Overexpression of AtGolS3 and CsRFS in poplar enhances ROS tolerance and represses defense response to leaf rust disease

Overexpression of AtGolS3 and CsRFS in poplar enhances ROS tolerance and represses defense... Abstract Plants respond to pathogens through an orchestration of signaling events that coordinate modifications to transcriptional profiles and physiological processes. Resistance to necrotrophic pathogens often requires jasmonic acid, which antagonizes the salicylic acid dependent biotrophic defense response. Recently, myo-inositol has been shown to negatively impact salicylic acid (SA) levels and signaling, while galactinol enhances jasmonic acid (JA)-dependent induced systemic resistance to necrotrophic pathogens. To investigate the function of these compounds in biotrophic pathogen defense, we characterized the defense response of Populus alba × grandidentata overexpressing Arabidopsis GALACTINOL SYNTHASE3 (AtGolS) and Cucumber sativus RAFFINOSE SYNTHASE (CsRFS) challenged with Melampsora aecidiodes, a causative agent of poplar leaf rust disease. Relative to wild-type leaves, the overexpression of AtGolS3 and CsRFS increased accumulation of galactinol and raffinose and led to increased leaf rust infection. During the resistance response, inoculated wild-type leaves displayed reduced levels of galactinol and repressed transcript abundance of two endogenous GolS genes compared to un-inoculated wild-type leaves prior to the up-regulation of NON-EXPRESSOR OF PR1 and PATHOGENESIS-RELATED1. Transcriptome analysis and qRT-PCR validation also revealed the repression of genes participating in calcium influx, phosphatidic acid biosynthesis and signaling, and salicylic acid signaling in the transgenic lines. In contrast, enhanced tolerance to H2O2 and up-regulation of antioxidant biosynthesis genes were exhibited in the overexpression lines. Thus, we conclude that overexpression of AtGolS and CsRFS antagonizes the defense response to poplar leaf rust disease through repressing reactive oxygen species and attenuating calcium and phosphatidic acid signaling events that lead to SA defense. Introduction Plant carbohydrates play a significant role in determining the outcome of plant-pathogen interactions. Successful pathogens acquire carbohydrates to further colonize host tissues and/or complete their life cycles. As an example, in several soil-borne diseases of peanut higher concentration of glucose in root exudates leads to greater spore germination and mycelial growth of Fusarium species (Li et al. 2013). In another plant pathosystem, the causal bacteria of rice blight disease Xanthomonas oryzae has evolved a TAL effector to evade host plant resistance responses specifically through activating transcription of OsSWEET11, a sucrose efflux transporter (Yang et al. 2006). However, modification to plant sugar concentrations can also induce the host resistance response. Exogenous applications of sucrose activates anthocyanin synthesis and PR gene expression in rice (Gómez-Ariza et al. 2007, Serrano et al. 2012). Furthermore, sucrose and glucose are precursors to myo-inositol, galactinol and the raffinose family oligosaccharides (RFOs). Recent evidence indicates these metabolites play an essential role in regulating abiotic stresses, reactive oxygen species (ROS), and enhancing defense against necrotrophic pathogens by modulating jasmonic acid (JA) signaling (Liu et al. 2007, Kim et al. 2008, Chaouch and Noctor 2010, Cho et al. 2010, Bruggeman et al. 2015). Myo-inositol is synthesized in a two-step process where phosphorylated glucose derived from sucrose metabolism is phosphorylated by INOSITOL-3-PHOSPHATE SYNTHASE (MIPS1/I3PS) and then dephosphorylated by INOSITOL MONOPHOSPHATASE (Loewus and Murthy 2000). Galactinol synthase (GolS) catalyzes the production of galactinol via the transfer of a galactosyl residue from UDP-d-galactose to myo-inositol. Galactinol serves as a precursor to RFOs; e.g., raffinose, stachyose and verbacose, where sucrose accepts the galactosyl residue and yields the larger oligosaccharides and myo-inositol (Lehle and Tanner 1973). Thus, these molecules are intimately linked through their biosynthetic pathways; however, the function of each RFO has not been individually determined. In Arabidopsis, myo-inositol-1-phosphate synthase1 (atips1/mips1/i3ps) loss of function mutants have reduced levels of myo-inositol and galactinol, accompanied by salicylic acid (SA)-dependent cell death and constitutively elevated SA levels. Elevated SA in the atips1mutant also reduced the growth of virulent Hyaloperonospora parasitica. (Meng et al. 2009). On the other hand, exogenous myo-inositol abolished cell death lesions by inhibiting SA accumulation in a catalase2 mutant. The application of exogenous myo-inositol also attenuated resistance to virulent bacteria (Chaouch and Noctor 2010). Galactinol is one of the products of myo-inositol metabolism that can also regulate several stress responses. For example, overexpression of a wheat GolS in Arabidopsis and rice enhanced expression of ROS-scavenging genes (Wang et al. 2015). GolS transcripts were also shown to be induced by water and salt stress, and necrotrophic fungi in several plant species (Kim et al. 2008, Cho et al. 2010, Zhou et al. 2014). Additionally, overexpression of GolS activated jasmonic acid signaling induced systemic resistance (Kim et al. 2008, Cho et al. 2010). In a similar fashion, overexpression of a rice UDP-glucose 4-epimerase gene in Arabidopsis led to accumulation of raffinose and enhanced tolerance to salt, drought and freezing stress (Liu et al. 2007). Recently, it has been shown that overexpression of AtGolS3 in hybrid poplar initiates metabolic changes that culminate in the formation of tension wood, which is a response to environmental stress on the tree (Unda et al. 2016). Myo-inositol can also be diverted to produce phosphatidylinositols (PtdIns) which leads to phosphatidic acid (PA) via the phosphoinositide-phospholipase C (PI-PLC) pathway. PA is a positive regulator of ROS and SA defense (de Jong et al. 2004, Munnik and Nielsen 2011). A key family of genes in the biosynthesis of PA are the phosphatidylinositol 4-phosphate 5-kinases (PIP5K), where type I and type II PIP5Ks produce phosphatidylinositol (4,5) bisphosphate (PtdIns(4,5)P2), a precursor to PA and inositol polyphosphates (InsP3) (Ma et al. 2006). Overexpression of a PHOSPHATIDIC ACID PHOSPHATASE and INOSITOL POLYPHOSPHATE 5-PHOSPHATASE, each result in compromised defense against biotrophic pathogens with reduced PR transcripts via suppressed PA and ROS, and InsP3 and Ca2+, respectively (Nakano, et al. 2013, Hung et al. 2014). PtdIns(4,5)P2 is also a required co-factor for phospholipase D (PLD) production of PA and PLD derived PA loops back to positively activate PIP5Ks (van den Bout and Divecha 2009). Moreover, this positive loop has been shown to be induced by exogenous SA, resulting in the activation of phospholipase C (PLC) and PLD (Profotova et al. 2006). Previously described in Unda et al. (2016), Populus alba × grandidentata hybrid P39 was transformed with a construct to overexpress the Arabidopsis thaliana GALACTINOL SYNTHASE3 (GolS) gene (35S:AtGolS3); and then characterized for altered growth and carbohydrate composition in leaf and stem tissues. Lines overexpressing AtGolS3; OEGolS_3, OEGolS_6, OEGolS_8 and OEGolS_11, each exhibited elevated levels of galactinol in stem phloem/developing xylem and source leaf tissue in comparison to the non-transformed wild-type poplar. OEGolS lines also had significantly higher levels of raffinose in source leaf tissues. OEGolS_6 and OEGolS_11 each were significantly shorter and had smaller stem diameters than wild-type trees, OEGolS_3, and OEGolS_8. The smaller stature also coincided with significantly higher amounts of glucose and lower total lignin content in woody tissues (Unda et al. 2016). Poplar trees are often challenged by poplar leaf rusts caused by several species of Melampsora (Fungi, Basidiomycota and Pucciniomycetes). Poplars and leaf rusts interact through effector triggered immunity or susceptibility, where virulent strains can decrease photosynthetic capacity and impact biomass, and increase susceptibility to additional pathogens (Steenackers et al. 1996, Hacquard et al. 2011). Poplar leaf rust disease has become a model system to study biotrophic pathogen interactions in tree species (Feau et al. 2007), and poplars offer a rich array of genomic tools to thoroughly investigate such interactions (Jansson and Douglas 2007, Duplessis et al. 2009, Hacquard et al. 2011). Transcriptome and genome-wide association study (GWAS) analysis on several Populus × Melampsora interactions have revealed an orchestrated defense response involving reactive oxygen species (ROS), phytohormones, Ca2+ influx, and myo-inositol signaling to regulate salicylic acid defense (Miranda et al. 2007, Rinaldi et al. 2007, Azaiez et al. 2009, Petre et al. 2012, La Mantia et al. 2013). In this study, we characterized the role of galactinol and raffinose in regulating the resistance response to a biotrophic pathogen of poplar, Melampsora aecidiodes, in Populus alba × grandidentata lines with enhanced and suppressed expression of a galactinol synthase and enhanced expression of raffinose synthase genes, independently. We now demonstrate that elevated galactinol and raffinose concentrations systemically attenuate the SA defense response by suppressing genes involved in PA biosynthesis and signaling, Ca2+ influx, and SA signaling, while enhancing ROS tolerance. Materials and methods Plasmids construction and plant transformation The Cucumis sativus RFS (AF073744) was cloned using the following primers: CsRFS2Fw 5′-TTCTTCTCACAAATGGCTCCTAGTT-3′ and CsRFS2Rv 5′-CAACAGCGACAACAAC AACAATCATT-3′.The gene was ligated into the pSM3 vector (pCambia 1390 with double 35 S promoter, Mansfield Lab, UBC). The vector was then transformed into Agrobacterium tumefasciens (EHA-105 strain). The Pa × gGolS-RNAi construct was generated using primers: GolSXhXb 5′-CTCGAGTCTAGACGGTTTGCTATGCCTTATTAT-3′ and GolSKpBa 5′-GGTACCGGATCCTGC CAGCATTGAAGTAGAGAG-3′. The restriction sites included on the primers sequence were used to amplify a 288 bp fragment of a conserved region of the galactinol synthase family. The fragment was ligated to the pKANNIBAL cloning vector (Helliwell and Waterhouse 2003). The NotI fragment from the pKANNIBAL vector was sub-cloned into the binary vector pART27 (Gleave 1992). The vector pART27 Pa × gGolSRNAi was transformed into A. tumefasciens EHA105 strain. The two vectors were then used for plant transformations Populus alba × grandidentata (P39) transformations were performed as described in Unda et al. (2016). Plants were confirmed as being transgenic by genomic DNA screening, using the CTAB (Sigma-Aldrich Co.) extraction method, and those identified as positive were then sub-cultured and multiplied on antibiotic-free woody plant media (WPM). Plant growth conditions and expression analysis of transgenic hybrid poplar trees Transgenic trees were multiplied in WPM media until approximately three to five plants of each transgenic event were of similar size, along with the appropriate control, non-transformed trees. The trees were then moved to 7.5 L pots containing perennial soil (50% peat, 25% fine bark and 25% pumice; pH 6.0)Trees were maintained on flood tables with supplemental lighting (16 h days) and daily water with fertilized water in the University of British Columbia greenhouse, Vancouver, BC Canada. After 5 or 6 months of growth (CsRFS and RNAiGols, respectively) trees were harvested. Transcript analysis to confirm presence of the transgene (CsRFS) or downregulation of the GolS (RNAiGolS) were performed by RT-PCR. RNA was isolated as per Kolosova et al. (2004), DNase I DIGEST kit (Ambion Inc.) was used to eliminate contaminating DNA. One microgram of RNA was used to generate cDNA using the iScript cDNA synthesis kit (Bio-Rad Laboratories, CA, USA). RT-PCR primers for the overexpression were: CsRFSrtFw 5′-TTTGGCATGCTTTGT GTGGATA-3′ and CsRFSrtRv 5′-CAAAATCCTCCATCGTCATCT-3′. RNAiGolS lines:, PtGolS3.1 (homolog to Pa × gGolSII as per Philippe et al. 2010), and Pa × gGolSIV Fw 5′-AACCTTTTGATTTCTCTAACC-3′ and Rv 5′-AAGGGAGTTGGTGT TGTTACG-3′. Q RT-PCR reactions consisted of 10 μl of SsoFast Eva Green® Supermix (Bio-Rad Laboratories, CA, USA), 20 pmol of primers, 1 μl of cDNA, and distilled deionized water to a total volume of 20 μl. RT-PCR was performed on a CFX 96 System® (Bio-Rad Laboratories, CA, USA). The following thermal cycler regime was used to amplify the fragments of the CsRFS and Pa × gGolSII, IV transcripts, respectively: 1 cycle of 30 s at 95°C, 39 cycles of 95°C for 5 s, and 58°C for 30 s, followed by 1 cycle of 95°C for 30 s, and a melt curve cycle of 58–95 °C increment of 0.5°C for 5 sec. Relative expression was calculated using the following equation ∆ct = 2-(ct target gene- ct TIF5A), where TIF5A is used as the reference gene (Coleman et al. 2009). GolSRNAi lines and wild-type trees were subjected to cold treatment by placing the transgenic and control trees in a refrigerated room (2 °C) with light (1.17 μmol s–1 m–2) for 12 days. Leaf samples were collected on days 4, 7 and 12. Source leaf tissue samples were used for RNA and soluble sugar extractions to measure transcript and product abundance. Inoculations and disease analysis Detached leaf inoculations were conducted using modified methods previously described by Dowkiw et al. (2003). A single fully expanded leaf between the fifth and ninth leaf plastocron index was detached at the base of stem: petiole junction from each biological replicate (individual plant) of each transformation event and wild type (n = 3–5 per event). The abaxial leaf surface was inoculated at a concentration of 8 mg of Melampsora aecidiodes (strain Ma07VIC01) urediniospores in 100 ml of 0.01% agar: water (w:v) and then floated abaxial surface facing up in a 150 mm sterilized petri dishes with autoclaved deionized water. Control leaves were mock inoculated with 0.01% agar: water without urediniospores. Leaves were maintained for 14 days under controlled growth chamber conditions (18 °C, 18 h/6 h light/dark cycle, 400–500 μmoles m–2 s–1). Leaves were re-floated as needed throughout the experiment. The inoculation was repeated twice. At the first sight of pustule development, the day (latent period) for each leaf was recorded. Fourteen days after inoculations (dpi), digital images were taken of each petri dish and final number of pustules were counted. Results were analyzed using the Kruskal–Wallis test for non-parametric analysis of variance. Pairwise analysis of each event was performed using the Nemenyi–Damico–Wolfe–Dunn post hoc test for multiple comparisons. Additional inoculations were carried out to quantify sugars, conjugated-salicylic acid, and gene expression analysis. At each time point, (P39; 20, 24, 48 and 96 hpi, OEGolS and OERFS lines; 24, 48 and 96 hpi) a 2 cm leaf disk was removed for RNA extraction, the rest of the leaf was cut in half for sugar and conjugated-salicylic acid, then immediately flash frozen and stored at −80 °C. Each event was biological replicated (n = 2–3). Extra replicates of OEGolS_6 and P39 were included and maintained for 14 dpi as a positive control for rust development. Sugar and conjugated-salicylic acid quantification Non-structural carbohydrates were extracted according to Park et al. (2009), briefly, ~50 mg of leaf tissue was ground and lyophilized for 24 h, then treated with 4 ml of methanol:chloroform:water (12:5:3) overnight at 4 °C. Following incubation, the solution was centrifuged and supernatant collected. The pellet was washed twice with 4 ml of the same solution and the supernatants were pooled (12 ml). Water (5 ml) was added to the pooled supernatant, mixed and centrifuged to induce phase separation. An aliquot (1 ml) of the upper phase was collected and dried using a vacuum centrifuge. For the RNAiGolS transgenic lines, the pellet was re-suspended in 1 ml of water and analyzed for, galactinol on an DX-600 anion exchange HPLC (Dionex, Sunnyvale, CA, USA) fit with a MA-1 column (Dionex) and electrochemical pulse amperometric detector. Post-column detection was performed using NaOH at a rate of 100 mM min–1. Fucose was added as internal standard. For CsRFS lines, sugars were measured using the ICS-5000 IC fit with Rezex RPM column (Phenomenex, CA, USA) with electrochemical pulse amperometric detector. Post-column detection was performed using NaOH at a rate of 100 mMmin–1. Fucose or galactitol were added as internal standards. For inoculated and control leaves, a Dionex ICS-5000 HPLC was used fit with a Hi-Plex Ca column (Agilent Technologies, Santa Clara, CA, USA) with a flow rate of 0.170 ml min–1 with a column temperature of 70 °C and post-column detection. Salicylic acid extraction was based on Yalpani et al. (1991) and Meuwly and Métraux (1993) with some modifications. Leaf tissue was ground and lyophilized for 24 h, 5 μl of internal standard (3, 4, 5 tri methoxyl cinnamic acid; 13 mg ml–1) was added to ~50 mg of tissue. One milliliter of 80% methanol was added to the homogenate, mixed by vortex, sonicated for 5 min, centrifuged for 5 min and the supernatant was collected. The pellet was re-suspended in 0.5 ml 100% methanol, and the sonication and centrifugation were repeated. The supernatants were combined and 10 μl of 0.2 M NaOH was added to the mixture and evaporated in a SpeedVac concentrator. To the residue, 250 μl TCA (5% solution in water) was added and mixed by vortex. The mixture was partitioned with 800 μl of ethyl acetate: cyclohexane (1:1, v/v) resulting in the separation of an upper phase of organic solvent with free SA and a lower aqueous phase with SAG (SA 2-O-D-glucoside). The partitioning was carried out twice. The organic phase was evaporated to dryness in a SpeedVac concentrator. The aqueous phase with SAG was hydrolyzed with 300 μl of 8 M hydrochloric acid to the remaining TCA fraction and heating the sample at 80 °C for 1 h. The acid fraction was partitioned with ethyl acetate: cyclohexane as described above. Sixty microliter of 0.2 M sodium acetate (pH 5.5) was added and evaporated in a SpeedVac concentrator. The residue was dissolved in 300 μl of methanol. Samples were analyzed in the Summit HPLC (Dionex) fit with a Symmetry C18 column (Waters) with a PDA-100 Photodiode Array Detector (Dionex). Salicylic acid from the samples was eluted from the column at a flow rate of 0.7 ml min. using a gradient from 95% A (99.9% water: 0.1% trifluoroacetic acid (TFA)) to 45% B (74.9% acetonitrile: 25% methanol: 0.1% TFA) over 50 min, followed by a 10-min wash with 75% B and re-acclimation of the column with 95% A for 10 min. Quantitative real-time polymerase chain reaction Leaf disks cut from detached leaves inoculated with urediniospores from M. aecidiodes and mock inoculated (sterile water) controls were used for qRT-PCR. Total RNA was extracted using a QIAGEN RNeasy Mini Plant Kit and treated with 1 unit μl–1 of DNase 1 (Invitrogen). First strand cDNA was synthesized with a poly t (18) primer using the High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems). Quantitative real-time PCR was run using Fast SYBR Green Master Mix (Life Technologies) on a Viia7 ABI thermocycler with primers Amplification was performed with 10ng of cDNA, 500 nM of each primer, and 5 μl of SYBR Green at a total volume of 10 μl. Fold-change of gene expression was calculated using the ΔΔCt as described by Rinaldi et al. (2007). Relative gene expression analysis comparing the wild-type to the overexpression lines was done using inoculated tissues using CELL DIVISION CONTROL2 as the reference gene (Rinaldi et al. 2007). Results were analyzed using an analysis of variance with means of three biological replicates and three technical replicates. Pairwise analysis of each event was performed using Tukey's post hoc test for multiple comparison. All primer sequences are available in Supplementary Data 1 at Tree Physiology Online. Relative electrolyte leakage A total of 28, 2 cm leaf disks were cut from two fully expanded leaves between the fifth and ninth leaf plastocron index. A total of 14 random leaf disks were floated in 100 mm sterilized petri dishes with either 150 mM of H2O2 (treated) or autoclaved deionized water (control). After 24 h, leaf disks were moved to 50 ml falcon tubes with 35 ml of autoclaved deionized water. After another 24 h, the initial electrolyte leakage was measured three times (technical replicates) using a VWR portable conductivity meter (model 2052). The final electrolyte leakage was measure after falcon tubes were submerged in a water bath at 65 °C for 60 min and cooled at room temperature for 24 h. The relative electrolyte leakage (Rel. E.L.) was calculated using the mean of technical replicates where Rel. E.L. = (Treated Initial E.L./ Final E.L. – Control Initial E.L./ Final E.L.) × 100. Results were analyzed using the Kruskal–Wallis test for non-parametric analysis of variance with the means of biological replicates (n = 3–5). Pairwise analysis of each event was performed using the Nemenyi–Damico-Wolfe–Dunn post hoc test for multiple comparisons. Results Growth characteristics and non-structural carbohydrates of transgenic Populus alba × grandidentata with downregulation of a galactinol synthase gene (GolSRNAi) and overexpression of a raffinose synthase gene (CsRFS) Populus alba × grandidentata hybrid P39 was transformed with an RNAi construct to silence the P.a × gGolS gene family members (see section Materials and methods). RNAi-suppressed lines GolSRNAi_3, GolSRNAi_4, GolSRNAi_11 and GolSRNAi_16 each displayed lower transcript abundance of the native P.a × gGolS gene family members II and IV compared to the wild type under stress conditions (see Figure S1 available as Supplementary Data at Tree Physiology Online). In source leaf tissue, galactinol concentrations were lower in line GolSRNAi_3 and significantly lower in GolSRNAi_4, GolSRNAi_11, and GolSRNAi_16 compared to wild type (see Figure S2 available as Supplementary Data at Tree Physiology Online). Reduction in P.a × gGolS transcripts and galactinol concentrations did not impact plant height or diameter (see Figure S3 available as Supplementary Data at Tree Physiology Online). Hybrid poplar trees overexpressing a Cucumber sativus raffinose synthase gene (see section Materials and methods) (CsRFS); OERFS_2, OERFS_7, OERFS_8, and OERFS_9, had higher concentrations of raffinose in source leaf tissue and significantly higher levels in stem phloem than wild-type trees (see Figure S4 available as Supplementary Data at Tree Physiology Online). Growth was not impacted in any of the OERFS lines (see Figure S5 available as Supplementary Data at Tree Physiology Online), while growth was reduced in lines OEGolS_6 and OEGolS_11 which were the lines with the highest overexpression of galactinol synthase (Unda et al. 2016). Overexpression of AtGolS3 and CsRFS attenuates resistance to Melampsora aecidiodes poplar leaf rust disease To test whether altered galactinol and raffinose accumulation modified biotrophic pathogen resistance, we used transgenic Populus alba × grandidentata lines overexpressing the AtGolS3 and CsRFS, as well as RNAi lines with reduced expression of GolS gene. The fully expanded leaves between the fifth and ninth leaf plastocron index of untransformed Populus alba × grandidentata control plants, as well as each of the transgenic lines were inoculated with M. aecidiodes urediniospores. Latent period (time until uredinia emerge on the abaxial leaf surface) and the number of uredinia pustules at 14 days post-inoculation (dpi) were measured. In lines overexpressing GolS and RFS, uredinia were observed above the pubescence of the abaxial leaf surface as early as nine and 11 dpi, respectively (see Figure S6 available as Supplementary Data at Tree Physiology Online). No disease symptoms or late development of uredinia were observed at 14 dpi in each of the RNAi lines and wild-type trees. Latent period was significantly different between lines (Kruskal–Wallis test; P = 5.351 × 10−7). A post hoc multiple comparison using Nemenyi–Damico–Wolfe–Dunn (NDWD) test indicated that the wild type had significantly delayed rust development when compared to each of the OEGolS lines, OERFS_2, OERFS_8 and OERFS_9. Moreover, GolSRNAi lines also had significantly fewer uredinia at 14 dpi than OEGolS_6 and OEGolS_11 (Figure 1). Figure 1. View largeDownload slide Summary of Melampsora aecidiodes poplar leaf rust development. Number of days post-inoculation until the first observation of pustules protruding from the abaxial leaf surface (latent period). Results were analyzed using the Kruskal–Wallis test for non-parametric analysis of variance. Significant differences in latent period were found among events (P = 5.351 × 10−7). Figure 1. View largeDownload slide Summary of Melampsora aecidiodes poplar leaf rust development. Number of days post-inoculation until the first observation of pustules protruding from the abaxial leaf surface (latent period). Results were analyzed using the Kruskal–Wallis test for non-parametric analysis of variance. Significant differences in latent period were found among events (P = 5.351 × 10−7). Similarly, the number of rust uredinia at 14 dpi indicated significantly higher rust severity in the OEGolS and OERFS lines. The wild-type trees produced, on average, less than one pustule per leaf at 14 dpi. Among the lines overexpressing AtGolS3, OEGolS_6 and OEGolS_11 showed the greatest amount of infection, averaging more than 50 pustules per leaf. In NDWD tests, all lines overexpressing AtGolS3 and CsRFS except one (OERFS_7) had significantly more rust pustules than the wild type (P < 0.05). All four GolSRNAi lines also produced fewer pustules than OEGolS_6 and OEGolS_11 (P < 0.019) (Figure 2). Figure 2. View largeDownload slide Count of pustules protruding from the abaxial leaf surface 14 days post-inoculation. Results were analyzed using the Kruskal–Wallis test for non-parametric analysis of variance. Significant differences for pustule counts were found among events (P = 2.989 × 10−5). Pairwise analysis of each event was performed using the Nemenyi–Damico–Wolfe–Dunn post hoc test for multiple comparisons. Significant differences are presented alongside (n = 6–10). Figure 2. View largeDownload slide Count of pustules protruding from the abaxial leaf surface 14 days post-inoculation. Results were analyzed using the Kruskal–Wallis test for non-parametric analysis of variance. Significant differences for pustule counts were found among events (P = 2.989 × 10−5). Pairwise analysis of each event was performed using the Nemenyi–Damico–Wolfe–Dunn post hoc test for multiple comparisons. Significant differences are presented alongside (n = 6–10). Response to rust alters sucrose and galactinol concentrations and the expression levels of the raffinose biosynthetic pathway Glucose-6-phosphate (G-6-P) is the product of sucrose metabolism and the subsequent phosphorylation of free glucose. G-6-P is the precursor to myo-inositol, which can participate in galactinol and consequently raffinose biosynthesis. We quantified the soluble sugars and sugar alcohols in the raffinose pathway and measured key biosynthetic gene expression during the wild type response to rust infection. At 20 h post-inoculation (hpi), sucrose concentrations were significantly elevated in inoculated leaves (5.66 μg mg–1) as compared to the un-inoculated control (2.25 μg mg–1) (P < 0.05). The ratio of sucrose to free hexose sugars (glucose + fructose) was also increased in inoculated tissue at 20 hpi, and nearly significant (P = 0.07). Myo-inositol and raffinose concentrations were not altered; however, galactinol was significantly decreased in inoculated leaves at 20 hpi (P = 0.037). These patterns of altered sucrose and galactinol concentrations were evident at 24 hpi, but were not significant (Figure 3) Figure 3. View largeDownload slide Concentration of sucrose, sucrose to hexose ratio, myo-inositol, galactinol and raffinose (μg/mg) in inoculated and non-inoculated control leaves at 20, 24, 48 and 96 h post-inoculation (hpi) in the wild type (P39). Significance differences were analyzed using student's t-tests between inoculated and control leaves at each time point. The data are mean ± SE of three biological replicates. *P < 0.05. Figure 3. View largeDownload slide Concentration of sucrose, sucrose to hexose ratio, myo-inositol, galactinol and raffinose (μg/mg) in inoculated and non-inoculated control leaves at 20, 24, 48 and 96 h post-inoculation (hpi) in the wild type (P39). Significance differences were analyzed using student's t-tests between inoculated and control leaves at each time point. The data are mean ± SE of three biological replicates. *P < 0.05. Quantitative Real-time PCR was used to measure the gene expression profiles of key biosynthetic genes in the raffinose pathway. We used leaf tissue sub-sampled from the sugar quantification experiment to have corresponding results. Transcripts levels of a myo-inositol synthase, Inositol-3-Phosphate Synthase (PtI3PS, Potri.007g089000) were increased 1.7, and 2.5 and 6-fold in inoculated leaves at 20, 24, and 96 hpi, respectively. In contrast, two galactinol synthases (PtGolS1, Potri.008G189400 and PtGolS2, Potri.010G042000) were each strongly suppressed at 20 hpi, and then were up-regulated at 48 and 96 hpi, respectively. The poplar gene encoding the final enzyme in the raffinose pathway; Raffinose Synthase (PtRFS, Potri.006G065700) had higher transcript levels at 24 hpi and then smaller incremental increases at 48 and 96 hpi (Figure 4) Figure 4. View largeDownload slide Quantitative real-time PCR (qRT-PCR) gene expression analysis of INOSITOL-3-PHOSPHATE SYNTHASE, GALACTINOL SYNTHASE1, GALACTINOL SYNTHASE2 and RAFFINOSE SYNTHASE in wild-type inoculated and control leaf tissue at 20, 24, 48 and 96 hpi. CELL DIVISION CONTROL2 was used as a housekeeping reference gene to calculate the differential expression using the 2ΔΔCt equation. Results represent the mean of three biological replicates and three technical replicates. Figure 4. View largeDownload slide Quantitative real-time PCR (qRT-PCR) gene expression analysis of INOSITOL-3-PHOSPHATE SYNTHASE, GALACTINOL SYNTHASE1, GALACTINOL SYNTHASE2 and RAFFINOSE SYNTHASE in wild-type inoculated and control leaf tissue at 20, 24, 48 and 96 hpi. CELL DIVISION CONTROL2 was used as a housekeeping reference gene to calculate the differential expression using the 2ΔΔCt equation. Results represent the mean of three biological replicates and three technical replicates. Overexpression of AtGolS3 and CsRFS suppress the up-regulation of PR1 We further characterized the wild-type response to M. aecidiodes inoculation by quantifying the expression of genes integral to defense signaling at 20, 24, 48 and 96 hpi with qRT-PCR. Glutamate receptors function in Ca2+ influx and the production of nitric oxide and reactive oxygen species (Manzoor et al. 2013). At 20 hpi, two GLUTAMATE RECEPTOR genes (PtGLR3.6; Potri.005G102700 and PtGLR3.2; Potri.009G168300) each had more abundant transcripts (2.1 and 9.5-fold, respectively) in inoculated leaves than in the control leaves (Figure 5). In our qRT-PCR analyses using wild-type leaves, transcripts from (PtPIP5K, Potri.008G128800) were more abundant (>3-fold) in inoculated leaf tissue in comparison to control leaves at 20, 24 and 96 hpi (Figure 5). Finally, we tested the expression of SA biosynthetic and signaling genes; PAL1 (Potri.006G126800), NPR1 (Potri.006G148100) and PR1 (Potri.009g082900). Each of these genes had elevated transcript levels at multiple time points in qRT-PCR comparison of inoculated and control wild-type leaves; however, their strongest expression were in succession at 20, 24 and 96 hpi, respectively (Figure 6). Figure 5. View largeDownload slide qRT-PCR gene expression analysis of PHENYLALANINE AMMONIA-LYASE 1, NONEXPRESSOR OF PATHOGENESIS-RELATED1 and PATHOGENESIS-RELATED1 in wild-type inoculated and control leaf tissue at 20, 24, 48 and 96 hpi. CELL DIVISION CONTROL2 was used as a housekeeping reference gene to calculate the differential expression using the 2ΔΔCt equation. Results represent the mean of three biological replicates and three technical replicates. Figure 5. View largeDownload slide qRT-PCR gene expression analysis of PHENYLALANINE AMMONIA-LYASE 1, NONEXPRESSOR OF PATHOGENESIS-RELATED1 and PATHOGENESIS-RELATED1 in wild-type inoculated and control leaf tissue at 20, 24, 48 and 96 hpi. CELL DIVISION CONTROL2 was used as a housekeeping reference gene to calculate the differential expression using the 2ΔΔCt equation. Results represent the mean of three biological replicates and three technical replicates. Figure 6. View largeDownload slide qRT-PCR gene expression analysis of GLUTAMATE RECEPTOR3.2, GLUTAMATE RECEPTOR3.6, PHOSPHATIDYLINOSITOL-4-PHOSPHATE-5-KINASE and PHOSPHOLIPASE D in wild-type inoculated and control leaf tissue at 20, 24, 48 and 96 hpi. CELL DIVISION CONTROL2 was used as a housekeeping reference gene to calculate the differential expression using the 2ΔΔCt equation. Results represent the mean of three biological replicates and three technical replicates. Figure 6. View largeDownload slide qRT-PCR gene expression analysis of GLUTAMATE RECEPTOR3.2, GLUTAMATE RECEPTOR3.6, PHOSPHATIDYLINOSITOL-4-PHOSPHATE-5-KINASE and PHOSPHOLIPASE D in wild-type inoculated and control leaf tissue at 20, 24, 48 and 96 hpi. CELL DIVISION CONTROL2 was used as a housekeeping reference gene to calculate the differential expression using the 2ΔΔCt equation. Results represent the mean of three biological replicates and three technical replicates. We then tested the expression levels of PIP5K, NPR1 and PR1 in inoculated OEGolS and OERFS lines and quantified the levels of conjugated-SA. HPLC quantification revealed a significant increase in the levels of conjugated-SA in the wild-type leaves at 24 hpi in comparison to the OEGolS_6 and OEGolS_11 (P = 0.04 and P = 0.02, respectively) (see Figure S7 available as Supplementary Data at Tree Physiology Online). The results of qRT-PCR in the OEGolS3 and OERFS lines indicated that PIP5K, NPR1 and PR1 were up-regulated in all lines over the course of infection (24, 48 and 96 hpi). However, the relative expression levels in inoculated OEGolS3 and OERFS lines were significantly lower than in inoculated wild-type leaves at 24 hpi for PIP5K and NPR1, and 48 and 96 hpi for PR1 (Figures 7–9). The level of transcript repression of these genes was correlated with the greater rust infection in the OEGolS compared to the OERFS lines. Figure 7. View largeDownload slide Relative expression of PHOSPHATIDYLINOSITOL-4-PHOSPHATE-5-KINASE, NONEXPRESSOR OF PATHOGENESIS-RELATED1 and PATHOGENESIS-RELATED1 in the wild type (P39) compared to OEGolS_3, OEGolS_6, OEGolS_11, OERFS_2, OERFS_7 and OERFS_8 at 24 hpi. Results represent the mean and standard error of three biological replicates and three technical replicates of inoculated tissues. All values are relative to the housekeeping reference gene CELL DIVISION CONTROL2. Results were analyzed using an analysis of variance and pairwise analysis of each event was performed using Tukey's post hoc test for multiple comparison. Figure 7. View largeDownload slide Relative expression of PHOSPHATIDYLINOSITOL-4-PHOSPHATE-5-KINASE, NONEXPRESSOR OF PATHOGENESIS-RELATED1 and PATHOGENESIS-RELATED1 in the wild type (P39) compared to OEGolS_3, OEGolS_6, OEGolS_11, OERFS_2, OERFS_7 and OERFS_8 at 24 hpi. Results represent the mean and standard error of three biological replicates and three technical replicates of inoculated tissues. All values are relative to the housekeeping reference gene CELL DIVISION CONTROL2. Results were analyzed using an analysis of variance and pairwise analysis of each event was performed using Tukey's post hoc test for multiple comparison. Figure 8. View largeDownload slide Relative expression of PHOSPHATIDYLINOSITOL-4-PHOSPHATE-5-KINASE, NONEXPRESSOR OF PATHOGENESIS-RELATED1 and PATHOGENESIS-RELATED1 in the wild type (P39) compared to OEGolS_3, OEGolS_6, OEGolS_11, OERFS_2, OERFS_7 and OERFS_8 at 48 hpi. Results represent the mean and standard error of three biological replicates and three technical replicates of inoculated tissues. All values are relative to the housekeeping reference gene CELL DIVISION CONTROL2. Results were analyzed using an analysis of variance and pairwise analysis of each event was performed using Tukey's post hoc test for multiple comparison. Figure 8. View largeDownload slide Relative expression of PHOSPHATIDYLINOSITOL-4-PHOSPHATE-5-KINASE, NONEXPRESSOR OF PATHOGENESIS-RELATED1 and PATHOGENESIS-RELATED1 in the wild type (P39) compared to OEGolS_3, OEGolS_6, OEGolS_11, OERFS_2, OERFS_7 and OERFS_8 at 48 hpi. Results represent the mean and standard error of three biological replicates and three technical replicates of inoculated tissues. All values are relative to the housekeeping reference gene CELL DIVISION CONTROL2. Results were analyzed using an analysis of variance and pairwise analysis of each event was performed using Tukey's post hoc test for multiple comparison. Figure 9. View largeDownload slide Relative expression of PHOSPHATIDYLINOSITOL-4-PHOSPHATE-5-KINASE, NONEXPRESSOR OF PATHOGENESIS-RELATED1 and PATHOGENESIS-RELATED1 in the wild type (P39) compared to OEGolS_3, OEGolS_6, OEGolS_11, OERFS_2, OERFS_7 and OERFS_8 at 96 hpi. Results represent the mean and standard error of three biological replicates and three technical replicates of inoculated tissues. All values are relative to the housekeeping reference gene CELL DIVISION CONTROL2. Results were analyzed using an analysis of variance and pairwise analysis of each event was performed using Tukey's post hoc test for multiple comparison. Figure 9. View largeDownload slide Relative expression of PHOSPHATIDYLINOSITOL-4-PHOSPHATE-5-KINASE, NONEXPRESSOR OF PATHOGENESIS-RELATED1 and PATHOGENESIS-RELATED1 in the wild type (P39) compared to OEGolS_3, OEGolS_6, OEGolS_11, OERFS_2, OERFS_7 and OERFS_8 at 96 hpi. Results represent the mean and standard error of three biological replicates and three technical replicates of inoculated tissues. All values are relative to the housekeeping reference gene CELL DIVISION CONTROL2. Results were analyzed using an analysis of variance and pairwise analysis of each event was performed using Tukey's post hoc test for multiple comparison. Overexpression of AtGolS3 and CsRFS enhances tolerance to ROS To test the role of galactinol and raffinose in ROS tolerance, we exposed leaf disks to 150 mM of H2O2 for 24 h and then measured electrolyte leakage. After 24 h, relative electrolyte leakage indicated significant differences between the overexpression lines and wild-type leaves and the RNAi lines (P = 1.738 × 10−4). The wild-type leaves had significantly higher relative electrolyte leakage than each OEGolS lines, OERFS_2, and OERFS_9. Moreover, GolSRNAi_3 and GolSRNAi_16 had higher electrolyte leakage than the wild-type leaves and were significantly different than all of the overexpression lines (Figure 10). Figure 10. View largeDownload slide Summary of the relative electrolyte leakage of leaf disks exposed to 24 h of 150 mM of H2O2 (treated) or autoclaved deionized water (control). Results represent the mean and standard error of 3–5 biological replicates where relative electrolyte leakage = (Treated Initial E.L./ Final E.L – Control Initial E.L./ Final E.L) × 100. Results were analyzed using the Kruskal–Wallis test for non-parametric analysis of variance. Pairwise analysis of each event was performed using the Nemenyi–Damico–Wolfe–Dunn post hoc test for multiple comparisons and are presented at the right of the figure. Figure 10. View largeDownload slide Summary of the relative electrolyte leakage of leaf disks exposed to 24 h of 150 mM of H2O2 (treated) or autoclaved deionized water (control). Results represent the mean and standard error of 3–5 biological replicates where relative electrolyte leakage = (Treated Initial E.L./ Final E.L – Control Initial E.L./ Final E.L) × 100. Results were analyzed using the Kruskal–Wallis test for non-parametric analysis of variance. Pairwise analysis of each event was performed using the Nemenyi–Damico–Wolfe–Dunn post hoc test for multiple comparisons and are presented at the right of the figure. Discussion Suppression of galactinol biosynthesis is necessary for leaf rust defense response Overexpression of AtGol3 and CsRFS in poplar dramatically alters sucrose metabolism and the host's ability to coordinate a defense response to leaf rust infection. Sucrose is one of the main products of photosynthesis and functions as the primary carbohydrate transported from source organs, a precursor to numerous plant metabolites, and signaling molecule (Lemoine 2000). In rice, sucrose is a key activator of anthocyanin biosynthesis and PR genes during plant defense response and pre-treatment has reduced proliferation of the hemibiotroph Magnaporthe oryzae (Gómez-Ariza et al. 2007, Serrano et al. 2012). In addition, partial resistance to multiple rust species was conferred through the wheat Lr67 locus that reduces glucose uptake to the host intracellular space (Moore et al. 2015). These results support a role for both elevated sucrose and reduced glucose in plant immunity; however, previous studies did not investigate whether changes also occurred in accumulation of myo-inositol, galactinol or raffinose. In poplar leaf rust transcriptome analysis, increased expression of I3PS was previously observed as part of the resistance response (Rinaldi et al. 2007). Along with the reductions in hexose sugars, galactinol and suppressed expression of two GolS genes, we expected to observe elevated levels of myo-inositol. The absence of changes in the levels of myo-inositol could be explained by the observation that myo-inositol antagonizes SA (Chaouch and Noctor 2010). Together, these results point toward a shunt diverting myo-inositol away from galactinol synthesis and toward other down-stream products as a necessary event in response to poplar leaf rust. Clearly, the overexpression of AtGolS3 and/or CsRFS along with accumulation of galactinol and raffinose directly oppose this node of the defense response. We also characterized the expression of known SA signaling genes involved in poplar leaf rust interactions (Rinaldi et al. 2007). Our finding revealed the up-regulation of several genes involved in poplar leaf rust interactions (PAL1, NPR1, PR1), suggesting that a reduction in galactinol levels may be a key modulator toward SA defense gene. In addition, transcriptome analysis comparing unchallenged wild type and OEGolS_6 (Unda et al. 2016) indicated reduced transcript abundance of two positive regulators of defense signaling; SUPPRESSOR OF NPR1 CONSTITUTIVE 4 and several NPR3-like genes, in the overexpression line. This may suggest that the accumulation of galactinol constitutively represses defense signaling events upstream of SA biosynthesis. Interestingly, in each GolSRNAi line uredinia counts were numerically higher than the wild-type leaves, which suggests that constitutively lower galactinol levels may also suppress some basal resistance toward leaf rusts. This is consistent with exogenous galactinol enhancing PR1a and PR1b transcripts in tobacco (Kim et al. 2008). Likewise, in transcriptome analysis several PR genes and chitinases were also up-regulated in the OEGolS_6 line (Unda et al. 2016). Overexpression of AtGolS3 and CsRFS transcriptionally inhibit PI-PLC/PLD pathway through ROS scavenging As part of a plant immune response, Zhang and Xiao (2015) proposed a biphasic model regulating PA-ROS-SA defense signaling. Initially, PI-PLC produced PA activates an early immediate cascade where RESPIRATORY BURST OXIDASE HOMOLOG D (RHOBD) production of ROS induces the accumulation of SA. A feed forward loop is then activated by PLD produced PA, which triggers a second wave of ROS and SA production, ultimately inducing PR1. This model is supported by pharmacological inhibitors of PLC, PLD and PtdIns(4,5)P2 each independently suppressing SA accumulation (Rodas-Junco et al. 2013) and conversely through SA activating PLC and PLD proteins (Profotova et al. 2006). In a previous study (Unda et al. 2016), RNA-Seq analysis of the unchallenged wild-type poplar and OEGolS_6 revealed reduced transcript abundance of several PIP5K genes in the transgenic line. This group included an ortholog of PIP5K9 a negative regulator of neutral invertases that inhibit sucrose metabolism (Lou et al. 2007). Ritsema et al. (2009) indicated that small GTPases are necessary for proper sugar sensing, while RHO proteins can activate PIP5K (Ren et al. 1996) and PLD (Liscovitch et al. 1999). This evidence points toward a signaling pathway in addition to the biosynthetic pathway linking sucrose to PA through PIP5K (Vallurua and Van den Ende 2011). In our previous research, we identified a SNP within a PIP5K gene (Potri.008G128800) that was associated with leaf rust resistance in P. trichocarpa (La Mantia et al. 2013). Transcripts from this gene were also less abundant in each of the OEGolS and OERFS lines compared to the wild-type leaves (Figures 7–9). The repression of these PIP5K gene members suggest that OEGolS and OERFS focus the biosynthetic precursors and transcriptional regime away from PtdIns(4,5)P2 production. The RNA-Seq analysis (Unda et al.2016) also indicated a constitutive increase in transcript abundance of ENHANCED DISEASE RESISTANCE 2 (EDR2), a negative regulator of SA defense (Tang et al. 2005). EDR2 binds PtdIns4P, the substrate of PIP5Ks (Vorwerk et al. 2007). Therefore, diversion away from the PI-PLC pathway may repress SA defense signaling genes. However, the regulation of EDR2, possibly through PtdIns4P, and its impact on PtdIns(4,5)P2 synthesis has not been explored. In addition, PIP5K was strongly up-regulated in the wild-type defense response at 20 hpi which coincided with increased transcript abundance of a PLD (Figure 5). PLD transcripts were suppressed after 20 hpi while PIP5K transcripts were elevated, to a lesser degree, at 24 and 48 hpi and then more strongly expressed at 96 hpi which may be indicative of a second response wave described by Zhang and Xiao (2015). However, it should be stated that several isoforms of PLDs negatively regulate SA (Zhao et al. 2013) and none of the PLD family members have been functionally characterized in poplar. Calcium (Ca2+) and ROS are also transmitted in waves to propagate stress signals from cell to cell (Mittler et al. 2011, Gilroy et al. 2014). This model may integrate precisely into the PI-PLC signaling pathway where PIP5K produced PtdIns(4,5)P2 is cleaved into InsP3; a precursor to InsP6 which increases cytosolic Ca2+, and diacyl glycerol; a precursor to PA which activates RHOBD. Unchallenged OEGolS_6 showed lower transcript abundance of four GLUTAMATE RECEPTOR2 (GLR2) and two GLR3 genes in comparison to the wild type (Unda et al. 2016). GLRs function as Ca2+ channels, but are necessary for ROS and nitric oxide production and disease resistance response (Manzoor et al. 2013). QRT-PCR revealed a robust elevation of transcripts from GLR3.2 and GLR3.6 at 20 hpi in inoculated wild-type leaves (Figure 5). Myo-inositol, galactinol and raffinose each play important roles as regulators of ROS homeostasis. Lower levels of myo-inositol in the Arabidopsis catalase2 mutant were associated with SA-dependent cell death (Chaouch and Noctor 2010). In addition, overexpression of a wheat GolS in Arabidopsis and rice increased expression of ROS-scavenging genes (Wang et al. 2015). Both galactinol and raffinose have inhibited radical-induced formation of 2,3-dihydroxy-benzoic acid, respectively (Nishizawa et al. 2008). We observed significantly lower amounts of relative electrolyte leakage after 24 h exposure to 150 mM of H2O2 in all lines overexpressing galactinol synthase (OEGolS) and nearly every OERFS line compared to the wild-type leaves (Figure 5). In OEGolS_6, transcriptome analysis revealed strong up-regulation of MYO-INOSITOL OXYGENASE 4 (MIOX4) (>5-fold) transcripts (Unda et al. 2016). MIOX4 uses myo-inositol to synthesize D-glucuronate, a precursor to the plant antioxidant ascorbic acid (Lorence et al. 2004). Thus, enhanced activity of MIOX4 would increase ROS tolerance, while further diverting the pool of myo-inositol away from the PI-PLC pathway. This may indicate that elevated galactinol and raffinose levels have a synergistic effect on ROS through suppressing signaling as an antioxidant and production via transcriptional repression of GLRs and PIP5Ks. Conclusion In the current study, we present a functional characterization of GolS and RFS validated as suppressors of biotrophic disease resistance and further elucidate the antagonism between JA and SA defense signaling. Results presented here point toward a transcriptional reprogramming to suppress galactinol accumulation as part of a biotrophic defense response. However, increased levels of galactinol and raffinose perturbs multiple components of the defense response allowing for enhanced disease progression. Future work is needed to further understand how galactinol and raffinose participate in regulating ROS, Ca2+ channels, PIP5K transcripts, PA and SA signaling. Supplementary Data Supplementary Data for this article are available at Tree Physiology Online. Acknowledgments The authors thank Dr Philippe Tanguay, Natural Resources Canada, for maintaining and providing the Melampsora aecidiodes strain. The authors also thank Genome British Columbia Applied Genomics Innovation Program (Project 103BIO) and Genome Canada Large-Scale Applied Research Project (Project168BIO) for their financial support. Conflict of interest None declared. Funding This work was supported by Genome British Columbia Applied Genomics Innovation Program (Project 103BIO) and Genome Canada Large-Scale Applied Research Project (Project168BIO), funds to R.C.H., S.D.M. and C.J.D. Authors' contribution J.L. conceived the research plan; C.D., S.D.M. and R.C.H. supervised the experiments; F.U. performed all experiments in the production of transgenic materials, quantification of sugars and salicylic acid, and contributed to the H2O2 experiments; J.L. performed all inoculations and QRT-PCR and contributed to the H2O2 experiments. F.U. and J.L. designed the experiments and analyzed the data; J.L. wrote the article with contributions of all the authors. C.D., S.D.M. and R.H. supervised and complemented the writing. References Azaiez A, Boyle B, Levée V, Séguin A ( 2009) Transcriptome profiling in hybrid poplar following interactions with Melampsora rust fungi. Mol Plant Microbe Interact  22: 190– 200. Google Scholar CrossRef Search ADS PubMed  Bruggeman Q, Raynaud C, Benhamed M, Delarue M ( 2015) To die or not to die? Lessons from lesion mimic mutants. Plant Physiol  6: 24. 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( 2014) Responses of Populus trichocarpa galactinol synthase genes to abiotic stresses. J Plant Res  127: 347– 356. Google Scholar CrossRef Search ADS PubMed  Author notes handling Editor Janice Cooke © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Tree Physiology Oxford University Press

Overexpression of AtGolS3 and CsRFS in poplar enhances ROS tolerance and represses defense response to leaf rust disease

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10.1093/treephys/tpx100
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Abstract

Abstract Plants respond to pathogens through an orchestration of signaling events that coordinate modifications to transcriptional profiles and physiological processes. Resistance to necrotrophic pathogens often requires jasmonic acid, which antagonizes the salicylic acid dependent biotrophic defense response. Recently, myo-inositol has been shown to negatively impact salicylic acid (SA) levels and signaling, while galactinol enhances jasmonic acid (JA)-dependent induced systemic resistance to necrotrophic pathogens. To investigate the function of these compounds in biotrophic pathogen defense, we characterized the defense response of Populus alba × grandidentata overexpressing Arabidopsis GALACTINOL SYNTHASE3 (AtGolS) and Cucumber sativus RAFFINOSE SYNTHASE (CsRFS) challenged with Melampsora aecidiodes, a causative agent of poplar leaf rust disease. Relative to wild-type leaves, the overexpression of AtGolS3 and CsRFS increased accumulation of galactinol and raffinose and led to increased leaf rust infection. During the resistance response, inoculated wild-type leaves displayed reduced levels of galactinol and repressed transcript abundance of two endogenous GolS genes compared to un-inoculated wild-type leaves prior to the up-regulation of NON-EXPRESSOR OF PR1 and PATHOGENESIS-RELATED1. Transcriptome analysis and qRT-PCR validation also revealed the repression of genes participating in calcium influx, phosphatidic acid biosynthesis and signaling, and salicylic acid signaling in the transgenic lines. In contrast, enhanced tolerance to H2O2 and up-regulation of antioxidant biosynthesis genes were exhibited in the overexpression lines. Thus, we conclude that overexpression of AtGolS and CsRFS antagonizes the defense response to poplar leaf rust disease through repressing reactive oxygen species and attenuating calcium and phosphatidic acid signaling events that lead to SA defense. Introduction Plant carbohydrates play a significant role in determining the outcome of plant-pathogen interactions. Successful pathogens acquire carbohydrates to further colonize host tissues and/or complete their life cycles. As an example, in several soil-borne diseases of peanut higher concentration of glucose in root exudates leads to greater spore germination and mycelial growth of Fusarium species (Li et al. 2013). In another plant pathosystem, the causal bacteria of rice blight disease Xanthomonas oryzae has evolved a TAL effector to evade host plant resistance responses specifically through activating transcription of OsSWEET11, a sucrose efflux transporter (Yang et al. 2006). However, modification to plant sugar concentrations can also induce the host resistance response. Exogenous applications of sucrose activates anthocyanin synthesis and PR gene expression in rice (Gómez-Ariza et al. 2007, Serrano et al. 2012). Furthermore, sucrose and glucose are precursors to myo-inositol, galactinol and the raffinose family oligosaccharides (RFOs). Recent evidence indicates these metabolites play an essential role in regulating abiotic stresses, reactive oxygen species (ROS), and enhancing defense against necrotrophic pathogens by modulating jasmonic acid (JA) signaling (Liu et al. 2007, Kim et al. 2008, Chaouch and Noctor 2010, Cho et al. 2010, Bruggeman et al. 2015). Myo-inositol is synthesized in a two-step process where phosphorylated glucose derived from sucrose metabolism is phosphorylated by INOSITOL-3-PHOSPHATE SYNTHASE (MIPS1/I3PS) and then dephosphorylated by INOSITOL MONOPHOSPHATASE (Loewus and Murthy 2000). Galactinol synthase (GolS) catalyzes the production of galactinol via the transfer of a galactosyl residue from UDP-d-galactose to myo-inositol. Galactinol serves as a precursor to RFOs; e.g., raffinose, stachyose and verbacose, where sucrose accepts the galactosyl residue and yields the larger oligosaccharides and myo-inositol (Lehle and Tanner 1973). Thus, these molecules are intimately linked through their biosynthetic pathways; however, the function of each RFO has not been individually determined. In Arabidopsis, myo-inositol-1-phosphate synthase1 (atips1/mips1/i3ps) loss of function mutants have reduced levels of myo-inositol and galactinol, accompanied by salicylic acid (SA)-dependent cell death and constitutively elevated SA levels. Elevated SA in the atips1mutant also reduced the growth of virulent Hyaloperonospora parasitica. (Meng et al. 2009). On the other hand, exogenous myo-inositol abolished cell death lesions by inhibiting SA accumulation in a catalase2 mutant. The application of exogenous myo-inositol also attenuated resistance to virulent bacteria (Chaouch and Noctor 2010). Galactinol is one of the products of myo-inositol metabolism that can also regulate several stress responses. For example, overexpression of a wheat GolS in Arabidopsis and rice enhanced expression of ROS-scavenging genes (Wang et al. 2015). GolS transcripts were also shown to be induced by water and salt stress, and necrotrophic fungi in several plant species (Kim et al. 2008, Cho et al. 2010, Zhou et al. 2014). Additionally, overexpression of GolS activated jasmonic acid signaling induced systemic resistance (Kim et al. 2008, Cho et al. 2010). In a similar fashion, overexpression of a rice UDP-glucose 4-epimerase gene in Arabidopsis led to accumulation of raffinose and enhanced tolerance to salt, drought and freezing stress (Liu et al. 2007). Recently, it has been shown that overexpression of AtGolS3 in hybrid poplar initiates metabolic changes that culminate in the formation of tension wood, which is a response to environmental stress on the tree (Unda et al. 2016). Myo-inositol can also be diverted to produce phosphatidylinositols (PtdIns) which leads to phosphatidic acid (PA) via the phosphoinositide-phospholipase C (PI-PLC) pathway. PA is a positive regulator of ROS and SA defense (de Jong et al. 2004, Munnik and Nielsen 2011). A key family of genes in the biosynthesis of PA are the phosphatidylinositol 4-phosphate 5-kinases (PIP5K), where type I and type II PIP5Ks produce phosphatidylinositol (4,5) bisphosphate (PtdIns(4,5)P2), a precursor to PA and inositol polyphosphates (InsP3) (Ma et al. 2006). Overexpression of a PHOSPHATIDIC ACID PHOSPHATASE and INOSITOL POLYPHOSPHATE 5-PHOSPHATASE, each result in compromised defense against biotrophic pathogens with reduced PR transcripts via suppressed PA and ROS, and InsP3 and Ca2+, respectively (Nakano, et al. 2013, Hung et al. 2014). PtdIns(4,5)P2 is also a required co-factor for phospholipase D (PLD) production of PA and PLD derived PA loops back to positively activate PIP5Ks (van den Bout and Divecha 2009). Moreover, this positive loop has been shown to be induced by exogenous SA, resulting in the activation of phospholipase C (PLC) and PLD (Profotova et al. 2006). Previously described in Unda et al. (2016), Populus alba × grandidentata hybrid P39 was transformed with a construct to overexpress the Arabidopsis thaliana GALACTINOL SYNTHASE3 (GolS) gene (35S:AtGolS3); and then characterized for altered growth and carbohydrate composition in leaf and stem tissues. Lines overexpressing AtGolS3; OEGolS_3, OEGolS_6, OEGolS_8 and OEGolS_11, each exhibited elevated levels of galactinol in stem phloem/developing xylem and source leaf tissue in comparison to the non-transformed wild-type poplar. OEGolS lines also had significantly higher levels of raffinose in source leaf tissues. OEGolS_6 and OEGolS_11 each were significantly shorter and had smaller stem diameters than wild-type trees, OEGolS_3, and OEGolS_8. The smaller stature also coincided with significantly higher amounts of glucose and lower total lignin content in woody tissues (Unda et al. 2016). Poplar trees are often challenged by poplar leaf rusts caused by several species of Melampsora (Fungi, Basidiomycota and Pucciniomycetes). Poplars and leaf rusts interact through effector triggered immunity or susceptibility, where virulent strains can decrease photosynthetic capacity and impact biomass, and increase susceptibility to additional pathogens (Steenackers et al. 1996, Hacquard et al. 2011). Poplar leaf rust disease has become a model system to study biotrophic pathogen interactions in tree species (Feau et al. 2007), and poplars offer a rich array of genomic tools to thoroughly investigate such interactions (Jansson and Douglas 2007, Duplessis et al. 2009, Hacquard et al. 2011). Transcriptome and genome-wide association study (GWAS) analysis on several Populus × Melampsora interactions have revealed an orchestrated defense response involving reactive oxygen species (ROS), phytohormones, Ca2+ influx, and myo-inositol signaling to regulate salicylic acid defense (Miranda et al. 2007, Rinaldi et al. 2007, Azaiez et al. 2009, Petre et al. 2012, La Mantia et al. 2013). In this study, we characterized the role of galactinol and raffinose in regulating the resistance response to a biotrophic pathogen of poplar, Melampsora aecidiodes, in Populus alba × grandidentata lines with enhanced and suppressed expression of a galactinol synthase and enhanced expression of raffinose synthase genes, independently. We now demonstrate that elevated galactinol and raffinose concentrations systemically attenuate the SA defense response by suppressing genes involved in PA biosynthesis and signaling, Ca2+ influx, and SA signaling, while enhancing ROS tolerance. Materials and methods Plasmids construction and plant transformation The Cucumis sativus RFS (AF073744) was cloned using the following primers: CsRFS2Fw 5′-TTCTTCTCACAAATGGCTCCTAGTT-3′ and CsRFS2Rv 5′-CAACAGCGACAACAAC AACAATCATT-3′.The gene was ligated into the pSM3 vector (pCambia 1390 with double 35 S promoter, Mansfield Lab, UBC). The vector was then transformed into Agrobacterium tumefasciens (EHA-105 strain). The Pa × gGolS-RNAi construct was generated using primers: GolSXhXb 5′-CTCGAGTCTAGACGGTTTGCTATGCCTTATTAT-3′ and GolSKpBa 5′-GGTACCGGATCCTGC CAGCATTGAAGTAGAGAG-3′. The restriction sites included on the primers sequence were used to amplify a 288 bp fragment of a conserved region of the galactinol synthase family. The fragment was ligated to the pKANNIBAL cloning vector (Helliwell and Waterhouse 2003). The NotI fragment from the pKANNIBAL vector was sub-cloned into the binary vector pART27 (Gleave 1992). The vector pART27 Pa × gGolSRNAi was transformed into A. tumefasciens EHA105 strain. The two vectors were then used for plant transformations Populus alba × grandidentata (P39) transformations were performed as described in Unda et al. (2016). Plants were confirmed as being transgenic by genomic DNA screening, using the CTAB (Sigma-Aldrich Co.) extraction method, and those identified as positive were then sub-cultured and multiplied on antibiotic-free woody plant media (WPM). Plant growth conditions and expression analysis of transgenic hybrid poplar trees Transgenic trees were multiplied in WPM media until approximately three to five plants of each transgenic event were of similar size, along with the appropriate control, non-transformed trees. The trees were then moved to 7.5 L pots containing perennial soil (50% peat, 25% fine bark and 25% pumice; pH 6.0)Trees were maintained on flood tables with supplemental lighting (16 h days) and daily water with fertilized water in the University of British Columbia greenhouse, Vancouver, BC Canada. After 5 or 6 months of growth (CsRFS and RNAiGols, respectively) trees were harvested. Transcript analysis to confirm presence of the transgene (CsRFS) or downregulation of the GolS (RNAiGolS) were performed by RT-PCR. RNA was isolated as per Kolosova et al. (2004), DNase I DIGEST kit (Ambion Inc.) was used to eliminate contaminating DNA. One microgram of RNA was used to generate cDNA using the iScript cDNA synthesis kit (Bio-Rad Laboratories, CA, USA). RT-PCR primers for the overexpression were: CsRFSrtFw 5′-TTTGGCATGCTTTGT GTGGATA-3′ and CsRFSrtRv 5′-CAAAATCCTCCATCGTCATCT-3′. RNAiGolS lines:, PtGolS3.1 (homolog to Pa × gGolSII as per Philippe et al. 2010), and Pa × gGolSIV Fw 5′-AACCTTTTGATTTCTCTAACC-3′ and Rv 5′-AAGGGAGTTGGTGT TGTTACG-3′. Q RT-PCR reactions consisted of 10 μl of SsoFast Eva Green® Supermix (Bio-Rad Laboratories, CA, USA), 20 pmol of primers, 1 μl of cDNA, and distilled deionized water to a total volume of 20 μl. RT-PCR was performed on a CFX 96 System® (Bio-Rad Laboratories, CA, USA). The following thermal cycler regime was used to amplify the fragments of the CsRFS and Pa × gGolSII, IV transcripts, respectively: 1 cycle of 30 s at 95°C, 39 cycles of 95°C for 5 s, and 58°C for 30 s, followed by 1 cycle of 95°C for 30 s, and a melt curve cycle of 58–95 °C increment of 0.5°C for 5 sec. Relative expression was calculated using the following equation ∆ct = 2-(ct target gene- ct TIF5A), where TIF5A is used as the reference gene (Coleman et al. 2009). GolSRNAi lines and wild-type trees were subjected to cold treatment by placing the transgenic and control trees in a refrigerated room (2 °C) with light (1.17 μmol s–1 m–2) for 12 days. Leaf samples were collected on days 4, 7 and 12. Source leaf tissue samples were used for RNA and soluble sugar extractions to measure transcript and product abundance. Inoculations and disease analysis Detached leaf inoculations were conducted using modified methods previously described by Dowkiw et al. (2003). A single fully expanded leaf between the fifth and ninth leaf plastocron index was detached at the base of stem: petiole junction from each biological replicate (individual plant) of each transformation event and wild type (n = 3–5 per event). The abaxial leaf surface was inoculated at a concentration of 8 mg of Melampsora aecidiodes (strain Ma07VIC01) urediniospores in 100 ml of 0.01% agar: water (w:v) and then floated abaxial surface facing up in a 150 mm sterilized petri dishes with autoclaved deionized water. Control leaves were mock inoculated with 0.01% agar: water without urediniospores. Leaves were maintained for 14 days under controlled growth chamber conditions (18 °C, 18 h/6 h light/dark cycle, 400–500 μmoles m–2 s–1). Leaves were re-floated as needed throughout the experiment. The inoculation was repeated twice. At the first sight of pustule development, the day (latent period) for each leaf was recorded. Fourteen days after inoculations (dpi), digital images were taken of each petri dish and final number of pustules were counted. Results were analyzed using the Kruskal–Wallis test for non-parametric analysis of variance. Pairwise analysis of each event was performed using the Nemenyi–Damico–Wolfe–Dunn post hoc test for multiple comparisons. Additional inoculations were carried out to quantify sugars, conjugated-salicylic acid, and gene expression analysis. At each time point, (P39; 20, 24, 48 and 96 hpi, OEGolS and OERFS lines; 24, 48 and 96 hpi) a 2 cm leaf disk was removed for RNA extraction, the rest of the leaf was cut in half for sugar and conjugated-salicylic acid, then immediately flash frozen and stored at −80 °C. Each event was biological replicated (n = 2–3). Extra replicates of OEGolS_6 and P39 were included and maintained for 14 dpi as a positive control for rust development. Sugar and conjugated-salicylic acid quantification Non-structural carbohydrates were extracted according to Park et al. (2009), briefly, ~50 mg of leaf tissue was ground and lyophilized for 24 h, then treated with 4 ml of methanol:chloroform:water (12:5:3) overnight at 4 °C. Following incubation, the solution was centrifuged and supernatant collected. The pellet was washed twice with 4 ml of the same solution and the supernatants were pooled (12 ml). Water (5 ml) was added to the pooled supernatant, mixed and centrifuged to induce phase separation. An aliquot (1 ml) of the upper phase was collected and dried using a vacuum centrifuge. For the RNAiGolS transgenic lines, the pellet was re-suspended in 1 ml of water and analyzed for, galactinol on an DX-600 anion exchange HPLC (Dionex, Sunnyvale, CA, USA) fit with a MA-1 column (Dionex) and electrochemical pulse amperometric detector. Post-column detection was performed using NaOH at a rate of 100 mM min–1. Fucose was added as internal standard. For CsRFS lines, sugars were measured using the ICS-5000 IC fit with Rezex RPM column (Phenomenex, CA, USA) with electrochemical pulse amperometric detector. Post-column detection was performed using NaOH at a rate of 100 mMmin–1. Fucose or galactitol were added as internal standards. For inoculated and control leaves, a Dionex ICS-5000 HPLC was used fit with a Hi-Plex Ca column (Agilent Technologies, Santa Clara, CA, USA) with a flow rate of 0.170 ml min–1 with a column temperature of 70 °C and post-column detection. Salicylic acid extraction was based on Yalpani et al. (1991) and Meuwly and Métraux (1993) with some modifications. Leaf tissue was ground and lyophilized for 24 h, 5 μl of internal standard (3, 4, 5 tri methoxyl cinnamic acid; 13 mg ml–1) was added to ~50 mg of tissue. One milliliter of 80% methanol was added to the homogenate, mixed by vortex, sonicated for 5 min, centrifuged for 5 min and the supernatant was collected. The pellet was re-suspended in 0.5 ml 100% methanol, and the sonication and centrifugation were repeated. The supernatants were combined and 10 μl of 0.2 M NaOH was added to the mixture and evaporated in a SpeedVac concentrator. To the residue, 250 μl TCA (5% solution in water) was added and mixed by vortex. The mixture was partitioned with 800 μl of ethyl acetate: cyclohexane (1:1, v/v) resulting in the separation of an upper phase of organic solvent with free SA and a lower aqueous phase with SAG (SA 2-O-D-glucoside). The partitioning was carried out twice. The organic phase was evaporated to dryness in a SpeedVac concentrator. The aqueous phase with SAG was hydrolyzed with 300 μl of 8 M hydrochloric acid to the remaining TCA fraction and heating the sample at 80 °C for 1 h. The acid fraction was partitioned with ethyl acetate: cyclohexane as described above. Sixty microliter of 0.2 M sodium acetate (pH 5.5) was added and evaporated in a SpeedVac concentrator. The residue was dissolved in 300 μl of methanol. Samples were analyzed in the Summit HPLC (Dionex) fit with a Symmetry C18 column (Waters) with a PDA-100 Photodiode Array Detector (Dionex). Salicylic acid from the samples was eluted from the column at a flow rate of 0.7 ml min. using a gradient from 95% A (99.9% water: 0.1% trifluoroacetic acid (TFA)) to 45% B (74.9% acetonitrile: 25% methanol: 0.1% TFA) over 50 min, followed by a 10-min wash with 75% B and re-acclimation of the column with 95% A for 10 min. Quantitative real-time polymerase chain reaction Leaf disks cut from detached leaves inoculated with urediniospores from M. aecidiodes and mock inoculated (sterile water) controls were used for qRT-PCR. Total RNA was extracted using a QIAGEN RNeasy Mini Plant Kit and treated with 1 unit μl–1 of DNase 1 (Invitrogen). First strand cDNA was synthesized with a poly t (18) primer using the High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems). Quantitative real-time PCR was run using Fast SYBR Green Master Mix (Life Technologies) on a Viia7 ABI thermocycler with primers Amplification was performed with 10ng of cDNA, 500 nM of each primer, and 5 μl of SYBR Green at a total volume of 10 μl. Fold-change of gene expression was calculated using the ΔΔCt as described by Rinaldi et al. (2007). Relative gene expression analysis comparing the wild-type to the overexpression lines was done using inoculated tissues using CELL DIVISION CONTROL2 as the reference gene (Rinaldi et al. 2007). Results were analyzed using an analysis of variance with means of three biological replicates and three technical replicates. Pairwise analysis of each event was performed using Tukey's post hoc test for multiple comparison. All primer sequences are available in Supplementary Data 1 at Tree Physiology Online. Relative electrolyte leakage A total of 28, 2 cm leaf disks were cut from two fully expanded leaves between the fifth and ninth leaf plastocron index. A total of 14 random leaf disks were floated in 100 mm sterilized petri dishes with either 150 mM of H2O2 (treated) or autoclaved deionized water (control). After 24 h, leaf disks were moved to 50 ml falcon tubes with 35 ml of autoclaved deionized water. After another 24 h, the initial electrolyte leakage was measured three times (technical replicates) using a VWR portable conductivity meter (model 2052). The final electrolyte leakage was measure after falcon tubes were submerged in a water bath at 65 °C for 60 min and cooled at room temperature for 24 h. The relative electrolyte leakage (Rel. E.L.) was calculated using the mean of technical replicates where Rel. E.L. = (Treated Initial E.L./ Final E.L. – Control Initial E.L./ Final E.L.) × 100. Results were analyzed using the Kruskal–Wallis test for non-parametric analysis of variance with the means of biological replicates (n = 3–5). Pairwise analysis of each event was performed using the Nemenyi–Damico-Wolfe–Dunn post hoc test for multiple comparisons. Results Growth characteristics and non-structural carbohydrates of transgenic Populus alba × grandidentata with downregulation of a galactinol synthase gene (GolSRNAi) and overexpression of a raffinose synthase gene (CsRFS) Populus alba × grandidentata hybrid P39 was transformed with an RNAi construct to silence the P.a × gGolS gene family members (see section Materials and methods). RNAi-suppressed lines GolSRNAi_3, GolSRNAi_4, GolSRNAi_11 and GolSRNAi_16 each displayed lower transcript abundance of the native P.a × gGolS gene family members II and IV compared to the wild type under stress conditions (see Figure S1 available as Supplementary Data at Tree Physiology Online). In source leaf tissue, galactinol concentrations were lower in line GolSRNAi_3 and significantly lower in GolSRNAi_4, GolSRNAi_11, and GolSRNAi_16 compared to wild type (see Figure S2 available as Supplementary Data at Tree Physiology Online). Reduction in P.a × gGolS transcripts and galactinol concentrations did not impact plant height or diameter (see Figure S3 available as Supplementary Data at Tree Physiology Online). Hybrid poplar trees overexpressing a Cucumber sativus raffinose synthase gene (see section Materials and methods) (CsRFS); OERFS_2, OERFS_7, OERFS_8, and OERFS_9, had higher concentrations of raffinose in source leaf tissue and significantly higher levels in stem phloem than wild-type trees (see Figure S4 available as Supplementary Data at Tree Physiology Online). Growth was not impacted in any of the OERFS lines (see Figure S5 available as Supplementary Data at Tree Physiology Online), while growth was reduced in lines OEGolS_6 and OEGolS_11 which were the lines with the highest overexpression of galactinol synthase (Unda et al. 2016). Overexpression of AtGolS3 and CsRFS attenuates resistance to Melampsora aecidiodes poplar leaf rust disease To test whether altered galactinol and raffinose accumulation modified biotrophic pathogen resistance, we used transgenic Populus alba × grandidentata lines overexpressing the AtGolS3 and CsRFS, as well as RNAi lines with reduced expression of GolS gene. The fully expanded leaves between the fifth and ninth leaf plastocron index of untransformed Populus alba × grandidentata control plants, as well as each of the transgenic lines were inoculated with M. aecidiodes urediniospores. Latent period (time until uredinia emerge on the abaxial leaf surface) and the number of uredinia pustules at 14 days post-inoculation (dpi) were measured. In lines overexpressing GolS and RFS, uredinia were observed above the pubescence of the abaxial leaf surface as early as nine and 11 dpi, respectively (see Figure S6 available as Supplementary Data at Tree Physiology Online). No disease symptoms or late development of uredinia were observed at 14 dpi in each of the RNAi lines and wild-type trees. Latent period was significantly different between lines (Kruskal–Wallis test; P = 5.351 × 10−7). A post hoc multiple comparison using Nemenyi–Damico–Wolfe–Dunn (NDWD) test indicated that the wild type had significantly delayed rust development when compared to each of the OEGolS lines, OERFS_2, OERFS_8 and OERFS_9. Moreover, GolSRNAi lines also had significantly fewer uredinia at 14 dpi than OEGolS_6 and OEGolS_11 (Figure 1). Figure 1. View largeDownload slide Summary of Melampsora aecidiodes poplar leaf rust development. Number of days post-inoculation until the first observation of pustules protruding from the abaxial leaf surface (latent period). Results were analyzed using the Kruskal–Wallis test for non-parametric analysis of variance. Significant differences in latent period were found among events (P = 5.351 × 10−7). Figure 1. View largeDownload slide Summary of Melampsora aecidiodes poplar leaf rust development. Number of days post-inoculation until the first observation of pustules protruding from the abaxial leaf surface (latent period). Results were analyzed using the Kruskal–Wallis test for non-parametric analysis of variance. Significant differences in latent period were found among events (P = 5.351 × 10−7). Similarly, the number of rust uredinia at 14 dpi indicated significantly higher rust severity in the OEGolS and OERFS lines. The wild-type trees produced, on average, less than one pustule per leaf at 14 dpi. Among the lines overexpressing AtGolS3, OEGolS_6 and OEGolS_11 showed the greatest amount of infection, averaging more than 50 pustules per leaf. In NDWD tests, all lines overexpressing AtGolS3 and CsRFS except one (OERFS_7) had significantly more rust pustules than the wild type (P < 0.05). All four GolSRNAi lines also produced fewer pustules than OEGolS_6 and OEGolS_11 (P < 0.019) (Figure 2). Figure 2. View largeDownload slide Count of pustules protruding from the abaxial leaf surface 14 days post-inoculation. Results were analyzed using the Kruskal–Wallis test for non-parametric analysis of variance. Significant differences for pustule counts were found among events (P = 2.989 × 10−5). Pairwise analysis of each event was performed using the Nemenyi–Damico–Wolfe–Dunn post hoc test for multiple comparisons. Significant differences are presented alongside (n = 6–10). Figure 2. View largeDownload slide Count of pustules protruding from the abaxial leaf surface 14 days post-inoculation. Results were analyzed using the Kruskal–Wallis test for non-parametric analysis of variance. Significant differences for pustule counts were found among events (P = 2.989 × 10−5). Pairwise analysis of each event was performed using the Nemenyi–Damico–Wolfe–Dunn post hoc test for multiple comparisons. Significant differences are presented alongside (n = 6–10). Response to rust alters sucrose and galactinol concentrations and the expression levels of the raffinose biosynthetic pathway Glucose-6-phosphate (G-6-P) is the product of sucrose metabolism and the subsequent phosphorylation of free glucose. G-6-P is the precursor to myo-inositol, which can participate in galactinol and consequently raffinose biosynthesis. We quantified the soluble sugars and sugar alcohols in the raffinose pathway and measured key biosynthetic gene expression during the wild type response to rust infection. At 20 h post-inoculation (hpi), sucrose concentrations were significantly elevated in inoculated leaves (5.66 μg mg–1) as compared to the un-inoculated control (2.25 μg mg–1) (P < 0.05). The ratio of sucrose to free hexose sugars (glucose + fructose) was also increased in inoculated tissue at 20 hpi, and nearly significant (P = 0.07). Myo-inositol and raffinose concentrations were not altered; however, galactinol was significantly decreased in inoculated leaves at 20 hpi (P = 0.037). These patterns of altered sucrose and galactinol concentrations were evident at 24 hpi, but were not significant (Figure 3) Figure 3. View largeDownload slide Concentration of sucrose, sucrose to hexose ratio, myo-inositol, galactinol and raffinose (μg/mg) in inoculated and non-inoculated control leaves at 20, 24, 48 and 96 h post-inoculation (hpi) in the wild type (P39). Significance differences were analyzed using student's t-tests between inoculated and control leaves at each time point. The data are mean ± SE of three biological replicates. *P < 0.05. Figure 3. View largeDownload slide Concentration of sucrose, sucrose to hexose ratio, myo-inositol, galactinol and raffinose (μg/mg) in inoculated and non-inoculated control leaves at 20, 24, 48 and 96 h post-inoculation (hpi) in the wild type (P39). Significance differences were analyzed using student's t-tests between inoculated and control leaves at each time point. The data are mean ± SE of three biological replicates. *P < 0.05. Quantitative Real-time PCR was used to measure the gene expression profiles of key biosynthetic genes in the raffinose pathway. We used leaf tissue sub-sampled from the sugar quantification experiment to have corresponding results. Transcripts levels of a myo-inositol synthase, Inositol-3-Phosphate Synthase (PtI3PS, Potri.007g089000) were increased 1.7, and 2.5 and 6-fold in inoculated leaves at 20, 24, and 96 hpi, respectively. In contrast, two galactinol synthases (PtGolS1, Potri.008G189400 and PtGolS2, Potri.010G042000) were each strongly suppressed at 20 hpi, and then were up-regulated at 48 and 96 hpi, respectively. The poplar gene encoding the final enzyme in the raffinose pathway; Raffinose Synthase (PtRFS, Potri.006G065700) had higher transcript levels at 24 hpi and then smaller incremental increases at 48 and 96 hpi (Figure 4) Figure 4. View largeDownload slide Quantitative real-time PCR (qRT-PCR) gene expression analysis of INOSITOL-3-PHOSPHATE SYNTHASE, GALACTINOL SYNTHASE1, GALACTINOL SYNTHASE2 and RAFFINOSE SYNTHASE in wild-type inoculated and control leaf tissue at 20, 24, 48 and 96 hpi. CELL DIVISION CONTROL2 was used as a housekeeping reference gene to calculate the differential expression using the 2ΔΔCt equation. Results represent the mean of three biological replicates and three technical replicates. Figure 4. View largeDownload slide Quantitative real-time PCR (qRT-PCR) gene expression analysis of INOSITOL-3-PHOSPHATE SYNTHASE, GALACTINOL SYNTHASE1, GALACTINOL SYNTHASE2 and RAFFINOSE SYNTHASE in wild-type inoculated and control leaf tissue at 20, 24, 48 and 96 hpi. CELL DIVISION CONTROL2 was used as a housekeeping reference gene to calculate the differential expression using the 2ΔΔCt equation. Results represent the mean of three biological replicates and three technical replicates. Overexpression of AtGolS3 and CsRFS suppress the up-regulation of PR1 We further characterized the wild-type response to M. aecidiodes inoculation by quantifying the expression of genes integral to defense signaling at 20, 24, 48 and 96 hpi with qRT-PCR. Glutamate receptors function in Ca2+ influx and the production of nitric oxide and reactive oxygen species (Manzoor et al. 2013). At 20 hpi, two GLUTAMATE RECEPTOR genes (PtGLR3.6; Potri.005G102700 and PtGLR3.2; Potri.009G168300) each had more abundant transcripts (2.1 and 9.5-fold, respectively) in inoculated leaves than in the control leaves (Figure 5). In our qRT-PCR analyses using wild-type leaves, transcripts from (PtPIP5K, Potri.008G128800) were more abundant (>3-fold) in inoculated leaf tissue in comparison to control leaves at 20, 24 and 96 hpi (Figure 5). Finally, we tested the expression of SA biosynthetic and signaling genes; PAL1 (Potri.006G126800), NPR1 (Potri.006G148100) and PR1 (Potri.009g082900). Each of these genes had elevated transcript levels at multiple time points in qRT-PCR comparison of inoculated and control wild-type leaves; however, their strongest expression were in succession at 20, 24 and 96 hpi, respectively (Figure 6). Figure 5. View largeDownload slide qRT-PCR gene expression analysis of PHENYLALANINE AMMONIA-LYASE 1, NONEXPRESSOR OF PATHOGENESIS-RELATED1 and PATHOGENESIS-RELATED1 in wild-type inoculated and control leaf tissue at 20, 24, 48 and 96 hpi. CELL DIVISION CONTROL2 was used as a housekeeping reference gene to calculate the differential expression using the 2ΔΔCt equation. Results represent the mean of three biological replicates and three technical replicates. Figure 5. View largeDownload slide qRT-PCR gene expression analysis of PHENYLALANINE AMMONIA-LYASE 1, NONEXPRESSOR OF PATHOGENESIS-RELATED1 and PATHOGENESIS-RELATED1 in wild-type inoculated and control leaf tissue at 20, 24, 48 and 96 hpi. CELL DIVISION CONTROL2 was used as a housekeeping reference gene to calculate the differential expression using the 2ΔΔCt equation. Results represent the mean of three biological replicates and three technical replicates. Figure 6. View largeDownload slide qRT-PCR gene expression analysis of GLUTAMATE RECEPTOR3.2, GLUTAMATE RECEPTOR3.6, PHOSPHATIDYLINOSITOL-4-PHOSPHATE-5-KINASE and PHOSPHOLIPASE D in wild-type inoculated and control leaf tissue at 20, 24, 48 and 96 hpi. CELL DIVISION CONTROL2 was used as a housekeeping reference gene to calculate the differential expression using the 2ΔΔCt equation. Results represent the mean of three biological replicates and three technical replicates. Figure 6. View largeDownload slide qRT-PCR gene expression analysis of GLUTAMATE RECEPTOR3.2, GLUTAMATE RECEPTOR3.6, PHOSPHATIDYLINOSITOL-4-PHOSPHATE-5-KINASE and PHOSPHOLIPASE D in wild-type inoculated and control leaf tissue at 20, 24, 48 and 96 hpi. CELL DIVISION CONTROL2 was used as a housekeeping reference gene to calculate the differential expression using the 2ΔΔCt equation. Results represent the mean of three biological replicates and three technical replicates. We then tested the expression levels of PIP5K, NPR1 and PR1 in inoculated OEGolS and OERFS lines and quantified the levels of conjugated-SA. HPLC quantification revealed a significant increase in the levels of conjugated-SA in the wild-type leaves at 24 hpi in comparison to the OEGolS_6 and OEGolS_11 (P = 0.04 and P = 0.02, respectively) (see Figure S7 available as Supplementary Data at Tree Physiology Online). The results of qRT-PCR in the OEGolS3 and OERFS lines indicated that PIP5K, NPR1 and PR1 were up-regulated in all lines over the course of infection (24, 48 and 96 hpi). However, the relative expression levels in inoculated OEGolS3 and OERFS lines were significantly lower than in inoculated wild-type leaves at 24 hpi for PIP5K and NPR1, and 48 and 96 hpi for PR1 (Figures 7–9). The level of transcript repression of these genes was correlated with the greater rust infection in the OEGolS compared to the OERFS lines. Figure 7. View largeDownload slide Relative expression of PHOSPHATIDYLINOSITOL-4-PHOSPHATE-5-KINASE, NONEXPRESSOR OF PATHOGENESIS-RELATED1 and PATHOGENESIS-RELATED1 in the wild type (P39) compared to OEGolS_3, OEGolS_6, OEGolS_11, OERFS_2, OERFS_7 and OERFS_8 at 24 hpi. Results represent the mean and standard error of three biological replicates and three technical replicates of inoculated tissues. All values are relative to the housekeeping reference gene CELL DIVISION CONTROL2. Results were analyzed using an analysis of variance and pairwise analysis of each event was performed using Tukey's post hoc test for multiple comparison. Figure 7. View largeDownload slide Relative expression of PHOSPHATIDYLINOSITOL-4-PHOSPHATE-5-KINASE, NONEXPRESSOR OF PATHOGENESIS-RELATED1 and PATHOGENESIS-RELATED1 in the wild type (P39) compared to OEGolS_3, OEGolS_6, OEGolS_11, OERFS_2, OERFS_7 and OERFS_8 at 24 hpi. Results represent the mean and standard error of three biological replicates and three technical replicates of inoculated tissues. All values are relative to the housekeeping reference gene CELL DIVISION CONTROL2. Results were analyzed using an analysis of variance and pairwise analysis of each event was performed using Tukey's post hoc test for multiple comparison. Figure 8. View largeDownload slide Relative expression of PHOSPHATIDYLINOSITOL-4-PHOSPHATE-5-KINASE, NONEXPRESSOR OF PATHOGENESIS-RELATED1 and PATHOGENESIS-RELATED1 in the wild type (P39) compared to OEGolS_3, OEGolS_6, OEGolS_11, OERFS_2, OERFS_7 and OERFS_8 at 48 hpi. Results represent the mean and standard error of three biological replicates and three technical replicates of inoculated tissues. All values are relative to the housekeeping reference gene CELL DIVISION CONTROL2. Results were analyzed using an analysis of variance and pairwise analysis of each event was performed using Tukey's post hoc test for multiple comparison. Figure 8. View largeDownload slide Relative expression of PHOSPHATIDYLINOSITOL-4-PHOSPHATE-5-KINASE, NONEXPRESSOR OF PATHOGENESIS-RELATED1 and PATHOGENESIS-RELATED1 in the wild type (P39) compared to OEGolS_3, OEGolS_6, OEGolS_11, OERFS_2, OERFS_7 and OERFS_8 at 48 hpi. Results represent the mean and standard error of three biological replicates and three technical replicates of inoculated tissues. All values are relative to the housekeeping reference gene CELL DIVISION CONTROL2. Results were analyzed using an analysis of variance and pairwise analysis of each event was performed using Tukey's post hoc test for multiple comparison. Figure 9. View largeDownload slide Relative expression of PHOSPHATIDYLINOSITOL-4-PHOSPHATE-5-KINASE, NONEXPRESSOR OF PATHOGENESIS-RELATED1 and PATHOGENESIS-RELATED1 in the wild type (P39) compared to OEGolS_3, OEGolS_6, OEGolS_11, OERFS_2, OERFS_7 and OERFS_8 at 96 hpi. Results represent the mean and standard error of three biological replicates and three technical replicates of inoculated tissues. All values are relative to the housekeeping reference gene CELL DIVISION CONTROL2. Results were analyzed using an analysis of variance and pairwise analysis of each event was performed using Tukey's post hoc test for multiple comparison. Figure 9. View largeDownload slide Relative expression of PHOSPHATIDYLINOSITOL-4-PHOSPHATE-5-KINASE, NONEXPRESSOR OF PATHOGENESIS-RELATED1 and PATHOGENESIS-RELATED1 in the wild type (P39) compared to OEGolS_3, OEGolS_6, OEGolS_11, OERFS_2, OERFS_7 and OERFS_8 at 96 hpi. Results represent the mean and standard error of three biological replicates and three technical replicates of inoculated tissues. All values are relative to the housekeeping reference gene CELL DIVISION CONTROL2. Results were analyzed using an analysis of variance and pairwise analysis of each event was performed using Tukey's post hoc test for multiple comparison. Overexpression of AtGolS3 and CsRFS enhances tolerance to ROS To test the role of galactinol and raffinose in ROS tolerance, we exposed leaf disks to 150 mM of H2O2 for 24 h and then measured electrolyte leakage. After 24 h, relative electrolyte leakage indicated significant differences between the overexpression lines and wild-type leaves and the RNAi lines (P = 1.738 × 10−4). The wild-type leaves had significantly higher relative electrolyte leakage than each OEGolS lines, OERFS_2, and OERFS_9. Moreover, GolSRNAi_3 and GolSRNAi_16 had higher electrolyte leakage than the wild-type leaves and were significantly different than all of the overexpression lines (Figure 10). Figure 10. View largeDownload slide Summary of the relative electrolyte leakage of leaf disks exposed to 24 h of 150 mM of H2O2 (treated) or autoclaved deionized water (control). Results represent the mean and standard error of 3–5 biological replicates where relative electrolyte leakage = (Treated Initial E.L./ Final E.L – Control Initial E.L./ Final E.L) × 100. Results were analyzed using the Kruskal–Wallis test for non-parametric analysis of variance. Pairwise analysis of each event was performed using the Nemenyi–Damico–Wolfe–Dunn post hoc test for multiple comparisons and are presented at the right of the figure. Figure 10. View largeDownload slide Summary of the relative electrolyte leakage of leaf disks exposed to 24 h of 150 mM of H2O2 (treated) or autoclaved deionized water (control). Results represent the mean and standard error of 3–5 biological replicates where relative electrolyte leakage = (Treated Initial E.L./ Final E.L – Control Initial E.L./ Final E.L) × 100. Results were analyzed using the Kruskal–Wallis test for non-parametric analysis of variance. Pairwise analysis of each event was performed using the Nemenyi–Damico–Wolfe–Dunn post hoc test for multiple comparisons and are presented at the right of the figure. Discussion Suppression of galactinol biosynthesis is necessary for leaf rust defense response Overexpression of AtGol3 and CsRFS in poplar dramatically alters sucrose metabolism and the host's ability to coordinate a defense response to leaf rust infection. Sucrose is one of the main products of photosynthesis and functions as the primary carbohydrate transported from source organs, a precursor to numerous plant metabolites, and signaling molecule (Lemoine 2000). In rice, sucrose is a key activator of anthocyanin biosynthesis and PR genes during plant defense response and pre-treatment has reduced proliferation of the hemibiotroph Magnaporthe oryzae (Gómez-Ariza et al. 2007, Serrano et al. 2012). In addition, partial resistance to multiple rust species was conferred through the wheat Lr67 locus that reduces glucose uptake to the host intracellular space (Moore et al. 2015). These results support a role for both elevated sucrose and reduced glucose in plant immunity; however, previous studies did not investigate whether changes also occurred in accumulation of myo-inositol, galactinol or raffinose. In poplar leaf rust transcriptome analysis, increased expression of I3PS was previously observed as part of the resistance response (Rinaldi et al. 2007). Along with the reductions in hexose sugars, galactinol and suppressed expression of two GolS genes, we expected to observe elevated levels of myo-inositol. The absence of changes in the levels of myo-inositol could be explained by the observation that myo-inositol antagonizes SA (Chaouch and Noctor 2010). Together, these results point toward a shunt diverting myo-inositol away from galactinol synthesis and toward other down-stream products as a necessary event in response to poplar leaf rust. Clearly, the overexpression of AtGolS3 and/or CsRFS along with accumulation of galactinol and raffinose directly oppose this node of the defense response. We also characterized the expression of known SA signaling genes involved in poplar leaf rust interactions (Rinaldi et al. 2007). Our finding revealed the up-regulation of several genes involved in poplar leaf rust interactions (PAL1, NPR1, PR1), suggesting that a reduction in galactinol levels may be a key modulator toward SA defense gene. In addition, transcriptome analysis comparing unchallenged wild type and OEGolS_6 (Unda et al. 2016) indicated reduced transcript abundance of two positive regulators of defense signaling; SUPPRESSOR OF NPR1 CONSTITUTIVE 4 and several NPR3-like genes, in the overexpression line. This may suggest that the accumulation of galactinol constitutively represses defense signaling events upstream of SA biosynthesis. Interestingly, in each GolSRNAi line uredinia counts were numerically higher than the wild-type leaves, which suggests that constitutively lower galactinol levels may also suppress some basal resistance toward leaf rusts. This is consistent with exogenous galactinol enhancing PR1a and PR1b transcripts in tobacco (Kim et al. 2008). Likewise, in transcriptome analysis several PR genes and chitinases were also up-regulated in the OEGolS_6 line (Unda et al. 2016). Overexpression of AtGolS3 and CsRFS transcriptionally inhibit PI-PLC/PLD pathway through ROS scavenging As part of a plant immune response, Zhang and Xiao (2015) proposed a biphasic model regulating PA-ROS-SA defense signaling. Initially, PI-PLC produced PA activates an early immediate cascade where RESPIRATORY BURST OXIDASE HOMOLOG D (RHOBD) production of ROS induces the accumulation of SA. A feed forward loop is then activated by PLD produced PA, which triggers a second wave of ROS and SA production, ultimately inducing PR1. This model is supported by pharmacological inhibitors of PLC, PLD and PtdIns(4,5)P2 each independently suppressing SA accumulation (Rodas-Junco et al. 2013) and conversely through SA activating PLC and PLD proteins (Profotova et al. 2006). In a previous study (Unda et al. 2016), RNA-Seq analysis of the unchallenged wild-type poplar and OEGolS_6 revealed reduced transcript abundance of several PIP5K genes in the transgenic line. This group included an ortholog of PIP5K9 a negative regulator of neutral invertases that inhibit sucrose metabolism (Lou et al. 2007). Ritsema et al. (2009) indicated that small GTPases are necessary for proper sugar sensing, while RHO proteins can activate PIP5K (Ren et al. 1996) and PLD (Liscovitch et al. 1999). This evidence points toward a signaling pathway in addition to the biosynthetic pathway linking sucrose to PA through PIP5K (Vallurua and Van den Ende 2011). In our previous research, we identified a SNP within a PIP5K gene (Potri.008G128800) that was associated with leaf rust resistance in P. trichocarpa (La Mantia et al. 2013). Transcripts from this gene were also less abundant in each of the OEGolS and OERFS lines compared to the wild-type leaves (Figures 7–9). The repression of these PIP5K gene members suggest that OEGolS and OERFS focus the biosynthetic precursors and transcriptional regime away from PtdIns(4,5)P2 production. The RNA-Seq analysis (Unda et al.2016) also indicated a constitutive increase in transcript abundance of ENHANCED DISEASE RESISTANCE 2 (EDR2), a negative regulator of SA defense (Tang et al. 2005). EDR2 binds PtdIns4P, the substrate of PIP5Ks (Vorwerk et al. 2007). Therefore, diversion away from the PI-PLC pathway may repress SA defense signaling genes. However, the regulation of EDR2, possibly through PtdIns4P, and its impact on PtdIns(4,5)P2 synthesis has not been explored. In addition, PIP5K was strongly up-regulated in the wild-type defense response at 20 hpi which coincided with increased transcript abundance of a PLD (Figure 5). PLD transcripts were suppressed after 20 hpi while PIP5K transcripts were elevated, to a lesser degree, at 24 and 48 hpi and then more strongly expressed at 96 hpi which may be indicative of a second response wave described by Zhang and Xiao (2015). However, it should be stated that several isoforms of PLDs negatively regulate SA (Zhao et al. 2013) and none of the PLD family members have been functionally characterized in poplar. Calcium (Ca2+) and ROS are also transmitted in waves to propagate stress signals from cell to cell (Mittler et al. 2011, Gilroy et al. 2014). This model may integrate precisely into the PI-PLC signaling pathway where PIP5K produced PtdIns(4,5)P2 is cleaved into InsP3; a precursor to InsP6 which increases cytosolic Ca2+, and diacyl glycerol; a precursor to PA which activates RHOBD. Unchallenged OEGolS_6 showed lower transcript abundance of four GLUTAMATE RECEPTOR2 (GLR2) and two GLR3 genes in comparison to the wild type (Unda et al. 2016). GLRs function as Ca2+ channels, but are necessary for ROS and nitric oxide production and disease resistance response (Manzoor et al. 2013). QRT-PCR revealed a robust elevation of transcripts from GLR3.2 and GLR3.6 at 20 hpi in inoculated wild-type leaves (Figure 5). Myo-inositol, galactinol and raffinose each play important roles as regulators of ROS homeostasis. Lower levels of myo-inositol in the Arabidopsis catalase2 mutant were associated with SA-dependent cell death (Chaouch and Noctor 2010). In addition, overexpression of a wheat GolS in Arabidopsis and rice increased expression of ROS-scavenging genes (Wang et al. 2015). Both galactinol and raffinose have inhibited radical-induced formation of 2,3-dihydroxy-benzoic acid, respectively (Nishizawa et al. 2008). We observed significantly lower amounts of relative electrolyte leakage after 24 h exposure to 150 mM of H2O2 in all lines overexpressing galactinol synthase (OEGolS) and nearly every OERFS line compared to the wild-type leaves (Figure 5). In OEGolS_6, transcriptome analysis revealed strong up-regulation of MYO-INOSITOL OXYGENASE 4 (MIOX4) (>5-fold) transcripts (Unda et al. 2016). MIOX4 uses myo-inositol to synthesize D-glucuronate, a precursor to the plant antioxidant ascorbic acid (Lorence et al. 2004). Thus, enhanced activity of MIOX4 would increase ROS tolerance, while further diverting the pool of myo-inositol away from the PI-PLC pathway. This may indicate that elevated galactinol and raffinose levels have a synergistic effect on ROS through suppressing signaling as an antioxidant and production via transcriptional repression of GLRs and PIP5Ks. Conclusion In the current study, we present a functional characterization of GolS and RFS validated as suppressors of biotrophic disease resistance and further elucidate the antagonism between JA and SA defense signaling. Results presented here point toward a transcriptional reprogramming to suppress galactinol accumulation as part of a biotrophic defense response. However, increased levels of galactinol and raffinose perturbs multiple components of the defense response allowing for enhanced disease progression. Future work is needed to further understand how galactinol and raffinose participate in regulating ROS, Ca2+ channels, PIP5K transcripts, PA and SA signaling. Supplementary Data Supplementary Data for this article are available at Tree Physiology Online. Acknowledgments The authors thank Dr Philippe Tanguay, Natural Resources Canada, for maintaining and providing the Melampsora aecidiodes strain. The authors also thank Genome British Columbia Applied Genomics Innovation Program (Project 103BIO) and Genome Canada Large-Scale Applied Research Project (Project168BIO) for their financial support. Conflict of interest None declared. Funding This work was supported by Genome British Columbia Applied Genomics Innovation Program (Project 103BIO) and Genome Canada Large-Scale Applied Research Project (Project168BIO), funds to R.C.H., S.D.M. and C.J.D. Authors' contribution J.L. conceived the research plan; C.D., S.D.M. and R.C.H. supervised the experiments; F.U. performed all experiments in the production of transgenic materials, quantification of sugars and salicylic acid, and contributed to the H2O2 experiments; J.L. performed all inoculations and QRT-PCR and contributed to the H2O2 experiments. F.U. and J.L. designed the experiments and analyzed the data; J.L. wrote the article with contributions of all the authors. C.D., S.D.M. and R.H. supervised and complemented the writing. References Azaiez A, Boyle B, Levée V, Séguin A ( 2009) Transcriptome profiling in hybrid poplar following interactions with Melampsora rust fungi. Mol Plant Microbe Interact  22: 190– 200. Google Scholar CrossRef Search ADS PubMed  Bruggeman Q, Raynaud C, Benhamed M, Delarue M ( 2015) To die or not to die? Lessons from lesion mimic mutants. Plant Physiol  6: 24. 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Tree PhysiologyOxford University Press

Published: Mar 1, 2018

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