Open Access

A rice calcium-dependent protein kinase OsCPK9 positively regulates drought stress tolerance and spikelet fertility

  • Shuya Wei1,
  • Wei Hu1, 2,
  • Xiaomin Deng1, 2,
  • Yingying Zhang1,
  • Xiaodong Liu1,
  • Xudong Zhao1,
  • Qingchen Luo1,
  • Zhengyi Jin1,
  • Yin Li1,
  • Shiyi Zhou1,
  • Tao Sun1,
  • Lianzhe Wang1,
  • Guangxiao Yang1Email author and
  • Guangyuan He1Email author
Contributed equally
BMC Plant Biology201414:133

https://doi.org/10.1186/1471-2229-14-133

Received: 10 December 2013

Accepted: 12 May 2014

Published: 17 May 2014

Abstract

Background

In plants, calcium-dependent protein kinases (CDPKs) are involved in tolerance to abiotic stresses and in plant seed development. However, the functions of only a few rice CDPKs have been clarified. At present, it is unclear whether CDPKs also play a role in regulating spikelet fertility.

Results

We cloned and characterized the rice CDPK gene, OsCPK9. OsCPK9 transcription was induced by abscisic acid (ABA), PEG6000, and NaCl treatments. The results of OsCPK9 overexpression (OsCPK9-OX) and OsCPK9 RNA interference (OsCPK9-RNAi) analyses revealed that OsCPK9 plays a positive role in drought stress tolerance and spikelet fertility. Physiological analyses revealed that OsCPK9 improves drought stress tolerance by enhancing stomatal closure and by improving the osmotic adjustment ability of the plant. It also improves pollen viability, thereby increasing spikelet fertility. In OsCPK9-OX plants, shoot and root elongation showed enhanced sensitivity to ABA, compared with that of wild-type. Overexpression and RNA interference of OsCPK9 affected the transcript levels of ABA- and stress-responsive genes.

Conclusions

Our results demonstrated that OsCPK9 is a positive regulator of abiotic stress tolerance, spikelet fertility, and ABA sensitivity.

Keywords

Abscisic acid (ABA) signaling Abiotic stresses Calcium-dependent protein kinase (CDPK) Drought stress tolerance Rice Spikelet fertility

Background

Calcium, as a second messenger, plays important roles in a variety of signal transduction pathways. Several classes of calcium-sensing proteins, including calcium-dependent protein kinases (CDPKs), calcineurin B-like (CBL) proteins, and calmodulin (CaM), have been characterized in plants [1]. CDPKs activated by Ca2+ and modulate downstream targets of calcium signaling in plants [24]. CDPKs participate in stress signaling transduction pathways through either stimulus-dependent activation or directed functional target protein phosphorylation [2, 3, 57].

Genome-wide analyses have identified 34 CDPK genes in Arabidopsis [8, 9]. Some Arabidopsis CDPKs have been reported to be involved in abiotic stress responses and abscisic acid (ABA) signaling. Loss-of-function mutants of CPK4 and CPK11 showed decreased tolerance to salt and drought stresses, and ABA-insensitive phenotypes for seed germination, seedling growth, and stomatal movement. CPK4 and CPK11 phosphorylate two ABA-responsive transcription factors, ABF1 and ABF4 to mediate the ABA signaling pathway [10]. CPK6-overexpressing plants showed enhanced tolerance to salt and drought stresses and cpk3 mutants exhibited a salt-sensitive phenotype [11, 12]. CPK3 and CPK6 also function in controlling of ABA-regulated stomatal signaling and guard cell ion channels. ABA-induced stomatal closure was partially impaired in a cpk3/cpk6 mutant [13]. CPK6 activates the slow anion channel (SLAC1) and CPK3 activates SLAC1 as well as its guard cell homolog SLAH3. These activations are calcium-dependent and are controlled by the ABA signaling component phosphatase ABI1 [14, 15]. CPK32 phosphorylates the ABA-responsive transcription factor ABF4 in vitro, and CPK32-overexpressing plants displayed increased sensitivity to ABA during seeds germination as a result of up-regulated expressions of genes controlled by ABF4 [16]. CPK10-overexpression and T-DNA insertion mutant analyses have shown that CPK10 is involved in drought stress tolerance. Moreover, CPK10, through its interaction with heat shock protein 1 (HSP1), plays a role in ABA- and Ca2+-mediated regulation of stomatal movement [17]. Together, these studies have shown that Arabidopsis CPK family members can positively regulate abiotic stress tolerance and ABA signaling.

However, Arabidopsis CPK23-overexpressing lines showed a drought- and salt-sensitive phenotype and increased stomatal aperture. Accordingly, cpk23 mutants showed improved tolerance to drought and salt stresses and reduced stomatal aperture [18]. Arabidopsis seedlings with a loss-of-function of CPK21 also showed increased tolerance to hyperosmotic stress [19]. CPK21 and CPK23 were shown to control the activation state of SLAC1 in Ca2+-independent manner [20]. Arabidopsis CPK12-RNAi lines were hypersensitive to ABA during seed germination and root elongation [21]. The results of these studies suggested that some Arabidopsis CPKs function as negative regulators of abiotic stress tolerance and ABA signaling. Therefore, the experimental evidences indicate that CDPK-mediated abiotic stress and ABA responses are complex in Arabidopsis.

Although 31 CDPK genes have been identified in the rice genome [22, 23], the functions of only a few have been explored so far. For example, OsCDPK7-overexpressing plants exhibited increased resistance to cold, drought, and salinity stresses [24]. OsCPK21 was shown to be involved in increasing ABA sensitivity and conferring salt stress tolerance. Compared with wild-type, OsCPK21-overexpressing plants showed a higher survival rate under salt stress and a stronger inhibition of seedling growth by ABA [25]. OsCPK12 overexpression and OsCPK12 RNA interference analyses revealed that OsCPK12 positively regulates rice tolerance to salt stress by controlling the expression of OsAPx2, OsAPx8 and OsrbohI. Moreover, OsCPK12-overexpressing lines showed increased sensitivity to ABA and enhanced susceptibility to blast fungus, probably because of decreased production of reactive oxygen species and/or the involvement of OsCPK12 in the ABA signaling pathway [26].

The calcium-dependent seed-specific protein kinase (SPK) is a key regulator of seed development. SPK is involved in regulating the metabolic pathway responsible for the conversion of sucrose into storage starch in immature seeds [27]. OsCDPK1 negatively regulates the expressions of enzymes required for GA biosynthesis and seed size, but positively regulates drought stress tolerance through the14-3-3 protein [28]. However, it is unclear whether CDPKs play a role in regulating spikelet fertility. Spikelet fertility that is affected by anther dehiscence, pollen production and the number of germinating pollen grains on the stigma is an important component of yield [2931]. In the present research, OsCPK9 overexpression (OsCPK9-OX) and interference (OsCPK9-RNAi) analyses indicate that OsCPK9 positively regulates abiotic stress tolerance, spikelet fertility, and ABA sensitivity. These findings contribute to our understanding of CDPK-mediated abiotic stress responses and ABA signaling, and will be useful for improving the stress tolerance and quality of rice.

Results

Expression patterns of OsCPK9in rice

To investigate the OsCPK9 expression patterns in different rice organs, we conducted quantitative reverse transcription-polymerase chain reaction (qRT-PCR) analyses using mRNA isolated from various organs as the templates. OsCPK9 transcripts present in all organs tested including the root, basal part, stem, leaf blade, anther, and spikelet, with higher transcript levels in the leaf blade and stem than in other organs (Figure 1A). To detect the transcriptional response of OsCPK9 to abiotic stresses and ABA, various treatments were applied to rice plants. After ABA treatment, the expression of OsCPK9 increased at 1 h and reached the highest level at 3 h followed by a decrease (Figure 1B). OsCPK9 transcription was also induced to the highest level at 5 h and 2 h after NaCl and PEG6000 treatments respectively (Figure 1C; 1D). Therefore, OsCPK9 transcription was up-regulated by ABA, NaCl, and PEG6000 treatments in comparison to control, implying its function in the responses to abiotic stresses and ABA.
Figure 1

qRT-PCR analysis of OsCPK9 expression in different organs (A) and in rice leaves after 100 μM ABA (B), 200 mM NaCl (C), or 20% PEG6000 (D) treatments. R: root; BP: basal part; S: stem; LB: leaf blade; A: anther; SP: spikelet. The mRNA fold difference is relative to that of root samples for (A) or distilled water-treated samples at 0 h for (B, C and D). Data are means ± SE of three independent experiments.

Generation of OsCPK9transgenic rice lines

To further study the function of OsCPK9 in planta, we generated OsCPK9-OX (OE) and OsCPK9-RNAi (Ri) transgenic lines. The RT-PCR results showed that the transcript levels of OsCPK9 were markedly higher in OsCPK9-OX lines than in wild type (WT) with the highest transcriptional levels of OsCPK9 in OE28 (Additional file 1: Figure S1). In contrast, the transcript levels of OsCPK9 were reduced in OsCPK9-RNAi lines, with the lowest transcript levels of OsCPK9 in Ri2 (Additional file 1: Figure S1). We detected the intron sequence introduced into the construct, confirming the presence of the construct in OsCPK9-RNAi lines (Additional file 1: Figure S1). These results confirmed that OsCPK9-OX and OsCPK9-RNAi transgenic lines were successfully produced.

OsCPK9 increases plants’ tolerance to drought, osmotic, and dehydration stresses

To investigate the drought stress tolerance of OsCPK9-OX and OsCPK9-RNAi lines, 3-week-old rice seedlings were subjected to a drought treatment. After 20 or 27 days of drought, OsCPK9-OX lines grew well. In contrast, the growth of the OsCPK9-RNAi lines was inhibited compared with that of control (Figure 2A). After 27 days of drought and 3 days of recovery, the survival rates of OsCPK9-OX lines OE28 and OE16 (67% and 54% respectively) were higher than that of WT (25%), while OsCPK9-RNAi lines Ri16 and Ri2 showed very low survival rates (5% and 4% respectively) (Figure 2A; 2B). Although there were no significant differences in chlorophyll and malondialdehyde (MDA) contents between controls and transgenic lines under normal growth conditions, clear differences were observed between control and transgenic lines after the drought treatment. The chlorophyll content was higher in OsCPK9-OX lines, but lower in OsCPK9-RNAi lines compared with that in the control after drought treatment (Figure 2B). The MDA content was lower in OsCPK9-OX lines, but higher in OsCPK9-RNAi lines, compared with that in the control after drought treatment (Figure 2B). These results indicated that OsCPK9 plays a positive role in drought stress tolerance.
Figure 2

Drought stress tolerance of OsCPK9 -OX and OsCPK9 -RNAi transgenic lines. (A) Photographs of transgenic lines and controls after drought treatment. Three-week-old rice seedlings were deprived of water for 20 or 27 days, followed by 3 days of recovery. Photos of transgenic lines and controls were taken at these time points. (B) Survival rates, chlorophyll, and MDA content of transgenic lines and controls with or without drought treatment. Three-week-old rice seedlings were deprived of water for 27 days, followed by 3 days recovery, then survival rates were calculated. Three-week-old rice seedlings were deprived of water for 15 days and then chlorophyll, and MDA content were measured in leaf samples. Data are means ± SE of four independent experiments. Asterisks indicate significant difference between WT and transgenic lines (*p <0.05; **p <0.01).

To determine the osmotic stress tolerance of OsCPK9-OX and OsCPK9-RNAi lines, 2-week-old rice seedlings were treated with 20% PEG6000 for 8 h and followed with 1, 2, or 7 days of recovery. At different treatment stages, the OsCPK9-OX lines showed better growth than that of controls, and the OsCPK9-RNAi lines showed worse growth (Additional file 1: Figure S2A). After the 8 h osmotic treatment, OsCPK9-OX plants showed a lower MDA content and higher soluble sugars and proline contents, while OsCPK9-RNAi plants showed a higher MDA content and lower soluble sugars and proline contents, compared with those of wild type (WT) and the vector control (VC) (Additional file 1: Figure S2B). After 7 days of recovery, compared with controls, OsCPK9-OX plants had higher biomass, reflected by longer roots and shoots, greater fresh weight, less wilted leaves, and more green leaves. In contrast, the biomass of OsCPK9-RNAi plants was lower than that of control plants (Additional file 1: Table S3). These analyses of physiological indices confirmed that osmotic stress tolerance is increased in OsCPK9-OX lines and decreased in OsCPK9-RNAi lines.

To analyze the dehydration stress tolerance of OsCPK9-OX and OsCPK9-RNAi lines, 2-week-old rice seedlings were exposed to air. OsCPK9-OX lines tolerated a 5 h dehydration treatment (Additional file 1: Figure S3). After a 10 days recovery, OsCPK9-OX lines grew more robustly than did WT and VC, as reflected by their longer roots and shoots and greater fresh weight (Additional file 1: Figure S3; Additional file 1: Table S4). These results indicated that OsCPK9-OX plants have increased tolerance to dehydration stress.

OsCPK9 functions in water retention by increasing proline and soluble sugars contents and improving stomatal closure under drought stress

Plants with high capacity for water retention can better survive drought or dehydration stress. During 0 to 25 hours of a dehydration treatment, OsCPK9-OX lines retained a high relative water content (RWC) and showed a low water loss rate (WLR), while OsCPK9-RNAi lines had lower RWC and higher WLR compared with those of WT and VC (Figure 3A). These results indicated that OsCPK9 plays a positive role in improving the ability of the plant to retain water under dehydration conditions.
Figure 3

WLR, RWC, soluble sugars, proline, and stomatal status of OsCPK9 -OX and OsCPK9 -RNAi transgenic lines. (A) WLR, RWC, soluble sugars, and proline contents of OsCPK9-OX and OsCPK9-RNAi transgenic lines. (B) Scanning electron microscope images of stomatal status; open, closed, partially open. (C) Proportions of open, closed, and partially open stomata. Leaves of 3-week-old rice seedlings were collected to determine the WLR and RWC of control plants and transgenic lines. Three-week-old rice seedlings were deprived of water for 15 days and then soluble sugars, proline and stomatal status were examined with leaf samples. Data are means ± SE of four independent experiments for (A) and three independent experiments for (C). Asterisks indicate significant difference between the WT and transgenic lines (*p <0.05; **p <0.01).

Osmotic adjustment and stomatal closure are the main physiological mechanisms to reduce water loss under dehydration or drought conditions in plants. To elucidate the physiological mechanism by which OsCPK9 confers tolerance to drought and dehydration stresses and improves the ability of plant to retain water, we quantified osmolytes (proline and soluble sugars) in OsCPK9-OX and OsCPK9-RNAi lines. Under normal growth conditions, there were no significant differences between controls and transgenic lines in terms of their proline and soluble sugars contents (Figure 3A). Under drought conditions, OsCPK9-OX lines accumulated larger amounts of proline and soluble sugars, but OsCPK9-RNAi lines accumulated smaller amounts of proline and soluble sugars, compared with those in controls (Figure 3A). Additionally, the status of stomata was observed and counted in controls and transgenic lines. Under normal growth conditions, there were no significant differences in stomatal status between controls and transgenic lines. After the drought treatment, 35% and 37% of stomata were completely closed in WT and VC plants, respectively, while greater proportions of stomata were closed in OsCPK9-OX lines (52% in OE28 and 48% in OE16). Accordingly, there were smaller proportions of completely opened stomata in OsCPK9-OX lines, but larger proportions in OsCPK9-RNAi lines (Figure 3B; 3C; Additional file 1: Table S5). There was a slightly lower proportion of partially opened stomata in OsCPK9-RNAi lines than in controls. These results indicated that OsCPK9 affects osmotic balance and stomatal movement under drought conditions.

OsCPK9 improves pollen maturation and spikelet fertility under normal conditions

We harvested and analyzed spikelets to evaluate the grain development in the transgenic lines under normal conditions. Spikelet weight is 1.29 g and spikelet fertility is 81.88% in WT rice plants. OsCPK9-OX lines had greater spikelet weight (OE16 2.07 g; OE28 1.90 g) and spikelet fertility (OE16 88.45%; OE28 88.19%), compared with those of controls. In contrast, the spikelets of OsCPK9-RNAi lines were less fertile (Ri16 71.24%; Ri2 55.36%) and had a smaller spikelet weight (Ri16 0.98 g; Ri2 0.87 g) than those of WT and VC lines. There was no obvious difference in grain length and width between WT and transgenic lines (Figure 4A; Figure 4B). Therefore, spikelet weight and spikelet fertility of rice were correlated with the expression of OsCPK9. Because the number of mature pollen is an important impact factor of spikelet fertility, we further investigate pollen status of control plants and transgenic lines using I2-KI staining. The results indicated that OsCPK9-OX lines had a higher mature pollen staining ratio, while OsCPK9-RNAi lines had a lower ratio than those of WT and VC (Figure 4C). Mature pollen staining ratio reflects pollen viability. The mature pollen staining ratio correlated with the expression of OsCPK9 suggested that OsCPK9 functions in increasing pollen viability. Collectively, these results indicated that OsCPK9 enhances spikelet fertility by regulating pollen maturation.
Figure 4

Spikelet fertility and mature pollen viability of transgenic lines and WT under normal conditions. Photographs of mature spikelets harvested from control plants and transgenic lines were taken (A). Grain length, grain width, spikelet weight, and spikelet fertility of control plants and transgenic lines (B). Mature pollen grains from control plants and transgenic lines were stained by I2-KI (C). Data are means ± SE calculated from four independent experiments. Asterisks indicate significant difference between WT and transgenic lines (*p <0.05; **p <0.01).

Responses of OsCPK9-OX and OsCPK9-RNAi lines to ABA

To explore whether OsCPK9 is involved in the ABA signaling response, OsCPK9-OX and OsCPK9-RNAi lines were treated with exogenous ABA. Under 1 μM ABA treatment, OsCPK9-OX lines showed shorter roots and shoots and lower root and shoot dry weights than those of WT and VC (Figure 5; Additional file 1: Table S6). Although seedlings growth of control and transgenic plants was inhibited by a 3 μM ABA treatment, it was more strongly inhibited in OsCPK9-OX plants than in WT and VC plants (Figure 5A). The 3 μM ABA treatment had a stronger negative effect on root length, shoot length, and root and shoot dry weights of OsCPK9-OX plants than on those parameters in WT and VC plants (Figure 5B; Additional file 1: Table S7). Conversely, ABA did not significantly affect seedling growth and root elongation of OsCPK9-RNAi lines, compared with that of control plants after ABA treatment. These results confirmed that OsCPK9-OX lines are more sensitive to ABA than WT and VC.
Figure 5

ABA sensitivity of OsCPK9 -OX and OsCPK9 -RNAi rice lines. Three-day-old rice seedlings were treated with 1 μM or 3 μM ABA for 14 days and then photographed (A). Length and dry weight of roots and shoots of rice seedlings harvested after the 14-day ABA treatment (B). Data are means ± SE calculated from four independent experiments. Asterisks indicate significant difference between the WT and transgenic lines (*p <0.05; **p <0.01).

OsCPK9 regulates ABA- and stress-responsive genes under osmotic stress and ABA treatment

To gain a deeper understanding of OsCPK9 function in osmotic stress tolerance and the ABA response, we analyzed the transcript levels of some selected ABA- and stress-responsive genes by qRT-PCR analysis in control and transgenic lines under normal conditions, osmotic stress, and ABA treatment (Figure 6). The following genes were selected for analysis: Rab21, which encodes a basic glycine-rich protein [32]; OsLEA3, encoding a late embryogenesis abundant protein [33]; OsP5CS, encoding Δ1-pyrroline-5-carboxylate synthetase, which is involved in proline biosynthesis [34]; OsNAC6, OsNAC9 and OsNAC45, which encode NAC-type transcription factors [3538]; OsRSUS, encoding sucrose synthase [27] and Osbzip23, Osbzip66, and Osbzip72, which encode ABF-type transcription factors [3941]. Under normal conditions, the transcript levels of OsNAC9 were higher in OsCPK9-OX lines and lower in OsCPK9-RNAi lines, compared with that in WT. The transcript levels of OsLEA3, Rab21, OsRSUS, and OsP5CS were higher in OsCPK9-OX lines than in WT and VC. After ABA treatment, the transcript levels of Rab21, Osbzip66, OsNAC45, and OsRSUS were higher in OsCPK9-OX but lower in OsCPK9-RNAi lines, compared with their respective levels in WT and VC. The transcript levels of Osbzip23, OsLEA3, OsP5CS, OsNAC9 and Osbzip72 were higher in OsCPK9-OX than in WT and VC. Under PEG6000 treatment, the transcript levels of all of the selected genes except for OsNAC6 and OsNAC45 were higher in OsCPK9-OX plants than in the control. The transcript levels of the tested genes were confirmed by RT-PCR, and the results were generally consistent with those detected by qRT-PCR analysis (Additional file 1: Figure S4). These results suggested that OsCPK9 expression affects the transcription of ABA- and stress-associated genes.
Figure 6

Expression analysis of selected ABA- and stress-responsive genes in OsCPK9 -OX, OsCPK9- RNAi, and control lines under no stress, ABA, or PEG6000 treatments. Three-day-old rice seedlings were treated with 1 μM ABA for 14 days. Two-week-old rice seedlings were treated without (normal conditions) or with 20% PEG6000 for 8 h. Leaves were collected to detect transcript levels of those ABA- and stress-responsive genes. The mRNA fold difference is relative to that of WT samples under normal conditions. Data are means ± SE of three independent experiments.

Discussion

OsCPK9 plays a positive role in drought, osmotic, and dehydration stress responses

OsCPK9 belongs to the group III-b CDPK family [22]. The OsCPK9 gene contains five exons and four introns. The OsCPK9 protein is composed of 574 amino acid residues with a predicted relative molecular mass of 63.9 kDa. It has a protein kinase domain, a calmodulin-like domain with four conserved EF-hand motifs, an autoinhibitory junction domain, and an N-terminal variable region [22]. It also has potential N-terminal myristoylation and palmitoylation sites [22]. Previously, OsCPK9 expression in response to abiotic stresses was examined using a cDNA microarray. The results showed that OsCPK9 was induced by salt and desiccation treatments [23]. In this study, OsCPK9 transcription was induced by a PEG6000 treatment, implying that OsCPK9 also functions in the osmotic stress response (Figure 1). To assess the role of OsCPK9 under drought conditions, we engineered rice lines in which OsCPK9 was overexpressed or knocked down. Our results suggested that OsCPK9 is a positive regulator of the responses to drought, osmotic, and dehydration stresses (Figure 2; Additional file 1: Figure S2 and S3). These results are consistent with those of previous studies on some other CDPK genes that positively regulate drought stress tolerance [18, 24, 28].

OsCPK9 confers tolerance to drought stress by improving osmotic adjustment and stomatal movement

The ability to retain water is crucial for plants to combat drought. Our results show that OsCPK9 is involved in maintaining the ability of plants to retain water, and hence, it confers drought stress tolerance (Figure 3A). We further explored the physiological mechanism by which OsCPK9 enables the plant to retain water. When water is limiting, plants accumulate compatible osmolytes such as soluble sugars and proline to decrease the cellular osmotic potential [42]. Our results showed that there were increased contents of both soluble sugars and proline in OsCPK9-OX lines, but decreased contents of these substances in OsCPK9-RNAi lines (Figure 3A). Thus, OsCPK9 functions in osmotic adjustment, improving the ability of the plant to retain water during drought. Also, stomatal movement controls not only CO2 uptake but also water loss to the atmosphere, thereby playing important roles in drought tolerance of crops [43]. Some CDPKs play vital roles in regulating stomatal movement. For example, overexpression of ZmCPK4 resulted in increased ABA-mediated stomatal closure [44]. ABA- and Ca2+-induced stomatal closure were partially impaired in a cpk3cpk6 mutant [13]. The Arabidopsis CPK4 and CPK11 genes were shown to be involved in ABA-regulated stomatal closure [10]. In the present study, OsCPK9-OX lines showed a significantly higher proportion of completely closed stomata under drought treatment, which may contribute to reduced water loss (Figure 3B and 3C). These results provided physiological evidence that OsCPK9 confers drought stress tolerance by enhancing the osmotic adjustment ability of the plant and by promoting stomatal closure, thereby reducing water loss.

OsCPK9 regulates expression of stress-associated genes in response to drought

To gain a deeper understanding of the function of OsCPK9 under abiotic stresses, we analyzed the transcript levels of some stress-inducible genes. Under osmotic stress, the transcript levels of Rab21, OsP5CS, OsLEA3, OsNAC9, Osbzip23, Osbzip66, and Osbzip72 were higher in OsCPK9-OX lines than in WT and VC (Figure 6). In previous studies, Rab21 was shown to be induced by water stress, and overexpression of OsP5CS, OsLEA3, OsNAC9, Osbzip23, and Osbzip72 enhanced tolerance to abiotic stresses [32, 38, 40, 41, 45, 46]. It was also reported that transcript levels of some stress-responsive genes were higher in other OsCPK-overexpressing rice lines than in controls under abiotic stresses. The transcript levels of OsLEA3, OsP5CS, Osbzip23, and OsNAC6 were higher in OsCPK21-FOX and OsCPK13-FOX plants than in WT plants under salt stress [25]. Similarly, OsCDPK7-overexpressing plants showed increased transcription of OsLEA3 in roots after a salt treatment [24]. These results demonstrated that OsCPK9 is involved in increasing transcription of stress-associated genes, thereby improving tolerance to drought stress.

OsCPK9 is involved in spikelet fertility

In a previous study, an analysis of CDPK gene family members revealed that transcripts for 23 genes deferentially accumulated during reproductive developmental stages [23]. In maize, a pollen-specific CDPK was only transcribed at the late stages of pollen development [47]. In petunia, PiCDPK1 and PiCDPK2 were involved in divergently regulating pollen tube growth. PiCDPK1 played an important role in growth polarity, whereas PiCDPK2 functioned in pollen tube extension [48]. These studies demonstrated that CDPKs function as important calcium sensors in pollen tube growth and seed development. However, it remained unknown whether CDPKs play a role in spikelet fertility. We detected OsCPK9 transcript not only in vegetative organs, but also in two reproductive organs, anther and spikelet (Figure 1A). Further investigations suggested that OsCPK9 plays a role in increasing spikelet fertility (Figure 4A; 4B). Pollen viability reflected by mature pollen staining ratio plays an important role in spikelet fertility [49]. The mature pollen staining ratio determined by I2-KI staining was correlated with the expression of OsCPK9, indicating that OsCPK9 positively regulates starch accumulation, pollen viability, and hence increases spikelet fertility (Figure 4C). The formation of mature and fertile pollen grains, taking place inside the anther, depends on supply of assimilates, in the form of sucrose, provided mainly by the leaves [50]. Starch biosynthesis during the final phases of pollen maturation is critical not only because starch provides a source of energy for pollen germination, but also because it is a checkpoint of pollen maturity [51]. The absence of starch deposition is a remarkable phenotype in male-sterile pollen [52]. Upregulation of OsRSUS in leaves of OsCPK9-overexpressing rice plants may increase sucrose supply to pollen for starch accumulation, therefore contributes to improved pollen viability and spikelet fertility (Figure 6). Whether OsCPK9 could directly influence starch accumulation in pollen needs further investigation.

OsCPK9 possibly acts in an ABA-dependent manner

It is well established that the phytohormone ABA maintains seed dormancy and inhibits seed germination and seedling growth [53]. Drought induces ABA biosynthesis and triggers ABA-dependent signaling pathways [54]. Thus, we investigated the OsCPK9 response to ABA. The OsCPK9-overexpressing lines were more sensitive to ABA than WT and VC (Figure 5). Arabidopsis CDPKs are involved in ABA signaling by phosphorylating basic leucine zipper class transcription factor proteins (bZIP). Arabidopsis CPK4 and CPK11 phosphorylate two bZIP factors, ABF1 and ABF4 [10]. Consistently, Arabidopsis CPK32 interacts with ABF4 and phosphorylates it in vitro [16]. Moreover, CPK4, CPK11, and CPK32 are involved in ABA-regulated physiological processes and abiotic stress tolerance [10, 16]. Additionally, Osbzip66, Osbzip72, and Osbzip23 function in ABA signaling and/or abiotic stress tolerance [3941, 55, 56]. The transcript levels of Osbzip66, Osbzip72, and Osbzip23 increased in OsCPK9-OX lines under osmotic and ABA treatments (Figure 6). OsCPK9 may function with Osbzip66, Osbzip72, and Osbzip23 to mediate ABA signaling and abiotic stress responses. Furthermore, our results showed that OsCPK9 plays a positive role in regulating Rab21, OsNAC9, OsLEA3, and OsP5CS transcription under osmotic stress and ABA treatment (Figure 6). These genes are responsive to abiotic stresses and ABA signaling [5760]. Therefore, the increased ABA sensitivity and higher transcript levels of ABA- and stress-responsive genes in OsCPK9-OX rice lines indicate that OsCPK9 positively regulates abiotic stress tolerance in an ABA-dependent manner.

Conclusions

We characterized the function of OsCPK9, a rice CDPK gene. OsCPK9 overexpression and interference analyses revealed that OsCPK9 positively regulates drought stress tolerance by enhancing stomatal closure and the osmotic adjustment ability of the plant. OsCPK9 also improves pollen viability, thereby increasing spikelet fertility. The OsCPK9-OX rice lines exhibited increased sensitivity to ABA. These findings help to clarify details of the CDPK-mediated abiotic stress responses and the role of ABA signaling in improving stress tolerance and rice quality. In the future, identifying the direct targets of OsCPK9 would be useful to determine the molecular mechanism of CDPKs.

Methods

Plant materials and treatments

Rice (Oryza sativa L. cv. Nipponbare) seeds were germinated on MS agar medium and grown on hydroponic culture in a growth chamber (70% humidity, 14 h light/10 h dark cycle, 26°C) [61]. For OsCPK9 expression assays under PEG6000, NaCl, and ABA treatments, rice seeds were germinated and grown for two weeks. Rice seedlings were then transferred into plastic boxes containing either 20% PEG6000, 200 mM NaCl, or 100 μM ABA for up to 24 h. A no treatment control was always included. Transcript levels of OsCPK9 were detected in rice seedling leaves. To assess OsCPK9 expression in different organs, root, basal part (30 mm) of seedling, stem, leaf blade, anther, and spikelet were collected from the rice plants.

qRT-PCR analysis

qRT-PCR was employed to examine OsCPK9 expression in different organs, in response to PEG6000, NaCl and ABA treatments, and for the expression of ABA- and stress-responsive genes. Primers (Additional file 1: Table S1) used in qRT-PCR showed high specificity, as determined by agarose gel electrophoresis and sequencing. In all experiments, appropriate negative controls without template were included to detect primer dimers and/or contamination. Prior to experiments, qRT-PCR was optimized through a series of template and primer dilutions. Amplification efficiencies for the internal control and target genes were between 0.92 and 1.14. Samples were run in triplicates and analyzed using the Opticon Monitor 2 qRT-PCR software. Expression levels of target genes were normalized to OsActin expression. Relative expression level of genes was calculated using the 2–ΔΔCt formula [62].

Plant transformation and transgenic plant generation

To construct the OsCPK9-OX vector, the coding sequence of OsCPK9 was introduced into pCAMBIA1301 under CaMV 35S promoter control using primers P1 and P2 (Additional file 1: Table S2). To construct the OsCPK9 RNAi vector, a 280 bp cDNA fragment encoding partial OsCPK9 was included downstream of the CaMV 35S promoter in both sense and antisense orientations spaced by a 548 bp intron of wheat TAK14 (Accession: AF325198) (Additional file 1: Table S2, P3-P8). These recombinant plasmids and vacant pCAMBIA1301 vector were introduced into Agrobacterium tumefaciens strain EHA105 to transform rice plants. Transgenic rice plants were generated using an Agrobacterium-mediated transformation method [63]. Seeds obtained from transgenic and vacant vector lines were selected on MS medium with 50 mg/L hygromycin. The hygromycin-resistant T1 seedlings were further examined by PCR analysis using primers to amplify HYG (Additional file 1: Table S2, P9 and P10). The homozygous T2OsCPK9-OX lines OE28 and OE16, OsCPK9-RNAi lines Ri16, Ri2 and Ri26, and VC line were used in further studies. OsCPK9 expression in these T2 lines was detected by RT-PCR analysis using an OsActin control.

Stress tolerance and ABA response analysis of WT and transgenic lines

For drought stress tolerance analysis, rice seeds were germinated on MS agar medium for 5 days and then grown in soil for 16 days in a growth chamber. Three-week-old rice seedlings were deprived of water for 27 days. This mimicked drought period was followed by a 3 days recovery. Survival rates were calculated (each sample contains 30 seedlings). Three-week-old rice seedlings were deprived of water for 15 days and then the chlorophyll, MDA, proline, soluble sugars, and status of stomata were examined by leaf samplings. Each sample represented four replicates (each replicate had 4-6 seedlings). For the osmotic stress tolerance assay, rice seeds germinated on MS agar medium for 5 days and then grown on hydroponic culture for 9 days in a growth chamber. Two-week-old rice seedlings with similar growth state were treated with 20% PEG6000 for 8 h. Seedlings were then allowed to recover for 7 days. After treatment with PEG6000 for 8 h, rice seedling leaves were sampled to detect soluble sugars, proline, MDA levels. Each sample represented four replicates (each replicate contained three leaves from the same position of independent plants). After recovery, root and shoot length, fresh weight, wilted and green leaves of rice seedlings were examined. Each sample represented four replicates (each replicate had 4-6 seedlings). For the dehydration stress tolerance assay, rice seeds were germinated on MS agar medium for 5 days and then grown on hydroponic culture for 9 days in a growth chamber. Two-week-old rice seedlings were placed on a bench in the growth chamber for 5 h, followed by recovery for 10 days. Rice seedlings were collected to examine root and shoot length and fresh weight. Each sample represented four replicates (each replicate had 4-6 seedlings). For the ABA sensitivity assay, rice seeds germinated on MS agar medium for 3 days, and then grown on hydroponic culture containing either 1 μM or 3 μM ABA for 14 days. After a 14 days treatment, rice seedlings were collected to examine the length and dry weight of root and shoot. Each sample again represented four replicates (each replicate had 6-7 seedlings).

Physiological indices measurement

WLR was measured according to methods described by Zhang et al. [42]. Briefly, rice leaves were detached from seedlings and fresh weight (FW) was assessed. Detached leaves were placed on a bench at room temperature to induce dehydration and weighed at designated time intervals (desiccated weight). WLR (%) = (FW – desiccated weight)/FW × 100. RWC was measured according to Hu et al. [64]. The dehydrated leaves were soaked in distilled water for 4 h and turgid weight (TW) was recorded. Leaves were finally dried for 48 h at 80°C to obtain total dry weight (DW). RWC was calculated as follows: RWC (%) = [(desiccated weight – DW)/(TW– DW)] × 100. Proline was detected as described by Troll & Lindsley [65]. Soluble sugars was measured via a phenol–sulphuric acid method [66]. Chlorophyll content was determined by UV spectrophotometry [67], and MDA content measured via a method described by Heath & Packer [68]. Rice stomatal status was determined through scanning electron microscopy (VEGA 3, TESCAN, The Czech) according to Zhang et al. [42].

Spikelet fertility and pollen analysis

Thirty days after sowing, WT and transgenic plants were transplanted in the experimental field of the Chinese National Center of Plant Gene Research (Wuhan) HUST Part (Wuhan, Hubei Province, China) with four replicates of each line (30 seedlings each replicate). Rice plants and the mature spikelets were harvested to determine spikelet fertility and weight. Pollen grains were stained with 1% I2-KI solution based on methods described by Zou et al. [69].

Statistical analysis

Statistical analysis was carried out by both Microsoft Excel and the Statistical Package for the Social Sciences (Chicago, IL, USA). Variance analysis was conducted by comparing the statistical difference based on a Student’s t-test.

Notes

Abbreviations

ABA: 

Abscisic acid

ABF: 

ABA-responsive transcription factor

CDPKs: 

Calcium-dependent protein kinases

SPK: 

Calcium-dependent seed-specific protein kinase

CBL: 

Calcineurin B-like

CaM: 

Calmodulin

DW: 

Dry weight

FW: 

Fresh weight

HSP: 

Heat shock protein

MDA: 

Malondialdehyde

OsCPK9-OX OsCPK9

overexpression

OsCPK9-RNAi OsCPK9

RNA interference

qRT-PCR: 

Quantitative reverse transcription-polymerase chain reaction

RWC: 

Relative water content

SLAC: 

Slow anion channel

TW: 

Turgid weight

WT: 

Wild type

VC: 

Vector control

WLR: 

Water loss rate.

Declarations

Acknowledgements

This work was supported by Key Project of S & T Research of MoE of China (Grant no. 109105), Research Fund for the Doctoral Program of Higher Education of China (Grant no. 2012014211075), Open Research Fund of State Key Laboratory of Hybrid Rice in Wuhan University (Grant no. KF201302) and the Major Technology Project of Hainan (ZDZX2013023-1). We also thank China Rice Data Center for helping us to search related data (http://www.ricedata.cn).

Authors’ Affiliations

(1)
The Genetic Engineering International Cooperation Base of Chinese Ministry of Science and Technology, Key Laboratory of Molecular Biophysics of Chinese Ministry of Education, College of Life Science and Technology, Huazhong University of Science & Technology
(2)
Institute of Tropical Bioscience and Biotechnology, Chinese Academy of Tropical Agricultural Sciences

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