the suppressive effect of CA became more pronounced, with 16 bHLH TFs (1 upregulated, 15 downregulated) in the control vs CA comparison. The CA vs CA\u0026thinsp;+\u0026thinsp;Si comparison identified only 5 bHLH TFs (3 upregulated, 2 downregulated) demonstrating the sustained protective effect of Si on bHLH gene expression. NAC are plant-specific TFs containing a highly conserved N-terminal domain, and several NAC TFs have been reported to participate in salt stress[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. After 2 d of treatment, 29 NAC TFs were differentially expressed between control and CA, with the majority up-regulated (19 upregulated, 10 downregulated), suggesting an active stress response. The CA vs CA\u0026thinsp;+\u0026thinsp;Si comparison revealed 15 NAC TFs with predominantly positive regulation (11 upregulated, 4 downregulated). After 7 d of treatment, the control vs CA comparison showed 17 NAC TFs with mostly downregulation (2 upregulated, 15 downregulated), indicating a shift in the stress response over time. Remarkably, the CA vs CA\u0026thinsp;+\u0026thinsp;Si comparison identified only 2 NAC TFs genes, both of which were upregulated.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eqRT-PCR validation of soybean DEGs treated with sodium silicate under cinnamic acid stress\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo validate the reliability and accuracy of our RNA-seq data, twelve DEGs were randomly selected for quantitative real-time PCR (qRT-PCR) analysis. 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.\u0026nbsp;10). 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.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eCinnamic acid, as a prominent autotoxic substance, significantly affecta the growth and development of many crops, including legumes[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], 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[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. At present, Si application has become an effective foliar strategy to improve plant productivity and stress resistance. 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.Author Contributions.\u003c/p\u003e\u003cp\u003e\u003cb\u003eCinnamic acid inhibits root growth and nodulation, but exogenous silicon alleviates this inhibition\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe root system, being the primary organ that interacts with soil-borne toxic substances, is particularly vulnerable to allelopathic compounds[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Although CA originates from crop root secretion, its excessive accumulation transforms it into a potent allelopathic substance that significantly impacts root growth[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Our findings demonstrate that CA directly affected soybean root dry weight, fresh root weight, and nodule number, consistent with previous studies showing that CA treatment reduces root length and dry weight in broad beans[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Root nodules hold special significance for leguminous crop growth and development, and CA accumulation inevitably affects nodulation in these crops. Autotoxic substances may inhibit the recognition or signaling of rhizobial nodulation factors in legumes. Additionally, these compounds may impair nodule function and activity, reducing nitrogen fixation efficiency and nitrogen supply capacity to legumes.\u003c/p\u003e\u003cp\u003eSi plays a crucial role in inducing root nodule formation, which is essential for biological nitrogen fixation and plant growth, particularly in legumes Under salt and water stress conditions, Si significantly enhanced root nodulation and nitrogen fixation in sesame leguminous plants. Steiner et al.[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] observed a two-fold increase in soybean root nodule numbers following with Si fertilizer application. Furthermore, Tripathi et al.[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] revealed that Si application to soybean soil and leaves significantly increased both the number and size of root nodules, with significantly changes in root morphological characteristics compared with control plants[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Our study confirmed that exogenous Si added to nutrient solutions significantly improve root growth of soybean seedlings under CA stress.\u003c/p\u003e\u003cp\u003e\u003cb\u003eEffects of exogenous silicon on photosynthetic characteristics of soybean seedlings\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePhotosynthesis provides essential materials and energy for plant growth, development and yield formation. Pn, Tr, Gs and Ci serve as important indicators of photosynthesis[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Chlorophyll fluorescence parameters reflect photosynthetic quantum efficiency regulation and the plant's ability to utilize light energy effectively. Many studies have shown that high concentrations of CA inhibit plant photosynthetic characteristics. For example, Zhang et al.[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] found that CA reduce Pn, Tr and Gs in treated plants. Yang et al.[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]reported that chlorophyll fluorescence parameters Fv/Fm, ΦPSII and qP of broad bean leaves significantly decreased under CA stress, with concurrent reductions in Pn and Gs, indicating obvious photosynthetic system damage. Similarly,Ma et al.[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]observed decreased trends in all major photosynthetic parameters in cucumber seedlings under CA treatment. This result is consistent with our research. There have been many reports on the improvement of photosynthetic characteristics of crops by exogenous Si application. Liang et al.[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e] found that Si nanoparticles enhanced photosynthesis of cotton seedlings under salt and low temperature stress. Li et al.[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] found that Si significantly increased Pn in both salt-sensitive and salt-tolerant genotypes of cotton seedlings. Our results showed that exogenous Si application increased Pn, Tr, Gs and Ci in soybean seedlings under CA stress, indicating that exogenous Si effectively alleviates CA damage to photosynthetic system.\u003c/p\u003e\u003cp\u003e\u003cb\u003eChanges of antioxidant enzyme activity under exogenous silicon\u003c/b\u003e\u003c/p\u003e\u003cp\u003eReactive oxygen species (ROS) are inevitable byproducts of aerobic metabolism in plant cells. Plants have evolved complex enzymatic and non-enzymatic mechanisms to eliminate excess ROS. However, under stress conditions, the balance between intracellular ROS production and clearance becomes disrupted, resulting in oxidative stress[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Oxidative stress damages cellular proteins and biomembranes, impairs the antioxidant system and affects primary plant metabolic activities. Si enhances plant tolerance to oxidative stress by increasing antioxidant enzyme activities and reducing the production of ROS and lipid peroxidation. Si can enhance activities of SOD, CAT and GR, thereby alleviating the damage of oxidative stress [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Previous studies have shown that CA stress causes oxidative damage in various crops. Meng et al.[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e] reported that CA induced oxidative stress in cucumber seedlings, and induced the enhancement of MDA, Pro, SOD and CAT activities. Zhang et al.[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e] found that the autotoxic substance coumarin caused oxidative stress damage in alfalfa, accumulating large amount of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, O\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e, POD and APX. Wei et al. [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e] found that exogenous Si application significantly enhanced antioxidant defense mechanisms in plants under cadmium stress. Beyond increasing POD and APX activities, exogenous Si treatment significantly increased the activities of antioxidant enzymes such as SOD, CAT, GR and GST[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Additionally, Si supplementation increased the contents of antioxidant substances ASA and cadmia-chelating related substances GSH, PCs and TP[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Our experimental results demonstrated that CA stress caused oxidative stress and membrane lipid peroxidation in the roots and leaves of soybean seedlings, while exogenous Si activated the activities of soybean antioxidant enzymes to enhance ROS removal capacity. This indicates that exogenous Si was participates in the regulating the soybean antioxidant enzyme system under CA stress and enhanced the tolerance of soybean to CA.\u003c/p\u003e\u003cp\u003e\u003cb\u003eBiosynthesis of flavonoids and their role in nodulation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFlavonoids 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[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. 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 decreased 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 increased 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.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTranscriptome analysis revealed the mechanism of alleviating allelopathic inhibition of cinnamic acid on soybean seedlings by exogenous silicon\u003c/b\u003e\u003c/p\u003e\u003cp\u003eOur transcriptome analysis revealed the intricate molecular mechanisms by which exogenous Si mitigates CA stress effects on soybean seedlings, particularly focusing on transcriptional regulation of genes involved in plant hormone signaling and phenylpropanoid biosynthesis pathways. The findings reveal that CA stress significantly alters the transcriptional landscape, predominantly downregulating genes associated with these pathways. However, Si application not only reverses the expression of a substantial proportion of these downregulated genes but also upregulates key stress-responsive genes.\u003c/p\u003e\u003cp\u003eThe upregulation of genes encoding enzymes such as PAL, HCT, and peroxidases in the phenylpropanoid biosynthesis pathway under Si treatment highlights Si's potential to enhance lignin, flavonoids and phenolic compounds synthesis, which are vital for plant defense mechanisms[\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Similarly, the modulation of genes involved in plant hormone signaling, including DELLA proteins, GID1, and MYC2 transcription factors, underscores Si's role in fine-tuning hormonal stress responses[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe identification of key TFs such as MYB, AP2/ERF, WRKY, bHLH, and NAC, known to be pivotal in plant stress responses, further corroborates Si's protective role. These TFs likely orchestrate a complex regulatory network that enhances the plant's ability to withstand CA-induced stress[\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. The significant upregulation of WRKY TFs particular aligns with previous studies demonstrating their role in transcriptional reprogramming during stress[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eOur comprehensive analysis demonstrates that exogenous Si mitigates CA stress in soybean seedlings through multiple coordinated mechanisms reversing the downregulation of critical genes, enhancing stress-responsive genes, modulating antioxidant enzyme activities, improving photosynthetic performance and enhancing flavonoid biosynthesis for better nodulation. This transcriptional reprogramming, mediated by key TFs and metabolic pathways, underscores Si's potential as an effective agent for improving plant stress tolerance.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur study demonstrates that CA-induced autotoxic stress affects multiple physiological parameters in soybean seedlings, including stem, root biomassplant height, nodule number, photosynthetic capacity and antioxidant enzyme activities. Exogenous application of Si effectively counteracts these negative effects through complex molecular mechanisms. Transcriptome analysis revealed that 9,235 DEGs participate in various metabolic pathways and biosynthesis in response to exogenous Si under CA stress, including phenylpropanoid metabolism, nitrogen metabolism, plant hormone signal transduction, isoflavone biosynthesis, hydrogen peroxide metabolism and nodulation processes. Key transcription factor families including AP2/ERF, C2H2, MYB, NAC, bHLH and WRKY play crucial roles in mediating soybean toleranc to CA stress. Our results clearly indicate that Si application at appropriate concentrations is an effective strategy for alleviating autotoxic stress in soybean seedlings. These findings provide valuable insights for overcoming CA-induced autotoxic stress through the strategic use of Si in agricultural production system.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCinnamic acid\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePAL\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePhenylalaninammo-nialyase\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eC4H\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ecinnamate-4-hydroxylase\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e4CL\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003e4-coumaric acid CoA ligase\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCHS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003echalketone synthetase\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHCT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eshikimic acid/quinic acid hydroxycinnamyl transferase\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTFC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003elignin and total flavonoids content\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSOD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eSuperoxide dismutase\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eNBT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003enitroblue tetrazolium\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePOD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePeroxidase\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCAT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ecatalase\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eMDA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eMalondialdehyde\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eO2\u0026minus;\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eSuperoxide\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eH2O2\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eHydrogen peroxide\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTCA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003etrichloroacetic acid\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eSupplementary Information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSupplementary Table\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThanks 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.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eZhichao Sun\u003c/strong\u003e and \u003cstrong\u003eXiaohuan Yang\u003c/strong\u003e: Conceptualization, Methodology, Data Curation, Writing - Original Draft, Writing - Review \u0026amp; Editing,Visualization, Investigation. \u003cstrong\u003eYaping Song\u003c/strong\u003e: Methodology, Writing - Review \u0026amp; Editing, Visualization, Investigation. \u003cstrong\u003eAilian Lu:\u003c/strong\u003e Writing - Review \u0026amp; Editing, Visualization, Validation. \u003cstrong\u003eFei Wu\u003c/strong\u003e: Writing - Review \u0026amp; Editing, Validation. \u003cstrong\u003eMinghao Chen\u003c/strong\u003e: Writing - Review \u0026amp; Editing, Validation. \u003cstrong\u003eXinghai Shi\u003c/strong\u003e: Writing - Review \u0026amp; Editing. \u003cstrong\u003eJun Ren\u003c/strong\u003e: Writing - Review \u0026amp; Editing. \u003cstrong\u003eXiuzhen Qin\u003c/strong\u003e: Writing - Review \u0026amp; Editing. \u003cstrong\u003eJinhu Ma\u003c/strong\u003e: Funding acquisition, Writing - Review \u0026amp; Editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research is supported by the project of the central government guiding local science and technology development fund in Shanxi Province (YDZJSX2024D039).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe 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.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eCollege of Agriculture, Shanxi Agricultural University, Taigu, Shanxi 030801, China\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u0026nbsp;\u003c/sup\u003eCollege of Horticulture, Shanxi Agricultural University, Taigu, Shanxi 030801, China. \u003csup\u003e3\u0026nbsp;\u003c/sup\u003eSchool of Innovation and Intrepreneurship, Shanxi Agricultural University, Taigu, Shanxi 030801, China. \u003csup\u003e+\u0026nbsp;\u003c/sup\u003eEqual contribution and first authorship: These authors contributed equally to this work and share first authorship\u003c/p\u003e\u003cp\u003e\u003cstrong\u003ePublisher\u0026rsquo;sNote\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSpringer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKato-Noguchi H, Nakamura K, Okuda N. Involvement of an autotoxic compound in asparagus decline. J Plant Physiol. 2018;224:49\u0026ndash;55. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jplph.2018.03.005\u003c/span\u003e\u003cspan address=\"10.1016/j.jplph.2018.03.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYan SL, Cai B, Tang HL, Yuan Y, Ao S. Study on the allelopathic effects of different parts of bitter gourd. Journal of Agricultural Science \u0026amp; Technology; 2018. (1008\u0026thinsp;\u0026ndash;\u0026thinsp;0864), 20(8).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWu B, Long Q, Gao Y, Wang Z, Shao T, Liu Y, et al. Comprehensive characterization of a time-course transcriptional response induced by autotoxins in Panax ginseng using RNA-Seq. BMC Genomics. 2015;16(1):1010. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12864-015-2151-7\u003c/span\u003e\u003cspan address=\"10.1186/s12864-015-2151-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiu MC, Zuo YJ, Liu YL. A new molecular identification method for soybean plants (Glycine Willd.) based on chloroplast whole genome nucleotide variation sites. Bot Res. 2024;13:124.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBellaloui N, Reddy KN, Bruns HA, Gillen AM, Mengistu A, Zobiole LH, et al. Soybean seed composition and quality: Interactions of environment, genotype, and management practices. Soybeans: Cultivation, Uses and Nutrition. New York, USA: Nova Science Publishers, Inc.; 2011. pp. 1\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiu X, Herbert SJ. Fifteen years of research examining cultivation of continuous soybean in northeast China: a review. Field Crops Res. 2002;79(1):1\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMehmood A, Hussain A, Irshad M, Hamayun M, Iqbal A, Rahman H, et al. Cinnamic acid as an inhibitor of growth, flavonoids exudation and endophytic fungus colonization in maize root. Plant Physiol Biochem. 2019;135:61\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.plaphy.2018.11.029\u003c/span\u003e\u003cspan address=\"10.1016/j.plaphy.2018.11.029\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiu CW, Murray JD. The role of flavonoids in nodulation host-range specificity: an update. Plants. 2016;5(3):33.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFeduraev P, Skrypnik L, Riabova A, Pungin A, Tokupova E, Maslennikov P, et al. Phenylalanine and tyrosine as exogenous precursors of wheat (Triticum aestivum L.) secondary metabolism through PAL-associated pathways. Plants. 2020;9(4):476. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/plants9040476\u003c/span\u003e\u003cspan address=\"10.3390/plants9040476\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLin L, CHEN FANGJ, AI G, Y. Cloning and Bioinformatics of Chalcone Synthase Gene of Moringa oleifera. Fujian J Agricultural Sci. 2021;36(5):549\u0026ndash;55.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNie HZ, Xue YC, Gao ZH. Research progress on hydroxylases in lignin biosynthesis. J Henan Agricultural Sci. 2008;37(4):5.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCen Z, Zheng Y, Guo Y, Yang S, Dong Y. Nitrogen fertilization in a faba bean\u0026ndash;wheat intercropping system can alleviate the autotoxic effects in faba bean. Plants. 2023;12(6):1232.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMa L, Ma S, Chen G, Lu X, Chai Q, Li S. Mechanisms and mitigation strategies for the occurrence of continuous cropping obstacles of legumes in China. Agronomy. 2023;14(1):104.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLima RB, Salvador VH, dos Santos WD, Bubna GA, Finger-Teixeira A, Soares AR, et al. Enhanced lignin monomer production caused by cinnamic acid and its hydroxylated derivatives inhibits soybean root growth. PLoS ONE. 2013;8(12):e80542. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0080542\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0080542\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSalvador VH, Lima RB, dos Santos WD, Soares AR, B\u0026ouml;hm PAF, Marchiosi R, et al. Cinnamic acid increases lignin production and inhibits soybean root growth. PLoS ONE. 2013;8(7):e69105. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0069105\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0069105\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEtesami H, Jeong BR. Silicon (Si): Review and future prospects on the action mechanisms in alleviating biotic and abiotic stresses in plants. Ecotoxicol Environ Saf. 2018;147:881\u0026ndash;96.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSheng H, Chen S. Plant silicon-cell wall complexes: Identification, model of covalent bond formation and biofunction. Plant Physiol Biochem. 2020;155:13\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.plaphy.2020.07.020\u003c/span\u003e\u003cspan address=\"10.1016/j.plaphy.2020.07.020\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRizwan M, Ali S, Ibrahim M, Farid M, Adrees M, Bharwana SA, et al. Mechanisms of silicon-mediated alleviation of drought and salt stress in plants: a review. Environ Sci Pollut Res. 2015;22(20):15416\u0026ndash;31. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11356-015-5305-x\u003c/span\u003e\u003cspan address=\"10.1007/s11356-015-5305-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDebona D, Rodrigues FA, Datnoff LE. Silicon's role in abiotic and biotic plant stresses. Annu Rev Phytopathol. 2017;55:85\u0026ndash;107.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLyu J, Jin N, Meng X, Jin L, Wang S, Xiao X, et al. Exogenous silicon alleviates the adverse effects of cinnamic acid-induced autotoxicity stress on cucumber seedling growth. Front Plant Sci. 2022;13:968514. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fpls.2022.968514\u003c/span\u003e\u003cspan address=\"10.3389/fpls.2022.968514\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGong H, Zhu X, Chen K, Wang S, Zhang C. Silicon alleviates oxidative damage of wheat plants in pots under drought. Plant Sci. 2005;169(2):313\u0026ndash;21. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.plantsci.2005.02.023\u003c/span\u003e\u003cspan address=\"10.1016/j.plantsci.2005.02.023\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYang Y, Liu Q, Wang GX, Wang XD, Guo JY. Germination, osmotic adjustment, and antioxidant enzyme activities of gibberellin-pretreated Picea asperata seeds under water stress. New Forest. 2010;39(2):231\u0026ndash;43. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11056-009-9167-2\u003c/span\u003e\u003cspan address=\"10.1007/s11056-009-9167-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMu Y, Li Y, Zhang Y, Guo X, Song S, Huang Z, et al. A comparative study on the role of conventional, chemical, and nanopriming for better salt tolerance during seed germination of direct seeding rice. J Integr Agric. 2024;23(12):3998\u0026ndash;4017. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jia.2023.12.013\u003c/span\u003e\u003cspan address=\"10.1016/j.jia.2023.12.013\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eElstner EF, Heupel A. Formation of hydrogen peroxide by isolated cell walls from horseradish (Armoracia lapathifolia Gilib). Planta. 1976;130(2):175\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePatterson BD, MacRae EA, Ferguson IB. Estimation of hydrogen peroxide in plant extracts using titanium (IV). Anal Biochem. 1984;139(2):487\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBiswal B, Joshi PN, Raval MK, Biswal UC. (2011). Photosynthesis, a global sensor of environmental stress in green plants: stress signalling and adaptation. Curr Sci, 47\u0026ndash;56.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShan X, Li Y, Jiang Y, Jiang Z, Hao W, Yuan Y. Transcriptome profile analysis of maize seedlings in response to high-salinity, drought and cold stresses by deep sequencing. Plant Mol biology Report. 2013;31(6):1485\u0026ndash;91. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11105-013-0622-z\u003c/span\u003e\u003cspan address=\"10.1007/s11105-013-0622-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStracke R, Werber M, Weisshaar B. The R2R3-MYB gene family in Arabidopsis thaliana. Curr Opin Plant Biol. 2001;4(5):447\u0026ndash;56.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRushton PJ, Somssich IE, Ringler P, Shen QJ. WRKY transcription factors. Trends Plant Sci. 2010;15(5):247\u0026ndash;58. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4161/psb.27700\u003c/span\u003e\u003cspan address=\"10.4161/psb.27700\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMahmood K, El-Kereamy A, Kim SH, Nambara E, Rothstein SJ. ANAC032 positively regulates age-dependent and stress-induced senescence in Arabidopsis thaliana. Plant Cell Physiol. 2016;57(10):2029\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYang W, Guo Y, Li Y. Cinnamic acid toxicity on the structural resistance and photosynthetic physiology of faba bean Promoted the occurrence of Fusarium Wilt of faba bean, which was alleviated through wheat and faba bean intercropping[J]. Front Plant Sci. 2022;13:857780.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAlamri S, Hu Y, Mukherjee S, Aftab T, Fahad S, Raza A, et al. Silicon-induced postponement of leaf senescence is accompanied by modulation of antioxidative defense and ion homeostasis in mustard (Brassica juncea) seedlings exposed to salinity and drought stress. Plant Physiol Biochem. 2020;157:47\u0026ndash;59.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSalim BBM, El-Yazied A, Salama A, Raza YAM, Osman A, H. S. Impact of silicon foliar application in enhancing antioxidants, growth, flowering and yield of squash plants under deficit irrigation condition. Annals Agricultural Sci. 2021;66(2):176\u0026ndash;83. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.aoas.2021.12.003\u003c/span\u003e\u003cspan address=\"10.1016/j.aoas.2021.12.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLIN KM, YE FM, LIN Y, LI QS. Research advances of phenolic functional mechanisms in soils and plants. Chin J Eco-Agriculture. 2010;18(5):1130\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3724/sp.j.1011.2010.01130\u003c/span\u003e\u003cspan address=\"10.3724/sp.j.1011.2010.01130\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGao X, Zhang G, Hu Q, Xu S, Gong G. Y. (2013). Effects of cinnamic acid on growth and chlorophyll fluorescence parameters of Pisum sativum L. seedlings.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhao Q, Chen L, Dong K, Dong Y, Xiao J. Cinnamic acid inhibited growth of faba bean and promoted the incidence of fusarium wilt. Plants. 2018;7(4):84.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSteiner F, Zuffo AM, Bush A, Santos DMDS. Silicate fertilization potentiates the nodule formation and symbiotic nitrogen fixation in soybean1. Pesquisa Agropecu\u0026aacute;ria Trop. 2018;48(3):212\u0026ndash;21. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1590/1983-40632018v4851472\u003c/span\u003e\u003cspan address=\"10.1590/1983-40632018v4851472\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTripathi P, Na CI, Kim Y. Effect of silicon fertilizer treatment on nodule formation and yield in soybean (Glycine max L). Eur J Agron. 2021;122:126172. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.eja.2020.126172\u003c/span\u003e\u003cspan address=\"10.1016/j.eja.2020.126172\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYang W, Zhang Z, Yuan T, Li Y, Zhao Q, Dong Y. Intercropping improves faba bean photosynthesis and reduces disease caused by Fusarium commune and cinnamic acid-induced stress. BMC Plant Biol. 2024;24(1):650. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12870-024-05326-8\u003c/span\u003e\u003cspan address=\"10.1186/s12870-024-05326-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHaider FU, Liqun C, Coulter JA, Cheema SA, Wu J, Zhang R, et al. Cadmium toxicity in plants: Impacts and remediation strategies. Ecotoxicol Environ Saf. 2021;211:111887. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ecoenv.2020.111887\u003c/span\u003e\u003cspan address=\"10.1016/j.ecoenv.2020.111887\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang Xiaoyan. Physiological and molecular mechanisms of response to autotoxicity coumarin in alfalfa (Medicago sativa L.) varieties. Gansu Agricultural University; 2022.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMa N, Chen B, Yang H. Photosynthetic fluorescence characteristics of cucumber seedlings and response of root antioxidant system to exogenous cinnamic acid. Jiangsu Agricultural Sci. 2020;48(12):113\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiang Y, Liu H, Fu Y, Li P, Li S, Gao Y. Regulatory effects of silicon nanoparticles on the growth and photosynthesis of cotton seedlings under salt and low-temperature dual stress. BMC Plant Biol. 2023;23(1):504. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12870-023-04509-z\u003c/span\u003e\u003cspan address=\"10.1186/s12870-023-04509-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi L, Qi Q, Zhang H, Dong Q, Iqbal A, Gui H, Antioxidants et al. 11(8), 1520. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/antiox11081520\u003c/span\u003e\u003cspan address=\"10.3390/antiox11081520\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang P, Huang H, Liu W, Zhang C. Physiological mechanisms of a wetland plant (Echinodorus osiris Rataj) to cadmium detoxification. Environ Sci Pollut Res. 2017;24(27):21859\u0026ndash;66. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11356-017-9744-4\u003c/span\u003e\u003cspan address=\"10.1007/s11356-017-9744-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiang Y, Chen QIN, Liu Q, Zhang W, Ding R. Exogenous silicon (Si) increases antioxidant enzyme activity and reduces lipid peroxidation in roots of salt-stressed barley (Hordeum vulgareL). J Plant Physiol. 2003;160(10):1157\u0026ndash;64. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1078/0176-1617-01065\u003c/span\u003e\u003cspan address=\"10.1078/0176-1617-01065\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMeng X. The effect of exogenous silicon on cucumber seed germination and growth under cinnamic acid stress. Gansu Agricultural University; 2022.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang Z, Wu J, Xi Y, Zhang L, Gao Q, Wang-Pruski G. Effects of autotoxicity on seed germination, gas exchange attributes and chlorophyll fluorescence in melon seedlings. J Plant Growth Regul. 2022;41(3):993\u0026ndash;1003. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00344-021-10355-w\u003c/span\u003e\u003cspan address=\"10.1007/s00344-021-10355-w\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWei Xiaoman. The response of stem tumor mustard to cadmium stress and the physiological and biochemical mechanisms of silicon alleviating cadmium toxicity. Chongqing Three Gorges University; 2024.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAbdel-Lateif K, Bogusz D, Hocher V. The role of flavonoids in the establishment of plant roots endosymbioses with arbuscular mycorrhiza fungi, rhizobia and Frankia bacteria. Plant Signal Behav. 2012;7(6):636\u0026ndash;41. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4161/psb.20039\u003c/span\u003e\u003cspan address=\"10.4161/psb.20039\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMollavali M, Perner H, Rohn S, Riehle P, Hanschen FS, Schwarz D. Nitrogen form and mycorrhizal inoculation amount and timing affect flavonol biosynthesis in onion (Allium cepa L). Mycorrhiza. 2018;28(1):59\u0026ndash;70. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00572-017-0799-3\u003c/span\u003e\u003cspan address=\"10.1007/s00572-017-0799-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDixon RA, Achnine L, Kota P, Liu CJ, Reddy MS, Wang L. The phenylpropanoid pathway and plant defence\u0026mdash;a genomics perspective. Mol Plant Pathol. 2002;3(5):371\u0026ndash;90. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1046/j.1364-3703.2002.00131.x\u003c/span\u003e\u003cspan address=\"10.1046/j.1364-3703.2002.00131.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eColebrook EH, Thomas SG, Phillips AL, Hedden P. The role of gibberellin signalling in plant responses to abiotic stress. J Exp Biol. 2014;217(1):67\u0026ndash;75. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1242/jeb.089938\u003c/span\u003e\u003cspan address=\"10.1242/jeb.089938\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNakashima K, Takasaki H, Mizoi J, Shinozaki K, Yamaguchi-Shinozaki K. (2012). NAC transcription factors in plant abiotic stress responses. Biochimica et Biophysica Acta (BBA)-Gene Regulatory Mechanisms, 1819(2), 97\u0026ndash;103. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.bbagrm.2011.10.005\u003c/span\u003e\u003cspan address=\"10.1016/j.bbagrm.2011.10.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-plant-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pbio","sideBox":"Learn more about [BMC Plant Biology](http://bmcplantbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pbio/default.aspx","title":"BMC Plant Biology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Soybean, Si, Autotoxicity, Nodulation, Transcriptome analysis","lastPublishedDoi":"10.21203/rs.3.rs-7165248/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7165248/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eSoybean (\u003cem\u003eGlycine max\u003c/em\u003e (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.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eWe 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 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 CO\u003csub\u003e2\u003c/sub\u003e 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.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eIn 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.\u003c/p\u003e","manuscriptTitle":"Transcriptome analysis revealed the mechanism of exogenous silicon alleviating allelopathic inhibition of cinnamic acid on soybean seedlings","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-26 21:45:41","doi":"10.21203/rs.3.rs-7165248/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-11T15:47:03+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-09T19:17:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"211525798371655446071253735856459395560","date":"2025-11-09T08:40:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"130099194667692086774691972201246859180","date":"2025-11-09T07:24:49+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-07T09:40:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"55511146401682045258903861883771352739","date":"2025-11-06T14:56:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"67519552664249734446127836654952919719","date":"2025-11-06T10:41:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"170100579024204064000723215857512614035","date":"2025-11-05T08:06:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"3971059686811413985209622501957215995","date":"2025-11-04T09:02:12+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-15T09:55:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"149507785761568914029382765258296972345","date":"2025-08-23T11:55:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"73534834552424935047065036406952894489","date":"2025-08-20T18:20:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"98517086632353033770277704913754428567","date":"2025-08-20T08:01:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"164485519183562672355765345730657347496","date":"2025-08-19T02:46:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"5221125803207928521084935844241969410","date":"2025-08-18T20:03:38+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-18T08:00:26+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-24T10:22:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-23T12:02:43+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-23T12:02:35+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Plant Biology","date":"2025-07-19T14:57:16+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-plant-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pbio","sideBox":"Learn more about [BMC Plant Biology](http://bmcplantbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pbio/default.aspx","title":"BMC Plant Biology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"11fd0413-ec70-4433-813f-d9762b541b0f","owner":[],"postedDate":"August 26th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-09T16:02:12+00:00","versionOfRecord":{"articleIdentity":"rs-7165248","link":"https://doi.org/10.1186/s12870-026-08425-w","journal":{"identity":"bmc-plant-biology","isVorOnly":false,"title":"BMC Plant Biology"},"publishedOn":"2026-03-06 15:57:07","publishedOnDateReadable":"March 6th, 2026"},"versionCreatedAt":"2025-08-26 21:45:41","video":"","vorDoi":"10.1186/s12870-026-08425-w","vorDoiUrl":"https://doi.org/10.1186/s12870-026-08425-w","workflowStages":[]},"version":"v1","identity":"rs-7165248","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7165248","identity":"rs-7165248","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}