Abstract
Tropospheric ozone (O3) significantly reduces rice
yield. Koshihikari, a leading Japanese rice cultivar, has been
recognized as an O3 tolerant cultivar; however, the
mechanisms underlying its high O3 tolerance remain
unknown. Therefore, we aimed to elucidate the genetic and physiological
mechanisms underlying high O3 tolerance in Koshihikari.
A series of chamber experiments were conducted to examine
photosynthesis, growth, yield-related traits, and gene expression
profiles under chronic O3 conditions in Koshihikari and
Takanari, with contrasting O3 tolerance. Koshihikari
showed no reduction in unhulled-grain weights due to higher total dry
weight under chronic O3 conditions, whereas Takanari
showed significantly lower grain weights. The high O3tolerance in Koshihikari was attributed to its highly stable
photosynthetic performance and increased biomass allocation to its leaf
blades. RNA-seq and gene co-expression network analyses revealed that
the genes involved in photosynthesis and carbohydrate metabolism are
associated with contrasting O3 tolerance.OsRbcS3 , encoding the RuBisCO small subunit, showed contrasting
expression profiles between the two cultivars. In Koshihikari,OsRbcS3 was identified as a hub gene candidate in the gene
co-expression network, which was highly correlated with photosynthetic
performance. These results suggest that OsRbcS3 plays a key role
in the genetic mechanisms underlying the high O3tolerance of Koshihikari.
Introduction
Tropospheric ozone (O3) is a major air pollutant that
negatively impacts crop growth and yield (Fiscus, Booker & Burkey 2005;
Ainsworth, Yendrek, Sitch, Collins & Emberson 2012). While tropospheric
O3 concentrations ([O3]) exhibit
spatial and temporal variability, most agricultural regions are exposed
to elevated [O3] during the crop growing season,
leading to a reduction in global crop production (Ainsworth 2008, 2017).
In China, where the O3 is the major air pollutant, the
relative yield losses in wheat (Triticum aestivum L.), rice
(Oryza sativa L.), and maize (Zea mays L.) have been
estimated to reach 33%, 23%, and 9%, respectively, during last
decades (Feng et al. 2022). Tropospheric [O3]
has more than doubled since the Industrial Revolution (Monks et
al. 2015), and a further increase is predicted in Asia, the world’s
largest producer of rice (Ainsworth, 2017). On this background,
improving O3 tolerance in rice is a critical challenge
for a secure and sustainable food production (Frei 2015). In field
environments, chronic O3 stress (typically
<150 nmol mol-1) can mainly occur during the
crop growing season, which causes visible injury to rice in the short
term and yield reduction in the long term (Frei 2015). Therefore, it is
important to elucidate the mechanisms underlying tolerance to chronic
O3 stress to develop a practical breeding strategy for
rice.
Natural genetic variations in O3 tolerance have been
observed in model plants (Brosché et al. 2010) and several crop
plants such as maize (Choquette et al. 2019), rice (Sawada &
Kohno 2009), soybean (Betzelberger et al. 2010), and wheat (Zhuet al. 2011). In rice, certain cultivars showed no yield
reduction under chronic O3 conditions (Sawada & Kohno
2009). Genetic analyses such as quantitative trait loci analysis and
genome-wide association studies using mapping populations have
identified the chromosomal regions associated with the natural genetic
variations in leaf bronzing (Ueda et al. 2015) and grain yield
(Tsukahara, Sawada, Matsumura, Kohno & Tamaoki 2013) of rice under
elevated O3 conditions. Tsukahara et al. (2015)
indicated the involvement of the ABERRANT PANICLE ORGANIZATION 1in genotypic variations associated with O3-induced yield
reduction in rice. Importantly, the pyramiding of two quantitative trait
loci, OzT8 and OzT9 , resulted in improved
O3 tolerance in terms of biomass and grain yield in rice
(Wang et al. 2014). Although these results indicate the
importance of utilizing genetic variations in O3tolerance, the associated genetic and physiological factors have been
identified in only a small number of cultivars. For example,
Koshihikari, a leading Japanese
rice cultivar, has been recognized as an O3 tolerant
cultivar; however, the mechanisms underlying its high O3tolerance remain unknown (Cho et al. 2013a). An understanding of
the mechanisms underlying natural variations in such untapped genetic
resources is essential to breed rice for higher O3tolerance.
Under elevated O3 conditions, the downregulation of gas
diffusion and biochemical processes results in reduced photosynthetic
performance and biomass production in crops (Frei 2015; Ainsworth 2017).
O3 induces rapid stomatal closure within minutes to
hours and prevents additional O3 uptake by plants
(Kollist et al. 2007; Vahisalu et al. 2010).
O3-induced stomatal closure reduces the
CO2 assimilation rate (A ), because the
conductance of gas diffusion via the stomata (g s)
is a major limiting factor for leaf photosynthesis (Farquhar & Sharkey
1982; Ainsworth 2017). The absorbed O3 is immediately
decomposed into reactive oxygen species (ROS) such as hydrogen peroxide
(H2O2), superoxide anion
(O2-), hydroxyl radical
(· OH), and nitric oxide (NO) in the apoplast (Hoigne and Bader
1975). ROS damage membrane lipids, proteins, and nucleic acids and
induce programmed cell death, causing visible injury to the plant body
(Fuhrer and Booker 2003). In addition, ROS destroy
photosynthesis-related pigments and proteins, which lead to the
downregulation of photosynthesis. Thus, differences in the response of
gas diffusion and biochemical processes could be responsible for the
natural variations among rice cultivars in the O3tolerance of photosynthesis and biomass production (Wilkinson, Mills,
Illidge & Davies 2012).
Genome-wide transcriptional profiles revealed by microarray and RNA-seq
analyses help elucidate the genetic factors associated with plant
responses to the environment. Previous studies using transcriptome
analysis identified O3-responsive genes associated with
various biological processes in plants (Miyazaki et al. 2004; Liet al. 2006; Ludwikow & Sadowski 2008; Yendrek, Koester &
Ainsworth 2015). However, there is limited knowledge on gene expression
profiles associated with natural genetic variations in
O3 tolerance (Frei, Tanaka, Chen & Wissuwa 2010; Choet al. 2013b). Little is known about how the expression levels of
such genes are organized and how they function in coordination to
regulate O3 tolerance. In recent years, gene
co-expression network analysis has become available to understand the
key factors involved in the gene-expression regulation (Langfelder &
Horvath 2008). Constructing gene co-expression networks with
transcriptomic data obtained from O3 tolerant cultivars
would reveal the genetic basis of mechanisms of O3tolerance and the associated natural variations in rice.
The present study aimed to elucidate the genetic and physiological
mechanisms underlying high O3 tolerance in the rice
cultivar, Koshihikari. We focused on two Japanese rice cultivars,
Koshihikari and Takanari, which have been reported to have contrasting
O3 tolerances (Sawada & Kohno 2009; Sawada, Komatsu,
Nanjo, Khan & Kohno 2012; Cho et al. 2013b). We conducted
chamber experiments over two consecutive years to examine the effects of
chronic O3 conditions on photosynthesis, growth, and
yield-related traits in the two cultivars. In addition, we combined
RNA-seq and gene co-expression network analyses to elucidate gene
expression profiles and their regulatory networks associated with the
contrasting O3 tolerance between the two rice cultivars.
Materials and Methods
Plant materials and cultivation
The experiments were performed in 2019 and 2020 using two rice
cultivars: a leading Japanese rice cultivar of the subspeciesjaponica , Koshihikari (O3 tolerant), and a
high-yielding rice cultivar of the subspecies indica , Takanari
(O3 sensitive). Seeds of the two cultivars were sown in
a seedling box on May 9 in both 2019 and 2020 and grown in a sunlit
growth chamber (Koito Electric Industries, Shizuoka, Japan) at the
National Institute for Environmental Studies, Tsukuba-city, Ibaraki,
Japan (36°02’56.2 N, 140°07’02.8 E). In the growth chamber, air
temperature and relative humidity were maintained at 25℃ and 70%,
respectively. The seedlings were transplanted 11 d after sowing to
1/5000 Wagner pots, with one seedling per pot. Pots were filled with a
mixture of commercial nursery soil (Kumiai Ibaraki Baido [0.5 g N, 0.9
g P, 0.5 g K kg-1], Ibaraki Kumiai Baido Co. Ltd.,
Ibaraki, Japan) and vermiculite (Fukushima no vermiculite, Fukushima
Vermi Co. Ltd., Fukushima, Japan). Pots were watered and fertilized
using 0.4 g of granular chemical fertilizer (Kumiai Kasei 7 Go [8% N,
8% P, and 5% K] Katakura Chikkarin Co. Ltd., Tokyo, Japan).
For chronic O3 exposure, the seedlings at four days
after transplanting were transferred to a growth chamber, where
[O3] was maintained at 80/0 nmol
mol-1 for 7:00/19:00 and air temperature was
controlled at 28℃/22℃ for 7:00/19:00, with a relative humidity of 70%
under natural sunlight. The same was replicated in another chamber but
under control conditions where only filtered air was circulated with 6
nmol mol-1 O3 throughout the day on an
average. We cultivated 6 plants in 2019 and 16 plants in 2020 for
Koshihikari and 6 plants in 2019 and 8 plants in 2020 for Takanari per
treatment. Plant appearance was captured 53 days after the beginning of
the treatment (DAT) in 2019.
Analysis of growth and yield-related traits
The aboveground parts of the plants were harvested after reaching full
maturity in 2019 and 2020. Unhulled grain weight and total aboveground
dry weight were measured after drying at 70°C for 72 h. Harvest index
was calculated as the ratio of unhulled grain weight to total
aboveground dry weight. Using unhulled grains, the 1000-grain weight and
total number of grains were determined, and the number of grains per
panicle was calculated. In 2020, plant height and tiller number were
measured at 66–67 DAT and 89–90 DAT, respectively. The aboveground
parts of the plants were harvested at 90 DAT to measure the total dry
weight, leaf blade area and weight, and leaf-sheath weight of the whole
plant. The number of replications for each cultivar and treatment was
4–11.
Gas exchange and chlorophyll fluorescence measurements
Concurrent measurements of gas exchange and chlorophyll fluorescence
were conducted using a portable gas exchange system, LI-6800
(LI-COR , Lincoln, NE, USA). Measurements were made with rice
plants at four growth stages in 2019, 49–50, 68–69, 88–89, and
108–109 DAT, and at two growth stages in 2020, 66–67 and 89–90 DAT.
The CO2 assimilation rate (A ), stomatal
conductance (g s), and CO2concentration [CO2] at intercellular airspaces
(C i) per unit leaf area were measured in the
uppermost fully expanded leaf from 8:30 to 14:00 under a
[CO2] of 400 µmol m–1,
photosynthetic photon flux densivty (PPFD) of 1500 µmol
m–2 s–1, and air temperature of
30°C. In 2020, we estimated A for a single leaf blade
(A leaf) by multiplying the leaf blade area andA per unit leaf area. The quantum yield of PSⅡ
(Φ PSⅡ) was estimated using the following
equation, as described by Baker (2008):
Φ PSⅡ = (F m’ –F ’)/F m’
The electron transport rate for photosystem II (ETRⅡ) was estimated
using the following equation:
ETRⅡ = PPFD × 0.5 × 0.875 × Φ PSⅡ
In addition, A was measured under a series of
[CO2] at 100, 200, 300, 400, 500, 600, 750, 900,
1200, and 1500 µmol mol–1 forA -C i analysis at 54–56 DAT in 2019. The
maximum rate of ribulose-1,5-bisphosphate (RuBP) carboxylation
(V cmax) was estimated according to the
biochemical model of C3 photosynthesis (Farquhar,
Caemmerer and Berry, 1980) as described by Sakoda et al. (2016). The
number of replications for each cultivar and treatment was 4–6.
Analysis of the physiological and morphological traits
related to leaf photosynthesis
The Soil Plant Analysis Development (SPAD) value was measured on the top
1st, 2nd, 3rd, and
4th leaves of 4–5 plants at 49–50 DAT in 2019 using
an SPAD meter (SPAD-502, Konica Minolta , Tokyo, Japan). In
addition, the contents of nitrogen, ribulose-1,5-bisphosphate
carboxylase/oxygenase (RuBisCO), and chlorophyll a +b per
unit leaf area were measured on the same leaf where gas exchange was
measured in 2019. For nitrogen quantification, the sampled leaf tissue
(> 2 cm2) was dried at 70°C for 72 h,
weighed, and ground into a powder. The nitrogen content per unit leaf
area was determined as described by Kimura, Hashimoto-Sugimoto, Iba,
Terashima & Yamori (2020). For RuBisCO and chlorophyll quantification,
the sampled leaf tissue (> 2 cm2) was
homogenized using a pre-cold mortar and pestle in an extraction buffer
described by Sakoda et al. (2016). RuBisCO and chlorophylla +b contents were quantified as described by Sakoda et al.
(2016).
The RuBisCO activation state was measured on the same leaf used for gas
exchange measurements at 68–69, 88–89, and 108–109 DAT in 2019. After
gas exchange measurements, the leaf section clamped in the chamber
(< 2 cm2) was immediately sampled and frozen
in liquid nitrogen. The rate of the carboxylation reaction catalyzed by
RuBisCO before and after the activation of RuBisCO by
MgCl2 and NaHCO3 was measured by
coupling 3-phosphoglyceric acid formation with NADH oxidation, as
described by Qu et al. (2021).
Stomatal density, defined as the stomatal number per unit leaf area, was
measured on the same leaf as the gas exchange measurements and was
conducted in 2019, as described by Sakoda et al. (2019). A
replica of the abaxial side of the leaf blade was prepared using the
nail polish impression method (Ceulemans et al., 1995). The replica was
observed at 200× magnification using an optical microscope, and a
digital image was obtained (VHX-6000, Keyence, Osaka, Japan). The
stomatal number and guard cell length was manually counted using the
image analysis software ImageJ (Schneider, Rasband & Eliceiri 2012).
RNA-seq analysis
Total RNA was extracted from leaf tissues at 66–67 and 89–90 DAT in
2020 using the RNeasy Plant Mini Kit (QIAGEN, Hilden, Germany). The
poly-A mRNA was purified, and then, the library was constructed using
the Illumina Truseq Stranded mRNA Sample Preparation Kit (Illumina,
Inc., San Diego, USA). A total of 37 libraries were multiplexed and
sequenced using the Illumina HiSeq X platform (Table S5). These sequence
data have been submitted to the Sequence Read Archive (SRA) of the DNA
Data Bank of Japan (DDBJ) under accession number DRA014708. Raw sequence
data were processed for trimming and mapping onto the reference
sequence, as described by Hashida et al. (2022), with minor
modifications. The count data of each transcript were normalized by the
iDEGES normalization method of a Shiny-based application, TCC-GUI (Su,
Sun, Shimizu & Kadota 2019), with default settings.
We performed hierarchical clustering and principal component analysis
(PCA) with the normalized expression level of the top-1000 highly
expressed genes. The differentially expressed genes (DEGs) under chronic
O3 conditions were detected at 66–67 and 89–90 DAT for
each cultivar (Fig. S1) with
|log2(fold-change)| >1
and false discovery rate = 0.05, using the TCC-GUI. To visualize the
intersection of up- or downregulated DEGs among four groups of two
cultivars in two stages, we used the package UpSetR (Conway, Lex &
Gehlenborg 2017) in R software version 3. 6. 1 (R Foundation for
Statistical Computing, Vienna, Austria). In addition, gene ontology (GO)
and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses
were performed on the web server application g:Profiler (Raudvereet al. 2019), with a false discovery rate of 0.05.
Weighted gene co-expression network analysis (WGCNA)
To construct the gene co-expression network, we compared the
transcriptome data merging 66–67 and 89–90 DAT between the control and
chronic O3 conditions in Koshihikari and Takanari,
respectively (Fig. S1). The co-expression network of DEGs was
constructed using the R package WGCNA (Langfelder & Horvath 2008), with
the following parameters: softthreshold = 21, minModuleSize = 20,
mergeCutHeight = 0.1. WGCNA assigned the DEGs to 26 modules in
Koshihikari and 33 modules in Takanari. Thereafter, Pearson’s
correlation co-efficient (r ) was calculated between the module
eigengene (ME), the first component in PCA of the gene expression
profiles for each module, and the physiological traits that were
investigated concurrently with the sampling for RNA extraction.
The constructed networks were visualized using the open-source software
platform, Cytoscape ver. 3.8.2 (Shannon et al. 2003), with the
edge weight > 0.1 in Koshihikari and 0.2 in Takanari. To
explore the hub genes that play a central role in the gene co-expression
network regulation in each module, we used NetworkAnalyzer and MCDS in
Cytoscape. The hub genes in each module were detected as the genes that
showed the top-5% highest degree and betweenness centrality calculated
by NetworkAnalyzer and were assigned to the dominator or connector by
MCDS.
Statistical analysis
The significance of differences in the SPAD values of the leaves at each
position was compared between the plants under control and chronic
O3 conditions for each cultivar using one-way ANOVA atp <0.05. The significance of differences in all
physiological traits was also compared between the plants under control
and chronic O3 conditions of each cultivar using one-way
ANOVA at p <0.05. Pot was regarded as the unit for
ANOVA. Statistical analyses were conducted using R. The correlations
among all physiological traits were analyzed using a correlation
analysis tool in the Scikit-learn and Seaborn libraries of Python.
Results
Effects of chronic O3 conditions on
yield-related traits
We examined the effects of chronic O3 on yield-related
traits in Koshihikari and Takanari (Fig. 1). Chronic O3conditions significantly decreased the total dry weight, unhulled grain
weight, harvest index, 1000-grains weight, and total grain number in
Takanari during both experimental years, whereas its effect on panicle
number was inconsistent between the two years. In contrast, chronic
O3 conditions significantly increased the total dry
weight of Koshihikari in both years, whereas an increase in grain yield,
harvest index, and total grain number was observed in 2020 only. The
effects of chronic O3 on harvest index, 1000-grains
weight, and panicle number were inconsistent between the two years in
Koshihikari.
Effects of chronic O3 conditions on the
photosynthesis- and growth-related traits
The effects of chronic O3 exposure on gas exchange and
chlorophyll fluorescence parameters were evaluated at the four growth
stages in 2019 (Fig. 2). Chronic O3 conditions
significantly decreased A in both cultivars at all stages, except
for the 1st measurement in Koshihikari. In addition,
chronic O3 conditions decreasedg s and ETRⅡ in both cultivars throughout all the
stages, although the decrease was not significant at some stages. The
decrease in photosynthetic parameters by chronic O3conditions was greater in Takanari than in Koshihikari at later growth
stages. There was no significant effect of chronic O3conditions on C i in Takanari, whereasC i was significantly higher under chronic
O3 conditions than under the control conditions in
Koshihikari. In addition, A -C i analysis
showed lower A under chronic O3 conditions than
under control conditions at any C i value in
Koshihikari. A was lower under chronic O3conditions at C i below 600 µmol
mol-1, whereas it was similar between the control and
chronic O3 conditions at C i above
700 µmol mol-1 in Takanari. In both cultivars, chronic
O3 conditions significantly decreasedV cmax.
The appearance of the plants under control and chronic
O3 conditions in 2019 is shown in Fig. 2G and H. The
chronic O3 conditions seemed to have a positive effect
on growth and induced minor visible injury in Koshihikari. In contrast,
this condition induced severe growth inhibition and visible injury in
Takanari plants. The magnitude of visible injury was evaluated at
several leaf positions based on the SPAD values (Fig. 2I and J). The
SPAD values at the 2nd, 3rd, and
4th leaves were significantly lower under chronic
O3 conditions than under control conditions in both
cultivars. The decrease in SPAD value was similar among the leaves at
different positions in Koshihikari, whereas in Takanari, it was larger
in the older leaves than that in the younger leaves.
In 2019, the nitrogen content significantly decreased under chronic
O3 conditions at all stages in Koshihikari and at 88–89
and 108–109 DAT in Takanari (Fig. 3). In addition, chronic
O3 conditions significantly decreased the chlorophyll
and RuBisCO contents at most of the measurement stages but had no effect
on the RuBisCO activation state in either cultivar. Chronic
O3 conditions had no clear or consistent effect on
stomatal density and guard cell length throughout all measurement
stages.
In 2020, we evaluated A , a single leaf blade area, andA leaf at 66–67 and 89–90 DAT under control and
chronic O3 conditions (Fig. 4). Chronic
O3 conditions significantly decreased A at 89–90
DAT in Koshihikari and at both stages in Takanari. The single leaf-blade
area was significantly higher in Koshihikari under chronic
O3 conditions than under control conditions, whereas it
was lower at both stages in Takanari under chronic O3conditions. Chronic O3 conditions had no significant
effect on A leaf in Koshihikari at either stage,
whereas they significantly decreased A leaf in
Takanari at both stages. At 89–90 DAT, plant height, tiller number,
total dry weight, and whole leaf blade area and weight were
significantly lower in Takanari plants under chronic O3conditions than under control conditions. Plant height, whole leaf blade
area and weight, and the ratio of whole leaf blade weight to leaf sheath
weight (blade/sheath) were significantly higher in Koshihikari under
chronic O3 conditions than that under control
conditions.
Correlations among photosynthesis, growth, and
yield-related traits
We investigated correlations among photosynthesis, growth, and
yield-related traits in Koshihikari and Takanari under control and
chronic O3 conditions (Fig. 5). For most trait
combinations, Takanari showed higher r values than Koshihikari,
suggesting a greater sensitivity to chronic O3conditions in Takanari. Grain weight showed a significant correlation
with the single leaf-blade area, plant height, and C i in
Koshihikari, whereas it showed a significant correlation with all traits
except for A and ETRⅡ in Takanari. In addition, grain yield
showed the highest r value with a single leaf blade area
(r = 0.790) in Koshihikari and tiller number (r = 0.909)
in Takanari. A significant correlation was observed between grain yield
and single leaf-blade area (r = 0.590) in Takanari, whereas in
Koshihikari, no clear relationship between grain yield and tiller number
was noted.
Transcriptional profile and gene co-expression network
under chronic O3 conditions
To elucidate the gene co-expression network associated with
O3 response in Koshihikari and Takanari, we conducted
RNA-seq and network analyses in 2020. Hierarchical clustering analysis
and PCA showed the major effects of genotype and chronic
O3 conditions on the variations in the transcriptional
profiles (Figs. S2 and S3). In Koshihikari, chronic O3conditions upregulated 963 genes and downregulated 1542 genes at 66–67
DAT and upregulated 2653 genes and downregulated 2680 genes at 89–90
DAT (Fig. 6). In Takanari, chronic O3 conditions
upregulated 5231 genes and downregulated 3948 genes at 66–67 DAT and
upregulated 5548 genes and downregulated 4258 genes at 89–90 DAT,
indicating that chronic O3 conditions had a larger
impact on the transcriptional profiles in Takanari than in Koshihikari.
Under chronic O3 conditions, 431 upregulated and 321
downregulated DEGs were detected in both cultivars and growth stages,
which is important for the genotype-unspecific O3response of rice (Fig. 6, Table S6). In contrast, 126 upregulated and
525 downregulated DEGs were detected in Koshihikari but not in Takanari
at both growth stages, indicating the possible association of these DEGs
with a Koshihikari-specific O3 response.
We listed the up- and downregulated DEGs with the top-25 lowest adjustedp -values at each stage in Koshihikari (Table 1) and Takanari
(Table 2). Among the 50 genes, seven upregulated and four downregulated
DEGs were commonly detected at both stages in Koshihikari, whereas six
upregulated and eight downregulated DEGs were commonly detected in
Takanari. In addition, the upregulated gene, Os03g0103300 (hybrid
proline- or glycine-rich protein, control of low-temperature
germinability, and pre-harvest sprouting resistance), showed the lowestp values at both stages in Koshihikari.
The enriched GO terms and KEGG pathways under chronic O3conditions were investigated in Koshihikari and Takanari at the two
growth stages (Table S7). In the present study, we focused on the
enriched GO terms for biological processes and showed those with the
top-10 lowest p -value for each cultivar and stage (Fig. 6). In
Koshihikari, the top-10 enriched GO terms with upregulation were
inconsistent between the two stages. Among the top-10 enriched GO terms
with downregulation, “Energy reserve metabolic process” (GO:0006112)
was consistent between the two stages. In Takanari, eight out of the
top-10 upregulated GO terms, including transport and localization, and
eight out of the top-10 downregulated GO terms, including
photosynthesis, were commonly enriched at two stages. The GO terms
associated with photosynthesis (GO:0015979, GO:0019684, GO:0009765, and
GO:0009768) were highly enriched with upregulation in Koshihikari at 66
DAT and with downregulation in Takanari at both stages. In addition, the
GO terms associated with carbohydrate metabolic process (GO:0005975 and
GO:0044262) were highly enriched with downregulation in Koshihikari at
both stages, whereas they were not affected by chronic
O3 conditions in Takanari.
On comparing the transcriptome data merging 66–67 and 89–90 DAT
between the control and chronic O3 conditions in
Koshihikari and Takanari, respectively, we detected 5081 genes in
Koshihikari and 13352 genes in Takanari as DEGs induced by chronic
O3 conditions (Fig. S1). We performed WGCNA with these
DEGs in Koshihikari and Takanari, respectively. The DEGs were assigned
to 26 modules, including 27–663 genes, in Koshihikari (Fig. 7), and 33
modules, including 38–2827 genes, in Takanari (Fig. 8). We then
analyzed the r value between the ME of each module and the single
leaf-blade area in Koshihikari or tiller number in Takanari because
these traits showed the highest r value with unhulled-grain
weight (Fig. 5). The MEs of 17 modules showed a significant correlation
with the single leaf-blade area in Koshihikari and those of 33 modules
showed a significant correlation with the tiller number in Takanari.
Topological analysis of these modules detected 34 hub gene candidates in
Koshihikari and 83 hub gene candidates in Takanari (Table S9). The hub
gene candidates with the highest degree in each module were listed for
Koshihikari (Table 3) and Takanari (Table 4).
Among the constructed modules, the blue, brown, turquoise, and yellow
modules play an important role in the gene regulatory mechanisms
underlying O3 tolerance because these were the largest
of all modules and those MEs showed a significant correlation between
single leaf-blade area in Koshihikari and tiller number in Takanari. In
Koshihikari, the following genes showed the highest degree and
betweenness centrality in each of the four modules: Os02g0127900(“Conserved hypothetical protein”) in brown module,Os09g0572900 (Dynamin-related protein 1E, Negative regulation of
programmed cell death, Control of cytochrome c release) in blue module,Os04g0482300 (“Kelch related domain containing protein”) in
turquoise module, and Os12g0576600 (“Metallophosphoesterase
domain containing protein”) in yellow module (Fig. 7B-E, Table 3). In
addition, three hub gene candidates, Os06g0160700 (“Starch
synthase”) in the turquoise module and Os07g0106000(“Metallophosphoesterase domain containing protein”) andOs11g0658900 (“Similar to Lipase family protein”) in the brown
module, were included in the up- or down-regulated DEGs with the top-100
lowest adjusted p values. In Takanari, the turquoise module had
the largest size and the highest r value (0.940) between its ME
and tiller number of all modules. The following genes showed the highest
degree in each of the blue, brown, turquoise, and yellow modules:Os03g0803000 (synaptobrevin domain containing protein) in the
brown module, Os02g0819600 (serine/threonine protein
kinase-related domain containing protein) in the blue module,Os02g0156600 (hypothetical conserved gene) in the turquoise
module, and Os07g0685500 (alpha/beta hydrolase family protein) in
the yellow module. The three hub gene candidates, Os02g0156600and Os04g0623800 (similar to aminomethyltransferase,
mitochondrial precursor (EC 2.1.2.10) (glycine cleavage system T
protein; GCVT) in the turquoise module and Os12g0182300 (protein
kinase, core domain containing protein) in the blue module, were
included in the up- or down-regulated DEGs with the top-100 lowestp values.
The enriched GO terms and KEGG pathways in each module were also
investigated for both the cultivars (Table S10). Focusing on the GO
terms associated with carbohydrate metabolic process and photosynthesis,
which were differently enriched between the two cultivars, those terms
were highly enriched in the turquoise and green modules in Koshihikari.
In the turquoise module, two genes functioning in carbohydrate metabolic
processes, Os01g0897600 (glycoside hydrolase, family 1 protein)
and Os07g0662900 (similar to 4-alpha-glucanotransferase (EC
2.4.1.25)), were identified as hub genes (Fig. 7, Table S9). In the
green module of Koshihikari, three genes, Os12g0291100 (similar
to Petunia ribulose 1, 5-bisphosphate carboxylase small subunit mRNA
(clone pSSU 51), partial cds. (fragment)].), Os01g0662700(similar to naphthoate synthase (EC 4.1.3.36)), and Os03g0563300(magnesium-chelatase subunit ChlI, Mg-chelatase I subunit, chlorophyll
biosynthesis, chloroplast development), were identified as hub gene
candidates (Fig. 9). The expression levels of these three genes were
significantly upregulated at 66–67 DAT in Koshihikari but downregulated
at both stages in Takanari under chronic O3 conditions.
Discussion
Physiological mechanisms underlying the high
O3 tolerance in Koshihikari
Koshihikari and Takanari showed contrasting responses to chronic
O3 conditions in the leaf blade area at the single-leaf
and whole-plant levels (Fig. 4). The greater leaf area due to increased
biomass allocation to leaf blades might enhance light interception
efficiency at the whole-plant level, contributing to greater
CO2 assimilation and biomass production in Koshihikari
under chronic O3 conditions than under control
conditions (Fig. 1–5). In contrast, the decreased single leaf blade
area and tiller number resulted in a severe reduction in the whole leaf
blade area and biomass production in Takanari under chronic
O3 conditions (Fig. 1 and 4). It is commonly known that
chronic O3 conditions affect biomass allocation in
various plant species (Cooley & William 1987). Elevated
O3 conditions resulted in greater biomass production in
Japanese oak species owing to increased biomass allocation to leaves
(Kitao et al., 2015). Kobayashi et al. (1995) also reported higher
biomass allocation to leaf blades in Koshihikari but lower grain yields
under elevated O3 conditions. In Koshihikari, the
O3 effects on growth and yield varied under different
nitrogen fertilization regimes (Tatsumi, Abiko, Kinose, Inagaki & Izuta
2019). These results suggest that increased biomass allocation to leaf
blades can be an important factor for the high O3tolerance in Koshihikari, depending on environmental conditions such as
soil nutrient levels.
While chronic O3 conditions significantly reducedA in Koshihikari and Takanari, a greater reduction in Awas observed in Takanari at the later growth stage (Fig. 2), which might
contribute to a more severe reduction in biomass.
O3-induced A reduction is attributable to the
decreased activity of gas diffusion from the atmosphere to the
chloroplast stroma and biochemical reactions related to
CO2 fixation in chloroplasts (Ainsworth et al.2012). In the present study, chronic O3 conditions
decreased g s in both cultivars; this decrease was
much larger in Takanari than in Koshihikari. g scan be regulated by the size, depth, and opening of a single stoma and
its density (Franks & Beerling 2009). There was no consistent reduction
in stomatal density and size in either cultivar during the growth
period, indicating that the g s reduction was due
to O3-induced stomatal closure (Frei 2015). Chronic
O3 conditions also significantly decreased the
biochemical activity evaluated by ETRⅡ and V cmax,
which was accompanied by reduced nitrogen and RuBisCO contents in the
leaves of both cultivars (Fig. 2 and 3). In contrast, the single
leaf-blade area substantially increased, andA leaf was not affected in Koshihikari under
chronic O3 conditions (Fig. 4). These results suggest
that increased leaf blade area with a decrease in leaf thickness
resulted in lower N and RuBisCO contents per unit leaf area, which would
cause an apparent reduction in A in Koshihikari. Therefore, it
could be concluded that photosynthetic performance was maintained in
Koshihikari under chronic O3 conditions, contributing to
the superior O3 tolerance.
There was no clear difference in g s between
Koshihikari and Takanari under chronic O3 conditions
(Fig. 3 and 4), whereas visible injury was more severe in Takanari,
especially in older leaves (Fig. 2). This suggests superior ROS
detoxification ability after generation of ROS in the leaves of
Koshihikari compared to those of Takanari. Iseki, Homma, Endo &
Shiraiwa (2013) reported that the japonica rice cultivars such as
Koshihikari show greater tolerance to oxidative stress than theindica rice cultivars such as Takanari. Moreover, Sawada and
Kohno (2009) indicated that in rice, the japonica cultivars are
superior to indica cultivars in terms of O3tolerance. Possibly, the high ROS detoxification ability may enable to
maintain stomatal opening and biochemical activity for photosynthesis
and biomass production under chronic O3 conditions in
Koshihikari.
Genetic mechanisms underlying variations in
O3 tolerance between Koshihikari and Takanari
Many studies have been conducted to elucidate O3tolerance mechanisms using mutant populations of model plants,
deciphering the involvement of various genes (Kanna et al. 2003;
Tamaoki et al. 2003; Saji et al. 2008, 2017; Nagatoshiet al. 2016). In addition, previous studies using transcriptome
analysis have identified O3-responsive genes involved in
transcription, signal transduction, transport, metabolism, redox
control, senescence, and defense response (Ludwikow & Sadowski 2008).
We confirmed that the genes associated with these biological processes
were significantly affected by chronic O3 conditions in
Koshihikari and Takanari (Fig. 6, Tables S6 and S7). Using microarray
analysis, Frei et al. (2010) identified the gene encoding a putative
ascorbate oxidase, which is associated with natural genetic variations
in rice O3 tolerance. In the present study, RNA-seq
analysis detected 124 upregulated and 525 downregulated DEGs in
Koshihikari but not in Takanari under chronic O3 conditions, which
possibly contributed to the high O3 tolerance in
Koshihikari (Fig. 6). In addition, gene co-expression network analysis
revealed the gene modules whose expression profiles corresponded to
O3 response in each cultivar (Fig. 7 and 8). The hub
gene candidates detected in the modules could have key functions in the
chronic O3 responses of Koshihikari and Takanari (Tables
3, 4, S9). The hub gene candidates did not overlap between the two
cultivars, suggesting that the gene regulatory mechanisms underlying
O3 response can differ between rice cultivars.
In Koshihikari, Os03g0815800 (OsERF58 ; similar to
ethylene-responsive transcription factor 5 (ethylene-responsive element
binding factor 5; EREBP-5 ) was detected as the hub gene candidate
in the brown module, whose ME showed the highest r value with a
single leaf-blade area (Fig. 7B, Table S9). Using genome-wide
association studies, Ueda et al. (2015) reported that
polymorphisms in EREBP were associated with natural genetic
variations in O3 tolerance in rice. It is possible thatOsERF58 plays an important role in the gene regulatory mechanisms
underlying the O3 response of the leaf blade area in
Koshihikari.
In Koshihikari, two hub gene candidates, Os07g0106000 in the
brown module and Os12g0576600 in the yellow module, encoded
metallophosphoesterase (MPE) domain-containing proteins (Tables 3 and
S9). The MPE domain is included in diverse enzymes such as mammalian
phosphoprotein phosphatases, acid sphingomyelinases, and purple acid
phosphatases (Matange, Podobnik & Visweswariah 2015). In Arabidopsis,
an activation-tagging mutant of purple acid phosphatase increased foliar
ascorbate content and improved acute O3 tolerance
(Zhang, Gruszewski, Chevone & Nessler 2008). In contrast,Os12g0576600 , annotated as purple acid phosphatase, andOs07g0106000 were significantly downregulated by chronic
O3 conditions in Koshihikari. It is suggested that the
change in the expression level of these genes might be associated with
the O3 response of the leaf blade area in Koshihikari;
however, these genes did not directly contribute to ROS detoxification.
The GO terms associated with carbohydrate metabolism were highly
enriched and downregulated under chronic O3 conditions
in Koshihikari at both growth stages but not in Takanari (Fig. 6, S7).
The relationship between carbohydrate metabolism and grain quality under
chronic O3 conditions has been previously discussed in
rice (Frei 2015; Sawada et al. 2016). However, carbohydrate
metabolism has not been recognized as an important factor underlying the
O3 response in terms of growth, yield, and the
associated genetic variation in crops. Genes associated with
carbohydrate metabolism were highly enriched in the turquoise module of
Koshihikari; three genes, Os01g0897600 , Os06g0160700 , andOs07g0662900 , were identified as hub genes (Table S9).
Importantly, Os06g0160700 , soluble starch synthase I, was
included among the DEGs with the top-100 lowest adjusted p -values
at both growth stages in Koshihikari. It is suggested that the
co-expression network of genes involved in carbohydrate metabolism is
associated with superior O3 tolerance in Koshihikari
compared to that in Takanari.
Typically, the genes associated with photosynthesis are downregulated
under chronic O3 conditions (Ludwikow & Sadowski 2008),
as observed in Takanari (Fig. 6). In contrast, these genes were
significantly upregulated or unaffected in Koshihikari under chronic
O3 conditions (Fig. 6), consistent with the lack of
decrease in A leaf. This result is supported by
Sawada et al. (2012), who reported the upregulation of
photosynthesis-related proteins in Koshihikari under chronic
O3 conditions. The photosynthesis-related genes were
highly enriched in the green module in Koshihikari and the
turquoise-module in Takanari, whose ME was significantly correlated withA leaf (r = 0.58, Koshihikari and 0.85,
Takanari). Under chronic O3 conditions, the hub gene
candidates Os12g0291100 , Os01g0662700 , andOs03g0563300 in the green module of Koshihikari were
significantly upregulated or unaffected in Koshihikari, whereas their
expression levels were downregulated at both stages in Takanari. This
contrasting response is associated with the genotypic variation in the
O3 response in terms of photosynthesis.
Among all the analyzed genes, the expression level ofOs12g0291100 (OsRbcS3 ), which encodes the RuBisCO small
subunit (RbcS), was relatively high in both cultivars. The five genes
(OsRbcS1-5 ) were identified to encode the RbcS in rice (Suzuki,
Miyamoto, Yoshizawa, Mae & Makino 2009). OsRbcS3 is a
representative RbcS gene in rice (Suzuki et al. 2009). In
addition, the expression level of OsRbcS3 in photosynthetic
tissues is typically high and has a significant effect on RuBisCO
content and photosynthetic performance in rice (Morita, Hatanaka, Misoo
& Fukayama 2014; Kanno, Suzuki & Makino 2017). Downregulation ofOsRbcS s has been reported in rice exposed to acute
O3 conditions (Cho et al. 2008). In the present
study, the expression level of OsRbcS3 was nearly 3-fold higher
under chronic O3 conditions than under control
conditions in Koshihikari at 66–67 DAT, whereas it decreased by up to
57.7% in Takanari (Fig. 9). It suggests that OsRbcS3 plays a
central role in the regulatory network of photosynthesis-related genes
under chronic O3 conditions, contributing to superior
O3 tolerance in Koshihikari compared to that in
Takanari.
In conclusion, Koshihikari showed no reduction in growth- and
yield-related traits under chronic O3 conditions,
whereas Takanari showed a substantial reduction. The greater
O3 tolerance in Koshihikari than in Takanari could be
attributed to (1) increased leaf blade area due to increased biomass
allocation to leaf blades and (2) higher stability of photosynthetic
performance in Koshihikari. RNA-seq and gene co-expression network
analyses revealed significant differences in the gene expression
profiles and regulatory networks between Koshihikari and Takanari. The
different expression profiles of genes involved in carbohydrate
metabolism and photosynthesis could be associated with the genetic
variation in O3 tolerance between the two rice
cultivars. OsRbcS3 , which encodes the RuBisCO small subunit,
showed contrasting expression patterns between the two cultivars under
chronic O3 conditions. In addition, this gene was
identified as a hub gene candidate in the gene co-expression network,
which was highly correlated with photosynthetic performance, suggesting
that OsRbcS3 plays a key role in the genetic mechanisms
underlying the O3-response in Koshihikari. The genes
which were suggested to contribute to the high O3tolerance of Koshihikari in the present study may be a promising target
in rice breeding towards improved O3 tolerance.