MAPK kinase 10.2 promotes disease resistance and drought tolerance by activating different MAPKs in rice

Mitogen-activated protein kinase (MAPK) cascades, with each cascade consisting of a MAPK kinase kinase (MAPKKK), a MAPK kinase (MAPKK) and a MAPK, have important roles in different biological processes. However, the signal transduction in rice MAPK cascades remains to be elucidated. We show that the structural non-canonical MAPKK, MPKK10.2, enhances rice resistance to Xanthomonas oryzae pv. oryzicola (Xoc), which causes bacterial streak disease, and increases rice tolerance to drought stress by phosphorylating and activating two MAPKs, MPK6 and MPK3, respectively. MPKK10.2-overexpressing (oe) plants showed enhanced resistance to both Xoc and drought, whereas MPKK10.2-RNA interference (RNAi) plants had increased sensitivity to both Xoc and drought. MPKK10.2 physically interacted with MPK6 and MPK3, and phosphorylated the two MAPKs in vivo. Transcriptionally modulating MPKK10.2 influenced MPK6 phosphorylation during rice-Xoc interaction, and MPKK10.2-oe/MPK6-RNAi double mutants showed increased sensitivity to Xoc. MPKK10.2-oe/MPK3-RNAi double mutants showed survival rates similar to those of control plants, although the survival rates of MPKK10.2 transgenic plants changed after drought stress. These results suggest that MPKK10.2 is a node involved in rice response to biotic and abiotic responses by functioning in the cross-point of two MAPK cascades leading to Xoc resistance and drought tolerance.


INTRODUCTION
Mitogen-activated protein kinase (MAPK) cascades are evolutionarily conserved in eukaryotes. Each cascade comprises three central components, a MAPK kinase kinase (MAPKKK), a MAPK kinase (MAPKK) and a MAPK. This type of cascade transduces extracellular signals into cellular responses through sequential phosphorylation. Signals can activate a MAPKKK, which in turn can activate a MAPKK by phosphorylating its serine (S) and/or threonine (T) residues in the S/T-X 3-5 -S/T (X represents any amino acid residue) motif. The MAPKK then activates a MAPK by phosphorylating its threonine and tyrosine (Y) residues in the T-X-Y motif, which can be divided into at least two types, the T-aspartic acid (D)-Y and T-glutamic acid (E)-Y motifs, in plants ( Kyriakis and Avruch, 2012;Meng and Zhang, 2013). The activated MAPK phosphorylates other proteins to activate or repress their functions.
Plant MAPK cascades are involved in various physiological responses, including biotic and abiotic stresses. Plant genomes contain relatively less MAPKK genes compared with the numbers of MAPKKK and MAPK genes. For example, the Arabidopsis genome has 60 MAPKKK, 10 MAPKK and 20 MAPK genes (Ichimura et al., 2002); the rice genome has 74 MAPKKK (MPKKK), eight MAPKK (MPKK) and 17 MAPK (MPK) genes (Hamel et al., 2006;Reyna and Yang, 2006;Rao et al., 2010;Yang et al., 2015). This characteristic implies that multiple signal flows converge at the MAPKK level.
Biotic and abiotic stresses are limiting factors in crop production. Although the importance of MAPK cascades in eukaryote signal communication has been well recognized, no single MAPK cascade has been unambiguously characterized in the rice response to stresses. However, a few MPKKK and MPK genes that function in rice biotic or abiotic responses have been identified. MPKKK1 (also known as EDR1) and MPKKK6 (also known as DSM1) were reported to regulate rice resistance to bacterial blight caused by Xanthomonas oryzae pv. oryzae (Xoo) and drought tolerance, respectively (Ning et al., 2010;Shen et al., 2011;Yang et al., 2015). MPK3 (LOC_Os03 g17700; also known as MPK5), the ortholog of Arabidopsis MPK3, negatively regulates rice resistance to blast caused by Magnaporthe oryzae and positively regulates drought and submergence tolerance (Xiong and Yang, 2003;Singh and Sinha, 2016). MPK4 (also known as MPK6, the ortholog of Arabidopsis MPK4) and MPK17-1 (also known as MPK12, the ortholog of Arabidopsis MPK17) regulate rice resistance to Xoo infection (Shen et al., 2010;Seo et al., 2011).
Rice MPKKs can be divided into four groups (Hamel et al., 2006). Group A consists of MPKK1 and MPKK6. MPKK1 is involved in the salt signaling pathway via the activation of MPK4 . Overexpression of constitutively activated MPKK6 also enhances rice chilling and salt tolerance (Xie et al., 2012;Kumar and Sinha, 2013). To date, there is no research regarding MPKK3, which is the only member of Group B. Group C comprises MPKK4 and MPKK5. MPKK4-MPK3 and MPKK4-MPK6 (LOC_Os06 g06090; the ortholog of Arabidopsis MPK6) cascades are activated by chitin, a fungal pathogen-associated molecular pattern, and contribute to the synthesis of antimicrobial compounds (Kishi-Kaboshi et al., 2010). Group D consists of MPKK10.1, MPKK10.2 and MPKK10.3. Mutated MPKK10.2 can phosphorylate MPK6 in vitro, which then positively regulates WRKY45-mediated blast resistance (Ueno et al., 2015). These results suggest that MAPK cascades appear to have important roles in rice responses to biotic and abiotic stresses.
Rice bacterial streak, which is caused by biotroph Xanthomonase oryzae pv. oryzicola (Xoc), is a disease in China that requires quarantine (Li and Wang, 2013). Xoc infects rice via the stomata or wound. The molecular mechanism of rice resistance to Xoc is poorly understood; however, the rice gene xa5/TFIIAc5 V39E , which mediates passive and quantitative resistance to Xoc, has been reported recently (Yuan et al., 2016). Drought stress is an environmental disaster that can result in more than 50% yield loss of crops (Hu and Xiong, 2014). Although a few MAPK cascade genes have been identified as being involved in the rice response to drought stress, MAPK cascade signaling in the drought tolerance of rice has been rarely defined.
To understand the roles of MAPK cascades in the rice response to pathogens, we generated transgenic plants of several MPKKs and found that MPKK10.2 promoted rice resistance to Xoc. In addition, MPKK10.2 promoted rice tolerance to drought stress. Further genetic and biochemical studies have indicated that MPKK10.2 regulates resistance to Xoc and drought by phosphorylating and activating two MAPKs, MPK6 and MPK3, respectively.

MPKK10.2 was transcriptionally induced by both biotic stress and abiotic stress
To determine whether MPKK10.2 is involved in the rice response to biotic or abiotic stress, rice seedlings at the four-leaf stage were exposed to Xoc inoculation, drought stress and treatment with benzothiadiazole (BTH), which is an analog of defense hormone salicylic acid (SA) to biotrophic pathogens, or abscisic acid (ABA), which frequently contributes to plant tolerance to abiotic stresses. MPKK10.2 expression was highly induced by Xoc infection and drought stress, and it was also rapidly induced by BTH or ABA treatment (Figure 1a). These results suggest that MPKK10.2 may be involved in rice responses to biotic stress and abiotic stress.  Asterisks indicate a significant difference between non-treated and stress-treated plants at P < 0.01. The letter 'a' or 'b' above the bar indicates a significant difference between transgenic plants and wild-type (WT; Zhonghua 11) at P < 0.01 or P < 0.05, respectively. (a) MPKK10.2 expression in rice leaves with Xoc strain RH3 infection, drought stress, and 0.5 mM benzothiadiazole (BTH) or 100 lM abscisic acid (ABA) treatment. Zhonghua 11 plants at the four-leaf stage were used for analysis. 0 h and 0 d, immediately before treatment; Re, 3 days after re-watering. Bars represent mean (three replicates) AE standard deviation (SD). (b) Modulating MPKK10.2 expression influenced the rice response to Xoc. Flag leaves of transgenic plants of the T 2 generation were inoculated with the Xoc strain RH3 at the booting stage. Bars represent mean (five-six plants, with each plant having one flag leaf and each leaf having two inoculation sites, total 10-12 data) AE SD. N, negative transgenic plant.   Figure S1c). Hence, the progenies from three MPKK10.2-RNAi T 0 plants (3, 8 and 11) and three MPKK10.2-oe T 0 (6, 9 and 13) were further analyzed. The MPKK10.2-RNAi plants showed increased susceptibility to Xoc compared with WT, and the increased susceptibility was significantly correlated (P < 0.01) with reduced MPKK10.2 transcripts in T 1 families ( Figure S2). The correlation coefficients of the lesion length and MPKK10.2 expression level were 0.912, 0.802 and 0.939 (n = 20, P < 0.01) for MPKK10.2-RNAi3, MPKK10.2-RNAi8 and MPKK10.2-RNAi11 T 1 families, respectively. In contrast, the MPKK10.2-oe plants had reduced susceptibility to Xoc compared with WT, and the reduced susceptibility significantly correlated (P < 0.01) with the increased MPKK10.2 transcript in T 1 families ( Figure S3). The correlation coefficients of the lesion length and MPKK10.2 expression level were 0.826 (n = 19, P < 0.01), 0.876 (n = 13, P < 0.01) and 0.766 (n = 18, P < 0.01) for MPKK10.  Figure 1b). The negative transgenic plants showed a level of lesion length that was similar to that of WT. Furthermore, the average Xoc growth rate of rice leaves was 7.6-fold higher for MPKK10.2-RNAi-positive plants and 11.6-fold lower for MPKK10.2-oe-positive plants compared with WT ( Figure 1c). These results suggest that MPKK10.2 promotes rice resistance to Xoc.
The MPKK10.2-RNAi lines were more sensitive to drought treatment, with approximately 3.1-fold lower survival rates after treatment compared with WT ( Figure 1d). However, the MPKK10.2-oe lines showed enhanced drought tolerance, with 3.9-fold higher survival rates compared with WT ( Figure 1d). These results suggest that MPKK10.2 also promotes rice tolerance to drought stress.
MPK3 functioned downstream of MPKK10.2 in the rice response to drought Among 17 MAPK genes in the rice genome, only MPK3 has been reported to function in disease resistance and drought tolerance (Xiong and Yang, 2003). To clarify whether MPK3 functions downstream of MPKK10.2, we suppressed and overexpressed MPK3 in the same WT (Figure S4). The targeted region of MPK3 by the RNAi construct was the same as that previously reported (Xiong and Yang, 2003). In accordance with a previous report (Xiong and Yang, 2003), suppression of MPK3 (MPK3-RNAi) reduced rice tolerance to drought stress ( Figure S5a), and overexpression of MPK3 (MPK3-oe) enhanced rice tolerance to drought stress ( Figure S5b). However, both MPK3-RNAi and MPK3-oe plants showed a response to Xoc infection that was similar to that of WT (Figures S6 and S7). Further analysis showed that the MPK3 knockdown (MPK3-RI) plants (named MPK5-RI in the original articles) generated previously (Xiong and Yang, 2003;Xie et al., 2014) also exhibited a response similar to that of WT Nipponbare to Xoc ( Figure S8). We then crossed MPKK10.2-oe lines with MPK3-RNAi lines, and the MPKK10.2-oe/MPK3-RNAi double mutants had significantly increased MPKK10.2 transcripts and suppressed MPK3 transcripts (Figure 2a). The double mutants showed survival rates similar to those of WT after drought treatment (Figure 2b), although the MPKK10.2-oe plants had a significantly higher survival rate than WT, and MPK3-RNAi plants had a significantly lower survival rate than WT after drought treatment (Figures 1d and S5a). In comparison, the double mutants showed a level of resistance to Xoc similar to that of MPKK10.2-oe plants ( Figure 2c). These results suggest that, considering MAPK cascade signaling, MPKK10.2 may regulate the rice response to drought stress through MPK3 and that it regulates the rice response to Xoc infection through another MAPK other than MPK3.

MPK6 functioned downstream of MPKK10.2 in the rice response to Xoc infection
To determine which MAPK was involved in MPKK10.2mediated defense against Xoc, we analyzed the phosphorylation status of MAPKs in MPKK10.2 transgenic plants in vivo after Xoc infection using anti-pTEpY antibody, which is commonly used to detect plant-phosphorylated MAPKs on the conserved T-E-Y motif by MAPKKs (Yamaguchi et al., 2013;Willmann et al., 2014). A MAPK with a molecular mass of approximately 48 kD was highly phosphorylated after inoculation of Xoc in WT plants compared with non-inoculated plants (Figure 3a,b). Because the phosphorylated band was absent in MPK6 knockout mutant (mpk6; Figure 3a,b), which has a single nucleotide deletion in the coding region resulting in loss of kinase activity and highly reduced protein expression (Liu et al., 2015; Figure S9), the phosphorylated band was considered to correspond to MPK6. Further analysis showed that MPKK10.2-oe plants had more phosphorylated MPK6 molecules than WT before and after inoculation of Xoc (Figure 3a), whereas the MPKK10.2-RNAi plants had less phosphorylated MPK6 molecules than WT after inoculation of Xoc (Figure 3b). These results suggest that Xoc infection increases phosphorylated MPK6 and that MPKK10.2 promotes accumulation of phosphorylated MPK6 after Xoc infection.
MPK6 negatively regulated rice resistance to drought stress Further analysis was performed to examine the role of MPK6 in the rice response to drought stress. The MPK6-oe lines were more sensitive to drought treatment, with approximately 2.1-fold to 2.6-fold lower survival rates after treatment compared with WT ( Figure 4a). However, the mpk6 mutant showed enhanced drought tolerance with 3.4-fold higher survival rates compared with the WT (Figure 4b). These results suggest that MPK6 is a negative regulator of rice tolerance to drought stress.

MPKK10.2 could interact with and phosphorylate MPK6 and MPK3
To learn whether MPKK10.2 directly regulates MPK6 and MPK3, co-immunoprecipitation assays were performed in rice plants. Protein extracted from the leaves of WT, MPKK10.2-RNAi3, mpk6 and MPK3-RNAi4 plants without or exposed to Xoc infection or drought stress was immunoprecipitated with MPKK10.2-specific antibody. Without stress, MPKK10.2 was detected in the immunoprecipitated protein complex from WT, and MPK6 and MPK3 were not detected in the immunoprecipitated protein complex from WT ( Figure 5a). After Xoc infection, MPKK10.2  and MPK6 were both detected in the immunoprecipitated protein complex from WT; however, MPK3 was not detected (Figure 5a). After drought stress, MPKK10.2 and MPK3 were both detected in the immunoprecipitated protein complex of WT; however, MPK6 was not detected (Figure 5a). In addition, MPK3 was not detected in the immunoprecipitated protein complex from mpk6 mutant exposed to Xoc infection and MPK6 was not detected in the immunoprecipitated protein complex from MPK3-RNAi plants exposed to drought stress ( Figure S14). These results suggest that MPKK10.2 and MPK6 functioned in the same protein complex in the rice response to Xoc infection, and that MPKK10.2 and MPK3, but not MPKK10.2 and MPK6, were in the same protein complex in the rice response to drought stress.
To determine whether MPKK10.2 could phosphorylate MPK6 and MPK3, we expressed and purified these three proteins from bacterium. Both MPK6 and MPK3 could autophosphorylate and phosphorylate the myelin basic protein, a common substrate of MAPKs (Figure 5b). We then generated the kinase-inactive versions of MPK6 (MPK6 K96R ) and MPK3 (MPK3 K65R ) by substituting a conserved lysine (K) residue (K96 in MPK6 and K65 in MPK3) for arginine (R) in the ATP-binding domain. Both MPK6 K96R and MPK3 K65R lacked autophosphorylation activity, but they were phosphorylated by MPKK10.2 (Figure 5c). We also immunoprecipitated MPKK10.2 from the leaves of WT plants before and after Xoc infection or drought stress. The phosphorylation of MPK6 K96R and MPK3 K65R by immunoprecipitated MPKK10.2 was detected using the anti-pTEpY antibody. The results showed that immunoprecipitated MPKK10.2 (+IP:MPKK10.2) after Xoc infection and drought stress could phosphorylate MPK6 K96R and MPK3 K65R , respectively (Figure 5d,e). All these results suggest that MPKK10.2 may perform its function in Xoc resistance and drought tolerance via activating MPK6 and MPK3 through phosphorylation.
Xoc resistance and drought tolerance required MPK6mediated SA signaling and MPK3-mediated ABA signaling pathways It has been reported that SA treatment activates MPK6 but not MPK3 (Xiong and Yang, 2003;Ueno et al., 2015). To determine whether the SA signaling pathway contributed to MPK6-mediated Xoc resistance, SA-deficient transgenic rice (named NahG rice), which has a reduced SA level by expressing bacterial salicylate hydroxylase that degrades SA , was used for inoculation analysis. The NahG rice showed increased susceptibility to Xoc compared with WT Nipponbare, and the Xoc growth rate was higher for NahG rice compared with WT (Figure 6a,b). Moreover, after BTH pre-treatment, both WT and NahG rice showed significantly reduced (P < 0.01) lesion lengths compared with that treated with deionized water ( Figure 6c). These results suggest that the SA signaling pathway contributed to Xoc resistance. Next, MPK6 and MPK3 were detected in NahG rice after Xoc infection. Consistent with these results (Figure 3a,b), MPK6 was highly phosphorylated after inoculation of Xoc in WT (cultivar Nipponbare) compared with non-inoculated  plants, whereas NahG rice had less phosphorylated MPK6 molecules than WT after inoculation of Xoc (Figure 6d). The MPK6 expression level and the phosphorylation of immunoprecipitated MPK3 were normal in both WT and NahG rice before and after Xoc inoculation, as detected using the anti-MPK6 antibody and the anti-pTEpY antiboly (Figure 6e,f), suggesting that MPK6 but not MPK3 phosphorylation is required in SA-mediated Xoc resistance.
Abscisic acid treatment induced and activated MPK3 but inactivated MPK6 (Xiong and Yang, 2003;Ueno et al., 2015). Based on this, we detected MPK6 and MPK3 after drought stress in ABA-deficient mutant phs3-1, which has a G-to-C transition in the donor site of intron 6 of a carotenoid isomerase-like gene resulting in mis-splicing and reduced ABA level (Fang et al., 2008). The phs3-1 mutant was more sensitive to drought stress compared with WT (cultivar Xiushui11; Du et al., 2010). After drought stress, the phosphorylation of MPK6 was decreased in WT, but normal in phs3-1 mutant ( Figure 6g); MPK3 was highly induced in WT, but much less induced in the phs3-1 mutant ( Figure 6h); the phosphorylation of immunoprecipitated MPK3 was enhanced in WT, but normal in phs3-1 mutant (Figure 6i). These results suggest that the expression and phosphorylation of MPK3 but the dephosphorylation of MPK6 is necessary in ABA-mediated drought tolerance.

DISCUSSION
The present results suggest that rice MPKK10.2 positively regulates bacterial resistance and drought tolerance via phosphorylating and activating two distinct MAPKs, MPK6 and MPK3. These results facilitate our understanding of the tight control of MAPK cascades in the biological processes of rice.

MPKK10.2 possesses the typical MAPKK kinase activity
Rice MPKKs of group D, including MPKK10.2, belong to structural non-canonical MPKKs because they do not have the typical S/T-X 5 -S/T motif of most plant MAPKKs that are phosphorylation sites of MAPKKKs (Hamel et al., 2006;Figure S15). Therefore, it is not clear whether MPKK10.2 can function as a canonical MAPKK to phosphorylate and activate MAPKs. Although a previous study reported that mutated MPKK10.2 (named OsMKK10-2D in the original article), which has constitutively activated kinase activity, can phosphorylate MPK6 (Ueno et al., 2015), it is unknown whether the WT MPKK10.2 possesses such ability. Here, we provide the evidence that WT MPKK10.2 is activated by Xoc infection and drought stress, and can phosphorylate MPK6 and MPK3 on the T-E-Y motif as the phosphorylation site of canonical MAPKKs (Figures 3a,b and 5c-e).

MPKK10.2 is a cross-point in rice responses to biotic and abiotic stresses
There are much less MPKK genes than MPKKK and MPK genes in the rice genome, suggesting that each MPKK may be phosphorylated by multiple MPKKKs and that each MPKK may phosphorylate multiple MPKs during signal transduction. Therefore, each MPKK could be involved in the regulation of diverse physiological activities. An example is MPKK6, which positively regulates rice responses to both chilling stress and salt stress (Xie et al., 2012;Kumar and Sinha, 2013). However, no MPKK has been reported to regulate both biotic stress and abiotic stress in rice. The present results indicate that MPKK10.2 enhances rice resistance to both Xoc infection and drought stress. The MPKK10.2 gene was transcriptionally activated by Xoc infection, drought stress, SA analog and ABA (Figure 1a). MPKK10.2 kinase activity was also induced by Xoc infection and drought stress (Figure 5d,e). SA is known to regulate the plant defense to biotrophic pathogens (McDowell and Dangl, 2000), including Xoc (Figure 6a-c), and ABA is frequently involved in plant tolerance to abiotic stresses (Zhu, 2002), including rice drought tolerance (Du et al., 2010). MPK6 and MPK3 were required for SA-mediated Xoc resistance and ABA-mediated drought tolerance, respectively (Figure 6d-i). We suggest that Xoc infection and drought stress induce accumulation of SA and ABA, respectively, and that increased SA and ABA levels may result in the activation of unknown MPKKKs, which in turn activate MPKK10.2 by phosphorylating the latter (Figure 7). Activated MPKK10.2 likely promotes resistance to Xoc through phosphorylating and activating MPK6, and likely promotes drought tolerance through phosphorylating and activating MPK3 (Figure 7). Therefore, MPKK10.2 is a node in the rice response to biotic stress and abiotic stress by functioning in the cross-point of two MAPK cascades leading to Xoc resistance and drought tolerance, respectively. How rice MPKK10.2 distinguishes different stimuli and modulates distinct but proper output is a principal question. A co-immunoprecipitation experiment showed that MPKK10.2 co-immunoprecipitated with MPK6, but not MPK3, after Xoc infection, and with MPK3, but not MPK6, after drought stress (Figures 5a and S14). Therefore, one explanation is that different scaffold proteins may function in MPKK10.2-involved cascades. Each scaffold protein that binds components of one MPKK10.2-involved MAPK cascade together could restrict the signaling that occurs only in a certain protein complex to avoid erroneous response. For example, the Arabidopsis MKK4/MKK5-MPK3/MPK6 cascade regulates the immune response and stomatal development and patterning (Asai et al., 2002;   to the upstream heterotrimeric G-protein (Cheng et al., 2015). During stomatal development and patterning, an unknown protein, BASL, is a scaffold protein in YDA-MKK4/MKK5-MPK3/MPK6 cascade-mediated signal transduction . Therefore, identification of scaffold proteins that interact with MPKK10.2-involved MAPK cascades could require further attention to understand rice MAPK cascades.
Negative role of MPK6 in rice response to drought stress MPK6 was negatively involved in rice response to drought stress (Figure 4), and its respressed activity is necessary in ABA-dependent drought response (Figure 6g), while in SA-mediated disease resistance, MPK6 activity is required ( Figure 6). The antagonistic interaction between SA-and ABA-signaling pathways was previously reported in plants but was not fully elucidated (Yasuda et al., 2008;Ueno et al., 2015). Identification of the substrates of MPK6 will be helpful to elucidate the opposite role of MPK6 in biotic and abiotic stresses. MPK3 was positively involved in ABA-dependent drought tolerance (Figures 6h,i and S5; Xiong and Yang, 2003). A potential hypothesis is that MPK3 repressed MPK6 in ABA-mediated drought tolerance. MPK6 was reported to be inactivated by protein tyrosine phosphatases, OsPTP1/2, which were induced by ABA treatment (Ueno et al., 2015). The elucidation of the relationship of MPK3 and OsPTP1/2 will be helpful to understand the relationship between MPK3 and MPK6 in drought tolerance. Another hypothesis is that a MAPK cascade that contains MPK6 but not MPKK10.2-MPK3 was negatively involved in rice drought tolerance. Further analysis of the function of other MPKKs in rice drought tolerance may help to understand this hypothesis.

Unique role of MPK3 in rice responses to biotic stresses
In addition to promoting rice drought adaption, MPK3 negatively regulates the rice defense against various pathogens, including bacterial pathogens Burkholderia glumae and Xanthomonas oryzae pv. oryzae, and fungal pathogen M. oryzae (Xiong and Yang, 2003;Seo et al., 2011). However, our results suggest that MPK3 was not involved in the rice response to Xoc infection ( Figures S6 and S7). A MAPK cascade gene can regulate different responses to different pathogens. One example is rice EDR1, a MAPKKK. The edr1 knockout mutant showed enhanced resistance to X. oryzae pv. oryzae but increased susceptibility to M. oryzae (Shen et al., 2011). Knockdown of rice MPK6 using RNAi did not influence the rice response to the blast pathogen (Lieberherr et al., 2005), but caused increased susceptibility to Xoc (Figures 3e and S12). The Arabidopsis mpk3 (the ortholog of rice MPK3) knockout mutant showed reduced susceptibility to bacterial pathogen Pseudomonas syringae pv. tomato DC3000 (Frei dit Frey et al., 2014), but enhanced susceptibility to powdery mildew Golovinomyces cichoracearum, a fungal pathogen (Zhao et al., 2014). Rice MPK3 is another example.
A previous study reported that rice CPK18, a calciumdependent protein kinase, negatively regulates rice resistance to M. oryzae through phosphorylating and activating MPK3 (Xie et al., 2014), indicating that the MPK3-mediated defense may include the MAPKK-independent pathway.

Rice materials
Rice varieties Zhonghua 11, Nipponbare and Xiushui 11 belong to the japonica (Oryza sativa ssp. japonica) subgroup of Asian cultivated rice. The mpk6 knockout mutant, which has a single nucleotide deletion in the sixth exon resulting in the loss of kinase activity, has the genetic background of Zhonghua 11 (Liu et al., 2015). NahG rice, which has reduced the SA level by expressing bacterial salicylate hydroxylase that degrades SA, has the genetic background of Nipponbare . The phs3-1 mutant, which has a G-to-C transition at the donor site of intron 6 of a carotenoid isomerase-like gene resulting in mis-splicing and reduced ABA level, has the genetic background of Xiushui 11 (Fang et al., 2008). MPK3 knockdown (MPK3-RI) plants (named MPK5-RI in the original articles; Xiong and Yang, 2003;Xie et al., 2014) have the genetic background of Nipponbare.

Vector construction and rice transformation
The full-length and fragments of cDNAs MPKK10.2, MPK3 and MPK6 were amplified from Zhonghua 11 using the primers listed in Table S1. For construction of the overexpressing vector, the amplified cDNA was inserted into the pU1301 vector . For construction of the RNA interference (RNAi) vector, the polymerase chain reaction (PCR) product was inserted into the pDS2301 vector, which was constructed based on the pDS1301 vector (Yuan et al., 2007) and contains a G418 antibiotic selection marker. Agrobacterium-mediated transformation was performed according to protocol (Lin and Zhang, 2005). For construction of the protein expression vectors, the open reading frames (ORFs) of target genes were cloned into the pET28a vector (Invitrogen, USA) and pMAL-c2x vector (New England Biolabs, USA).

Pathogen inoculation
Plants were inoculated with Xoc strain RH3 using the needle stab method during the seedling or booting stage (Tao et al., 2009). Lesion lengths were measured 2-3 weeks after inoculation. Xoc growth in rice leaves was determined by counting colony-forming units (Sun et al., 2004). The inoculation of transgenic plants with RH3 was biologically repeated at least twice with similar results, and only one replicate was presented. dimethyl sulfoxide and then diluted with autoclaved deionized water to make 0.5 mM solution. Rice seedlings at the four-leaf stage were sprayed with the solution containing 0.02% (v/v) Tween 20 (Sangon, China) to increase adhesion or with the autoclaved deionized water containing 0.02% (v/v) Tween 20 as a control. Xoc inoculation was performed 24 h after BTH or the deionized water spray.

Drought stress
Stress was generated as reported previously (Tao et al., 2011). In brief, transgenic and control plants growing in the same pot were kept in a greenhouse with light strength maintained at 12 000-14 000 lux and with a 14 h light/10 h dark cycle at 25°C until the five-to six-leaf stage. The plants were withheld from water until all leaves were wilted; then, they were recovered by the provision of water for 7-9 days. Survival rates were recorded. Drought stress assay was biologically repeated threesix times.

Gene expression
Quantitative reverse transcription PCR (qRT-PCR) was conducted as described previously using gene-specific primers (Table S2; Qiu et al., 2007). The expression of the rice actin gene was used as an internal control to standardize the RNA sample for each qRT-PCR.

Point mutation
To introduce point mutations in ORFs of MPK6 and MPK3, PCRmediated site mutagenesis was performed using the primers listed in Table S3. A site-directed Mutagenesis Kit (Sangon, China) was used according to the manufacturer's protocol.

Recombinant protein expression, purification and in vitro phosphorylation assay
To express protein in Escherichia coli BL21 (DE3), the ORFs of MPKK10.2, MPK6 and MPK3 were cloned into the pET28a vector (Invitrogen, USA) and pMAL-c2x vector (New England Biolabs, USA). Expression and purification of the recombinant proteins were performed according to the manufacturer's protocols.
The in vitro phosphorylation analysis was performed as described previously (Ning et al., 2011). In brief, proteins were incubated at room temperature in reaction buffer containing 50 mM Tris-HCl (pH 7.5), 10 mM MgCl 2 , 10 mM MnCl 2 , 1 mM dithiothreitol (DTT), 0.1 mM ATP and 5 lCi c-32 P-ATP for 30 min. The reaction was stopped by adding 5 9 sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) loading buffer containing 250 mM Tris-HCl (pH 6.8), 10% SDS (W/V), 0.5% bromphenol blue (W/V), 50% glycerol and 50 mM DTT. The samples were boiled for 3-5 min before being separated on SDS-PAGE. The gel was then dried on filter papers and exposed to Fuji X-ray film. Each phosphorylation analysis was biologically repeated two-three times with similar results, and only one replicate was presented.

Statistical analysis
The significant differences between control and treatment of the samples were analyzed by the pair-wise t-test installed in the Microsoft Office Excel program. The correlation analysis between disease and gene expression levels was performed using the COR-REL analysis installed in the Microsoft Office Excel program.
The authors declare no conflict of interest.

SUPPORTING INFORMATION
Additional Supporting Information may be found in the online version of this article. Figure S1. Gene expression analysis in MPKK10.2 transgenic plants. Figure S2. Analysis of lesion length and MPKK10.2 expression level of MPKK10.2-RNAi transgenic plants in three T 1 families. Figure S3. Analysis of lesion length and MPKK10.2 expression level of MPKK10.2-oe transgenic plants in three T 1 families. Figure S4. MPK3 expression in MPK3-suppressing (RNAi) and MPK3-overexpressing (oe) transgenic plants. Figure S5. Effects of modulating MPK3 expression on responses to drought stress in rice. Figure S6. Effect of suppressing MPK3 on responses to Xoc infection in rice. Figure S7. Effects of overexpressing MPK3 on responses to Xoc infection in rice. Figure S8. Effect of MPK3 knockdown (MPK3-RI; original name MPK5-RI) rice plants (provided by Dr Yinong Yang of Pennsylvania State University) on response to Xoc infection. Figure S9. Analysis of MPK6 protein expression level. Figure S10. MPK6 expression in MPK6-overexpressing (oe) transgenic plants. Figure S11. Analysis of lesion length and MPK6 expression level of MPK6-oe transgenic plants. Figure S12. Analysis of lesion length and MPK6 expression level of MPK6-RNAi transgenic plants. Figure S13. Analysis of lesion length and MPK6 expression level of MPKK10.2-oe/MPK6-RNAi transgenic plants. Figure S14. Co-immunoprecipitation assays between MPKK10.2 and MPK6 or MPK3 in WT, mpk6 and MPK3-RNAi plants. Figure S15. The S/T-X 5 -S/T motif of rice MPKKs. Table S1. Primers used for vector construction. Table S2. PCR primers used for gene expression analysis. Table S3. PCR primers used for PCR-mediated site mutagenesis.