The molecular mechanism of the α-linolenic acid metabolism pathway in rice in response to Cd stress

Abstract

Background

Cadmium (Cd) toxicity induces changes in gene expression and metabolite profiles, thereby affecting plant growth. However, the molecular basis of Cd toxicity in rice remains unclear. This study investigated the responses of rice leaves and roots to Cd stress using integrated transcriptomic and metabolomic analyses.

Result

Cd stress significantly inhibited rice growth, impaired antioxidant enzyme systems in leaves and roots, and altered nutrient uptake. Under Cd stress (10 µM Cd), compared with the control group (0 µM Cd), activities of superoxide dismutase (SOD), peroxidase (POD), catalase (CAT), and ascorbate peroxidase (APX) in leaves increased by 47.9%, 156.9%, 104.8%, and 233.0%, respectively; proline, soluble sugar, and soluble protein increased by 205.6%, 296.4%, and 30.4%, respectively. Under the same conditions, soluble sugar and soluble protein in roots increased by 29.1% and 23.2%, respectively, while SOD, POD, CAT, and APX activities increased by 28.2%, 95.4%, 39.9%, and 133.8%, respectively. Cd stress increased soluble sugar and soluble protein in both leaves and roots and reduced chlorophyll content. Transcriptomic analysis identified 4,366 differentially expressed genes (DEGs) in leaves and 4,971 DEGs in roots, associated with antioxidant enzyme expression, ion transport, and hormone-related pathways. Metabolomic analysis detected 1,054 differentially expressed metabolites (DEMs) in leaves and 882 DEMs in roots. Under Cd stress, both tissues showed significant enrichment of the α-linolenic acid metabolism pathway. Genes encoding lipoxygenase (LOX; including LOX2S) and allene oxide synthase (AOS) were differentially expressed, which mitigated oxidative stress.

Conclusion

This study clarifies physiological and molecular responses of rice to Cd stress and highlights the role of α-linolenic acid metabolism in tolerance to Cd toxicity. These findings advance understanding of Cd effects on rice development and identify candidate molecular targets for genetic approaches to improve Cd stress resistance.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12870-026-08539-1.

Introduction

Cadmium (Cd) is one of the most toxic elements to which humans may be exposed in occupational or environmental settings [1]. Humans absorb and accumulate Cd through food, water, and inhaled gases. Once absorbed, Cd persists in the body. Cd disrupts the structure and function of multiple organs by inducing oxidative stress and is associated with cardiovascular disease, early atherosclerosis, kidney disease, and hypertension, with particularly severe effects in smokers [2].

Cd is not required for plant growth and development. Even low Cd exposure can exert toxic effects as a harmful element [3]. Cd enters plants through uptake pathways for essential elements such as calcium, iron, manganese, and zinc and subsequently accumulates in aboveground tissues [4]. Cd initially binds to pectin in root cell walls, reduces cell-wall elasticity, damages root nodules, and inhibits root growth [5, 6]. Excessive Cd accumulation in rice (Oryza sativa) leaves suppresses chlorophyll biosynthesis and reduces photosynthetic rate [7], leading to chlorosis, leaf yellowing, and brown spots [8]. Cd stress induces the accumulation of reactive oxygen species (ROS) in cell membranes and triggers lipid peroxidation, thereby altering the activities of antioxidant enzymes, including peroxidase (POD), catalase (CAT), superoxide dismutase (SOD), ascorbate peroxidase (APX), and glutathione reductase (GR) [9]. Under Cd stress, chlorophyll synthesis in sweet potato (Ipomoea batatas) is significantly suppressed, and Rubisco activity is significantly reduced [10]. These changes affect multiple metabolic pathways, such as protein metabolism and secondary metabolism, and ultimately constrain plant growth and development [11].

Rice is a staple crop for more than half of the global population and plays a central role in food security [12]. However, the physiological processes and molecular regulatory networks that mediate rice responses to Cd toxicity remain incompletely defined. Therefore, elucidating the physiological and molecular mechanisms underlying rice tolerance to Cd stress is of substantial significance.

Advances in transcriptomic and metabolomic technologies have promoted comprehensive analyses of plant responses to Cd stress [13], including studies in cotton (Gossypium hirsutum) [14], maize (Zea mays) [15], and peanut (Arachis hypogaea) [16]. In Arabidopsis thaliana, the HMA3 transporter sequesters Zn into vacuoles in roots and retains Zn in root tissues, thereby promoting Ni hyperaccumulation in aboveground parts, which has potential value for remediating contaminated land [17]. In Sedum plumbizincicola, SpZIP60 enhances Cd stress tolerance by regulating cell-wall components (lignin, cellulose, and pectin) and promoting lignin deposition through direct regulation of the lignin-biosynthesis gene SpBglu, resulting in cell-wall thickening that restricts Cd entry into root cells [18]. In addition, high Cd stress stimulates melatonin synthesis in cotton seedlings; exogenous melatonin promotes alkaloid and flavonoid synthesis, suppresses the synthesis of lipids, amino acids, and their derivatives, and alleviates Cd toxicity in cotton seedlings [14]. Therefore, integrated multi-omics analyses of plant roots and leaves under Cd stress are essential for elucidating molecular regulatory mechanisms of Cd responses.

In this study, transcriptome sequencing and non-targeted metabolomics were applied to investigate response mechanisms in rice roots and leaves under Cd stress. The objectives were to: (a) characterize physiological and phenotypic changes in rice under different Cd levels; (b) identify differentially expressed genes (DEGs) and DEMs and define key metabolic networks; and (c) clarify molecular regulatory mechanisms underlying rice responses to Cd stress. By identifying key genes, metabolites, and response pathways, this study provides a scientific basis for breeding Cd-tolerant rice varieties and offers reference information for studies of Cd stress in other plant species.

Materials and methods

Rice treatment method

The experimental material was Haihong11 (HH11) rice, bred by the College of Coastal Agricultural Sciences, Guangdong Ocean University. Healthy, plump seeds were selected and disinfected in 15% hydrogen peroxide solution (Guangzhou Reagents, Guangzhou, China) for 3 min. Seeds were then rinsed with sterile water and placed in Petri dishes lined with moist absorbent paper (Devan, Jiangsu, China) for dark germination. On day 3 after germination, seedlings were transferred to a 96-well hydroponic box (Huishijie Company, Nantong, China) for seedling establishment. After 14 days, uniform and healthy seedlings were selected and subjected to 20 days of hydroponic treatment. Seedlings were transplanted into 5-L plastic buckets containing 4 L of hydroponic nutrient solution (Kimura B [19]), ; detailed composition is provided in Table S1. Cd was supplied as CdCl₂ at concentrations of 0, 5, 10, 15, and 30 µM. The control received an equal volume of deionized water. All nutrient solutions were prepared with analytical-grade reagents from Guangzhou Chemical Reagents Factory (China). Growth conditions were 28/25°C (day/night), a 14/10 h (day/night) photoperiod, and a light intensity of 240 µmol/m²·s. The nutrient solution was renewed every 5 days, and pH was maintained at 5.8–6.0 using 1 M HCl or NaOH (Sinopharm Group Chemical Reagents, Shanghai, China).

Phenotypic observation and phenotypic data acquisition

After 20 days of hydroponic treatment, phenotypes were observed and photographed. Phenotypic traits included plant height, stem diameter, number of root tips, root volume, total root length, average root diameter, and root surface area. Plant height was measured with a 50-cm steel ruler (Deli, China), and stem diameter with a 150-mm vernier caliper (Deli, China). Root traits were analyzed using WinRHIZO software (Professional Version V2013e; Regent Instruments, Quebec, Canada) [20]. Root images were obtained with a scanner (Epson DS-50000, Tokyo, Japan), and image analysis was conducted using WinRHIZO 2013e Professional Edition [21].

Biomass accumulation analysis and chlorophyll content determination

After 20 days of Cd treatment, roots and leaves were harvested, surface moisture was removed, and fresh weights were recorded using an electronic balance (Sartorius CP4202S, Göttingen, Germany). Samples were then dried at 65 °C for approximately one week, and dry weights were measured (Yiheng Company, Shanghai, China) [22].

Chlorophyll content was determined by ethanol extraction [23]. Approximately 0.2 g of fresh green leaves from each treatment group were excised and immersed in 95% ethanol (Guangzhou Reagents, Guangzhou, China) in the dark for 24 h. Absorbance at 663, 645, and 652 nm was measured using a UV–visible spectrophotometer (Metash Instruments UV-5100B, Shanghai, China) [24]. Chlorophyll content was expressed as mg/g.

Physiological data collection

Malondialdehyde, soluble sugar, proline, and soluble protein

After 20 days of Cd treatment, approximately 0.2 g of leaves or roots were sampled. Soluble protein content was determined by the Coomassie Brilliant Blue method [25]. Soluble sugar content was measured using the anthrone method [26]. Proline content was determined by the acid ninhydrin method [27]. Malondialdehyde (MDA) content was measured using the improved thiobarbituric acid method [28].

POD, SOD, CAT and APX activities

After 20 days of Cd treatment, fresh tissue (approximately 0.2 g per sample) was homogenized in pre-cooled phosphate buffer (0.05 M, pH 7.8) on ice. Homogenates were centrifuged at 10,000 rpm and 4 °C for 20 min, and the supernatants were used for enzyme assays. POD activity was determined using the crotonolactone method [29]. SOD activity was measured at 560 nm, and CAT activity at 240 nm, using a UV–visible spectrophotometer (Metash Instruments UV-5100B, Shanghai, China) [30, 31]. APX activity was determined by monitoring the change in ascorbic acid absorbance at 290 nm [32].

Ion content determination

Metal contents in roots and leaves from the 0 and 10 µM Cd treatment groups were determined using inductively coupled plasma atomic emission spectrometry (Hitachi PS7800, Tokyo, Japan) following Kalogiouri et al. [33]. Approximately 0.2 g of dried sample was digested with 5 mL of 8 M concentrated nitric acid (Sinopharm Group Chemical Reagents, Shanghai, China) at 25 °C for 24 h, followed by heating to 180 °C on a DB-XWJ electric heating plate (MITR, Changsha, Hunan, China). After drying and cooling, 2 mL of 8 M nitric acid and 2 mL of 30% hydrogen peroxide were added, and digestion continued at 180 °C until the solution became clear. The digest was heated to near dryness, then supplemented with 1 mL of concentrated nitric acid for final digestion. The resulting solution and residue were transferred to 25-mL borosilicate glass colorimetric tubes (Beibog, Beijing, China) for determination of Zn, Cd, Fe, B, Mg, and Ca contents.

Transcriptome analysis

After 20 days of treatment with 0 and 10 µM Cd, leaf and root samples (0.1 g) were collected from rice seedlings for transcriptome analysis. Three biological replicates were included for each treatment. Transcriptome sequencing was conducted following Liu et al. [34]. Total RNA extraction, purification, and library construction were performed, and libraries were sequenced on an Illumina platform (NovaSeq 6000, Illumina, USA) using the PE150 mode. Raw sequencing reads were filtered to obtain high-quality clean data. Clean reads were aligned to the reference rice genome (https://ftp.ncbi.nlm.nih.gov/genomes/all/GCF/001/433/935/GCF_001433935.1_IRGSP-1.0) using HISAT2 (version 2.0.4, USA). Gene-level read counts and raw expression levels were quantified using HTSeq (version 0.9.1, Germany). Differential expression analysis was carried out with DESeq2 (version 1.39.0, USA), with thresholds of Fold Change ≥ 2 and false discovery rate (FDR) < 0.01. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed according to Li et al. [35]. The sequencing data were deposited in the NCBI database under accession number PRJNA137067 (https://www.ncbi.nlm.nih.gov/sra/PRJNA1370671).

Metabolomics analysis

After 20 days of treatment with 0 and 10 µM Cd, root and leaf samples (0.1 g) were collected for metabolomic analysis. Four biological replicates were analyzed for each treatment. Samples were analyzed by Suzhou Panomic Biomedical Technology Co., Ltd. (Suzhou, Jiangsu, China). Procedures for metabolite extraction, reagent preparation, chromatographic separation, and mass spectrometry followed previously reported methods [34]. Raw mass spectrometry data were processed as described by Navarro-Reig et al. [36] and Rasmussen et al. [37], and metabolites were quantified. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal partial least squares discriminant analysis (OPLS-DA) were applied for dimensionality reduction and regression analysis. Metabolite identification was performed by comparison with standard metabolite databases (HMDB, Mass Bank, Lipid Maps, mz Cloud, KEGG, Nomi Metabolism). Metabolites with secondary mass spectra were identified by matching fragment ions to database spectra. DEMs were screened at P1 based on qualitative identification. DEMs were defined using thresholds of P < 0.05 and variable importance in projection (VIP) > 1 [38]. Identified DEMs were subjected to KEGG pathway enrichment analysis and integrated co-analysis with transcriptomic data.

Quantitative RT-PCR (qRT-PCR) analysis

Leaves and roots from rice plants treated with 0 and 10 µM Cd for 20 days were collected for qRT-PCR analysis. Total RNA was extracted using the MolPure^® Plant RNA Kit (Yeasen, Shanghai, China). First-strand cDNA was synthesized using the Hifair II 1st Strand cDNA Synthesis Kit (Yeasen, Shanghai, China). Quantitative RT-PCR was performed as described previously [39].

Each 20 µL reaction contained 0.5 µL of forward primer, 0.5 µL of reverse primer, 8 µL of nuclease-free water, 1 µL of cDNA template, and 10 µL of Hifair UNICON Universal Blue qPCR SYBR Green Premix (Yeasen, China). The amplification program was as follows: 95 °C for 10 min; 40 cycles of 95 °C for 15 s and 60 °C for 1 min. An internal reference gene (actin-1-like; LOC4333919) was used for normalization, and relative expression levels were calculated as the ratio of target gene expression to reference gene expression. Primer sequences are listed in Table S2.

Data statistical analysis

All data were processed using Microsoft Office Excel 2010 (Microsoft, Redmond, WA, USA) and IBM SPSS Statistics 17.0 (IBM, Armonk, NY, USA). An independent samples t-test was used to compare the significance of differences between the two datasets. For multiple data groups, multiple comparisons and analysis of significant differences were performed using the Waller-Duncan test in one-way analysis of variance (ANOVA).

Results

Phenotypic changes and physiological characteristics of rice under Cd stress

With increasing Cd concentration, rice growth was significantly inhibited (Fig. 1Aa–f). Compared with the control, treatment with 10 µM Cd reduced dry weight and fresh weight by 41.02% and 77.06%, respectively (Fig. 1B, C), and decreased plant height and root length by 64.16% and 80.01%, respectively (Fig. 1D, E). Root surface area, average root diameter, root tip number, and root volume decreased by 53.71%, 40.31%, 65.31%, and 49.07%, respectively (Fig. 1F, I).

Fig. 1.

Effects of different concentrations of Cd on the growth of rice. A From left to right, the phenotypes of rice after 20 days of treatment with (a) 0, (b) 5, (c) 10, (d) 15, and (e) 30 µM Cd (Bar = 5 cm). B Fresh weight; C Dry weight; D Plant height; E Root length; F Root surface area; G Average diameter; H Number of root tips; I Root volume. The data were analyzed using the Duncan model. Different lowercase letters on the bar charts indicated significant differences between the data (P < 0.05)

Compared with the control, activities of antioxidant enzymes in leaves and roots changed significantly with increasing Cd concentration (Fig. 2A–H). At 10 µM Cd, CAT, POD, SOD, and APX activities in leaves increased by 39.88%, 95.44%, 28.20%, and 133.77%, respectively (Fig. 2A–D). In roots, CAT, POD, SOD, and APX activities increased by 104.84%, 156.89%, 47.92%, and 233.00%, respectively (Fig. 2E–H).

Fig. 2.

Effects of Cd treatment on the physiology of rice. A CAT, (B) POD, (C) SOD, (D) APX activities in leaves. E CAT, (F) POD, (G) SOD, (H) APX activities in roots. I Proline, (J) Soluble protein, (K) Soluble sugar, (L) Malondialdehyde content in leaves. M Proline, (N) Soluble protein, (O) Soluble sugar, (P) Malondialdehyde (MDA) content in roots

Proline, soluble protein, soluble sugar, and MDA showed concentration-dependent changes under Cd stress (Fig. 2I–P). Compared with the control (0 µM Cd), at 10 µM Cd, proline, soluble protein, soluble sugar, and MDA in leaves increased by 139.68%, 23.23%, 29.16%, and 15.44%, respectively (Fig. 2I–L). In roots, these indices increased by 205.62%, 30.43%, 296.40%, and 225.84%, respectively (Fig. 2M–P).

With increasing Cd concentration, chlorophyll a, chlorophyll b, and total chlorophyll in leaves decreased significantly, reaching the lowest levels at 30 µM Cd (Fig. S1A–C). Compared with the control, chlorophyll a, chlorophyll b, and total chlorophyll decreased by 63.07%, 68.44%, and 64.37%, respectively, at 10 µM Cd (Fig. S1A–C).

Physiological and phenotypic data analysis revealed that 10 µM Cd represented a critical threshold for rice responses to Cd stress. At this concentration, the majority of physiological and morphological indicators started to show significant alterations. Therefore, samples treated with 10 µM Cd were selected for subsequent ion content determination, transcriptomic and metabolomic analysis.

Ion changes in rice under Cd stress

In leaves treated with 10 µM Cd, compared with the control (0 µM Cd), Cd, Fe, and Mg contents increased by 1917.46%, 25.68%, and 10.68%, respectively, compared with the control (Fig. 3A, C, E). Zn and Ca content decreased by 35.85% and 14.99% (Fig. 3B, D), B content increased by 11.11% (Fig. 3F). In roots, Cd, Fe, and B contents increased by 1988.42%, 15.46%, and 160.47%, respectively (Fig. 3G, I, L), while Zn, Ca, and Mg contents decreased by 67.67%, 15.47%, and 36.44%, respectively (Fig. 3H, J, K).

Fig. 3.

Effects of high Cd stress on ion accumulation contents in rice. Contents of (A) Cd, (B) Zn, (C) Fe, (D) Ca, (E) Mg, (F) B in leaves; contents of (G) Cd, (H) Zn, (I) Fe, (J) Ca, (K) Mg, (L) B in roots

Transcriptome analysis

Transcriptome sequencing and differential gene analysis

Whole-genome transcriptome sequencing was performed on leaves and roots treated with 0 and 10 µM Cd. A total of 12 libraries were constructed, with three biological replicates per tissue and treatment. In total, 89.87 Gb of clean reads were obtained, with each sample yielding at least 5.40 Gb. Q30 values exceeded 94% (Table S3), indicating high data quality suitable for downstream analyses. Differential expression analysis identified 4,971 DEGs in roots (2,930 up-regulated and 2,041 down-regulated) and 4,366 DEGs in leaves (1,668 up-regulated and 2,698 down-regulated). Among these, 609 DEGs were up-regulated in both tissues and 411 were down-regulated in both (Fig. 4A, B). Additionally, 65 DEGs were down-regulated in roots but up-regulated in leaves, whereas 449 DEGs were up-regulated in roots but down-regulated in leaves (Fig. 4A, B).

Fig. 4.

Transcriptome analysis results of rice leaves and roots under high Cd stress. A Statistical results of DEGs in leaves and roots; (B) Venn diagram analysis. KEGG pathway enrichment in (C) leaves and (D) roots. The horizontal axis represented the enrichment value, and the vertical axis represented the enrichment path. The size of the bubbles represented the number of DEGs. The color of the bubbles represented the size of the FDR value

GO and KEGG analyses of rice root systems and leaves

GO enrichment analysis was conducted to evaluate functional categories of DEGs under Cd stress (Fig. S2). The top 20 GO terms with the smallest Q values are presented (Table S4). DEGs were primarily enriched in biological processes and cellular components. In leaves, DEGs were enriched in transferase activity, kinase activity, and catalytic activity (Fig. S2A; Table S4). In roots, enrichment was observed in regulation of RNA biosynthesis, macromolecular biosynthesis, and catalytic activity (Fig. S2B; Table S4). KEGG pathway analysis showed co-enrichment of several pathways in both tissues, including phenylpropanoid biosynthesis, flavonoid biosynthesis, ABC transporters, diterpenoid biosynthesis, glutathione metabolism, starch and sucrose metabolism, and valine, leucine, and isoleucine degradation (Fig. 4C, D; Table S5).

Identification and screening of DEGs

In leaves and roots, 82 DEGs associated with antioxidant functions responded to Cd stress (Table S6). These included genes related to POD, CAT, glutathione peroxidase, and APX, with peroxidase-related genes being the most abundant (78 DEGs). A total of 176 DEGs encoded transcription factors, including 8 bZIPs, 45 MYBs, 39 WRKYs, 42 bHLHs, 5 TCPs, and 37 NACs (Table S7). DEGs related to metal transport were also identified, including 7 ZIP family metal cation transporters, 6 K transporters, 6 magnesium transporters, 5 NRAMP metal ion transporters, and 4 copper transporters (Table S8).

Metabolomics analysis

DEMs in rice roots and leaves

Metabolomic profiling was used to examine metabolic changes in rice roots and leaves under high Cd stress. Hierarchical cluster analysis showed that samples from the same treatment and tissue clustered together, whereas samples from different treatments or tissues were clearly separated (Fig. S3A, B). Multivariate analyses using PCA (Fig. S4A–D), PLS-DA (Fig. S5A–D), and OPLS-DA (Fig. S6A–D) further confirmed this separation. These results indicate marked metabolic differences between roots and leaves under 0 and 10 µM Cd treatments.

DEMs were defined using thresholds of P < 0.05 and VIP > 1. Under high Cd stress, 1,054 DEMs were detected in leaves (730 up-regulated and 324 down-regulated), whereas 882 DEMs were identified in roots (473 up-regulated and 409 down-regulated) (Fig. 5A). Among these, 75 DEMs were up-regulated in leaves but down-regulated in roots, while 34 DEMs were up-regulated in roots but down-regulated in leaves (Fig. 5B). The four largest DEM categories in both tissues were amino acids, peptides, and their derivatives (107 in leaves and 74 in roots); carbohydrates and carbohydrate conjugates (27 in leaves and 20 in roots); linoleic acid and its derivatives (18 in leaves and 17 in roots); and fatty acids and fatty acid conjugates (43 in both leaves and roots) (Table S9).

Fig. 5.

DEMs analysis of rice leaves and roots under high Cd stress. A DEMs statistics; (B) Venn diagram analysis. KEGG pathway enrichment in (C) leaves and (D) roots. The horizontal axis represents the enrichment value, and the vertical axis represents the enrichment path. The size of the bubbles represents the number of DEMs. The color of the bubbles represents the size of the FDR value

KEGG functional enrichment analysis

KEGG pathway enrichment analysis was conducted to identify metabolic pathways associated with responses of rice roots and leaves to high Cd stress. Based on enrichment and topological analyses, the top 20 pathways with the smallest P values were selected for each tissue (Fig. 5C, D; Table S10). DEMs in roots and leaves were mainly associated with 11 pathways, including alanine, aspartate, and glutamate metabolism; linoleic acid metabolism; α-linolenic acid metabolism; arginine biosynthesis; aminoacyl-tRNA biosynthesis; D-amino acid metabolism; arginine and proline metabolism; carbon fixation in photosynthetic organisms; and biosynthesis of pantothenate and CoA biosynthesis.

Comprehensive analysis of transcriptome and metabolome

Correlation analysis between DEMs and DEGs

To assess relationships between DEMs and DEGs in rice roots and leaves under high Cd stress, nine-quadrant correlation plots were generated to depict DEMs with correlation coefficients greater than 0.8 and correlation test P values less than 0.05. Correlation analysis (Fig. 6A, B) showed that many genes in both tissues were positively correlated with metabolite changes under high Cd stress. KEGG co-enrichment analysis identified two shared pathways between the transcriptome and metabolome in leaves and roots (Table S11). Specifically, in leaves, both datasets were co-enriched in the α-linolenic acid metabolism and linoleic acid metabolism pathways (Fig. 6C; Table S11). In roots, co-enrichment was observed in the α-linolenic acid metabolism pathway (Fig. 6D; Table S11). Detailed information of DEGs and DEMs in the α-linolenic metabolism pathway was provided in Table S12 and Table S13.

Fig. 6.

Comprehensive analysis of transcriptome and metabolome of rice leaves and roots under high Cd stress. Nine-quadrant correlation diagrams of transcriptome and metabolome of leaves (A) and roots (B). C Bar charts of KEGG enrichment analysis results of transcriptome and metabolome of leaves and (D) roots. Pearson’s correlation analysis was employed to evaluate the correlation between mRNA and metabolites

Critical path analysis

Integrated transcriptomic and metabolomic analyses indicated that both DEGs and DEMs were enriched in the α-linolenic acid metabolism pathway in rice roots and leaves (Fig. 7). Within this pathway, DEGs encoded enzymes including PLA2G (1 up-regulated in leaves and 1 down-regulated in roots), 14 LCAT3 (1 up-regulated in leaves; 3 up-regulated and 5 down-regulated in roots), DOX (1 up-regulated in roots), LOX2S (2 up-regulated in leaves; 3 up-regulated and 1 down-regulated in roots), HPL (1 down-regulated in leaves), AOS (1 up-regulated in leaves; 3 up-regulated and 1 down-regulated in roots), ADH1 (1 up-regulated in leaves and 2 up-regulated in roots), CEQORH (1 up-regulated in leaves; 3 down-regulated and 1 up-regulated in roots), OPR (4 up-regulated in leaves and 4 up-regulated in roots), E1.1.3.6 (3 up-regulated in leaves), MFP2 (1 up-regulated and 1 down-regulated in leaves), and E2.1.1.141 (1 down-regulated in leaves and 2 down-regulated in roots). Metabolite analysis of this pathway showed that 9 S-HpOTrE, 10-OPDA, 13(S)-hydroperoxylinolenic acid, (+)-7-iso-jasmonate, and jasmonic acid (JA) were up-regulated only in leaves, whereas (−)-methyl jasmonate (MeJA) was up-regulated only in roots. Traumatin was down-regulated in both tissues, while heptadecatrienal, colnelenic acid, and 12,13-EOTrE were down-regulated only in roots. Detailed information on DEGs and DEMs within the α-linolenic acid metabolism pathway is provided in Tables S12 and S13.

Fig. 7.

The α-linolenic acid metabolic pathway in rice under high Cd stress. Diagram depicting changes in leaves versus roots. Enzyme nodes (blue ovals) were influenced by DEGs. Metabolite nodes (green rounded rectangles) represented DEMs. Rectangular nodes denoted individual DEGs or DEMs, partitioned to show relative levels in leaves (left) and roots (right). Node color intensity indicated the degree of significant up- or down-regulation under Cd stress

In addition, selected DEGs from the α-linolenic acid metabolism pathway in leaves and roots were validated by qRT-PCR. The validation results and primer sequences were shown in Fig. S7 and Table S2. The expression trends determined by qRT-PCR were consistent with the transcriptome data, supporting the reliability of the transcriptomic analysis (Table S12).

Discussion

Physiological responses of rice plants to high Cd stress

High Cd stress induces typical toxic symptoms in plants, including inhibition of root growth, leaf chlorosis and discoloration, appearance of brown spots, leaf curling, and reductions in biomass [40]. In this study, rice exposed to high Cd stress showed pronounced growth inhibition, reflected by decreases in plant height, fresh and dry weights, root surface area, average root diameter, root tip number, and root volume. Similar effects have been reported in peanut, where high Cd conditions markedly suppress root development, plant height, and dry weight of both roots and aboveground tissues [41]. Under high Cd stress, reductions in root length, plant height, and biomass in rice may result from Cd-induced cell death, which impairs cell division and differentiation in root apical meristems and restricts cell division and elongation [42]. In parallel, photosynthetic pigment contents in rice leaves declined, indicating that high Cd conditions also interfere with chlorophyll synthesis, reduce photosynthetic efficiency, and ultimately suppress seedling growth and biomass accumulation.

Cd accumulation promotes excessive production of ROS in plants, leading to oxidative stress [43]. Antioxidant enzymes, including SOD, CAT, APX, and POD, are central to ROS scavenging, maintenance of cellular redox balance, and protection against oxidative damage [44]. In barley seedlings exposed to high Cd concentrations, activities of SOD, APX, and CAT increase markedly [45]. Consistent with these findings, the present study showed that SOD, CAT, APX, and POD activities in rice leaves and roots increased to different extents under Cd stress. These changes indicate that high Cd disrupts antioxidant homeostasis, leading to ROS accumulation and oxidative injury.

Under hydroponic conditions, Cd preferentially accumulates in plant roots [46]. In this study, Cd contents increased in both leaves and roots, with substantially higher levels in roots. Excess Cd also interferes with the uptake of other mineral nutrients. For example, elevated Cd reduces Ca, Cu, and Mn contents in tobacco leaves, while increasing Mg content [47]. Similarly, in the present study, Ca and Zn contents decreased in rice leaves, whereas Zn, Ca, and Mg contents declined in roots. Reduced Ca availability can limit biomass accumulation and exacerbate osmotic, oxidative, and ionic stresses in plants [48]. The observed decrease in root Ca content under high Cd stress suggests that insufficient Ca uptake intensifies osmotic and oxidative stress, thereby aggravating Cd toxicity in rice.

Metabolic responses of rice plants to high concentration of Cd

Metabolomic analysis showed that DEMs in rice leaves and roots were mainly associated with amino acids, carbohydrates, fatty acids, and linoleic acid derivatives. KEGG enrichment analysis indicated that amino acid metabolism and linoleic acid metabolism were significantly enriched in both tissues. In particular, alanine, aspartate, and glutamate metabolism showed strong responses, while linoleic acid metabolism and α-linolenic acid metabolism were prominent among unsaturated fatty acid pathways (Fig. 5C, D). These results indicate that modulation of amino acid metabolism and linoleic acid metabolism contributes to Cd tolerance in rice.

Amino acids are central to protein synthesis and are closely associated with energy metabolism, osmotic adjustment, antioxidant defense, and synthesis of signaling molecules, which are critical for plant adaptation to environmental stress [49]. Enhanced aspartate metabolism, for example, promotes conversion between malate, aspartate, and glutamate, and significantly reduces Cd accumulation in rice roots and shoots [50]. In addition, metabolism of aspartate, glutamate, and alanine is closely associated with stress tolerance and detoxification processes in plants [51]. Linoleic acid serves as a precursor for JA biosynthesis. JA is a key stress-responsive hormone that activates defense responses to Cd stress [52]. Linoleic acid also acts as an antioxidant, limiting lipid peroxidation by reducing ROS accumulation and contributing to metal detoxification [53]. In this study, aspartate, arginine, proline, and linoleic acid were significantly upregulated in both leaves and roots under high Cd stress. Integrated transcriptomic and metabolomic analyses further showed that linoleic acid metabolism was significantly enriched in leaves, while α-linolenic acid metabolism was co-enriched in both leaves and roots (Table S11).

Overall, under high Cd stress, rice leaves and roots enhance carbon and nitrogen metabolism, including aspartate, glutamate, and alanine pathways, as well as unsaturated fatty acid metabolism, particularly linoleic acid and α-linolenic acid metabolism. These coordinated metabolic adjustments strengthen antioxidant capacity, modulate metal ion uptake, and increase tolerance of rice plants to Cd stress.

Transcriptional responses of rice plants to high Cd stress

Cd stress altered gene expression in rice, with substantially more DEGs detected in roots than in leaves, indicating a stronger transcriptional response in the root system. KEGG analysis of root DEGs showed significant enrichment of plant hormone signal transduction and ABC transporter pathways (Fig. 4D). JA mitigates heavy-metal damage in plants, supported by evidence that endogenous JA levels change markedly under metal stress; for example, increased Cd sensitivity in tomato is associated with reduced endogenous JA [54]. Transcriptomic analysis showed significant enrichment of the α-linolenic acid metabolism pathway under Cd stress. Because JA is a product of this pathway, these results indicate an important role of JA in rice responses to Cd toxicity.

In plants, JA-related gene expression is regulated through activation or repression by transcription factors [55]. Transcriptomic profiling identified multiple transcription factor families, including bZIP, MYB, WRKY, bHLH, TCP, and NAC (Table S7). The bZIP family is widespread in plants, and specific bZIP factors are regulated during stress adaptation [56]. In rice, overexpression of bZIP72 produces phenotypes similar to those observed with SAPK10 overexpression; SAPK10-mediated phosphorylation enhances transcription of AOC and promotes endogenous JA synthesis [57]. In addition, overexpression of SpbZIP60 improves electron transfer efficiency and enhances Cd tolerance in Arabidopsis [58]. Therefore, modulation of bZIP transcription factor expression under Cd stress may increase JA accumulation in rice.

MYB transcription factors serve as central regulators of many plant-specific processes, including hormone responses, cell-cycle control, and stress responses [59]. Overexpression of MYB49 in Arabidopsis increases Cd accumulation, whereas loss-of-function reduces Cd accumulation, demonstrating its role in Cd regulation [60]. The R2R3-MYB gene ThRAX2 enhances antioxidant enzyme activity when overexpressed in Arabidopsis, reduces MDA levels and membrane lipid peroxidation, and improves Cd tolerance [61]. Consistent with these reports, numerous MYBs were identified in this study, showing both up- and down-regulation in leaves and roots, suggesting that rice adjusts MYB-mediated transcription to respond to Cd stress.

WRKY and bHLH transcription factors are also widely distributed in plants and contribute to development and abiotic stress responses [62, 63]. NAC transcription factors participate in transcriptional regulation of metal detoxification [64], whereas TCP transcription factors play roles in plant development and secondary metabolism [65]. Members of these families were detected in the transcriptome dataset (Table S7), although their specific functions in rice Cd responses require further investigation.

A total of 82 DEGs related to antioxidant enzymes were identified (Table S8), indicating transcriptional regulation of antioxidant systems under high Cd stress. Cd stress also affected mechanisms of metal uptake and transport. Twenty-seven metal transporter genes were identified, including ZIP family transporters, NRAMP metal ion transporters, potassium transporters, and copper transporters. ZIP and NRAMP transporters regulate metal ion homeostasis and are critical for plant responses to Cd stress [66, 67]. The ABC transporter SbABCB11 has been shown to mediate Cd transport in plants [68]. Differential expression of these transporter genes likely adjusts metal uptake and distribution, contributing to rice tolerance under Cd toxicity.

Joint analysis of transcriptome and metabolome

Integrated analysis revealed two KEGG pathways shared at the transcriptomic and metabolomic levels in leaves: α-linolenic acid metabolism and linoleic acid metabolism. In roots, a single shared pathway was identified: α-linolenic acid metabolism. Among these, α-linolenic acid metabolism was common to both tissues and emerged as a central pathway for rice responses to Cd stress.

Unsaturated fatty acids, as structural components and regulators of cell membranes, are critical for plant stress tolerance [69]. α-Linolenic acid, a plant-specific omega-3 polyunsaturated fatty acid, contributes to the stability of cellular structures [70]. Phospholipase A2G (PLA2G) can enhance α-linolenic acid turnover [65]. Transcriptomic data identified two DEGs associated with PLA2G (Table S12). However, PLA2G was not significantly upregulated or downregulated in the root system, which might be due to the fact that cadmium ions affected other factors in the α-linolenic acid pathway. Triglyceride lipase (TGL) catalyzes hydrolysis of triglyceride ester bonds and supports energy supply during seed germination and plant development [71, 72]. Upregulation of TGL expression in leaves suggests enhanced membrane lipid hydrolysis, release of fatty acids, and contribution to synthesis of lipid-derived defense signals, such as jasmonates, under Cd stress. DEFECTIVE IN ANTHER DEHISCENCE 1 (DAD1) is an initiating enzyme in the JA signaling pathway. Overexpression of Bna.A05DAD1 increases linoleic and linolenic acid contents and modulates JA and auxin signaling [73], thereby enhancing stress tolerance. In this study, majority of DAD1 family genes displayed a root-specific expression pattern, with their transcript abundances markedly decreased in foliar tissues; in contrast, a single gene screened from the TGL gene family showed elevated expression levels in leaves. This pattern suggests that Cd accumulation in roots may trigger early changes in DAD1 expression, followed by systemic signaling to aerial tissues; this hypothesis requires further validation. Together, these observations suggest coordinated effects of TGL and DAD1 that promote linoleic acid conversion and strengthen stress tolerance under Cd exposure.

Cd exposure altered fatty acid metabolism in rice. The AOS pathway converts polyunsaturated fatty acids, including linoleic and linolenic acids, into oxygenated derivatives and is essential for JA biosynthesis [74]. JA is a lipid-derived hormone that enhances antioxidant enzyme activity, limits cellular damage, and supports cellular homeostasis [75]. Under abiotic stress, accumulation of linolenic acid activates JA signaling and improves stress tolerance [76]. Traumatic acid is a direct precursor in the JA pathway and supports antioxidant responses [77]. In this study, activities of key antioxidant enzymes, including SOD, POD, APX, and CAT, were consistent with regulation by jasmonates. Lipid oxidation products generated through enzymatic or non-enzymatic oxidation of polyunsaturated fatty acids function in signaling and defense [78]. Following Cd exposure, the majority of genes associated with LOX2S were significantly upregulated in the root, accompanied by increased levels of 9(S)-HpOTrE and 13(S)-HpOTrE. In contrast, colnelenic acid and traumatic acid contents decreased, indicating altered regulation of traumatic acid metabolism at 10 µM Cd. At the same time, AOS-related genes were upregulated, promoting accumulation of JA signaling activators, including (+)-7-iso-jasmonate, and formation of (−)-MeJA. JA and its derivatives play established roles in plant tolerance to heavy metal stress [79, 80].

Collectively, these results indicate that, under high Cd stress, regulation of α-linolenic acid metabolism through genes such as LOX and AOS supports redox balance and limits damage caused by excessive ROS, thereby increasing Cd tolerance in rice.

Molecular mechanism of rice leaf and root responses to high Cd stress

Based on Fig. 8, a putative regulatory model for rice responses to Cd stress is proposed. Upon exposure to 10 µM Cd, roots first absorb and accumulate Cd ions, resulting in shortened, thickened, and brown roots. Cd is subsequently transported to leaves, where impaired development or necrosis occurs. Excess Cd elevates intracellular ROS, induces oxidative stress, disrupts antioxidant enzyme systems, and causes oxidative damage. During α-linolenic acid metabolism, rice mitigates oxidative injury by regulating expression of enzyme genes, including PLA2G and 14LCAT3, in roots and leaves, together with associated metabolite levels, such as aspartate and glutamate. Elevated Cd also perturbs uptake and transport of other metal elements, restricting acquisition of essential nutrients and contributing to nutrient deficiency. Overall, although rice initiates adaptive responses to high external Cd, sustained Cd accumulation continues to constrain growth and development. α-Linolenic acid, a key plant polyunsaturated fatty acid, serves as a precursor for jasmonate signaling molecules, including JA and MeJA. The accumulation of JA and MeJA, particularly in roots, supports a central role for JA signaling in rice responses to Cd stress. Future work should identify additional key genes to provide targets for genetic approaches aimed at improving Cd tolerance in rice.

Fig. 8.

Molecular reaction mechanisms of rice leaves and roots under high Cd stress conditions

Conclusion

Cd treatment significantly inhibits rice growth, with clear effects on both roots and leaves. Roots become shorter, thicker, and brown, whereas leaves are reduced in size, turn yellow, and develop necrotic spots. These morphological changes are accompanied by altered nutrient uptake, reduced chlorophyll content, and disruption of antioxidant enzyme systems. Integrated transcriptomic and metabolomic analyses show significant enrichment of the α-linolenic acid metabolism pathway in both leaves and roots. Within this pathway, LOX and AOS enzymes are central to oxidation of linoleic and linolenic acids, and LOX- and AOS-related genes show tissue-specific regulation. LOX- and AOS-related genes are specifically expressed in roots, yet both show upregulated expression in leaves. Lipid oxidation products generated during α-linolenic acid metabolism contribute to mitigation of oxidative damage under Cd stress. Overall, this study clarifies the physiological and molecular responses of rice to Cd toxicity and highlights the role of α-linolenic acid metabolism in alleviating Cd stress. These findings advance understanding of Cd effects on rice development and identify key metabolic pathways and candidate molecular targets for future genetic approaches to improve Cd tolerance in crops.

Authors’ contributions

C.L., Y.W. and Y.L.: Conceived and designed the experiments. C.L., Y.W., L.Q., Q.L., R.Z., Q.X., H.H., Y.X., and Y.L.: Performed the experiments and analyzed the data. C.L., Y.W. and Y.L.: Wrote the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Project of Rural Science and Technology Team “One-to-One” Service to Help the Town Full Coverage of Action Funding in Zhanjiang City (A23081); the Project of Social Services of Rural Science and Technology Specialists of Guangdong Ocean University (080503052212); the Graduate Education Innovation Program of Guangdong Ocean University (202401 and 202504); Provincial-level College Students’ Innovation and Entrepreneurship Training Program Project (S202510566025); Annual Outstanding Young Researcher Project of the Coastal Agriculture College of Guangdong Ocean University (BH2025JCQN004); the Innovation Team Project of Guangdong Ocean University for College Students (CXTD2021009).

Data availability

The raw sequencing data of the transcriptomics in this study can be found in the NCBI database under registration number PRJNA1370671 (https://www.ncbi.nlm.nih.gov/sra/PRJNA1370671).

Declarations

Ethics approval and consent to participate

Not applicable.

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Not applicable.

Competing interests

The authors declare no competing interests.