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Plant Soil (2023) 485:259–280

https://doi.org/10.1007/s11104-022-05827-1

RESEARCH ARTICLE

Transcriptomics, metabolomics, antioxidant enzymes

activities and respiration rate analysis reveal the molecular

responses of rice to Cd stress and/or elevated CO2

concentration

Lanlan Wang · Ge Wang · Jinghui Cui · Xuhao Wang · Meng Li · Xiufen Qi ·

Xuemei Li · Yueying Li · Lianju Ma

Received: 29 August 2022 / Accepted: 29 November 2022 / Published online: 8 December 2022

© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2022

Abstract

Purpose To explore the regulatory mechanism of

rice to Cd stress and/or elevated CO2 concentration.

Methods The rice seedlings (Oryza sativa L.) were

exposed to two CO2 concentrations (400±20 μmol mol−1,

AC; 800±20  μmol  mol−1, EC) and CdCl2 concentrations (0 µmol L−1, 150 µmol L−1) for 10 days. Antioxidant

enzymes activities, respiration rate, transcriptomics and

metabolomics changes of leaves were studied.

Results GR (glutathione reductase) activity, respiration rate, many sugars, polyols, amino acids and

organic acids contents increased under Cd stress.

DEGs (diferentially expressed genes) annotated

in photosynthesis-antenna proteins were downregulated; When CO2 increases, some antioxidant

enzymes activities and respiration rate decreased.

Genes and metabolites related to photosynthesis

were enhanced; Under the composite treatment, the

ascorbate–glutathione (ASA-GSH) cycle was regulated, some amino acids contents increased, respiration rate decreased. The DEGs mainly enriched in

substances transmembrane movement and enzymes

activities, etc.

Conclusion Under Cd stress, GR played an important antioxidant role. Sugar, polyol and amino acid

metabolisms were enhanced to provide energy,

improve osmotic adjustments, maintain cell membrane stability, etc. Organic acids contents increased

for regulating plant nutrition, the tricarboxylic acid

(TCA) cycle and as the secondary metabolites. Photosynthesis was adversely afected; Under high CO2,

photosynthesis increased, the decrease of partial O2

pressure resulted in the decrease of some antioxidant enzymes activities and respiration rate; Under

the composite treatment, Cd stress played a dominant role, elevated CO2 alleviated the Cd stress damage by regulating ASA-GSH cycle and amino acids

metabolism.

Keywords Elevated CO2 · Cd stress ·

Transcriptome · Metabolome · Antioxidant enzymes

activities · Respiration rate

Introduction

The elevated atmospheric CO2 concentration and the

heavy metals pollution are two environmental problems to plants at present. Since 2011 (measurements

Responsible Editor: Juan Barcelo.

Supplementary Information The online version

contains supplementary material available at https://doi.

org/10.1007/s11104-022-05827-1.

L. Wang (*) · G. Wang · J. Cui · X. Wang · M. Li · X. Qi ·

X. Li (*) · Y. Li · L. Ma 

College of Life Science, Shenyang Normal University,

Shenyang 110034, Liaoning, China

e-mail: wangqi5387402006@163.com

X. Li 

e-mail: lxmls132@163.com

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reported in AR5), CO2 concentration has continued to

increase in the atmosphere, reaching annual averages

of 410 μmol mol−1, in 2019, atmospheric CO2 concentrations were higher than at any time in at least 2 million years (high confdence), and CO2 emissions that

roughly double from current levels by 2050 (IPCC

2021). Most of the heavy metal pollutions in soil are

from the industrial wastewater discharge, agricultural

phosphate fertilizer and sewage sludge, and have seriously afected much farmland and crops (Zou et  al.

2020). Cadmium pollution is especially severer than

many other elements (Hang et  al. 2009; Xiao et  al.

2019). The plants under Cd stress can be afected in

cell damages, production of toxic metabolites, inhibition of photosynthesis and respiration (Meng et al.

2009; Liu et al. 2012; Hassan et al. 2014; Singh et al.

2016); Our study has shown that high CO2 could

improve photosynthesis, reduce stomatal conductance,

regulate endogenous hormones and organic acids contents of rice seedling leaves (Qi et al. 2021), and also

could alleviate the damage of heavy metals (Cd and

Pb) stresses by enhancing photosynthesis and changing hormone ratios (Li et al. 2021; Wang et al. 2021).

Other researchers have also studied the alleviating

efects of elevated CO2 when plants under heavy metals stresses (Tukaj et al. 2007; Li et al. 2010).

Plant antioxidant system is a defense mechanism

dealing with various abiotic and biotic stresses.

Pritchard et al. (2000) showed that under high CO2

concentration, the activities of SOD (superoxide

dismutase), POD (peroxidase), CAT (catalase), GR,

APX (ascorbate peroxidase) and GPX (glutathione

peroxidase) of the two genotypes of soybean

decreased, which may be because the partial pressure of CO2 in chloroplast increased and the partial

pressure of O2 decreased, enhancing the assimilation capacity of CO2 and reducing the excess excitation energy. At the same time, oxygen as electron

acceptor has less chance to form the ROS (reactive

oxygen species), which leads to the decrease of

ROS and antioxidant enzyme activities; Heavy metals such as cadmium can destroy the homeostasis

environment of plant cells, increase the ROS contents in cells, and then cause the defense and antioxidant response mechanism in plant cells, including the enzymatic scavenging system of ROS. The

ASA-GSH cycle and glutathione oxide cycle are the

main metabolic pathways of ROS removal in plants

(Mittler 2002), in which antioxidant enzymes such

as SOD, CAT, POD, APX, DHAR (dehydroascorbate reductase), MDAR (monodehydroascorbate

reductase) and GR play a major role.

The accumulation of biomass and the ability to adapt

to the environment during plant growth can be seen as

the ultimate expression of metabolic pathways (Meyer

et  al. 2007). At present, more than 200,000 kinds of

metabolites have been discovered in plants. Metabolomics research can provide insight into the deep and valuable molecular stress response, which is of great signifcance in understanding the metabolic pathways of plants,

improving the response of plants to adverse environmental stresses, and improving crop yield and quality (Saito

and Matsuda 2010, Adamski and Suhre 2013). Elevated

CO2 can regulate the generation of secondary metabolites

in plants, increasing the contents of phenolic compounds,

which is related to strong antioxidant capacity of plants

(Akula and Ravishankar 2011; Li et  al. 2018); When

plants are stressed by heavy metals, the metabolites and

metabolic pathways in plants will change accordingly, so

as to achieve the purpose of self-protection. Zeng et al.

(2021) found that most of carbohydrates and amino acids

of rice grain decreased under Cd stresses, energy metabolism was afected, content of inositol increased (has

inhibitory efect on cadmium toxicity), 13 (S)-HPOT

(associated with α-linolenic acid metabolism and jasmonic acid metabolism), 9, 10-DHOME (associated with

linolenic acid metabolism), citric acid, hexadecanoic acid

and organic acids contents increased.

RNA-seq is a high-throughput sequencing technique that does not require genomic background and

can be used to analyze gene transcription and expression in plants (Huang et al. 2018a). The transcriptome

analysis on rice seedlings under Cd stress showed that

the related genes including fve family of transcription

factors (zinc fnger, AP2-EREBP, WRKY, NAC and

MYB), mainly related to primary metabolism, redox,

irritant response, not folded protein binding, sulfur

assimilation, ROS clearance, stress reaction, cell wall

formation, and the biological processes, such as ion

transport and signal transduction (Lin et al. 2013; He

et  al. 2015). Oono et  al. study showed that several

genes related to defense system in rice were strongly

up-regulated under cadmium stress, and the expression of metal ion transporter genes may be related to

Cd concentration (2016).

The plants response to the changed environment is the

process interacting with multi-gene, multi-signal molecule and multi-metabolite. Combined transcriptomics

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and metabolomics analysis have been used to reveal gene

function, which provides a powerful tool for understanding plant biological processes and molecular tolerance

mechanisms (Schaefer et al. 2017, Huang et al. 2018b,

Wang et  al. 2019). There were many studies on single

environmental factor efects on plants, the combined

efect of high CO2 and Cd stress on plant antioxidant system, transcriptome and metabolome responses needs further study. Rice is one of the most important crops, and

it is also a type plant of C3 in monocotyledonous plants,

so rice was used to measure antioxidant enzymes activities and screen diferentially expressed genes, diferent

metabolites and identify diferent metabolic pathways

under Cd stress and elevated CO2 concentration basing

on combination of transcriptomics and metabolomics

techniques, so as to have a deeper understanding of the

molecular responses of rice to the future environmental

changes.

Materials and methods

Plant materials and treatments

The uniform and healthy rice seeds (Oryza sativa L.)

were sterilized, rinsed, and germinated in the dark. The

germinating seeds were transferred to beakers containing Hoagland solution. Seedlings were maintained in a

carbon dioxide artifcial climate box (16/8  h light/dark

period, 26/22 °C day/night, 80% relative air humidity and

800 μmol m−2 s

−1 photosynthetic photon fux density) until

to the stage of two leaves. Then the rice seedlings were

exposed to two CO2 concentrations (400±20 μmol mol−1,

AC; 800±20 μmol mol−1, EC) and CdCl2 concentrations

(0 µmol L−1, 150 µmol L−1) for 10 days. Total of 6 treatments in this experiment (Table 1).

After 10 days treatments, leaves of rice seedlings

were measured. 5 repeats were selected randomly

in each treatment for antioxidant enzymes activities

measurement, 9 repeats for respiratory rates measurement, 3 repeats for transcriptomic sequencing and

analysis, and 6 repeats for metabolic analysis.

Antioxidant enzymes activities and respiratory rates

measurements and data analysis

The activity of SOD was determined by photoreduction of azoblue tetrazole method described by Beyer

and Fridovich (1987); Activity of POD were measured

according to Chance and Maehly (1955); CAT activity

was determined by UV absorption method according to

Knorzer et al. (1996); Krivosheeva et al. (1996) determined the activities of APX, DHAR, MDAR and GR.

The respiration rate of rice leaves was measured by

oxygen electrode (Chlorolab2+liquid oxygen electrode,

Hanshatech, UK). After the equipment was connected,

the temperature of the reaction chamber was set at 20 ℃

and the atmospheric pressure was 101 kPa. The electrode

was calibrated, and air-saturated water was added into the

reaction cup. After the signal line was stabilized, an appropriate amount of insurance powder (Na2S2O4) was added

to establish the zero-oxygen line, and the correction result

was saved after the zero-oxygen line stabilized. The reaction cup was rinsed several times to eliminate interference

from the safety powder. Rice leaves (about 1 cm2

) after

10 days treatments were cut into uniform fragments, and

were put into a large needle flled with measuring medium

(air-saturated water), the air was extracted until the leaves

sank. Then the leaf fragments were taken out and put into

the reaction cup containing the determination medium,

the reaction cup plug was covered for measurement. The

measurement was stopped after the respiration curve was

stable. A slope of the same size interval was taken and the

record was saved. Respiration rate = slope×reaction volume/leaf area (μmol cm−2 min−1).

The signifcant diferences of parameters were

using the method of two-way ANOVA followed by

LSD’s multiple-range test for multiple comparisons.

The data analysis was done with the SPSS statistical

software (v20.0, SPSS, USA) and the fgures were

drawn by Origin (v9.0, Origin, USA) software.

Metabolic analysis

Metabolite extraction and profling analysis

Rice leaves (50±1 mg) were transferred to 2 ml Eppendorf tubes (EP), 0.45 ml methanol–water (3:1, v/v) and

Table 1 Names of treatments

Treatments Cd2+ (CdCl2·2.5H2O

μmol/L)

CO2 (μmol/mol)

AC 0 400±20

Cd 150 400±20

EC 0 800±20

EC+Cd 150 800±20

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10 μl L-2-chlorophenylalanine were added, then swirled

for 30  s. Magnetic beads were then added for 4  min

grinding and 5 min ultrasonic in ice water bath. The leaf

extracting solution was centrifuged at 4 ℃ for 15 min at

12000 rpm. 300 μl supernatant was transferred to 1.5 ml

EP tubes, 60 μl was taken from each sample and mixed

to QC sample, then the extract was dried in vacuum concentrator, 60 μl methoxamine salt reagent (dissolved in

20 mg ml−1 pyridine) was added to the dried metabolite,

mixed well and put into an oven at 80 ℃ for 30 min. 80 μl

derivatization reagent BSTFA (containing 1% TMCS,

v/v) was added to each sample and incubated for 1.5 h at

70 ℃. After cooled to indoor temperature, 5 μl FAMEs

(soluble in chloroform) was added to the mixed samples

for detection by GC-TOF/MS, the sequence was random.

1 μl grinding sample was injected into the injector (without shunt mode) with helium as carrier gas. The inlet purge

fow rate was 3 ml min−1, the fow rate was 1 ml min−1, and

the initial temperature was maintained at 50 ℃ for 1 min.

The temperature was then increased to 310 ℃ at a rate of

10 ℃ min−1 and kept for 8 min. The temperature of the forward sample outlet, transmission line and ion source were

280 ℃, 280 ℃ and 250 ℃ respectively, and the ionization

voltage was -70 eV. The mass spectrum data were collected

after a solvent delay of 6.25  min, with a mass range of

50–500 m z−1 and a scanning rate of 20 spectra s

−1.

Data analysis

Data were acquired and pre-processed using the

manufacturer’ Chroma TOF software (versions 4.3x,

LECO). Data analysis was performed by SIMCA-P

14.1 software package (Umetrics). Additionally, diferential metabolites were identifed using Student’s t-test

(p<0.05) and VIP (VIP>1), combined with similarity values>700. Subsequently, KEGG (http://www.

genome.jp/kegg/) was used to construct metabolic

pathway, which were then analyzed by MetaboAnalyst

5.0 (https://www.metaboanalyst.ca/) according to the

screened diferential metabolites. The metabolic pathways with impact value>0.1 were screened out.

Transcriptomic sequencing and analysis

RNA isolation and library construction

Samples were collected and stored at -80 ℃ after

liquid nitrogen quick-freezing. Total RNA was

extracted from polysaccharide polyphenol plant

total RNA extraction kit, and the integrity, purity

and concentration of RNA were detected by electrophoresis and then the sequenced library was constructed. Qubit2.0 was used to measure the RNA

concentration and Agilent Bioanalyzer 2100 system was used to assess the RNA integrity. After the

library inspection was qualifed, the pooling was

conducted according to the target disembarkation

data volume, and the Illumina HiSeq platform was

used for sequencing.

Quality control

TopHat2 was used to flter the outgoing data to get

the Clean Data, and then alignment of clean reads of

each sample were sequenced with the specifed reference genome to get the Mapped Data, and the quality

of the library Get Mapped Data was evaluated, and

library quality was evaluated.

Quantifcation of gene expression levels

After sequencing, bioinformatics analysis was performed,

and sequences were compared between HISAT2 (version 2.0.4) and the reference genome (Oryza sativa

Japonica Group 4.0). Using StringTie (version 1.3.4D),

gene expression levels were measured using FPKM.

DESeq2 (version 1.6.3) was used to analyze gene expression diferences between samples. FDR values<0.01 and

FC≥3.0 were used as DEGs screening indexes. The differentially expressed genes were functionally annotated in

GO and KEGG databases, and p≤0.05 was considered

statistically signifcant.

Quantitative real‑time PCR analysis

qRT-PCR (quantitative real-time PCR) was used

to validate the expression level of genes from RNA

sequencing (RNA seq). 12 DEGs (diferentially

expressed genes) were randomly selected for qRT-PCR

to verify the validity of the data. The qRT-PCR experiment was carried out by real-time fuorescence quantitative PCR instrument (analytikjena-qTOWER2.2,

Germany). Each gene was repeated 3 times in each

sample. Sequences of all primers used in the qRT-PCR

were listed in Table S1.

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Gene function annotation and diferentially expressed

genes (DEGs) analysis

Diferential expression analysis, functional annotation

and functional enrichment of diferentially expressed

genes) were conducted according to the expression levels

of genes in diferent samples, based on GO (http://www.

geneontology.org/) and KEGG (http://www.genome.jp/

kegg/), using R/clusterProfler 3.10.1 (minGSSize=1,

maxGSSize=10000, pAdjustMethod=\"fdr\").

Results

Antioxidant enzymes activities changes under Cd

stress and/or elevated CO2

Compared with AC: Cd stress increased SOD, POD and GR

activities, decreased CAT and MDAR activities signifcantly,

but did not change APX and DHAR activities. GR activity

has the largest increase rate of 71.71%; EC increased CAT,

APX and DHAR activities, decreased SOD, POD, MDAR

and GR activities signifcantly. There was a big increase in

DHAR activity, while a big decrease in MDAR activity, with

the increase factor and decrease rate reaching 16.76 times

and 83.59%, respectively; EC+Cd treatment increased POD,

DHAR and GR activities, decreased SOD, CAT and MDAR

activities and did not change APX activity.

Compared with Cd: EC+Cd treatment increased

DHAR and GR activities, decreased SOD, POD,

CAT and MDAR activities signifcantly, did not

change APX activity. The decrease rate of SOD activity reached 81.03% (Fig. 1).

Respiratory rate change under Cd stress and/or

elevated CO2

Compared with AC: Cd stress increased respiratory rate

signifcantly, the increase rate reached 18.24%, but EC

and EC+Cd decreased it signifcantly, decrease rate

reached 24.01% and 54.03%, respectively.

Compared with Cd: EC+Cd also decreased it signifcantly, decrease rate reached 61.13% (Fig. 2).

Metabolic changes under Cd stress and/or elevated

CO2

Principal component analysis (PCA) was used

to determine the factors infuencing metabolite

diferences. The frst principal component (PC1)

explained 76.20% of the variance, indicating metabolic changes between leaves under Cd and no Cd

stress (Fig. 3a). The main metabolites contributing to

PC1 were alanine, glucose, L-allothreonine, serine,

proline, citric acid, valine, aspartic acid, isoleucine,

asparagine, succinic acid and oxalic acid (Fig.  3b;

Table S2). The samples under atmospheric CO2 and

elevated CO2 treatments were almost separated by

the second principal component (PC2), which represented 8.05% of the total variation (Fig. 3a). Alanine,

asparagine, oxalic acid, proline, isoleucine and succinic acid were the main factors contributing to PC2

(Fig. 3b; Table S2). Obvious diferences in responses

to the Cd stress and/or elevated CO2 concentration

of metabolite levels in metabolic pathways in leaves

were shown by the PCA and loading plots (Fig.  3).

Total of 41 contents of metabolites changed signifcantly under diferent treatments. These diferential

metabolites consisted of 10 sugars and polyols, 15

amino acids, 12 organic acids, 1 fatty acid, and 3 others (Table 2).

Under Cd stress, compared with AC, sugar and

polyol metabolism was greatly enhanced, contents of

glucose, glucose-6-P and glucose-1-P (related to photosynthesis and glycolysis), rafnose, myo-inositol,

trehalose, melibiose, maltose, galactinol and cellobiose were all increased; Amino acid metabolism was

also enhanced, alanine, phenylalanine, glutamic acid,

oxoproline, proline, aspartic acid, valine, serine, glycine, isoleucine, L-cysteine, lysine and tyrosine contents were all increased; Among organic acids, citric

acid, L-malic acid, aconitic acid, quinic acid, salicylic

acid, D-glyceric acid, shikimic acid, ferulic acid and

glycolic acid contents increased, but oxalic acid, succinic acid and fumaric acid contents decreased; Linolenic acid and O-phosphorylethanolamine, putrescine,

5-Methoxytryptamine contents increased (Table  2;

Fig.  4). The main diferential metabolic pathways

were glycine, serine and threonine metabolism, citrate cycle (TCA cycle), glyoxylate and dicarboxylate

metabolism, pyruvate metabolism, alanine, aspartate

and glutamate metabolism, galactose metabolism and

alpha-linolenic acid metabolism (Fig. 5a).

Under EC, compared with AC, some of sugars

and polyols contents increased, include glucose-1-P,

rafnose, melibiose and galactinol, but myo-inositol

and trehalose contents decreased; Related to amino

acid metabolism, phenylalanine, glutamic acid,

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oxoproline, proline, aspartic acid, asparagine, valine,

serine, glycine and isoleucine contents all decreased,

only alanine content increased; Many organic acids

contents decreased, include oxalic acid, aconitic acid,

fumaric acid, salicylic acid, D-glyceric acid, shikimic acid and glycolic acid, only quinic acid content

Fig. 1 Antioxidant enzymes activities changes under Cd stress and/or elevated CO2. The bars indicated standard error. Diferent letters indicate a signifcant diference at p<0.05 (LSD test)

Fig. 2 Respiratory rates

changes under Cd stress

and/or elevated CO2. The

bars indicated standard

error. Diferent letters indicate a signifcant diference

at p<0.05 (LSD test)

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increased; Putrescine content increased, and 5-methoxytryptamine content decreased (Table  2; Fig.  4).

The main diferential metabolic pathways were glycine, serine and threonine metabolism, glyoxylate

and dicarboxylate metabolism, alanine, aspartate

and glutamate metabolism and galactose metabolism

(Fig. 5b).

Under EC+Cd, compared with AC, the overall

metabolic trend was similar to that under Cd treatment except that glucose-6-P, L-malic acid, shikimic acid, glycolic acid and linolenic acid contents

decreased, but asparagine content increased. Quinic

acid and D-glyceric acid showed no signifcant

change (Table 2; Fig. 4);

Under EC+Cd, compared with Cd, among sugars and polyols, only galactinol content increased,

glucose-1-P, trehalose, maltose, cellobiose contents

decreased; Many amino acids (include alanine, phenylalanine, proline, asparagine, valine, isoleucine,

L-cysteine, lysine and tyrosine) contents increased;

Among organic acids, oxalic acid, L-malic acid,

aconitic acid, fumaric acid, quinic acid, salicylic

acid, D-glyceric acid, shikimic acid and glycolic

acid contents decreased, only succinic acid content

increased. Also, content of putrescine increased

(Table  2; Fig.  4). The main diferential metabolic

pathways were pyruvate metabolism, glyoxylate and

dicarboxylate metabolism and citrate cycle (TCA

cycle) (Fig. 5c).

Transcriptional changes under Cd stress and/or

elevated CO2

The results of gene expression levels obtained by

qRT-PCR and RNA-Seq were consistent (Fig.  S1).

Transcriptome analysis of seedling leaves under

both treatments showed that 77.87 Gb of clean data

(Q30>94.33%) was obtained, with clean data for

each sample up to 5.88 Gb. The sequence alignment

rate between clean data of each sample and reference

genome ranged within 94.83–95.86%, and the GC

content was greater than 50.54% (Table 3).

In this study, 2745, 2314, 3184 and 1142 genes

with signifcant expression diferences were screened

from AC vs Cd, AC vs EC, AC vs EC+Cd and Cd vs

EC+Cd sample groups respectively. Among them, in

Fig. 3 PCA of metabolic

profles and loading plots

of metabolites in leaves of

rice seedings. (a) principal

component analysis (PCA);

(b) loading plot. The numbers in the fgure represent:

1 Alanine, 2 Glucose, 3

L-Allothreonine, 4 Serine,

5 Proline, 6 Citric acid, 7

Valine, 8 Aspartic acid, 9

Isoleucine, 10 Asparagine,

11 Succinic acid, 12 Oxalic

acid

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Table 2 Diference of metabolite profles in rice seedlings under Cd stress and /or elevated CO2

Metabolite’s names AC Cd EC EC+Cd Fold changes log2 /AC Fold

changes

log2 /

Cd

Cd EC EC+Cd EC+Cd

Sugars and polyols

  Glucose 79.49±6.71 181.02±28.84 84.84±7.72 169.56±14.71 1.19** 0.09 1.09** −0.09

  Glucose-6-P 3.28±0.52 4.96±0.77 3.35±0.53 4.25±0.83 0.68** 0.03 −0.37* −0.22

  Glucose-1-P 8.00±0.86 19.92±2.67 11.36±2.42 14.90±3.10 1.32** 0.51** 0.90** −0.42*

  Rafnose 8.58±1.10 29.44±6.81 11.12±2.46 32.14±4.05 1.78** 0.37* 1.90** 0.13

  Myo-inositol 98.27±9.21 150.03±27.37 73.92±7.51 128.12±18.28 0.61** −0.41** 0.38** −0.23

  Trehalose 3.03±0.62 15.47±1.37 2.24±0.26 10.03±1.24 2.35** −0.44** 1.73** −0.63**

  Melibiose 1.65±0.31 4.57±0.82 2.42±0.69 3.91±0.43 1.47** 0.55** 1.24** −0.22

  Maltose 0.39±0.08 1.26±0.21 0.41±0.07 0.96±0.14 1.68** 0.07 1.30** −0.38*

  Galactinol 6.23±0.85 12.53±2.63 9.03±0.86 17.64±3.45 1.01** 0.54** 1.50** 0.49*

  Cellobiose 0.25±0.06 0.93±0.07 0.26±0.07 0.54±0.06 1.89** 0.05 1.09** −0.79**

Amino acids

  Alanine 213.47±47.72 434.45±50.86 329.40±37.70 520.21±62.93 1.03** 0.63** 1.29** 0.26*

  Phenylalanine 10.79±2.11 21.98±3.86 4.08±0.76 34.06±5.71 1.03** −1.40** 1.66** 0.63**

  Glutamic acid 29.48±4.26 50.18±7.86 22.83±2.51 57.59±0.09 0.77** −0.37** 0.97** 0.20

  Oxoproline 87.60.00±4.34 117.90±15.97 70.68±8.08 114.12±13.23 0.43** −0.31** 0.38** −0.05

  Proline 47.02±4.87 151.77±49.35 21.13±3.24 315.29±73.29 1.69** −1.15** 2.75** 1.05**

  L-allothreonine 40.74±5.24 191.33±17.07 20.83±4.38 178.89±30.97 2.23** −0.97** 2.13** −0.10

  Aspartic acid 222.71±26.59 313.21±26.63 184.21±29.05 306.99±30.53 0.49** −0.27* 0.46** −0.03

  Asparagine 384.81±84.83 338.87±55.04 94.59±2.99 661.37±56.15 −0.18 −2.02** 0.78** 0.96**

  Valine 56.97±11.77 142.40±7.49 34.90±4.69 179.74±26.18 1.32** −0.71** 1.66** 0.34**

  Serine 102.03±24.51 328.21±58.25 75.07±4.16 338.53±34.52 1.69** −0.44* 1.73** 0.04

  Glycine 30.73±5.37 48.28±4.82 16.98±1.57 44.41±4.53 0.65** −0.86** 0.53** −0.12

  Isoleucine 19.03±6.07 39.01±2.92 5.56±0.86 87.71±5.83 1.04** −1.77** 2.20** 1.17**

  L-cysteine 0.43±0.04 1.51±0.23 0.44±0.08 2.15±0.44 1.82** 0.05 2.34** 0.52**

  Lysine 4.27±0.80 16.33±2.80 3.48±0.81 31.52±8.81 1.93** −0.29 2.88** 0.95**

  Tyrosine 5.73±0.78 12.94±2.17 5.61±0.88 21.44±6.15 1.18** −0.03 1.90** 0.73**

Organic acids

  Oxalic acid 810.46±59.66 220.17±56.14 326.80±33.78 104.54±14.58 −1.88** −1.31** −2.95** −1.07**

  Citric acid 114.61±26.47 211.99±24.66 91.63±6.96 212.76±18.01 0.89** −0.32 0.89** 0.01

  Succinic acid 119.94±21.81 61.83±6.73 110.37±32.62 87.28±8.41 −0.96** −0.12 −0.46** 0.50**

  L-malic acid 164.40±18.22 223.11±20.24 166.43±8.65 160.78±41.04 0.44** 0.02 −0.03* −0.47**

  Aconitic acid 0.32±0.06 0.78±0.09 0.20±0.03 0.60±0.04 1.28** −0.67** 0.89** −0.38**

  Fumaric acid 5.04±0.79 3.79±0.59 3.53±0.40 3.02±0.61 −0.41* −0.51** −0.74** −0.33*

  Quinic acid 20.49±2.87 47.46±6.93 27.24±4.98 25.79±6.53 1.21** 0.41* 0.33 −0.88**

  Salicylic acid 13.80±2.47 18.43±2.35 10.29±1.46 13.48±3.15 0.42** −0.42* −0.03 −0.45*

  D-glyceric acid 15.42±3.71 27.68±6.12 11.14±2.23 18.44±3.51 0.84** −0.47* 0.26 −0.59**

  Shikimic acid 56.08±7.56 77.82±9.07 41.18±5.50 44.40±7.02 0.47** −0.45** −0.34* −0.81**

  Ferulic acid 0.75±0.10 1.28±0.18 0.62±0.12 1.22±0.25 0.77** −0.28 0.70** −0.07

  Glycolic acid 8.15±0.28 9.58±1.18 7.48±0.51 6.68±0.74 0.23* −0.12* −0.29** −0.52**

Fatty acids

  Linolenic acid 2.74±0.64 1.84±0.19 2.18±0.22 1.91±0.27 0.58** −0.33 −0.52* 0.05

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AC vs Cd, 1491 DEGs were up-regulated and 1254

DEGs were down-regulated; In AC vs EC, 1250

DEGs were up-regulated and 1064 DEGs were downregulated; In AC vs EC+Cd, 1849 DEGs were upregulated and 1335 DEGs were down-regulated; In

Cd vs EC+Cd, 753 DEGs were up-regulated and 389

DEGs were down-regulated. The unique diferential

genes of AC vs Cd, AC vs EC, AC vs EC+Cd and

Cd vs EC+Cd were 815, 691, 555 and 235 respectively (Table S3; Fig. S2).

As the low content of individual metabolites, the relative content value and standard deviation increased by 100 times, and retaining

two decimal places. Signifcant diferences between treatments were determined by the ANOVA test and marked as * p<0.05 and **

p<0.01

Table 2 (continued)

Metabolite’s names AC Cd EC EC+Cd Fold changes log2 /AC Fold

changes

log2 /

Cd

Cd EC EC+Cd EC+Cd

Others

  O-phosphorylethanolamine

1.59±0.35 3.32±0.49 1.62±0.51 3.03±0.55 1.06** 0.03 0.93** −0.13

  Putrescine 3.67±0.46 8.13±0.66 7.21±0.52 11.91±3.31 1.15** 0.97** 1.70** 0.55*

  5-Methoxytryptamine

1.43±0.34 15.63±2.61 0.46±0.08 18.68±3.05 3.45** -1.65** 3.70** 0.26

Fig. 4 Changes in metabolic pathways in leaves of diferent treatments. Signifcant diferences between diferent ratio of treatments

were determined by the 2-way ANOVA test and marked as P<0.05 and P<0.01

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The GO functional annotation analysis showed

that these co-expressed genes were mainly distributed in 3 terms: biological process, cellular component and molecular function. When AC vs Cd,

DEGs mainly enriched in photosynthesis, favonoid

biosynthesis, second metabolite, toxin catabolic,

glutathione metabolic processes and oxalate oxidase activity, etc.; When AC vs EC, DEGs mainly

enriched in photosynthesis, such as light harvesting

in photosystem I, chloroplast thylakoid membrane,

chloroplast stroma and chlorophy II binding, etc.;

When AC vs EC+Cd, DEGs mainly enriched in

photosynthesis, favonoid biosynthesis, nitrate

assimilation, etc.; when Cd vs EC+Cd, except

DEGs enriched in photosynthesis and favonoid biosynthetic process, they also enriched in glycosy I

compound metabolic process, and water, glycerol,

iron transmembrane and plasmodesmata-mediated

Fig. 5 Diferential metabolite pathway enrichment maps of MetaboAnalyst between treatments. (Pathways impact>0.1 were

screened out)

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intercellular transport, and glucosidase, glucosyltransferase, alcohol dehydrogenase and oxalate

decarboxylase activities, etc. (Fig. 6).

The most signifcant 30 DEGs (15 up-regulated,

15 down-regulated) were analyzed based on KEGG,

When AC vs Cd, up-regulated DEGs mainly annotated in phenylpropanoid biosynthesis, amino acid

(alanine, aspartate, glutamate) metabolism, glutathione metabolism, amino sugar and nucleotide

sugar metabolism and protein processing in endoplasmic reticulum, etc. Down-regulated DEGs

mainly annotated in phenylpropanoid biosynthesis,

cysteine and methionine metabolism, photosynthesis-antenna proteins, brassinosteroid biosynthesis,

plant hormone signal transduction, oxidative phosphorylation and carotenoid biosynthesis, etc.; When

AC vs EC, up-regulated DEGs mainly annotated in

photosynthesis, plant hormone signal transduction,

starch and sucrose metabolism, alanine, aspartate

and glutamate metabolism, glutathione metabolism, etc. Down-regulated DEGs mainly annotated

in carotenoid biosynthesis, photosynthesis-antenna

proteins, TCA cycle and plant hormone signal

transduction, etc.; When AC vs EC+Cd, up-regulated DEGs annotations were just like AC vs Cd, of

course, other annotations just like photosynthesis,

phosphatidylinositol signaling system, and glycolysis/gluconeogenesis are worthy of attention. Downregulated DEGs mainly annotated in carotenoid biosynthesis, photosynthesis-antenna proteins, nitrogen

metabolism and citrate cycle (TCA cycle), etc.;

When Cd vs EC+Cd, up-regulated DEGs mainly

annotated in phenylpropanoid biosynthesis, peroxisome, brassinosteroid biosynthesis, photosynthesis, and cysteine and methionine metabolism, etc.

Down-regulated DEGs mainly annotated in phenylpropanoid biosynthesis, photosynthesis-antenna

proteins, TCA cycle and cysteine and methionine

metabolism, etc.(Tables 4, 5, 6 and 7).

The main DEGs correlated to substances and

metabolic processes were showed in Table S4.

Discussion

Responses of antioxidant enzymes activities,

respiratory rate, metabolomics and transcriptomics to

Cd stress

SOD, POD and CAT are the core of antioxidant

enzyme system. In this study, SOD and POD activities increased, promoted the conversion of more reactive oxygen species to H2O2. The ASA-GSH cycle

is one of the key material cycles in plants, and the

key enzymes involved in it include APX, DHAR,

MDAR and GR. Glutathione (GSH) and ascorbic acid

(ASA) are major intracellular antioxidants with strong

reducibility and are substrates of various antioxidant

enzymes, especially GSH, which has been proved to

play an important role in plant tolerance to cadmium

toxicity by many studies (Howden et  al. 1995; Cobbett et  al. 1998; Uraguchi et  al. 2009). In oxidative

stress response, GR not only removes H2O2, but also

regenerates NADP to ensure normal electron transfer

Table 3 Mapping of RNA-Seq data of 12 samples of four treatments to reference genome

Samples Total Reads Mapped Reads Clean reads Clean bases GC Content %≥Q30

AC1 42020668 40235115 (95.75%) 21010334 6291229800 51.93% 94.64%

AC2 39326336 37697399 (95.86%) 19663168 5883700370 52.49% 94.60%

AC3 49787168 47619572 (95.65%) 24893584 7448299222 52.45% 94.36%

Cd1 41040066 39162761 (95.43%) 20520033 6141067438 51.63% 94.41%

Cd2 40893088 38780577 (94.83%) 20446544 6114591458 51.55% 94.49%

Cd3 47141952 44872686 (95.19%) 23570976 7039313378 51.59% 94.54%

EC1 44343092 42184117 (95.13%) 22171546 6631142724 50.54% 94.33%

EC2 47024130 44759126 (95.18%) 23512065 7023296558 51.19% 94.66%

EC3 39558262 37699158 (95.30%) 19779131 5910440722 50.93% 94.68%

EC+Cd1 43333694 41324421 (95.36%) 21666847 6475544680 51.37% 94.53%

EC+Cd2 42203892 40112315 (95.04%) 21101946 6314904616 50.99% 94.52%

EC+Cd3 44156776 42039013 (95.20%) 22078388 6592293700 51.86% 94.64%

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(Gamble and Burke 1984). GR has the function of making GSSG (reduced glutathione) to GSH and plays an

important role in scavenging ROS (Alscher et al. 1997).

Cysteine residues in GSH molecules have strong nucleophilic properties and can react directly with ROS to

remove them (May et al. 1998; Graham et al. 1998). In

Fig. 6 Histogram of DEGs

enrichment GO pathway.

BP: Biological Process, CC:

Cellular Component, MF:

Molecular Function

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this study, GR activity was signifcantly increased and

played an important antioxidant role under Cd stress in

rice. Studies have found the genes participate in ASAGSH cycle were activated, and glutathione, ascorbic

acid and plants chelating protein content increased, in

order to ease the growth inhibition induced by oxidative

stress and Cd and reduce cadmium toxicity in plants

(Liang et al. 2016; Lou et al. 2017). Our study showed

DEGs also enriched in glutathione metabolic process,

Os09g0367700 (up-regulated DEG) mainly annotated

in glutathione metabolism. The role of DHAR is to

reduce the oxidation product of ascorbate to ASA and

maintain the dynamic balance of ASA in cells (Chen

et al. 2003; Deutsch 2000). APX uses ASA as an electron donor to remove H2O2 and protect chloroplasts

(Foyer and Hailiwell 1976). But in this study, DHAR

and APX did not play a leading role in antioxidant

activity under Cd stress.

Zeng et  al. (2020) found, under Cd stress, levels

of most carbohydrates were down-regulated in the

metabolomics study of two diferent varieties of indica

and hybrid rice grains. But in this study, in rice leaves,

sugar and polyol metabolism was greatly enhanced.

The increase of soluble sugar contents is a typical

stress response in plants under heavy metal stress

which requires a large amount of energy provided

Table 4 KEGG pathway annotation information of AC vs Cd DEGs

log2FC positive value (+) represents DEGs up-regulated and negative value (-) represents DEGs down-regulated

Gene names log2FC KEGG pathway annotation

Os09g0483200 6.8235 Ribosome (ko03010)

Os02g0811800 (OsCCR10) 6.5545 Phenylpropanoid biosynthesis (ko00940)

Os02g0466400 (OsITPK4) 6.5088 Phosphatidylinositol signaling system (ko04070)

Os04g0614500 5.9878 Alanine, aspartate and glutamate metabolism (ko00250)

Os09g0367700 5.7029 Glutathione metabolism (ko00480)

Os05g0399300 5.6779 Amino sugar and nucleotide sugar metabolism (ko00520)

Os07g0638400 5.6308 Phenylpropanoid biosynthesis (ko00940)

Os03g0828300 5.4449 Fructose and mannose metabolism (ko00051)

Os07g0529000 5.3364 Carbon metabolism (ko01200)

Os04g0107900 (OsHSP1) 5.2436 Protein processing in endoplasmic reticulum (ko04141)

Os01g0136100 5.1679 Protein processing in endoplasmic reticulum (ko04141)

Os05g0373900 5.1023 mRNA surveillance pathway (ko03015)

Os01g0136200 (OsHSP17.0; OsSHSP2) 4.9078 Protein processing in endoplasmic reticulum (ko04141)

Os03g0277300 4.8173 Protein processing in endoplasmic reticulum (ko04141)

Os03g0712800 (OsGS1; 3) 4.5326 Alanine, aspartate and glutamate metabolism (ko00250)

Os05g0135500 −6.7583 Phenylpropanoid biosynthesis (ko00940)

Os01g0703000 −6.3364 mRNA surveillance pathway (ko03015)

Os10g0320100 −5.9872 Flavonoid biosynthesis (ko00941)

Os11g0285000 −5.7607 Sesquiterpenoid and triterpenoid biosynthesis (ko00909)

Os01g0192900 (OsACS5) −5.6227 Cysteine and methionine metabolism (ko00270)

Os10g0109300 −5.5699 Phenylpropanoid biosynthesis (ko00940)

Os11g0530600 −5.4913 Circadian rhythm—plant (ko04712)

Os04g0457100 −5.2240 Photosynthesis—antenna proteins (ko00196)

Os01g0388000 (CYP734A6) −4.9472 Brassinosteroid biosynthesis (ko00905)

Os02g0697400 (Os4CL2) −4.9340 Phenylpropanoid biosynthesis (ko00940)

Os12g0601400 (OsIAA3) −4.6904 Plant hormone signal transduction (ko04075)

Os05g0114000 −4.6874 Oxidative phosphorylation (ko00190)

Os10g0533500 −4.6352 Carotenoid biosynthesis (ko00906)

Os01g0805900 −4.5539 Phagosome (ko04145)

Os08g0489300 −4.4988 Base excision repair (ko03410)

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by carbohydrate compounds and osmotic adjustment

substances. Respiration of plant can release energy to

resist stress, and our study showed that rice leaf respiration rate was enhanced by Cd stress, glucose, glucose-6-P and glucose-1-P (related to glycolysis) contents increased, citric acid, L-malic acid, aconitic acid

(related to TCA cycle) contents also increased. Dehydrogenation process in such reaction is accompanied

by NADH formation, which is essential to preserve the

antioxidant capacity of cells (Petrat et al. 2003); Rafnose is an oligosaccharide with the function of storing energy and can be a protective agent under stress.

The synthesis of rafnose involves in the formation of

myo-inositol (Fig. 4), which is not only an important

osmotic protective substance, but also is involved in a

variety of metabolic regulation, such as the regulation

of plant cell stress resistance, the promotion of seed

dehydration and the regulation of plant auxin, and also

participates in the synthesis of cell wall (Loewus and

Murthy 1964; Madden et al. 1985; Conde et al. 2015).

In this study, myo-inositol and rafnose were all

increased under Cd as important metabolic regulators.

The related up-regulated DEG Os02g0466400 (1,3,

4-phosphoinositol 5/6-kinase gene) need further focus.

Table 5 KEGG pathway annotation information of AC vs EC DEGs

log2FC positive value (+) represents DEGs up-regulated and negative value (-) represents DEGs down-regulated

Gene names log2FC KEGG pathway annotation

Os02g0578400 8.7500 Photosynthesis (ko00195)

Os03g0679700 7.9409 Thiamine metabolism (ko00730)

Os07g0529600 (OsDR8; OsXNP) 5.1310 Thiamine metabolism (ko00730)

Os09g0482680 5.0662 RNA transport (ko03013)

Os05g0535800 4.8333 Ribosome (ko03010)

Os12g0586100 (OsSAPK9) 4.8022 Plant hormone signal transduction (ko04075)

Os08g0248800 4.79262 Pyrimidine metabolism (ko00240)

Os01g0814800 4.6900 Carbon metabolism (ko01200)

Os08g0473900 (OsAmy3D; RAmy3D) 4.1071 Starch and sucrose metabolism (ko00500)

Os05g0555600 (OsNADH-GOGAT2) 4.0333 Alanine, aspartate and glutamate metabolism (ko00250)

Os08g0175300 3.9768 Purine metabolism (ko00230)

Os01g0182600 (OsGI) 3.9220 Circadian rhythm—plant (ko04712)

Os11g0547000 (OsFKF1) 3.7968 Circadian rhythm—plant (ko04712)

Os07g0406800 3.7166 Purine metabolism (ko00230)

Os08g0522400 3.6590 Glutathione metabolism (ko00480)

Os10g0533500 −10.3987 Carotenoid biosynthesis (ko00906)

Os01g0600900 −8.2712 Photosynthesis—antenna proteins (ko00196)

Os09g0346500 (OsCAB1R) −8.1948 Photosynthesis—antenna proteins (ko00196)

Os04g0457100 −6.8262 Photosynthesis—antenna proteins (ko00196)

Os03g0592500 −6.4207 Photosynthesis—antenna proteins (ko00196)

Os07g0562700 −6.1958 Photosynthesis—antenna proteins (ko00196)

Os05g0171000 (OsPLDα2) −6.0909 Glycerophospholipid metabolism (ko00564)

Os08g0157600 (OsCCA1; OsLHY) −6.0504 Circadian rhythm—plant (ko04712)

Os07g0630800 −5.8256 Carbon metabolism (ko01200); Citrate cycle (TCA

cycle) (ko00020)

Os11g0242800 (LHCB5) −5.7385 Photosynthesis—antenna proteins (ko00196)

Os01g0720500 −5.6834 Photosynthesis—antenna proteins (ko00196)

Os02g0197600 −5.3953 Photosynthesis—antenna proteins (ko00196)

Os08g0435900 −5.3653 Photosynthesis—antenna proteins (ko00196)

Os02g0194700 (OsLOX1) −4.8997 alpha-Linolenic acid metabolism (ko00592)

Os12g0601400 (OsIAA3) −4.8045 Plant hormone signal transduction (ko04075)

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The enhanced amino acid metabolism and the

accumulated small molecule amino acids can contribute to improving osmotic adjustments and maintaining cell membrane stability (Widodo et al. 2009).

It can also be used as a mediator for heavy metals

and form metal complexes (Bottini and Festa 1996).

Heavy metal stress inhibits normal nitrogen metabolic

pathways in plants. Free amino acids, as an important

form of N assimilates in plants and the main transport

form can refect the supply capacity of N assimilates

(Zhao et  al. 2019). Our study showed that the large

increase of carbohydrate promoted pyruvate metabolism and thus promoted the formation of many amino

acids (Fig. 4). Up-regulated DEGs also annotated in

amino acid (alanine, aspartate, glutamate) metabolism. Os04g0614500 and Os03g0712800 annotated in

alanine, aspartic acid and glutamic acid metabolism

were signifcantly up-regulated. Alanine and valine

are glucogenic amino acids, they also might promote

glyconeogenesis as an efective transformation pathway to resist Cd stress. The stress response of alanine

is mainly refected in the regulation of intracellular

environment pH, and the increase of alanine content

may be caused by the reduction of protein synthesis

rate and the slow reaction of alanine transaminase

after heavy metal stress (Xu et al. 2012a, b). Oxoproline is related with proline and arginine metabolism,

the accumulation of proline can decrease intracellular

Table 6 KEGG pathway annotation information of AC vs EC+Cd DEGs

log2FC positive value (+) represents DEGs up-regulated and negative value (-) represents DEGs down-regulated

Gene names log2FC KEGG pathway annotation

Os02g0578400 7.8161 Photosynthesis (ko00195)

Os03g0679700 7.1425 Thiamine metabolism (ko00730)

Os07g0529600 (OsDR8; OsXNP) 6.3715 Thiamine metabolism (ko00730)

Os02g0466400 (OsITPK4) 6.3108 Phosphatidylinositol signaling

system (ko04070)

Os09g0483200 6.1760 Ribosome (ko03010)

Os04g0614500 6.0388 Alanine, aspartate and glutamate

metabolism (ko00250)

Os07g0638400 5.8296 Phenylpropanoid biosynthesis (ko00940)

Os11g0210600 5.6962 Glycolysis / Gluconeogenesis (ko00010)

Os07g0638300 5.6674 Phenylpropanoid biosynthesis (ko00940)

Os10g0530800 5.5998 Glutathione metabolism (ko00480)

Os07g0529000 5.4800 Carbon metabolism (ko01200)

Os02g0113200 5.4356 Steroid biosynthesis (ko00100)

Os05g0399300 5.3394 Amino sugar and nucleotide sugar metabolism (ko00520)

Os04g0493400 5.3364 Amino sugar and nucleotide sugar metabolism (ko00520)

Os03g0828300 5.2944 Fructose and mannose metabolism (ko00051)

Os10g0533500 −8.9800 Carotenoid biosynthesis (ko00906)

Os01g0600900 −8.8464 Photosynthesis—antenna proteins (ko00196)

Os09g0346500 (OsCAB1R) −7.0415 Photosynthesis—antenna proteins (ko00196)

Os05g0171000 (OsPLDα2) −6.4822 Glycerophospholipid metabolism (ko00564)

Os08g0157600 (OsCCA1; OsLHY) −6.4627 Circadian rhythm—plant (ko04712)

Os02g0770800 (OsNR2; qCR2) −6.1891 Nitrogen metabolism (ko00910)

Os03g0592500 −6.0977 Photosynthesis—antenna proteins (ko00196)

Os07g0562700 −6.0288 Photosynthesis—antenna proteins (ko00196)

Os08g0435900 −5.9305 Photosynthesis—antenna proteins (ko00196)

Os12g0189400 −5.8617 Photosynthesis (ko00195)

Os04g0457100 −5.8131 Photosynthesis—antenna proteins (ko00196)

Os10g0109300 −5.5237 Phenylpropanoid biosynthesis (ko00940)

Os07g0630800 −5.4543 Carbon metabolism (ko01200); Citrate cycle (TCA cycle) (ko00020)

Os10g0320100 −5.4408 Flavonoid biosynthesis (ko00941)

Os11g0242800 (LHCB5) −5.2621 Photosynthesis—antenna proteins (ko00196)

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osmotic potential, balance protoplast osmotic pressure, protect enzyme activity, and reduce soluble protein precipitation (Yang et al. 2017).

Some abiotic stresses can induce plants to secrete

and accumulate organic acids, which can promote the

activation and absorption of mineral elements in soil,

and thus have the function of regulating plant nutrition (Yang et al. 2017; Wang et al. 2018), also they are

vital osmotic adjustment solutes (Yang et  al. 2017).

Oxalic acid has also been identifed as a diferential metabolite in several metabolomic studies under

heavy metal stress (Zeng et  al. 2008; Lyubenova

et al. 2013), but only in root of plants. In our experiment, oxalic content of rice leaves decreased under

Cd stress. Related to secondary metabolism, salicylic

acid, ferulic acid, quinic acid and shikimic acid contents increased, DEGs also enriched in the second

metabolite. The increase of these important secondary metabolites’ contents related to strong stress

resistant capacity of plants.

In our study, linolenic acid content increased,

alpha-linolenic acid metabolism enhanced and

O-phosphorylethanolamine, putrescine, 5-Methoxytryptamine contents increased under Cd stress.

Table 7 KEGG pathway annotation information of Cd vs EC+Cd DEGs

log2FC positive value (+) represents DEGs up-regulated and negative value (-) represents DEGs down-regulated

Gene names log2FC KEGG pathway annotation

Os04g0354600 5.5910 Peroxisome (ko04146)

Os06g0604200 (OsPLDα4) 5.3605 Glycerophospholipid metabolism (ko00564)

Os05g0135500 4.6313 Phenylpropanoid biosynthesis (ko00940)

Os05g0521600 4.5598 Starch and sucrose metabolism (ko00500)

Os03g0227700 (OsDWARF4; CYP90B2) 4.4900 Brassinosteroid biosynthesis (ko00905)

Os02g0578400 4.3595 Photosynthesis (ko00195)

Os11g0210600 4.2353 Fatty acid degradation (ko00071)

Os09g0400200 4.0084 Phenylpropanoid biosynthesis (ko00940)

Os03g0708000 3.8167 alpha-Linolenic acid metabolism (ko00592)

Os01g0192900 (OsACS5) 3.7646 Cysteine and methionine metabolism (ko00270)

Os06g0179000 3.5371 Glycosaminoglycan degradation (ko00531)

Os03g0679700 3.4990 Thiamine metabolism (ko00730)

Os09g0491100 3.4719 Phenylpropanoid biosynthesis (ko00940)

Os04g0137100 3.4227 Pentose and glucuronate interconversions (ko00040)

Os08g0248800 3.3218 Alanine, aspartate and glutamate metabolism (ko00250)

Os11g0707100 −6.6489 /

Os05g0171000 (OsPLDα2) −5.7501 Glycerophospholipid metabolism (ko00564)

Os03g0843800 −5.4442 /

Os08g0157600 (OsCCA1; OsLHY) −4.9177 Circadian rhythm—plant (ko04712)

Os09g0346500 (OsCAB1R) −4.5720 Photosynthesis—antenna proteins (ko00196)

Os04g0513700 −4.5492 /

Os07g0630800 −4.3508 Citrate cycle (TCA cycle) (ko00020); Carbon metabolism (ko01200)

Os03g0375300 −4.3452 /

Os06g0253100 −4.2108 Protein processing in endoplasmic reticulum (ko04141)

Os12g0189300 −3.6663 /

Os02g0758000 (OsHSP24.1) −3.3598 Protein processing in endoplasmic reticulum (ko04141)

Os05g0171050 −3.3373 Glycerophospholipid metabolism (ko00564)

Os01g0820000 −3.1124 Phenylpropanoid biosynthesis (ko00940)

Os12g0189400 −3.1073 Photosynthesis (ko00195)

Os09g0424300 −3.1002 Cysteine and methionine metabolism (ko00270)

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Ethanolamine is important for synthesis of choline,

phosphatidylethanolamine (PE) and phosphatidylcholine (PC) in plants. They are important in plants

growth and developmental processes as the major

phospholipids in eukaryotic membranes (Kwon et al.

2012). The increase of O-phosphorylethanolamine

under Cd maybe related to its protective efect on cell

membranes under adverse conditions. Polyamines are

a kind of low molecular weight secondary metabolites in nitrogen metabolism. Putrescine is the central

product of polyamine biosynthesis pathway. Studies have shown that polyamines are closely related

to stress tolerance in plants (Walters 2003). Under

stress, the polyamine content and polyamine synthase

activity of plants increased signifcantly in a certain

range (Cvikrová et al. 2012; Xu et al. 2012a, b). The

accumulation of putrescine is a sign of plant tolerance

to stress or alleviating the damage of stress to plants,

but whether it has special physiological signifcance

remains to be further studied.

When AC vs Cd, DEGs also enriched in photosynthesis, favonoid biosynthesis, toxin catabolic and

oxalate oxidase activity, etc.; Up-regulated DEGs

mainly annotated in phenylpropanoid biosynthesis

and protein processing in endoplasmic reticulum etc.

Down-regulated DEGs mainly annotated in photosynthesis-antenna proteins, brassinosteroid biosynthesis, plant hormone signal transduction, oxidative

phosphorylation and carotenoid biosynthesis, etc.

Os04g0457100 and Os10g0533500 were signifcantly

down-regulated in photosynthesis-antenna protein

and carotenoid biosynthesis. That indicates that the

photosynthetic process of rice has been adversely

afected, which has been verifed by our previous

study (Li et al. 2021).

Responses of antioxidant enzymes activities,

respiratory rate, metabolomics and transcriptomics to

elevated CO2 concentration

In this study, under EC, compared with AC, CAT,

APX and DHAR activities increased, SOD, POD,

MDAR and GR activities decreased signifcantly.

High concentration of CO2 promotes the synthesis

of photosynthates in plants, and sufcient photosynthates are conducive to the synthesis and metabolism of ascorbic acid (ASA). ASA is the substrate

of APX, so high ASA synthesis capacity is consistent with high APX activity. Study showed DHAR

activity of S-type soybean increased under high CO2

concentration (Asada and Takahashi 1987), we got

the same result. Plants growing under high concentrations of CO2 can regulate the photosynthetic electron conduction system and synthesize more NADPH

(Lichtenthaler 1987), and the synthesized NADPH

can be used for the ascorbate–glutathione cycle

(Rao et  al. 1995), which keeps ascorbic acid and

glutathione in a high reduction state in plants, thus

reducing the activities of antioxidant enzymes, such

as SOD (Foyer et al. 1994a, b). Studies have shown

that the activities of GR, SOD and POD in soybean

decreased under high CO2 concentration (Pritchard

et  al. 2000), which is consistent with the results of

this study. However, the decrease of antioxidant

enzyme activities under high CO2 may be caused by

the increase of partial pressure of CO2 in chloroplast

and the decrease of partial pressure of O2, and the

decrease of oxygen as electron acceptor to form ROS,

and the decrease of ROS and antioxidant enzymes

leading to the decrease of antioxidant enzyme activities (Pritchard et al. 2000).

Our study has shown that high CO2 reduced stomatal opening of leaves (Wang et  al. 2019), then

O2 intake dropped, so the respiration rate further

decreased. The decrease of aconitic acid and fumaric acid contents (the downstream products of TCA

cycle) and down-regulated DEG (Os07g0630800,

annotated in TCA cycle) also verify this result. Many

sugars and amino acids contents decreased, related to

galactose metabolism, glycine, serine and threonine

metabolism, alanine, aspartate and glutamate metabolism. Glutamic acid is the precursor of chlorophyll

(Woodward et al. 1990; Ito et al. 1994). The change

of the glutamic acid content in plants under high CO2

may be related to photosynthesis (Gong et al. 2013).

It was possible to synthesize more photosynthetic

pigments by consuming glutamic acid to increase the

photosynthetic intensity.

The increase of CO2 concentration can regulate the

production of secondary metabolites in plants (Idso

and Idso 2001). In our study, shikimic acid and salicylic acid contents decreased under EC, but quinic

acid content increased. The decrease of D-glyceric

acid and glycolic acid contents may be related to

the decrease of photorespiration under EC, the contents of amino acids (glycine and serine) and oxalic

acid associated with this process were also decreased

(Fig. 4). Putrescine content also increased under EC.

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When AC vs EC, DEGs mainly enriched in photosynthesis, such as light harvesting in photosystem

I, chloroplast thylakoid, chloroplast stroma and chlorophyl II binding, etc.; 1250 genes in AC vs EC were

up-regulated, mainly annotated in photosynthesis, plant

hormone signal transduction, starch and sucrose metabolism, alanine, aspartate and glutamate metabolism,

glutathione metabolism etc. Os02g0578400 annotation

is most signifcant in photosynthesis, Os08g0473900 is

annotated in starch metabolism and sucrose metabolism.

Those results showed that EC promoted photosynthesis, growth and energy metabolism of rice to a certain

extent, which can be verifed by our early studies (Li

et al. 2021; Wang et al. 2021); 1064 DEGs were downregulated, mainly annotated in carotenoid biosynthesis,

photosynthesis-antenna proteins, and plant hormone signal transduction, etc. In the photosynthesis-antenna proteins, Os01g0600900, Os09g0346500, Os04g0457100,

Os03g0592500, Os07g0562700, Os11g0242800,

Os01g0720500, Os02g0197600 and Os080g435900

were all down-regulated indicating that high CO2 would

inhibit the role of photosynthesis-antenna protein. It perhaps inhibited and regulated the light reaction process

of rice to cope with the phenomenon of \"photosynthetic

adaptation\" under high CO2.

Responses of antioxidant enzymes activities,

respiratory rate, metabolomics and transcriptomics to

Cd stress and elevated CO2 concentration

Under EC+Cd, compared with AC, POD, DHAR and

GR activities increased signifcantly. The results indicated that the antioxidant enzymes activities of leaves

were relatively higher, the peroxidation damage in rice

leaves under composite treatment still existed; Compared with Cd stress, EC could enhance the oxidation

resistance of rice by the higher DHAR and GR activities, regulating the ASA-GSH cycle, so as to alleviate

membrane lipid peroxidation to a certain extent.

Under EC+Cd, compared with AC, the overall

metabolic trend was similar to that under Cd treatment.

That means when rice seedlings were treated under

EC and Cd stress together, Cd stress play a dominant

role. Decrease of glucose-6-P, succinic acid, L-malic

acid and glycolic acid contents was related to glycolysis, TCA cycle and photorespiration pathway changes

under high CO2; When compared with Cd treatment,

EC promoted the increase of many amino acids for

osmotic regulation under Cd stress. In addition, DEGs

(Os01g0192900 and Os08g0248800) regulating amino

acid metabolism were up-regulated. The decrease of

glucose-1-P, L-malic acid, aconitic acid and fumaric

acid contents were related to glyoxylate and dicarboxylate metabolism and TCA cycle under EC. The downregulated DEGs also annotated in TCA cycle. Under

EC+Cd, secondary metabolites (quinic acid, salicylic

acid and shikimic acid) did not play an important role

in anti-stress. But, content of putrescine also increased.

When EC+Cd vs AC, 1849 genes were upregulated and annotations were just like Cd vs AC,

of course, other annotations just like photosynthesis, phosphatidylinositol signaling system, and glycolysis/gluconeogenesis are worthy of attention.

Os02g0466400 was up-regulated in the phosphatidylinositol signal system, and inositol plays an important role in coping with environmental stress, mainly

by participating in osmotic stress regulation, conveying information as a signal molecule, and enhancing

antioxidant enzyme activity. This is consistent with

the above results of increased myo-inositol content.

1335 genes were down-regulated, mainly annotated in

carotenoid biosynthesis, photosynthesis-antenna proteins, nitrogen metabolism and TCA cycle, etc. These

results showed that the efects of Cd stress on photosynthesis and energy metabolism of rice leaves were

greater than that of high CO2 treatment.

When EC+Cd vs Cd, DEGs enriched in glycosy I

compound metabolic process, and water, glycerol, iron

transmembrane and plasmodesmata-mediated intercellular transport, and glucosidase, glucosyltransferase,

alcohol dehydrogenase and oxalate decarboxylase

activities. That indicated, under Cd stress, EC could

regulate the metabolic function of rice by regulating

the transmembrane movement of substances and the

activities of some enzymes. This may be related to CO2

alleviating the loss of cellular moisture caused by Cd

stress, the underlying mechanism needs to be further

studied. 753 genes were up-regulated, Os05g0135500,

Os09g0400200 and Os09g0491100 are up-regulated in

phenylpropanoid biosynthesis. This metabolic pathway

involved in plant stress resistance. The frst compound

of phenylpropanoid pathway is L-phenylalanine which

biosynthesis from phenylpropanoid shikimate pathway

(Hu et al. 2017). This was consistent with the variation

of phenylalanine content in the above metabolic analysis; 389 DEGs were down-regulated mainly annotated

in photosynthesis-antenna proteins and TCA cycle, etc.

Studies have shown that increased CO2 concentration

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can alleviate the negative efects of drought stress by

improving photosynthesis, but this mitigation efect

decreases or even disappears with the increase of

drought severity (Gray et  al. 2016). In this study, the

concentration and treatment time of Cd were relatively

higher and longer, so the photosynthetic relief efect of

high CO2 on Cd stress was weak, mainly manifested

in the down-regulated gene (Os09g0346500) related to

photosynthesis-antenna proteins.

Conclusions

High concentration of CO2 and Cd pollution afect

plant growth and metabolism, our results showed that

the responding mechanism of rice leaves to the above

complex environmental changes was as follows:

(1) Under Cd stress, compared with AC, DEGs

enriched in glutathione metabolic process, and

GR played an important antioxidant role; sugar

and polyol metabolism was greatly enhanced to

provide energy and the osmotic adjustment substances. Rice leaf respiration rate was enhanced

which also can release energy to resist stress.

Myo-inositol and rafnose increased under Cd

as the important metabolic regulators; The large

increase of carbohydrate promoted pyruvate

metabolism and thus promoted the formation of

many amino acids to improve osmotic adjustment, maintain cell membrane stability and

supply N assimilates. Organic acids contents

increased for regulating plant nutrition, glycolysis and TCA cycle. They can also strong antioxidant capacity of plants as the secondary metabolites. Increase of putrescine content need further

research. Down-regulated DEGs in photosynthesis-antenna protein showed photosynthetic process of rice had been adversely afected.

(2) Under EC, compared with AC, sufcient photosynthates are consistent with high APX and DHAR

activities. However, the decrease of some antioxidant enzymes activities may be caused by the

decrease of partial pressure of O2; High CO2 could

reduce stomatal opening of leaves, and the dropped

O2 intake can also decreased respiration rate of

rice leaves. The decrease of aconitic acid and

fumaric acid contents and down-regulated DEG

(Os07g0630800) in our study verifed this result.

Glutamic acid maybe consumed to synthesize more

photosynthetic pigments. Down-regulated DEGs

annotated in photosynthesis-antenna protein maybe

inhibited and regulated the light reaction process of

rice to cope with the phenomenon of \"photosynthetic adaptation\" under high CO2.

(3) Under composite treatments, compared with AC,

peroxidation damage still existed, the overall metabolic trend was similar to that under Cd treatment;

Compared with Cd stress, EC could enhance the

oxidation resistance of rice by the higher DHAR

and GR activities through regulating the ASA-GSH

cycle. EC promoted the increase of many amino

acids for osmotic regulation under Cd stress, DEGs

(Os01g0192900, Os08g0248800) regulating amino

acid metabolism were up-regulated. Afected by

EC, respiration rate decreased, lucose-1-P, L-malic

acid, aconitic acid and fumaric acid contents

(related to glyoxylate and dicarboxylate metabolism and TCA cycle) decreased, down-regulated

DEGs were also annotated in TCA cycle. Contents

of putrescine and myo-inositol increased. EC could

alleviate the loss of cellular moisture by regulating

the transmembrane movement of substances and

the activities of some enzymes.

Authors’ contributions All authors contributed to the study

conception and design. Material preparation, data collection

and analysis were performed by Lanlan Wang, Xuemei Li,

Meng Li and Jiayu Wang. The frst draft of the manuscript was

written by Lanlan Wang and all authors commented on previous versions of the manuscript. All authors read and approved

the fnal manuscript.

Funding This work was supported by National Natural Science Foundation of China (31600314) the Department of Education of Liaoning Province, China (LJKZ0991).

Data availability All data generated or analyzed during this

study are included in this published article and its supplementary information fles. The raw RNA-Seq data in this manuscript are available for downloading from the NCBI Sequence

Read Archive (BioProject ID: PRJNA905486).

Code availability Not applicable.

Declarations

Ethics approval Not applicable.

278 Plant Soil (2023) 485:259–280

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Consent to participate Not applicable.

Consent for publication Not applicable.

Conficts of interest/competing interests The authors have

no relevant fnancial or non-fnancial interests to disclose.

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