Agronomic and
Physiological Evaluation of Wheat Cultivars under Deficit Irrigation Condition
Ruize Lin1,2†, Liguo
Guo3†, Shuang Zhang1,2, Le Han1,2 and Kai Xiao1,2*
1State Key Laboratory of North China Crop Improvement and Regulation,
Baoding, P. R. China 071001
2College of Agronomy, Hebei Agricultural University, Baoding, Hebei
071001, P. R. China
3Research Institutes of Science and Technology, Agricultural University
of Hebei, Baoding, Hebei 071001, P. R. China
*For correspondence: xiaokai@hebau.edu.cn
†Contributed equally to this
work and are co-first authors
Received 19 December
2020; Accepted 13 January 2021; Published 16 April 2020
Abstract
Improving crop productivity under drought conditions
contributes largely to the sustainable agriculture globally. In this study, the
agronomic traits and physiological processes related to osmolyte accumulation
and reactive oxygen species (ROS) homeostasis during late growth stage in wheat
under drought stress were studied. Three cultivars viz., Shimai 22 (drought tolerant), Zhongxinmai 99 (median drought-tolerant, control), and Shi
4185 (drought sensitive) sharing contrasting drought tolerance were grown under
normal irrigation (NI: with irrigations prior to sowing, and at jointing and
flowering stages) and deficit irrigation (DI, with irrigations prior to sowing
and at jointing) conditions. Data regarding yields, osmolyte (i.e., proline and soluble sugar)
contents, and antioxidant enzyme activities of superoxide dismutase (SOD), catalase
(CAT), and peroxidase (POD), and malondialdehyde (MDA) contents were recorded. Under deficit irrigation, the cultivars displayed
modified agronomic and physiological traits. Among cultivars, Shimai 22 showed best agronomic traits (6.47 to 7.23%
higher yield than control), osmolyte contents and AE activities (10.12 to
22.18% higher than control), and least MDA accumulation (12.30 to 17.06% lower
than control). In contrast, Shi 4185 cultivar performed worst regarding above
said traits. The transcripts of the genes in ¦¤1-Pyrroline-5-carboxylate
synthetase (P5CS) family that regulates proline biosynthesis and
those in AE families that modulate ROS homeostasis were evaluated. Results
revealed that the P5CS genes TaP5CS2
and TaP5CS5 and the AE ones TaSOD3, TaCAT2 and TaCAT5 were
modified on transcripts across the cultivars under DI condition, showing to be
significant upregulated compared with NI. These results suggested the essential
roles of osmolyte accumulation and AE proteins in improving the drought
tolerance of wheat during late growth stages. In addition, this study suggested
that the elevated transcription efficiencies of distinct P5CS and AE family
genes under water deprivation contribute to the enhanced drought tolerance in
drought-tolerant cultivars. © 2021 Friends Science Publishers
Keywords: Antioxidant enzymes; Agronomic traits; Drought
tolerance; Osmolytes; Wheat
Introduction
Drought
stress exerts drastic negative effects on growth and the productivity of cereal
crops (Wu et al. 2004; Sheffield 2014; Lesk et al. 2016). Given the climate change and
anthropogenic influences (AghaKouchak et al. 2015), the drought risk has been raised
and led to the yield loss of cereal species in past two decades (Li et al. 2009; Zhao and Running 2010; Dai
2013). In
North China, the large-scale cultivation of winter wheat (Triticum
aestivum L.), a crop
constituting the major cropping system (i.e.,
winter wheat/summer maize across whole year), contributes greatly to the
regional food safety and the production development. However, much more water
resource has been consumed by planting winter wheat due to elevated yields of
winter wheat together with the low rainfall amount during growth cycle (started
from early of October to maturity of mid-June) (Lobell et al. 2011; Ray et al. 2015; Ghahramani and Moore 2016). The intensified
consumption of water storage initiated by enhanced crop productivity combined
with low precipitation has been becoming the limiting factor for the
sustainable agriculture (Barnabas et
al. 2008; Praba et al. 2009; Lobell et al.
2011).
Therefore, developing water-saving management for the winter wheat production
has acted as an effective strategy to promote the productivity of this species
in a long term.
Crop plants have evolved a suite of strategies to cope
with the negative effects of drought, including accumulation of osmolytes in
plants once challenged with osmotic stress conditions (Anjum et al. 2017; Tanveer et al.
2019). Several
kinds of cellular metabolites, such as proline, soluble sugars, and a subset of
small molecules, are over-accumulated through enhanced biosynthesis metabolism
upon osmotic stressors, which regulate the plant adaptation to adverse environments
(Anjum et al. 2017). Thus far, it
has been recorded that osmolyte amounts are associated with improved
physiological processes in the drought-challenged plants, due to their positive
roles in regulating cellular osmotic potential and photosynthetic function (Farooq
et al. 2009). Additionally, exogenous application of osmo-protectants enhances
the yield traits of crop plants given improved regulation of the osmotic
potential that confers plants drought resistance (Ashraf and Foolad 2007). For example, external glycine betaine has endowed plants
enhanced drought tolerance, which is largely ascribed to the improvement of
leaf stomatal conductance, photosynthetic function, and proline biosynthesis
metabolism (Ma et al. 2007;
Hussain et al. 2008). Exogenous
application of spermidine, a kind of osmolytes frequently induced under osmotic
stress, alleviates the adverse effects of drought on the growth and development
behaviors of cereal plants (Kubis 2003). Moreover,
transgene analysis on the genes encoding rate-limiting enzymes involving
osmolyte biosynthesis, such as proline, has validated the function of distinct
genes in improving plant drought tolerance. These drought tolerant-associated
genes enhance the capacities of cell vigor and improve the drought
response-associated physiological processes (Gubis
et al. 2007). These findings together suggested
the essential roles of osmolytes in plant drought responses.
Cellular oxidative condition in abiotic stress-challenged
plants is present at the subsequent stage following stress progression. Under
drought stress, plants over accumulate reactive oxygen species (ROS), such as superoxide
radicals (O2·−) and hydrogen peroxide (H2O2) (Hussain et al. 2018). The ROS initiated exert negative roles to plant cells given
the damage of cellular macro-molecules, such as lipids, proteins, and nucleic
acids (Gill and Tuteja 2010). On the other hand, plants have evolved effective strategies
to alleviate the negative effects of ROS under osmotic stresses. Among them,
the antioxidant enzyme (AE) system is activated and plays essential roles in
scavenging ROS, contributing to plant stress tolerance via alleviation of cellular oxidative stress condition (Sunkar et al.
2006). Superoxide
dismutase (SOD), catalase (CAT), and peroxidase (POD), the critical enzymes
effecting on antioxidant enzyme (AE) system, sustain relatively cellular ROS
homeostasis under abiotic stresses (Signorelli et al. 2013). Moreover, distinct genes in AE families are modified on
transcripts abundance upon osmotic stress (Karinne et al. 2015). Over expression of a suite of AE
genes, such as SOD ones, endowed plants drought tolerance via improving
cellular ROS homeostasis as well as alleviating the extent of plant oxidative
stress (Wang et
al. 2005; Karinne et al. 2015). These results together provided novel insights in
breeding drought tolerant cultivars using the improved ROS homeostasis system.
Many efforts have been performed to evaluate behaviors
of agronomic trait, physiological processes and yield formation capacity in
cereal crops under varied water supply conditions (Kanbar 2013;
Signorelli et al. 2013; Li et al. 2015; Li 2016). However, the behaviors of
osmolyte accumulation, cellular ROS homeostasis, and the associated molecular
processes during late stage in drought-challenged plants of winter wheat are
needed to be further defined. In this study, we used wheat cultivars sharing
contrasting drought response to investigate osmolyte- and ROS-associated
parameters as well as related gene expression patterns under deficit
irrigation. The results provide insights into understanding of the
drought-associated physiological and molecular processes in wheat plants and
benefit breeding of wheat cultivars cultivated under the water-saving
conditions.
Materials and Methods
Experimental details and treatments
Experimental material: The field experiments were conducted
at Liujiazhuang village, Gaocheng
City, China, during the 2017–2018 and 2018–2019 growth seasons. Meteorological
factors at spring growth stage during the two growth seasons are shown in Table
1. The climate for experiments is specified with temperate continental monsoon,
with rainfall amounts to be concentrated at summer season. The surface soil
layer for experiments was loamy and contained organic mater 19.22 g kg-1,
available nitrogen 63.86 mg kg-1, available phosphorus (Olsen-P)
21.44 mg kg-1, and exchangeable potassium 121.75 mg kg-1
(determined based on conventional assay for soil sample). The soil texture was
alluvial type with soil pH 7.73.
Treatments: The plots were arranged based
on a randomized split design with triplicates, with irrigation as main-plot
whereas cultivar as sub-plot. The main-plot included two irrigation treatments:
normal irrigation (irrigation practices conducted prior to sowing and at stages
of jointing and flowering) and deficit irrigation (irrigation practices performed
prior to sowing and at jointing stage). Water irrigated amount was 70 mm
controlled by water amount analyzer at each time. The sub-plot included three
cultivars: median drought-tolerant Zhongxinmai 11
(control), drought-tolerant Shimai 22, and
drought-sensitive cultivar Shi 4185. Area of each plot was 24 m2 (6
m ˇÁ 4 m) and seeds of each cultivar were sown on October 8 and 7 during the
2017–2018 and 2018–2019 seasons, respectively. All the plots were fertilized
using amount 600 kg ha-1 basal complex fertilizer (N: P2O5:
K2O for 20: 15: 15, Liuguo Chemical Co.,
Ltd., Anhui, China) together with top-dressed N 120 kg ha-1 at
jointing stage. During two growth seasons, seeds were sown in row pattern with
15 cm distance to establish an approximately 3,750,000 seedling per hectare.
Prior to sowing, the straws of last crop (i.e.,
summer maize) were mechanically broken into pieces and mixed well with the
basal fertilizers as well top soil after ear harvest. Other cultivation
techniques conducted were similar to those adopted by the local farmers.
Measurements of yields and yield components
At maturity, the spikes in 2 m2 in each plot
were counted to calculate the population spike numbers. The seeds in each plot
were separately threshed at maturity (June 13 and 11 at 2018 and 2019,
respectively) using a mini harvesting machine. After air-drying, the seeds
harvested were weighed for calculation of yields. Seed weight was obtained by
weighing one thousand air-dried seeds and seed numbers per spike were
calculated based on total seed amounts in thirty representative spikes.
Measurements of osmolytes contents
At late growth stages
(i.e., stages of flowering,
mid-filling, and maturity), contents of osmolytes in the tested cultivars, including proline and
soluble sugar, were determined under normal and deficit irrigation conditions using
the upper expanded leaves as samples. Of which, the contents of proline in
various cultivar plants under different irrigation treatments were measured as
described previously by Bates et al.
(1973) whereas the contents of soluble sugar were analyzed following the
procedure of Hu et al. (2016).
Measurements of ROS-associated traits
At late stages mentioned above, a subset of parameters
associated with cellular reactive oxygen species (ROS) homeostasis, including
activities of superoxide dismutase (SOD), catalase (CAT), and peroxidase (POD),
and contents of malondialdehyde (MDA) that reflect cellular over-oxidation
degree upon stressors, were assessed under the normal and deficit irrigation treatments.
Likewise, the upper leaves of the tested cultivars under various irrigation
treatments were used as samples. Procedures for assessing the ROS-associated
parameters mentioned above were performed to be similar to those described previously
(Beauchamp and Fridovich 1971; Kar et al. 1976; Huang et
al. 2013).
Assay of expression patterns of the P5CS family genes
Five genes encoding delta-1-pyrroline-5-carboxylate synthase (P5CS)
proteins in T. aestivum,
which act as the rate-limiting enzymes in proline biosynthesis metabolism, were
subjected to evaluation of transcript levels in the tested cultivars under
various irrigation treatments. The GenBank accession numbers of the P5CS family
genes (i.e., TaP5CS1 to TaP5CS5) are
shown in Table 2. Transcripts of the genes were detected based on qRT-PCR performed as previously described (Guo et al. 2013), using gene specific primers (Table 2). The
upper leaves of the cultivars under normal irrigation and deficit irrigation
were used as samples. Tatubulin, a constitutive gene in T. aestivum, was used as an internal
reference to normalize transcripts of the target genes (Table 2).
Assay of expression patterns of the AE family genes
To
understand the putative genes in modulating AE activities in the water deprivation-treated
wheat plants, a subset of genes encoding SOD and POD proteins, respectively,
were subjected to evaluation of the expression levels in drought-challenged
wheat cultivars. Gene information of the five genes coding for SOD proteins (TaSOD1 to TaSOD5) and six for CAT proteins (TaCAT1 to TaCAT6) are
shown in Table 2. Transcripts
of the AE genes mentioned were analyzed based on qRT-PCR
performed to be similarly in evaluating the P5CS genes as aforementioned, with
gene specific primers (Table 2). Likewise, Tatubulin was
used as an internal standard to normalize the transcripts of the AE genes.
Data analysis
The yields, yield components, osmolytes contents, AE
activities, MDA contents, and the transcripts of the P5CS and AE family genes
were derived from randomized split design with three replications. Averages,
standard errors, and significant test analysis were statistically conducted
based on two-way ANOVA using COSTAT computer software (COHORT, Monterey,
California).
Results
Yield and yield components
The three wheat cultivars examined displayed improved
grain yield and yield components (i.e.,
population spike numbers, spike seed numbers, and grain weight) under the
normal irrigation condition relative to those shown under deficit irrigation
treatment (Table 3). Among the tested cultivars, although they showed different
yield components under normal irrigation, their yields were comparable with
each other. Under DI, the yields of drought-tolerant cultivar Shimai 22 were shown to be the highest (6.47 to 7.23%
higher than control), followed by Zhongxinmai 11
(control), and the drought-sensitive cultivar Shi 4185 the lowest (9.41 to
12.35% lower than control), which were closely associated with the variation on
population spike amounts across the cultivars (Table 3).
The osmolytes contents
At the growth stages of flowering, mid-filling, and
maturity, the proline and soluble sugar contents in the tested cultivars were
shown to be consistent with the yields obtained under normal and deficit
irrigation. The three cultivars were similar on contents of proline and soluble
sugar under normal irrigation whereas elevated on above osmolyte amounts under deficit
irrigation (Fig. 1A–B). In addition, the osmolyte contents were highest in Shimai 22 and lowest in Shi 4185 at various stages assessed
under the deficit irrigation conditions (Fig. 1A–B).
Table
1: Meteorological factors at spring growth stage during the 2017–2018 and
2018–2019 seasons
Growth season |
Factor |
April |
May |
June |
2017-2018 |
Average temperature (ˇăC) |
13.39 |
21.98 |
27.74 |
Precipitation (mm) |
23.58 |
71.79 |
51.19 |
|
Total sunshine (hour) |
238.83 |
245.03 |
254.78 |
|
Solar radiation (W/m2) |
713.52 |
766.61 |
702.74 |
|
2018-2019 |
Average temperature (ˇăC) |
12.47 |
20.66 |
27.50 |
Precipitation (mm) |
32.26 |
59.31 |
92.33 |
|
Total sunshine (hour) |
230.05 |
256.73 |
242.36 |
|
Solar radiation (W/m2) |
700.48 |
779.52 |
670.95 |
Fig. 1: Contents of proline (A) and soluble sugar (B)
of the wheat cultivars under normal and deficit irrigation conditions
Means ˇŔ standard deviation
with same letter differs non-significantly in wheat cultivars at each growth
stage under same irrigation treatment (P
> 0.05)
The expression patterns of the P5CS family genes
Five genes in the P5CS
family (i.e., TaP5CS1 to TaP5CS5) were
subjected to expression pattern assessment in the cultivars treated with normal
and deficit irrigation conditions. Among the genes examined, two of them,
namely, TaP5CS2 and TaP5CS5, displayed modified transcripts
in the cultivars upon altered irrigation treatments, showing significantly
upregulated expression levels under deficit irrigation with respect to normal
irrigation at various stages (Fig. 2). Additionally, the expression induction
extent of the genes under deficit irrigation was the highest in Shimai 22, followed by Zhongxinmai
11, and the lowest in Shi 4185 (Fig. 2). The expression patterns of these two
P5CS genes under deficit irrigation were in agreement with the proline contents
shown in the tested cultivars.
The ROS-associated parameters
Under normal irrigation
condition, the three cultivars exhibited higher SOD and CAT activities, and
less MDA contents compared with those shown under deficit irrigation.
Additionally, they were comparable on the POD activities under normal
irrigation and deficit at various stages (Fig. 3A–D). Under DI, the AE activities
of SOD and CAT and the contents of MDA were significantly varied across the
tested cultivars. Shimai 22 showed highest SOD and
CAT activities whereas lowest MDA contents, followed by Zhongxinmai
11, and Shi 4185 the lowest on above AE activities and the highest on MDA
accumulation (Fig. 3A–D).
The expression patterns of the AE family genes
The expression patterns
of a subset of AE family genes (TaSOD1 to TaSOD5 and TaCAT1 to TaCAT6) were
investigated using leaves of the tested wheat cultivars under NI and DI as
samples. In contrast to the genes that were unchanged on transcripts across
cultivar and irrigation treatments, TaSOD3,
TaCAT2, and TaCAT5 displayed significantly modified expression levels in the
tested cultivars under DI relative to NI. They all exhibited induced
transcripts under deficit irrigation compared with normal irrigation, with more
transcripts detected in Shimai 22 and less ones in
Shi 4185 (Fig. 4A–B).
Discussion
Drought negatively affects
various physiological processes associated with plant growth, development, and
yield formation (Farooq
et al. 2009). On the other hand, the plants in
diverse species have also evolved a suite of effective strategies to cope with
the adverse effects of the drought stressor (Duan et al. 2007). Among which, osmolytes that act as biochemical compounds to
stabilize cellular osmotic potentials under osmotic stresses, are noticed to be
increased in the osmotic-challenged plants (Wani
et al. 2013). The increased amount of proline,
sucrose, polyols, trehalose, and alanine betaine at cellular level alleviate
the damages of cell stress (Duan et al. 2007), and enhance the adaptation of
plants to a set of abiotic stresses, such as drought (Wani et al.
2013),
high salinity (Conde et al.
2011), and
temperature (Hayashi et al.
1998). In
this study, the contents of proline and soluble sugar, two crucial osmolytes in
plant stress responses, were investigated at the seed filling stage using three
contrasting drought response cultivars under various irrigation treatments.
Both osmolytes display a pattern to be Table 2: The
P5CS and AE family genes together with the PCR primers used in this study
Gene |
Accession number |
Forward primer (5´-) |
Reverse primer (5´-) |
Tatubulin (internal reference) |
U76558 |
catgcratcccrcgtctcgacct |
cgcacttcatgatggagttgtat |
TaP5CS1 |
AB193551 |
gcacgtggacctgtgggtgttg |
gttttcgcggaatccttaccacg |
TaP5CS2 |
KM523670 |
ggccgtatacatgcacgtggacct |
aggtccacgtgcatgtatacgg |
TaP5CS3 |
KT868850 |
ctcttacgagggaaagggcaa |
tcattgcaaaggaaggctc |
TaP5CS4 |
KT218497 |
caagttgataggtatttctgaa |
aataaggtatctgttgcctcaa |
TaP5CS5 |
AY888045 |
tggtcactacagatgataaagt |
tacttatgccaacctcagcacc |
TaSOD1 |
FJ890986 |
gacgctgatgatcttggcaagg |
atcttagccctggagcccgatg |
TaSOD2 |
FJ890987 |
ccccatggactatcaaactcgt |
gtcaagtctagctccacttgagt |
TaSOD3 |
JQ613154 |
caatgctgagggtgtggcggaga |
tctccgccacaccctcagcatt |
TaSOD4 |
AF092524 |
accaacatctggaaggtggt |
accaccttccagatgttggtc |
TaSOD5 |
KR069092 |
cagttgttgggagagcgtttgt |
acaaacgctctcccaacaact |
TaSOD6 |
TAU69536 |
ggtgggcatgagctcagcctca |
ccaggtaaaacgagaatggcgt |
TaCAT1 |
D86327 |
gcgagaagatggtgatcga |
aggagagccagatggccttg |
TaCAT2 |
X94352 |
gcctcagctggcgtcgatc |
acgcgctgacgacaccccac |
TaCAT3 |
GU984379 |
cgttcaggcaagagcgattcat |
atgaatcgctcttgcctgaac |
TaCAT4 |
HQ860268 |
ggagaagacgaggatcaagaag |
acttggagaggaagtcgatc |
TaCAT5 |
KP892532 |
ccagtggctcacccgcctcggt |
acaccaactatcattgttcatc |
TaCAT6 |
KP892533 |
gggcagaagctggcgtcgcgg |
ttcatggctacacccacagag |
Table
3: Yields and yield components of tested cultivars under various
irrigation treatments
Growth season |
Irrigation |
Cultivar |
Yield (kg/ha) |
Spike
number (thousand/ha) |
Kernel
number per spike |
1000-grain weight (g) |
2017-2018 |
Normal irrigation |
Zhongxinmai 11 |
8163.82 ˇŔ 159.67a |
6888.38 ˇŔ 200.22c |
32.25 ˇŔ 0.83a |
42.45 ˇŔ 0.30a |
Shimai 22 |
8286.72 ˇŔ 147.30a |
7251.56 ˇŔ 211.50b |
32.10 ˇŔ 0.72a |
42.03 ˇŔ 0.34a |
||
Shi 4185 |
8085.25 ˇŔ 156.82a |
7480.48 ˇŔ 209.44a |
31.79 ˇŔ 0.93a |
39.12 ˇŔ 0.36b |
||
Deficit irrigation |
Zhongxinmai 11 |
6748.62 ˇŔ 151.74b |
6178.69 ˇŔ 129.95b |
31.42 ˇŔ 0.88a |
41.12 ˇŔ 0.32a |
|
Shimai 22 |
7236.55 ˇŔ 180.05a |
6714.33 ˇŔ 121.69a |
31.27 ˇŔ 0.82a |
41.00 ˇŔ 0.34a |
||
Shi 4185 |
6113.86 ˇŔ 177.53c |
6126.48 ˇŔ 123.50b |
30.49 ˇŔ 0.94a |
37.23 ˇŔ 0.36b |
||
2018-2019 |
Normal irrigation |
Zhongxinmai 11 |
8763.82 ˇŔ 212.30a |
7088.35 ˇŔ 200.22c |
33.25 ˇŔ 0.86a |
43.22 ˇŔ 0.34a |
Shimai 22 |
8792.63 ˇŔ 186.26a |
7435.60 ˇŔ 238.34b |
32.50 ˇŔ 0.74a |
42.33 ˇŔ 0.32a |
||
Shi 4185 |
8708.45 ˇŔ 200.33a |
7712.13 ˇŔ 249.23a |
32.79 ˇŔ 1.01a |
40.34 ˇŔ 0.35b |
||
Deficit irrigation |
Zhongxinmai 11 |
7243.89 ˇŔ 158.26b |
6295.37 ˇŔ 120.22b |
32.25 ˇŔ 0.92a |
42.04 ˇŔ 0.40a |
|
Shimai 22 |
7712.72 ˇŔ 198.23a |
6907.97 ˇŔ 138.36a |
31.50 ˇŔ 0.78a |
41.33 ˇŔ 0.58a |
||
Shi 4185 |
6349.40 ˇŔ 188.06c |
6015.18 ˇŔ 149.23c |
32.02 ˇŔ 1.22a |
38.11 ˇŔ 0.40b |
Means ˇŔ standard deviation with same letter differs
non-significantly in wheat cultivars under same irrigation treatment (P > 0.05)
Fig. 2:
Expression levels of P5CS family genes of the wheat cultivars under normal (NI)
and deficit irrigation (DI) conditions
Means ˇŔ standard deviations with
same letter differ non-significantly in wheat cultivars at each growth stage under
same irrigation treatment (P > 0.05)
significantly
elevated under deficit irrigation relative to those shown under normal
irrigation conditions. These results were in agreement with previous findings
showing that osmolytes share a nature to be induction under water deprivation
conditions in cereal crops (Conde et al. 2011; Wani et al. 2013). In addition,
our results indicate a drastic variation on proline and soluble sugar
accumulation across cultivar plants at late stages (i.e., flowering, mid-filling, and maturity), with the pattern of Shimai 22 plants to be the highest, followed by Zhongxinmai 11 ones, and the Shi 4185 plants the lowest
among the tested cultivars. Therefore, the osmolytes mentioned contribute to
plant drought adaptation through positively regulating cellular
osmotic-regulatory capacity under the deficit irrigation condition.
Fig. 3: Activities of SOD (A),
CAT (B), POD (C) and MDA contents (D) of
the wheat cultivars under normal and deficit irrigation conditions
Means ˇŔ standard deviations with same letter differ
non-significantly in wheat cultivars at each growth stage under same irrigation
treatment (P > 0.05)
Fig. 4: Expression levels of SOD (A) and CAT (B) family
genes of the wheat cultivars under normal (NI) and deficit irrigation (DI) conditions
Means ˇŔ standard deviations with same letter differ
non-significantly in wheat cultivars at each growth stage under same irrigation
treatment (P>0.05)
The oxidative degree frequently intensifies at
cellular level once plants are exposed to abiotic stresses. Under drought
condition, ROS in plant cells is accumulated which further lead to lipid
peroxidation and injury of the plant tissues (Yue et al. 2011; Sun et al. 2012). Meanwhile, the
antioxidant defense system constituting either enzymatic or non-enzymatic
components is promoted in the osmotic stress-treated plants, alleviating the
negative effects of oxidative stress by scavenging ROS (Farooq et al. 2008). The AE proteins, such as SOD, POD
and CAT that constitute the enzymatic protection system, involve the scavenging
of drought-initiated ROS to sustain cellular ROS homeostasis (Anjum et al. 2011). In this study, the three cultivars
exhibited irregular patterns on the AE activities under normal irrigation, they
showed the ROS-associated parameters to be consistent with the drought tolerant
capacities under the DI condition. Of which, Shimai
22, a drought-tolerant cultivar, showed highest activities of SOD and CAT,
followed by Zhongxinmai 11, a median in
drought-tolerant. In contrast, Shi 4185, a cultivar to be drought-sensitive,
displayed the lowest activities of above AE activities. Moreover, these
cultivars displayed contrast MDA contents under the water deprivation
conditions. Therefore, the behavior of AE activities was also closely
associated with the plant drought tolerance due to their functions in improving
cellular ROS homeostasis.
Plant drought response is closely associated with the
modified transcription of numerous stress defensive-associated genes (Umezawa
et al. 2006). Results indicated that TaP5CS2 and TaP5CS5, two genes in the P5CS family and TaSOD3, TaCAT2, and TaCAT5, three genes that encode one SOD protein and two CAT
proteins, respectively, display modified transcription upon water deprivation.
The transcripts of all of the genes mentioned enhanced in tested cultivars
under deficit and normal irrigation conditions. Moreover, expression levels of
these differential genes in tested cultivars were consistent with the behaviors
on agronomic traits shown in cultivar plants, showing to be the highest in Shimai 22, followed by Zhongxinmai
11, and the lowest in Shi 4185. These results suggested
that the enhanced transcription efficiency of distinct genes in P5CS and AE
families positively effects plant drought tolerance in wheat plants, which is
associated with the gene functions in promoting osmolyte biosynthesis and
improving ROS homeostasis. In this study, though the internal relations between
plant drought tolerance and osmolytes contents and cellular ROS scavenging
capacity based on three wheat cultivars sharing contrasting water deprivation responses
was established; however other mechanisms related to plant drought adaptation
aside from above physiological traits are needed to be further addressed.
Conclusion
The drought-tolerant cultivar (i.e., Shimai 22) displayed improved
agronomic traits compared with the drought-sensitive cultivar (i.e., Shi 4185) under deficit irrigation
treatment. Shimai 22 plants showed higher osmolyte
contents (i.e., proline and soluble
sugar), activities of antioxidant enzymes (i.e.,
SOD and CAT), and lower MDA contents at late growth stages than Shi 4185 ones under
deficit irrigation condition. Improvement of osmolyte contents and
ROS-associated parameters positively regulates plant water deprivation
acclimation capacity in T. aestivum. The genes referred to as TaP5CS2 and TaP5CS5 in
P5CS family and the genes TaSOD3,
TaCAT2, and TaCAT5 in AE
families exhibited upregulated expression pattern upon water
deprivation, with much more transcripts of these genes detected in drought
tolerant cultivar. The proline accumulation was positively related to transcripts of TaP5CS2 and TaP5CS5 and AE activities to those of TaDOD2, TaCAT3, and TaPOD5. They are valuable molecular indices
in the guidance in breeding the drought-tolerant cultivars of wheat.
Acknowledgements
This work was financially supported by Chinese National
Key Research and Development Project on Science and Technology
(2017YFD0300902).
Author Contributions
RL, SZ and LH planned
the experiments, KX interpreted the results and made the write up, LG
statistically analyzed the data and made illustrations.
Conflicts of Interest
All other authors
declare no conflicts of interest
Data Availability
Data presented in this
study are available on fair request to the corresponding author.
Ethics Approval
Not applicable.
References
AghaKouchak A, D
Feldman, M Hoerling, T Huxman,
J Lund (2015). Water and climate: Recognize anthropogenic drought. Nature 524:409–411
Anjum SA, U Ashraf, M Tanveer, I Khan, S Hussain, B Shahzad, A Zohaib, F
Abbas, MF Saleem, I Ali, LC Wang (2017). Drought induced changes in growth,
osmolyte accumulation and antioxidant metabolism of three maize hybrids. Front Plant Sci 8; Article 69
Anjum SA, LC Wang, M Farooq, M Hussain,
LL Xue, CM Zou (2011). Brassinolide application
improves the drought tolerance in maize through modulation of enzymatic
antioxidants and leaf gas exchange. J Agron
Crop Sci 197:177–185
Ashraf M, MR Foolad (2007). Roles of glycine
betaine and proline in improving plant abiotic stress resistance. Environ
Exp Bot 59:206–216
Barnabas B, K Jäger, A Feh¨¦r (2008). The effect of drought and heat stress on reproductive processes
in cereals. Plant Cell Environ 31:11–38
Bates
LS, RP Waldren, ID Teare
(1973). Rapid determination of free proline for water-stress studies. Plant
Soil 39:205–207
Beauchamp C, I Fridovich (1971). Superoxide dismutase: Improved assays and
an assay applicable to acrylamide gels. Anal
Biochem 44:276–287
Conde A, P Silva, A Agasse,
C Conde, H Ger¨®s (2011). Mannitol transport and
mannitol dehydrogenase activities are coordinated in olea europaea under salt
and osmotic stresses. Plant Cell Physiol 52:1766–1775
Dai A (2013). Increasing
drought under global warming in observations and models. Nat Clim Change 3:52–58
Du X, X Zhao, X Liu, C Guo, W Lu, J Gu, K Xiao (2013). Overexpression
of TaSRK2C1, wheat SNF1-related
protein kinase gene, increases tolerance to dehydration, salt, and low
temperature in transgenic tobacco. Plant
Mol Biol Rep 31:810–821
Duan B, Y Yang, Y Lu, H Korpelainen, F Berninger, C Li (2007). Interactions between drought stress, ABA and genotypes in Picea asperata. J Exp Bot 58:3025–3036
Farooq M, A Wahid, N Kobayashi, D
Fujita, SMA Basra (2009). Plant drought stress: Effects,
mechanisms and management. Agron Sustain Dev 29:185–212
Farooq M, T Aziz, SMA Basra, MA Cheema,
H Rehman (2008). Chilling tolerance in hybrid maize
induced by seed priming with salicylic acid. J Agron
Crop Sci 194:161–168
Ghahramani A, AD
Moore (2016). Impact of climate changes on existing crop-livestock farming
systems. Agric Syst 146:142–155
Gill
SS, N Tuteja (2010).
Reactive oxygen species and antioxidant machinery in abiotic stress
tolerance in crop plants. Plant Physiol Biochem 48:909–930
Gubis J, R Va¨°kov¨˘, V Èerven¨˘, M Drag¨˛¨°ov¨˘, M Hudcovicov¨˘, H Lichtnerov¨˘
(2007). Transformed tobacco plants with increased
tolerance to drought. S Afr J Bot 73:505–511
Guo C, X Zhao, X Liu, L
Zhang, J Gu, X Li, W Lu, K Xiao (2013). Function
of wheat phosphate transporter gene TaPHT2;1 in Pi translocation and plant growth regulation under replete and
limited Pi supply conditions. Planta 237:1163–1178
Hayashi H, THH Chen, N Murata (1998).
Transformation with a gene for choline oxidase enhances the cold tolerance of Arabidopsis
during germination and early growth. Plant Cell Environ 21:232–239
Hu
DG, CH Sun, QJ Ma, CX You, L Cheng, YJ Hao (2016). MdMYB1 regulates anthocyanin
and malate accumulation by directly facilitating their transport into vacuoles
in apples. Plant Physiol
170:1315–1330
Huang X, W Wang, Q Zhang, J
Liu (2013). A basic helix-loop-helix transcription factor, Ptrb
HLH, of Poncirus trifoliata confers cold tolerance and
modulates peroxidase-mediated scavenging of hydrogen peroxide. Plant Physiol 162:1178–1194
Hussain M, S Farooq, W Hasan, S Ul-Allah, M
Tanveer, M Farooq, A Nawaz (2018). Drought stress in sunflower: Physiological
effects and its management through breeding and agronomic alternatives. Agric Water Manage 201:152–167
Hussain M, MA Malik, M
Farooq, MY Ashraf, MA Cheema (2008). Improving drought
tolerance by exogenous application of glycine betaine and salicylic acid in
sunflower. J Agron Crop Sci 194:193–199
Kanbar OZ (2013). Physiological traits
associated with yield improvement under rainfed condition in new wheat varieties.
Jord J Agric Sci 9:12–23
Kar M, D Mishra
(1976). Catalase, peroxidase, and polyphenoloxidase
activities during rice leaf senescence. Plant
Physiol 57:315–319
Karinne EDD, AC Lanna, FRM Abreu (2015). Molecular and biochemical
characterization of superoxide dismutase (SOD) in upland rice under drought. Aust J Crop Sci 9:744–753
Kubis J (2003). Polyamines and ˇ±scavenging systemˇ±:
Influence of
exogenous spermidine on catalase and guaiacol peroxidase activities, and free
polyamine level in barley leaves under water deficit. Acta Physiol Plantarum
25:337–343
Lesk C, P Rowhani, N Ramankutty (2016). Influence of extreme weather disasters
on global crop production. Nature 529:84–87
Li B (2016). Effects of irrigation on soil
and wheat yield under drought conditions in Sichuan. Meteor Environ Res 7:62–67
Li XM, ZH He, YG
Xiao (2015). QTL mapping for leaf senescence-related traits in common wheat
under limited and full irrigation. Euphytica 203:569–582
Li Y, W Ye, M Wang, X
Yan (2009). Climate change and drought: A risk assessment of crop-yield impacts.
Clim Res 39:31–46
Lobell DB, W Schlenker, J Costa-Roberts (2011). Climate
trends and global crop production since 1980. Science 333:616–620
Ma XL, YJ Wang, SL Xie, C Wang, W Wang (2007). Glycinebetaine application
ameliorates negative effects of drought stress in tobacco. Russ J
Plant Physiol 54:472–479
Praba ML, JE Cairns, RC Babu, HR Lafitte (2009). Identification of physiological traits underlying cultivar
differences in drought tolerance in rice and wheat. J Agron
Crop Sci 195:30–46
Ray DK, JS Gerber, GK
MacDonald, PC West (2015). Climate variation explains a third of global crop
yield variability. Nat Commun 6; Article 5989
Sheffield J (2014). A
drought monitoring and forecasting system for sub-Sahara African water
resources and food security. Bull Amer Meteorol Soc 95:861–882
Signorelli S, FJ Corpas,
O Borsani, JB Barroso, J Monza (2013). Water stress
induces a differential and spatially distributed nitro-oxidative stress
response in roots and leaves of Lotus japonicus. Plant Sci 201–202:137–146
Sun L, Y Liu, X Kong
(2012). ZmHSP16. 9, a cytosolic class I small heat shock protein in maize (Zea mays), confers heat tolerance in
transgenic tobacco. Plant Cell Rep
31:1473–1484
Sunkar R, A Kapoor, JK Zhu (2006). Post
transcriptional induction of two Cu/Zn superoxide dismutase genes in Arabidopsis is mediated by down
regulation of miR398 and important for oxidative stress tolerance. Plant
Cell 18:2051–2065
Tanveer M, B Shahzad, A Sharma, EA Khan (2019). 24-Epibrassinolide
application in plants: An implication for improving drought stress tolerance in
plants. Plant Physiol
Biochem 135:295–303
Umezawa T, M Fujita, Y Fujita (2006). Engineering drought
tolerance in plants: Discovering and tailoring genes to unlock the future. Curr Opin Biotchnol 17:113–122
Wang
YJ, YJ Hao, ZG Zhang, T Chen, JS Zhang, SY Chen (2005). Isolation of
trehalose-6-phosphate phosphatase gene from tobacco and its functional analysis
in yeast cells. J Plant Physiol
162:215–223
Wani SH, NB Singh, A Haribhushan,
JI Mir (2013). Compatible solute engineering in plants for abiotic stress
tolerance-role of glycine betaine. Curr Genom
14:157–165
Wu H, KG Hubbard, DA
Wilhite (2004). An agricultural drought risk-assessment model for corn and
soybeans. Intl J Clim
24:723–741
Yue Y, M Zhang, J Zhang
(2011). Arabidopsis LOS5/ABA3 overexpression in transgenic tobacco (Nicotiana
tabacum cv. Xanthi-nc) results in enhanced
drought tolerance. Plant Sci
181:405–411
Zhao M, SW
Running (2010). Drought-induced reduction in global terrestrial net primary
production from 2000 through 2009. Science
329:940–943