Plant Physiology and Biochemistry 166 (2021) 66–77 Contents lists available at ScienceDirect Plant Physiology and Biochemistry journal homepage: www.elsevier.com/locate/plaphy Research article Multiomics analysis provides insights into alkali stress tolerance of sunflower (Helianthus annuus L.) Huiying Lu, Ziqi Wang, Chenyang Xu, Luhao Li, Chunwu Yang * Key Laboratory of Molecular Epigenetics of Ministry of Education, Northeast Normal University, Changchun, 130024, China A R T I C L E I N F O A B S T R A C T Keywords: Sunflower Alkali stress Transcriptomics Metabolomics Lipidomics Phytohormone Alkali stress is an extreme complex stress type, which exerts negative effects on plants via chemical destruction, osmotic stress, ion injury, nutrient deficiency, and oxygen deficiency. Soil alkalization has produced severe problems in some area, while plant alkali tolerance is poorly understood. Sunflower (Helianthus annuus L.) is an important oilseed crop with strong alkali tolerance. Here we exposed sunflower plants to alkali stress (NaHCO3/ Na2CO3 = 9:1; pH 8.7) for whole life cycle. We applied transcriptomics, metabolomics, lipidomics and phyto­ hormone analysis to elucidate the alkali tolerance mechanism of sunflower plant. Lipidomic analysis showed that alkali stress enhanced accumulation of saccharolipids and glycerolipids and lowered the accumulation of glyc­ erophospholipids in sunflower seeds, indicating that alkali stress can change the lipid components of sunflower seeds, and that cultivating sunflower plants on alkalized farmlands will change the quality of sunflower seed oils. In addition, alkali stress downregulated expression of two rate-controlling genes of glycolysis in the leaves of sunflower but upregulated their expression in the roots. Enhanced glycolysis process provided more carbon sources and energy for alkali stress response of sunflower roots. Under alkali stress, accumulation of many fatty acids, amino acids, carbohydrates, and organic acids was greatly stimulated in sunflower roots. Alkali stress enhanced ACC, GA1, and ABA concentrations in the leaves but not in the roots, however, alkali stress elevated accumulation of BR (typhasterol) and CTK (Isopentenyladenosine) in the roots. We propose that multiple phy­ tohormones and bioactive molecules interact to mediate alkali tolerance of sunflower. 1. Introduction Soil salinization is an important factor limiting agricultural and grassland production in the world. NaCl, Na2SO4, NaHCO3 and Na2CO3 are major harmful salts for saline soils. The stress exerted by alkaline salts (NaHCO3 and Na2CO3) is defined as alkali stress, and the stress caused by both neutral salts and alkaline salts is defined as mixed salinealkali stress (Shi and Wang, 2005; Shi and Sheng, 2005). Globally, 54% of saline soils are sodic soil that consists of NaHCO3 and/or Na2CO3 (Shi and Sheng, 2005). Alkali stress has produced severe problems in some area. For example, in Northeastern China, more than 50% of grasslands are alkalinized (Kawanabe and Zhu, 1991; Zheng and Li, 1999; Shi and Sheng, 2005). In the past forty years, physiological and molecular mechanisms underlying plant salinity tolerance have been largely investigated (Flowers et al., 2019; Munns and Tester, 2008; Zhang et al., 2018; Zhao et al., 2020), however, relatively few attentions have been given to plant alkali tolerance. Recently, some researches have focused on alkali stress (Guo et al., 2016; Yu et al., 2013; Zhang et al., 2016; Zhao * Corresponding author. E-mail address: yangcw809@nenu.edu.cn (C. Yang). https://doi.org/10.1016/j.plaphy.2021.05.032 Received 17 February 2021; Accepted 19 May 2021 Available online 29 May 2021 0981-9428/© 2021 Elsevier Masson SAS. All rights reserved. et al., 2019; Han et al., 2019; Wang et al., 2012; Yang et al., 2019; Gao et al., 2020; Xiao et al., 2020a, 2020b). For example, H+-ATPase was demonstrated to play important role in alkali tolerance in two alkali-sensitive plants, Arabidopsis (Yang et al., 2019) and Maize (Gao et al., 2020). It is recognized that alkali-tolerant crops or halophytes and alkali-sensitive plants employ distinct mechanisms to against alkali stress. To date, the mechanism underlying alkali tolerance of alkali-tolerant crops remains poorly understood. Sunflower (Helianthus annuus L.) is one of the oilseed crops cultivated across the world (Wang et al., 2015; Liu et al., 2010; Mushke et al., 2019). About 25% of vegetable oil consumption in the world is provided by sunflower oil (Mushke et al., 2019). Sunflower oil has a higher con­ tent of linoleic acid (poliinsaturated) and lower saturated fatty acid content than the olive, corn, and soybean oils (López-Beceiro et al., 2011; Mushke et al., 2019). Sunflower oil is one of the healthiest food oils. In addition, sunflower plants can be used to produce polymers, lubricants, and biofuel (Mushke et al., 2019). Compared with other oilseed crops including brassica napus, olive, soybean, prominent H. Lu et al. Plant Physiology and Biochemistry 166 (2021) 66–77 quality of sunflower is its strong tolerance to salinity stress, alkali stress, drought stress and heavy metal stress (Wang et al., 2015; Liu et al., 2010). As sunflower has strong alkali tolerance, it has been widely cultivated in alkalized land in Northeastern China to recover and utilize these alkalized lands (Wang et al., 2015; Liu et al., 2010). Although physiological response of sunflower plants to alkali stress has been re­ ported (Wang et al., 2015; Liu et al., 2010), biochemical and molecular mechanisms underlying sunflower alkali tolerance remain unclear. High quality sunflower reference genome is publicly available now, which will benefit to uncover molecular mechanism underlying sunflower al­ kali tolerance. Developing of metabolomics, lipidomics and phytohor­ mone analysis techniques driven by innovation of mass spectrum instruments provides an opportunity to improve understanding of sun­ flower alkali tolerance. Salt stress affects plants through osmotic stress and ion injury. Compared with salt stress, alkali stress exerts additional effects of highpH on plants. High-pH caused by alkali stress can directly destroy the structure and function of biomacromolecule, membrane, and organelles, and it also can precipitate many nutrient ions including Ca2+, Mg2+, Fe2+, Mn2+, Cu2+, and Zn2+ at rhizosphere (Wang et al., 2012). Alkali stress is an extreme complex stress type, which exerts negative effects on plants via chemical destruction, osmotic stress, ion injury, nutrient deficiency, and oxygen deficiency caused by soil hardening (Shi and Wang, 2005; Shi and Sheng, 2005; Wang et al., 2012). Plant alkali tolerance is a complicated network coordinating all organs and most metabolism processes (Xiao et al., 2020a, 2020b; Han et al., 2019). Multiomics analysis will be a powerful tool to dissect the plant alkali tolerance network. In the present work, we exposed sunflower seeds to alkali stress for whole life cycle. We applied transcriptomics, metab­ olomics, lipidomics and phytohormone analysis to elucidate the alkali tolerance mechanism of sunflower. HITACHI). After exposure to alkali stress for 25 days, photosynthesis and chlorophyll fluorescence parameters of fully expanded mature leaves were measured using a portable open flow gas exchange system LI-6800 (LICOR, USA). Concentrations of carotenoids (Car) and chlorophyll (Chl) were measured using the methods of Zhu (1993). 2.3. Measurements of ions and phytohormones Mature leaves or roots of three individuals were pooled as a bio­ logical replicate, with three biological replicates for each organ and treatment. We measured the phytohormones with the workflow of Shao et al., (2019). Shortly, fresh plant samples were ground to a powder in liquid nitrogen, and then phytohormones were extracted with 1 mL acetonitrile:formic acid:H2O = 50:1:49 solution which had been spiked with internal stable isotope standards (OlChemIm, Czech Republic). The stable isotope standards included [2H5]trans-Zeatin (D-tZ)(ID 0300301, 2 mg L− 1), [2H5]trans-Zeatin Riboside (D-tZR)(ID 0300312, 2 mg L− 1), [2H6]N6-Isopentenyladenosine (D-iPR)(ID 0300171, 2 mg L− 1), [2H6] N6-Isopentenyladenine (D-iP) (ID 0300161, 2 mg L− 1), [2H3]Brassino­ lide (D-BL)(ID 0385893, 2 mg L− 1), [2H6](+)-cis,trans-Abscisic Acid (D-ABA) (ID 0342721, 2 mg L− 1), [2H4] 1-Aminocyclopropanecarboxylic Acid (D-ACC)(ID 0356001, 2 mg L− 1), [15N4]cis-Zeatin (15N-cZ) (ID 030 0321, 2 mg L− 1), [2H3]Dihy­ drozeatin (D-DHZ)(ID 0300601, 1 mg L− 1), [2H2]Gibberellin A1 (D-GA1)(ID 0322491, 5 mg L− 1), [2H2] Gibberellin A4(D-GA4)(ID 0322531, 5 mg L− 1), [2H2] Gibberellin A7(D-GA7)(ID 0322541, 5 mg L− 1), [2H2]N-[(− )-Jasmonoyl]-Isoleucine (D-(− )-JAILE)(ID 036 6863, 2 mg L− 1), [2H3]Castasterone (D-CS)(ID 0386653, 2 mg L− 1), [2H3]Typhasterol (D-TY)(ID 0387163, 5 mg L− 1), and [2H5] Indole-3-Acetic Acid (D-IAA)(ID 0311531, 2 mg L− 1). Phytohormones were measured using a UHPLC-ESI-MS/MS system (QTRAP 5500 sys­ tem, AB Sciex, Concord, Canada) with positive/negative ionization and multiple reaction monitoring (MRM) modes. The QTRAP 5500 system was equipped with Waters I-Class LC UHPLC with a C18 column (ACQUITY UPLC BEH C18 1.7 μm, 2.1 mm×100 mm, Waters). The UHPLC parameters were column temperature 45 ◦ C, flow rate 400 μL min− 1, and injection volume 2 μL. Mobile phase A was 0.05% formic acid in water, and mobile phase B was 0.05% formic acid in acetonitrile. ESI source parameter of mass spectrum was source temperature 500 ◦ C, ion source gas1(Gas1) 45, ion source gas2 (Gas2) 45, curtain gas (CUR) 30, and ionSapary voltage floating(ISVF) 4500 V. The freeze-dried leaves or roots were digested using 65% HNO3 at 120 ◦ C, and then the Na+ and K+ contents were measured by an atomic absorption spectro­ photometer (TAS-990super, PERSEE, China). 2. Material and methods 2.1. Plant material and growth condition Sunflower (Helianthus annuus L. var. XC909F1) seeds were sown in plastic pots containing thoroughly washed sand. After sowing seeds, control treatment pots (one seed per pot) were immediately watered with half-strength Hoagland nutrient solution, and stress treatment pots (one seed per pot) were immediately treated with alkali stress solution containing nutrient component of half-strength Hoagland nutrient so­ lution. Two alkaline salts NaHCO3 and Na2CO3 were mixed in a 9:1 M ratio as alkali stress treatment solution, with 40 mM total salinity and pH 8.7. The treatment duration was 25 days and 100 days. All experimental pots were placed in an experimental garden in Northeast Normal Uni­ versity with protection from the rain. The growth conditions were day/ night temperature range of 22–27 ◦ C/18–22 ◦ C and a 15–16 h day photoperiod. The experimental design was randomized complete block design. After exposure to alkali stress for 25 days, the mature leaves at same leaf position and roots were collected for chloroplast ultrastructure analysis, biochemical measurements, transcriptome analysis, and metabolome experiment. After exposure to alkali stress for 100 days, mature sees were collected and stored at − 80 ◦ C for lipidomic analysis and ion measurement. Leaves, roots or mature seeds of 3–5 individuals were pooled as a biological replicate, with three biological replicates for each treatment. 2.4. Metabolomics analysis Mature leaves or roots of five individuals were pooled as a biological replicate, with three biological replicates for each organ and treatment. Fresh plant samples were ground in liquid nitrogen and resuspended in 1 mL methanol/acetonitrile/H2O solution (2:2:1, v/v) following soni­ cation of 30 min, and then were kept at 4 ◦ C for 1 h to remove the protein. The mixture was centrifuged for 15 min (14000 g, 4 ◦ C). The supernatant was dried in a vacuum centrifuge. For UHPLC-MS/MS analysis, the samples were re-dissolved in 100 μL acetonitrile/water (1:1, v/v) solution. All samples were pooled as quality control samples which were analyzed regularly every 4 samples. Metabolomics analysis was conducted using a UHPLC-MS/MS system (AB Sciex TripleTOF 6600) equipped with a UHPLC (1290 Infinity LC, Agilent Technologies) and a 1.7 μm ACQUIY UPLC BEH column (2.1 mm × 100 mm, waters, Ireland) at Shanghai Applied Protein Technology company (Shanghai, China) according to workflow of Zhang et al., (2019). Shortly, a mix of 25 mM ammonium acetate and 25 mM ammonium hydroxide was used as A mobile phase of UHPLC, and pure acetonitrile as B mobile phase. Both ESI positive and negative modes were used. The mass spectrum parameters were set following: Gas1 60, Gas2 60, curtain gas as 30, 2.2. Chloroplast ultrastructure and photosynthetic measurements After exposure to alkali stress for 25 days, chloroplast ultrastructure of mature leaves was observed using method of (Xiao et al., 2020a, 2020b). Shortly, the leaf samples were fixed in 2.5% glutaraldehyde, and then were transferred into 1% OsO4 for 5 h at room temperature. Finally, 70 nm ultrathin sections were dyed with uranyl acetate and observed under a transmission electron microscope (HT7700, 67 H. Lu et al. Plant Physiology and Biochemistry 166 (2021) 66–77 Fig. 1. Effects of alkali stress on growth and photosynthesis of sunflower plants. (a) Growth status of sunflower seedling after expose to alkali stress for 25 days; (b) Mature seeds of sunflower after expose to alkali stress for 100 days; (c) chloroplast ultrastructure at 25 days of expose to alkali stress; (d) photosynthetic parameters and pigment concentrations at 25 days of expose to alkali stress. Star indicates significant difference between control and alkali stress conditions (P < 0.05), according to t-test. The sunflower plants were treated with 40 mM alkali stress condition (NaHCO3/ Na2CO3 = 9:1; pH 8.7) for whole life cycle. Each treatment has three biological repli­ cates. Fv/Fm, maximum quantum efficiency of photosystem II (PSII); Fv’/Fm’, effective quantum efficiency of PSII; PhiPS2, real quantum efficiency of PSII (fraction of absorbed PSII photons that are used in photochemistry); qP, photochemical quenching; qN, non-photochemical quench­ ing; ETR, electron transport rate; Chl, chlo­ rophyll; Car, carotenoid. source temperature 600 ◦ C, and IonSpray Voltage Floating ±5500 V. Identification of metabolites was carried out according to m/z value and MS/MS spectra fragment information against a lab database established by Shanghai Applied Protein Technology company, Shanghai, China. The variable importance in the projection (VIP) value of each variable in the orthogonal partial least-squares discriminant analysis (OPLS-DA) model was calculated to indicate its contribution to the classification. Differentially accumulating metabolites (DAPs) were defined as VIP value > 1 and P value < 0.05 (t-test). 2.5. Lipidomic analysis Mature seeds of three individuals were pooled as a biological repli­ cate, with three biological replicates for each treatment. Lipids of 68 H. Lu et al. Plant Physiology and Biochemistry 166 (2021) 66–77 Fig. 2. Effects of alkali stress on phytohormones in sunflower plants. The sunflower seeds were treated with 40 mM alkali stress condition (NaHCO3/Na2CO3 = 9:1; pH 8.7) for 25 days. Each treatment and tissue have three biological replicates. Star indicates significant difference between control and alkali stress conditions (P < 0.05), according to t-test. Abscisic acid, ABA; Indole-3-acetic acid, IAA; castasterone, CS; typhasterol, TY; cis-zeatin, cZ; cis-zeatin riboside, czR; Isopentenyladenine, iP; Isopentenyladenosine, iPR; trans-zeatin, tZ; trans-zeatin riboside, tzR; 1-Aminocyclopropanecarboxylic acid, ACC; Gibberellin, GA; cis-12-oxo-phytodienoic acid, cis-OPDA; Jasmonic acid, JA; Jasmonoyl-isoleucine, JA-Ile. sunflower seeds were extracted using MTBE method. The seeds were ground in liquid nitrogen. The powders were homogenized in 200 μL water at 4 ◦ C, flowing addition of 240 μL methanol and 800 μL MTBE. The mixed solutions were ultrasound at 4 ◦ C for 20 min, and then su­ pernatant after centrifugation was dried under nitrogen. The dried samples were re-dissolved in 0.2 mL of 90% isopropanol in acetonitrile, and 3 μL of the solution finally was loaded into a high resolution LC-MS/ MS system (Q Exactive™ Plus, Thermo Fisher Scientific, USA) equipped with a SH C18 column (1.7 μm, 2.1 mm× 100 mm, Waters). The mix of six extracts in equal volume was used as quality control sample, with three quality control samples. Mobile phase A was a mixture of aceto­ nitrile: water = 6:4 and 10 mM ammonium formate, and mobile phase B was a mixture of acetonitrile:isopropanol = 1:9 and 10 mM ammonium formate. Mass spectrum parameters of positive ion mode were temper­ ature 300 ◦ C, Sheath-Gas 45 arb, Aux-Gas 15 arb, Sweep-Gas 1arb, spray-voltage 3.0 KV, capillary temperature 350 ◦ C, S-Lens RF Level 50%, and MS1 scan m/z 200–1800. Mass spectrum parameters of negative ion mode parameters were temperature 300 ◦ C, Sheath-Gas 45 arb, Aux-Gas 15 arb, Sweep-Gas 1arb, spray-voltage 2.5 KV, capillarytemperature 350 ◦ C, SLens RF Level 60%, and MS1 scan m/z 250–1800. The lipids were identified using Lipid Search software (Thermo Fisher Scientific, USA). Differentially accumulated lipids (DALs) were defined as VIP >1 and P-value<0.05 (t-test). 2.6. RNA sequencing and qRT-PCR Roots or mature leaves at the same leaf position for each treatment were chosen for RNA sequencing. Three plants were pooled as a bio­ logical replicate, with three biological replicates. We used traditional method to conduct RNA sequencing and subsequent analysis (Bhanbhro et al., 2020). Sunflower reference genome (assembly HanXRQr2.0-SUNRISE) was downloaded from NCBI (Badouin et al., 2017). All DEGs were discovered with the DESeq2 R package (1.20.0). The DEGs were subjected to GO and KEGG enrichments by using the hypergeometric test with adjusted P values. qPCR was used to validate the results of the RNA sequencing. The RNA samples of the leaves were treated with DNaseI (Invitrogen), reverse-transcribed using Super­ ScriptTM RNase HReverse Transcriptase (Invitrogen), and then sub­ jected to real-time PCR analysis using gene-specific primers (Table S1) and SYBR Green. Amplification of Actin gene was used as internal reference genes (Fass et al., 2020). The relative gene expression level was calculated by the △△Ct method (Livak and Schmittgen, 2001). 69 H. Lu et al. Plant Physiology and Biochemistry 166 (2021) 66–77 Fig. 3. Effects of alkali stress on Na+ and K+ concentrations of sunflower plants. The sunflower plants were treated with 40 mM alkali stress condition (NaHCO3/ Na2CO3 = 9:1; pH 8.7) for 25 days or 100 days. Samples of leaves and roots were collected at 25 days, and mature seeds were collected at 100 days. Each treatment and organ have three biological replicates. 2.7. Statistical analysis roots than in leaves and seeds, and K+ concentration was much higher in leaves than in roots and seeds (Fig. 3). The experimental design was a randomized complete block design, with three biological replicates. The statistical significance of biochemical measurements and qRT-PCR was determined by the t-test at 0.05 level with SPSS version 16.0 (IBM). 3.3. Metabolomics We detected 404 metabolites in the present work. Differentially accumulated metabolites (DAMs) were defined as VIP > 1 and P < 0.05 (t-test). We discovered 116 DAMs in leaves, and 87 DAMs in roots (Tables S2–S3). In leaves, alkali stress did not enhance concentration of any amino acid, but it elevated concentrations of some amino acid an­ alogues such as 4-aminobutyric acid, 4-guanidinobutyric acid, L-pipe­ colic acid, and O-acetyl-L-serine (Table 1 and Fig. 4a). Alkali stress decreased concentrations of proline, aspartic acid, L-glutamate, Lglutamine, L-Serine and ornithine in leaves (Table 1 and Fig. 4a). In roots, alkali stress increased concentrations of proline, L-aspartate, and L-glutamate and decreased the concentrations of L-arginine and Lglutamine (Table 2 and Fig. 4b). In leaves, accumulation of eight fatty acids (2-Isopropylmalic acid, caproic acid, citraconic acid, citramalic acid, eicosapentaenoic acid, mesaconic acid, trans-vaccenic acid, and traumatic acid) was stimulated under alkali stress, while the concen­ trations of five fatty acids were decreased (Table 1 and Fig. 4a). How­ ever, in roots, concentrations of seven fatty acids were greatly enhanced under alkali stress, and concentration of only one fatty acid was decreased (Table 2 and Fig. 4b). Under alkali stress, concentrations of almost all organic acids especially carboxylic acids were elevated in both roots and leaves (Tables 1 and 2 and Fig. 4). In leaves, accumulation of six carbohydrates (D-lactose, myo-Inositol, D-mannose, raffinose, sor­ bose, and trehalose) was stimulated under alkali stress, but concentra­ tions of D-tagatose, isomaltose, and sucrose were reduced (Table 1 and Fig. 4a). In roots, concentrations of eight carbohydrates (myo-Inositol, D-galactarate, erythritol, fructose 1-phosphate, galactinol, glyceric acid, isomaltose, and sucrose) were elevated under alkali stress, and con­ centrations of only α-D-Glucose, D-mannose, and L-arabinose were lowered (Table 2 and Fig. 4b). In addition, under alkali stress, dihy­ droxyacetone concentration decreased in both leaves and roots, betaine concentration increased in both roots and leaves, and shikimate con­ centration was mightily enhanced in roots not in leaves (Tables 1 and 2). We noted that the change of ACC under alkali stress from Fig. 2 was not consistent with that from Tables 1-2. Quantitative data of ACC in Fig. 2 were generated by multiple reaction monitoring (MRM) method using a UHPLC-ESI-MS/MS system and internal phytohormone standards. Quantitative data of ACC in Tables 1-2 were generated by high throughput metabolome technology. It is recognized that targeted MRM 3. Results 3.1. Growth and photosynthesis We treated sunflower plants for whole life cycle. We observed a strong inhibition effect of alkali stress on growth and photosynthesis of sunflower plants (Fig. 1). When sunflower plants were exposed to alkali stress for 25 days, chloroplast remained intact ultrastructure and was not destroyed by alkali stress, but net photosynthetic rate (PN), stomatal conductance (gs), and transpiration rate (E) all greatly decreased (Fig. 1). Alkali stress only produced small effects on chlorophyll fluo­ rescence parameters and pigment concentrations of sunflower leaves (Fig. 1). Maximum quantum efficiency of photosystem II (Fv/Fm) in­ dicates an integrity and performance of photosynthetic electron trans­ port system. Alkali stress did not change value of this parameter, indicating a minor damage of alkali stress on photosynthetic electron transport system. The reduction of sunflower PN under alkali stress was due to stomatal closure. 3.2. Phytohormones and ions We used a QTRAP 5500 LC-MS-MS system to measure concentrations of 20 phytohormones covering seven major phytohormone types including auxin, ABA, brassinosteroid (BR), cytokinin (CTK), gibber­ ellin, ethylene, and jasmonic acid. We detected 15 phytohormones in control and stressed sunflower seedlings (Fig. 2). In leaves, alkali stress increased concentrations of ABA, GA1 and ACC (precursor of ethylene), and decreased concentrations of castasterone (CS), typhasterol (TY), four cytokinins (cZ, czR, tZ and tzR), cis-12-oxo-phytodienoic acid (cisOPDA), jasmonic acid (JA), and jasmonoyl-isoleucine(JA-Ile)(Fig. 2). In roots, alkali stress decreased concentrations of ABA, IAA, two cytokinins (czR and iP), JA and JA-Ile, and increased concentrations of TY, Iso­ pentenyladenosine (iPR), and cis-OPDA (Fig. 2). Alkali stress enhanced Na+ concentration in leaves and roots but not in seeds. Alkali stress reduced K+ concentration in roots and seeds but not in leaves. Under alkali stress, Na+ concentration and Na+/K+ ratio were much higher in 70 H. Lu et al. Plant Physiology and Biochemistry 166 (2021) 66–77 Table 1 Differentially accumulated metabolites (DAMs) between control and alkali stress conditions in leaves of sunflower plants. Four types of metabolites involved in alkali tolerance, including amino acids and analogues, organic acids, fatty acids and conjugates, and polyols and carbohydrates, were displayed. The sunflower seeds were treated with 40 mM alkali stress condition (NaHCO3/Na2CO3 = 9:1; pH 8.7) for 25 days. Fold change is ratio of stress treatment and control treatment. Each treatment has three biological replicates. Variable importance in the projection, VIP. Category Metabolite VIP Fold change P-value (t-test) Fatty acids and conjugates Docosahexaenoic acid 2-Ethyl-2-Hydroxybutyric acid 2-Isopropylmalic acid Caproic acid cis-9-Palmitoleic acid Citraconic acid Citramalic acid Eicosapentaenoic acid Mesaconic acid Mevalonic acid trans-Vaccenic acid Traumatic Acid Linolenic acid 1-Aminocyclopropanecarboxylic acid 4-Aminobutyric acid 4-Guanidinobutyric acid 5-L-Glutamyl-L-alanine Betaine D-Aspartic acid Dimethylglycine D-Proline L-Glutamate L-Glutamine L-Pipecolic acid L-Pyroglutamic acid L-Serine N-Acetyl-L-glutamate O-Acetyl-L-serine Ornithine Propionic acid Succinate cis-Aconitate Citrate Homocitrate DL-lactate L-Malic acid Galactonic acid alpha-ketoglutarate 2-Oxoadipic acid ketoisocaproic acid myo-Inositol Chlorogenic acid Quinate 2′ -Deoxy-D-ribose Dihydroxyacetone D-Lactose D-Mannose D-Tagatose Glucosamine Glyceric acid Isomaltose L-Threonate N-Acetyl-D-Glucosamine 6-Phosphate Raffinose Sucrose Sorbose Trehalose 1.552 1.105 1.968 1.055 1.449 2.097 1.241 2.215 4.006 1.065 1.072 1.826 2.923 7.588 1.471 1.296 2.072 15.239 2.253 1.228 3.884 5.105 2.497 1.273 3.026 1.190 1.258 1.141 2.109 2.227 4.191 3.296 1.412 1.128 2.267 6.142 2.555 1.406 9.130 3.648 3.354 1.370 3.894 1.046 1.503 1.212 1.619 1.090 1.243 1.022 1.064 1.358 1.645 1.718 1.175 1.028 1.243 0.304 0.346 7.505 2.353 0.581 4.114 1.843 15.383 9.668 0.398 3.388 1.127 0.460 0.257 1.682 1.890 0.671 2.852 0.386 0.378 0.147 0.574 0.115 117.969 0.282 0.287 0.324 5.747 0.132 3.345 3.437 10.092 6.141 11.430 0.331 1.736 2.681 1.606 7.018 0.632 2.498 5.221 0.465 0.378 0.664 4.477 2.543 0.370 0.489 1.649 0.567 17.875 6.108 5.841 0.787 3.060 6.190 0.0010 0.0001 0.0348 0.0017 0.0030 0.0020 0.0016 0.0023 0.0000 0.0001 0.0006 0.0173 0.0003 0.0001 0.0078 0.0004 0.0009 0.0001 0.0004 0.0331 0.0001 0.0001 0.0000 0.0001 0.0000 0.0001 0.0003 0.0002 0.0001 0.0000 0.0000 0.0000 0.0065 0.0185 0.0015 0.0007 0.0007 0.0001 0.0324 0.0001 0.0002 0.0005 0.0025 0.0000 0.0377 0.0158 0.0006 0.0002 0.0098 0.0023 0.0026 0.0014 0.0000 0.0004 0.0193 0.0096 0.0118 Amino acids and analogues Carboxylic acid and derivatives Other organic acids Polyols and carbohydrates measurement method with internal phytohormone standards is more precise than high throughput metabolome technology, therefore, the data of ACC from Fig. 2 were used for further analysis. Gene expression involved in photosynthesis, nitrogen metabolism, and respiration (oxidative phosphorylation, glycolysis, and pentose phos­ phate pathway) were greatly downregulated in leaves under alkali stress, but most genes of glycolysis pathway were strongly upregulated in roots (Fig. 5a). Pyruvate kinase and 6-phosphofructokinase are ratecontrolling enzyme for glycolysis. We found that the two gene families were dramatically upregulated in roots but were downregulated in leaves (Fig. 5b). The qRT-PCR experiment was used to validate the re­ sults of the RNAseq (Table S1). For nine of the 12 genes tested, the fold changes of qRT-PCR were similar to those of RNAseq, displaying that the results of RNAseq were reliable (Table S1). 3.4. Transcriptional profiling Unique mapping rate of RNA sequencing reads reached 86%–88% for tested RNA samples, indicating that reference genome of sunflower has high quality. 5092 differentially expressed genes (DEGs) were discov­ ered in roots, and 8169 DEGs in leaves (Tables S4–S5). All DEGs were exposed to KEGG and GO enrichment analyses (Fig. 5a and Fig. S1). 71 H. Lu et al. Plant Physiology and Biochemistry 166 (2021) 66–77 Fig. 4. The boxplot showing Log2(fold change) values of differentially accumulated metabolites (DAMs) between control and stress conditions in sunflower plants. The sunflower seeds were treated with 40 mM alkali stress condition (NaHCO3/Na2CO3 = 9:1; pH 8.7) for 25 days. Each treatment and tissue have three biolog­ ical replicates. 3.5. Gene expression involved in plant hormone signal transduction (Fig. 6). Some typical expression responses to salinity stress were observed in the present work. For example, alkali stress upregulated several late embryogenesis abundant protein (LEA) genes, V–H + -ATPase genes, potassium transporter genes and sodium/hydrogen exchanger (NHX) genes in roots or leaves, and alkali stress enhanced the expression level of potassium channel gene (AKT1) in roots (Table S6). Seven IAA/AUX (suppressor of IAA pathway) genes were upregu­ lated in leaves, and only one IAA/AUX gene (ID: 110880127) was upregulated in roots. Two TIR1 (IAA receptor) genes were down­ regulated in leaves but they were unaffected in roots (Fig. 6). Two DELLA (suppressor of GA pathway) genes were downregulated in the leaves but not in roots. Five JAZ (suppressor of JA pathway) genes were upregulated in leaves, while three JAZ genes were downregulated in roots (Fig. 6). ABA degradation gene CYP707A was downregulated in leaves, but it was unaffected in roots. ABA synthesis gene NCED was upregulated in leaves, whereas it was downregulated in roots (Fig. 6). 3.7. Lipidomics of mature seeds In sunflower seeds, we detected 444 lipid compounds including 31 sphingolipids, 27 saccharolipids, 182 glycerophospholipids, 193 glyc­ erolipids, one fatty acyl, 4 prenol lipids, and 6 serol lipids (Fig. 7). Two sphingolipids, six saccharolipids, fourteen glycerophospholipids, and eleven glycerolipids were differentially accumulated under control and stress conditions (Table 3). Concentrations of two sphingolipids, six saccharolipids, nine glycerolipids and one glycerophospholipids in the seeds were elevated under alkali stress (Table 3). Concentrations of two glycerolipids and thirteen glycerophospholipids in the seeds were reduced under alkali stress (Table 3). 3.6. Gene expression involved in osmotic regulation and ion balance Shikimate dehydrogenase gene was downregulated in leaves, but it was upregulated in roots. Three phenylalanine ammonia-lyase (PAL) genes were downregulated in leaves, and their expression levels were unaffected in roots. Two betaine synthesis genes (BADH and CMO) were upregulated in roots, whilst the two genes did not display significant changes in leaves during response to alkali stress (Fig. 6). Proline syn­ thesis gene P5CS was upregulated in roots not in leaves, and two proline degradation genes, P5CDH and ProDH, were downregulated in roots 72 H. Lu et al. Plant Physiology and Biochemistry 166 (2021) 66–77 Table 2 Differentially accumulated metabolites (DAMs) between control and alkali stress conditions in roots of sunflower plants. Four types of metabolites involved in alkali tolerance, including amino acids and analogues, organic acids, fatty acids and conjugates, and polyols and carbohydrates, were displayed. Fold change is ratio of stress treatment and control treatment. The sunflower seeds were treated with 40 mM alkali stress condition (NaHCO3/Na2CO3 = 9:1; pH 8.7) for 25 days. Each treatment has three biological replicates. Variable importance in the projection, VIP. Category Metabolite VIP Fold change P-value (t-test) Fatty acids and conjugates 2-Isopropylmalic acid Azelaic acid Citraconic acid Citramalic acid Mesaconic acid trans-Vaccenic acid Linoleic acid Linolenic acid 1.81 1.79 2.65 1.52 5.34 1.14 4.10 1.23 32.91 0.12 10.10 9.35 10.55 2.22 2.59 1.49 0.0003 0.0000 0.0000 0.0008 0.0000 0.0077 0.0028 0.0251 Amino acids and analogues 1-Aminocyclopropanecarboxylic acid 4-Aminobutyric acid Argininosuccinic acid Betaine D-Proline L-Arginine L-Aspartate L-Glutamate L-Glutamine L-Pyroglutamic acid Vigabatrin 2.45 1.10 1.47 3.30 1.52 1.10 1.38 3.50 2.64 2.30 1.43 0.69 14.28 5.29 1.82 7.00 0.61 3.22 2.92 0.27 0.28 0.30 0.0150 0.0002 0.0013 0.0009 0.0018 0.0363 0.0007 0.0007 0.0001 0.0001 0.0075 Carboxylic acid and derivatives Propionic acid Succinate cis-Aconitate Homocitrate 2.24 4.20 4.54 1.17 3.27 3.38 11.77 6.19 0.0005 0.0004 0.0000 0.0045 Other organic acids DL-lactate Galactonic acid alpha-ketoglutarate 2-Oxoadipic acid alpha-ketoisovaleric acid 1.77 1.01 3.28 21.46 1.66 1.27 1.60 4.36 34.83 22.39 0.0345 0.0103 0.0001 0.0002 0.0002 Polyols and carbohydrates Pantothenate myo-Inositol Quinate Shikimate Alpha-D-Glucose D-Galactarate Dihydroxyacetone D-Mannose Erythritol Fructose 1-phosphate Galactinol Glyceric acid Isomaltose L-Arabinose Sucrose 1.59 2.13 2.54 1.16 3.59 1.31 1.56 3.82 3.73 1.53 1.10 4.60 2.48 1.45 6.50 3.57 2.21 0.53 5.73 0.47 3.01 0.40 0.33 2.92 4.07 8.86 51.52 2.89 0.29 2.97 0.0016 0.0015 0.0269 0.0004 0.0010 0.0189 0.0060 0.0025 0.0017 0.0034 0.0009 0.0418 0.0006 0.0246 0.0004 4. Discussion sunflower seeds (Table 3). These changes revealed that alkali stress can change the lipid components of sunflower seeds, which will affect the quality of sunflower seed oils. We caution that cultivating sunflower plants on alkalized farmlands will change the quality of sunflower seed oils. Although alkali stress greatly downregulated gene expression involved in respiration, carbon metabolism, and nitrogen metabolism in sunflower leaves (Fig. 5a), it did not produce damage on chloroplast ultrastructure, photosynthetic pigments and photosynthetic electron transport system (Fig. 1). We propose that inhibition of leaf general metabolisms may be a growth strategy of sunflower plants to acclimatize to alkali stress, rather than a damage incurred by alkali stress. To shift energy and photosynthetic productions to root to fuel alkali stress response, sunflower plants may limit leaf growth through down­ regulating general metabolism genes and lowering BR and CTK accu­ mulation (Fig. 8). Lowered BR and CTK accumulation can limit leaf expansion and leaf cell division, reducing consumption of carbon resource and ATP. To survive alkali stress, sunflower plants need to regulate external pH. Secretion of organic acids, fatty acids, amino acids, 4.1. Enhanced root glycolysis process is critical response of sunflower plants to alkali stress Alkali stress involves in multiple stress factors, including osmotic stress, ionic toxicity and high-pH. As negative effects of high-pH, alkali stress shows much stronger damage to plant growth and development than does salt stress of the same salinity (Shi and Wang, 2005; Shi and Sheng, 2005). Transmembrane proton gradient generally drives Na+ exclusion and nutrient uptake processes. High-pH caused by alkali stress can break transmembrane proton gradient and inhibits Na+ exclusion and nutrient ion uptake, which is the basis of alkali stress injury. In addition, GEOCHEM software predicted that alkali stress precipitates 99% of Ca2+, Mg2+ and Fe2+ (Wang et al., 2012). In sunflower plants, alkali stress strongly inhibited growth and decreased leaf PN via stomatal limitation (Fig. 1), which is consistent with the finding in Liu et al., (2010). Alkali stress also strongly affected accumulation of lipids particularly saccharolipids, glycerolipids, and glycerophospholipids in 73 H. Lu et al. Plant Physiology and Biochemistry 166 (2021) 66–77 Fig. 5. KEGG enrichments of differentially expressed genes (DEGs) between control and stress conditions in sunflower plants. (a) KEGG enrichments of DEGs. (b) Expression of pyruvate kinase (PK) and 6-phosphofructokinase (PFK) genes. The sunflower seeds were treated with 40 mM alkali stress condition (NaHCO3/Na2CO3 = 9:1; pH 8.7) for 25 days. Each treatment and tissue have three biological replicates. Fig. 6. Effects of alkali stress on gene expression involved in phytohormone signal transduction and compatible solute biosynthesis of sunflower plants. Changes of phytohormones or compatible solutes were displayed in left of the panel, and related gene expression response on alkali stress in right of the panel. The sunflower seeds were treated with 40 mM alkali stress condition (NaHCO3/Na2CO3 = 9:1; pH 8.7) for 25 days. Each treatment and tissue have three biological replicates. TRANSPORT INHIBITOR RESPONSE 1, TIR1; Auxin-responsive protein IAA, IAA/AUX; DELLA protein GAI, DELLA; Ethylene receptor, ETR; Ethylene-responsive transcription factor, ERF; Protein TIFY, JAZ; Abscisic acid 8′ -hy­ droxylase 2, CYP707A; 9-cis-epoxycarotenoid diox­ ygenase, NCED; Shikimate dehydrogenase, SKD; Phenylalanine ammonia-lyase, PAL; Betaine alde­ hyde dehydrogenase, BADH; Choline mono­ oxygenase, CMO; Delta-1-pyrroline-5-carboxylate synthase, P5CS; Delta-1-pyrroline-5-carboxylate dehydrogenase, P5CDH; Proline dehydrogenase, ProDH. CO2 and H+ by roots is perceived as a major pH regulation mechanism for alkali-affected plants (Yang et al., 2010). Alkali stress-induced car­ boxylic acid secretion had been observed in Puccinellia tenuiflora (Guo et al., 2010), grape plants (Guo et al., 2018), and Chloris virgata (Yang et al., 2010). During response of sunflower plants to alkali stress, besides possible root secretion, larger accumulation of fatty acids, amino acids, carbohydrates, and organic acids in roots also will consume a massive amount of carbon sources and energy (Fig. 4b and Table 2). Under alkali 74 H. Lu et al. Plant Physiology and Biochemistry 166 (2021) 66–77 Fig. 7. Number of each lipid class detected in mature sunflower seeds. The sunflower plants were treated with 40 mM alkali stress condition (NaHCO3/Na2CO3 = 9:1; pH 8.7) for whole life cycle (100 days). Each treatment has three biological replicates. Table 3 Differentially accumulated lipids between control and alkali stress conditions in sunflower seeds. The sunflower seeds were treated with 40 mM alkali stress condition (NaHCO3/Na2CO3 = 9:1; pH 8.7) for whole life cycle (100 days). Each treatment has three biological replicates. Ceramides, Cer; Monogalactosyldiacylglycerol, MGDG; Digalactosyldiacylglycerol, DGDG; Sulfoquinovosyldiacylglycerol SQDG; phosphatidic acid, PA; phosphatidylserine, PS; phosphatidylcholine, PC; phosphatidylethanolamine, PE; diglyceride, DG; triglyceride, TG. Variable importance in the projection, VIP. Retention time, RT. Category Class name Lipid Formula m/z RT(min) Fold Change P-value (t-test) VIP Sphingolipids Cer Cer MGDG DGDG DGDG SQDG SQDG SQDG PA PS PC PC PC PC PC PC PC PC PE PE PE PE DG DG TG TG TG TG TG TG TG TG TG Cer(d18:1+hO/22:0) Cer(d18:1+hO/24:0) MGDG(18:2/18:2) DGDG(18:2/18:3) DGDG(18:2/18:2) SQDG(34:2) SQDG(18:2/18:2) SQDG(18:1/18:1) PA(18:2/18:2) PS(18:2/18:2) PC(34:2) PC(36:4) PC(36:3) PC(16:0/18:2) PC(16:0/18:1) PC(18:2/18:2) PC(18:1/18:2) PC(18:0/18:2) PE(16:0/18:2) PE(18:2/18:2) PE(18:2/18:2) PE(18:0/18:2) DG(18:2/18:2) DG(18:1/18:2) TG(16:0/16:0/18:2) TG(16:0/18:1/18:1) TG(18:0/18:0/18:2) TG(20:1/18:1/18:1) TG(18:1/18:2/22:0) TG(18:1/18:1/22:0) TG(18:1/18:3/24:0) TG(18:1/18:2/24:0) TG(18:1/18:1/24:0) 682.6 710.6 823.6 983.6 985.6 817.5 841.5 845.5 695.5 782.5 758.6 782.6 784.6 802.6 804.6 826.6 828.6 830.6 714.5 738.5 738.5 742.5 634.5 636.6 848.8 876.8 904.8 930.8 958.9 960.9 984.9 986.9 988.9 13.28 14.39 10.36 8.84 9.61 9.01 8.30 10.03 9.60 10.61 10.33 9.60 10.41 10.33 11.10 9.60 10.42 11.29 10.61 7.69 9.89 11.57 11.57 12.34 20.52 21.57 22.40 22.45 23.09 23.60 23.18 23.64 24.07 1.72 1.67 1.43 1.72 1.94 1.93 1.53 1.40 0.58 0.52 0.36 0.45 0.35 0.38 0.35 0.38 0.39 0.33 0.45 1.74 0.44 0.40 1.28 1.39 0.77 0.77 1.23 1.32 1.42 1.50 1.22 1.42 1.62 0.01 0.01 0.00 0.00 0.00 0.00 0.00 0.01 0.01 0.01 0.03 0.02 0.04 0.02 0.05 0.00 0.02 0.01 0.02 0.01 0.03 0.03 0.01 0.01 0.05 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 2.50 1.91 1.77 1.41 2.51 2.07 2.51 1.14 6.31 1.08 1.26 1.98 1.11 2.86 1.30 4.37 2.55 2.22 2.75 1.93 2.76 1.59 1.82 1.03 1.27 2.14 1.67 1.18 2.11 1.72 1.38 1.40 1.20 Saccharolipids Glycerophospholipids Glycerolipids stress, sunflower plants may enhance the glycolysis rate of the roots through upregulation of rate-controlling genes of glycolysis, pyruvate kinase gene and 6-phosphofructokinase gene (Fig. 5b). Enhanced root glycolysis process can provide more carbon sources and energy for synthesis of bioactive solutes in the roots of sunflower. 75 H. Lu et al. Plant Physiology and Biochemistry 166 (2021) 66–77 Fig. 8. Metabolic regulation network of alkali stress tolerance of sunflower plants. Red texts and blue texts indicate upregulation and downregulation, respectively. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.) 4.2. Phytohormones mediate growth balance of sunflower plants under alkali stress limit Na+ influx from roots into aboveground part. Metabolomics analysis of sunflower plants showed that concentra­ tions of many fatty acids, amino acids, carbohydrates, and organic acids were enhanced in the roots under alkali stress. We had observed that alkali stress can induce secretion of fatty acids, amino acids, and organic acids in many plants (manuscript in preparation). Under alkali stress, accumulated fatty acids, amino acids, and organic acids may be secreted into rhizosphere to regulate pH, and accumulated carbohydrates and fatty acids can be oxidated to produce NADH and FADH2 to fuel alkali stress response of sunflower roots. Among metabolites detected in the present study, we specially focused on betaine, and proline because their roles in salinity tolerance are relatively clear. Concentrations of betaine and proline were elevated in sunflower roots under alkali stress. Accordingly, in roots of sunflower, a proline synthesis gene (P5CS) and two betaine synthesis genes (BADH and CMO) were upregulated, while proline degradation genes (P5CDH and ProDH) were downregulated. These gene expression data provided an explanation for enhanced accumulation of betaine and proline in sunflower roots under alkali stress. Some typical gene expression re­ sponses to salinity stress also were observed in the present work. For example, LEA, potassium transporter genes, NHX, and AKT1 were upregulated in sunflower plants under alkali stress. ABA is well known as a salinity stress responsive phytohormone, and it plays central role in salinity stress response. We observed that alkali stress enhanced ABA concentration in sunflower leaves but decreased its concentration in the roots. In addition, concentrations of both ACC (precursor of ethylene) and GA1 also were elevated in sunflower leaves but not in its roots under alkali stress. The transcriptional analysis dis­ played that DELLA genes (suppressor of GA pathway) were down­ regulated in the leaves, and a ETR gene (receptor of ethylene) and two Ethylene-response factor (ERF) genes were greatly upregulated in the leaves. These gene expression and phytohormone quantitation results revealed that alkali stress enhanced ABA pathway, GA pathway and ethylene pathway in leaves of sunflower. Although it had been reported that the ethylene and GA may be involved in salinity stress response, roles played by ethylene and GA in salinity stress tolerance is poorly understood (Zheng et al., 2020; Borbély et al., 2020). Our results showed that ABA, ethylene and GA may play positive roles in response of sun­ flower leaves to alkali stress. However, in sunflower leaves, it is complex how ethylene, ABA and GA coordinate or interact to respond to alkali stress, which should be investigated in the future. Interestingly, alkali stress elevated accumulation of BR (typhasterol), CTK (Iso­ pentenyladenosine) and cis-OPDA in sunflower roots (Fig. 2), which may mediate the gene expression involved in alkali stress response of sunflower roots. We here provided some valuable gene expression data and biochemical data to dissect regulation network of multiple phyto­ hormones in sunflower alkali tolerance. 5. Conclusions Alkali tolerance of sunflower is unlikely controlled by single gene or several genes. Based on multiomics analysis, we illustrated the alkali tolerance network of sunflower plant at tissue, metabolism, and gene expression levels (Fig. 8). We propose that multiple phytohormones (GA, ABA, ethylene, BR, and CTK) and bioactive molecules interact to mediate alkali stress response of sunflower plants (Fig. 8). Enhanced glycolysis process provided more carbon source and energy for alkali stress response of sunflower roots. We believe that our results should improve understanding of plant alkali tolerance and provide helpful information for breeding alkali tolerant crops. 4.3. Metabolic response and gene expression To survive under alkali stress, plants need to cope with Na+ toxicity, osmotic stress, and high-pH (Yang et al., 2010). Na+ competes with K+ to bind sites on proteins (Munns and Tester, 2008). High cytosolic K+/Na+ ratio can decrease the binding frequency of Na+ to proteins with K+-binding sites (Zhao et al., 2020). Under salt stress or alkali stress, high K+ concentration and low Na+ concentration is essential to remain normal metabolism of plants (Zhao et al., 2020). At tissue level, under alkali stress, sunflower plants are able to remain relatively high K+ concentration in leaves and low Na+ concentration in leaves and seeds (Fig. 3). Under alkali stress, to relieve Na+ toxicity in leaves and seeds, sunflower plants accumulate much high Na+ concentration in roots and Data availability statement All raw data of RNA sequencing are deposited at NCBI (Accession numbers SRR13155365-SRR13155373). The datasets used and/or analyzed during the current study are available from the corresponding author on request. 76 H. Lu et al. Plant Physiology and Biochemistry 166 (2021) 66–77 Ethics approval and consent to participate quantities of organic acids and into the rhizosphere. J. 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(Ed.), Saline Plants in Songnen Plain and Restoration of Alkaline-Saline Grass. Science Press, Beijing, China, pp. 137–138. Zheng, L., Ma, H., Jiao, Q., Ma, C., Wang, P., 2020. Phytohormones: important participators in plant salt tolerance. Int. J. Agric. Biol. 24, 319–332. Zhu, G.L., 1993. Carotenoid and chlorophyll determination. In: Zhu, G.L. (Ed.), Laboratory Manual of Plant Physiology. Beijing University Press, Beijing, China, pp. 51–54. Not applicable. Consent for publication Not applicable. Author contribution CY and HL - Conception and design, execution of experiment, analysis and interpretation of the data, drafting of the article, and crit­ ical revision of the article for important intellectual content. HL, CY, ZW, LL, and CX - Execution of experiment analysis and interpretation of the data. Contribution We found that multiple phytohormones (GA, ABA, ethylene, BR, and CTK) and bioactive molecules (fatty acids, amino acids, organic acids, carbohydrates, and betaine) interact to mediate alkali stress response of sunflower plants. Enhanced glycolysis process provided more carbon source and energy for alkali stress response of sunflower roots. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgements This work was supported by the Fundamental Research Funds for the Central Universities (No. 2412019FZ026). Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi. org/10.1016/j.plaphy.2021.05.032. References Badouin, H., Gouzy, J., Grassa, C.J., Murat, F., Staton, S.E., Cottret, L., LelandaisBrière, C., Owens, G.L., Carrère, S., Mayjonade, B., et al., 2017. 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