huiying-lu-multiomics-analysis-provides-insights-into

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: [email protected] (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,
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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
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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).
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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
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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).
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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
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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
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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
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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.
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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.
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Plant Physiology and Biochemistry 166 (2021) 66–77
Ethics approval and consent to participate
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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.
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