Transcriptome and metabolome analyses provide insights into root and root-released organic anion responses to phosphorus deficiency in oat

Transcriptome and metabolome analyses provide insights into root and root-released organic anion... Abstract Roots and root-released organic anions play important roles in uptake of phosphorus (P), an essential macronutrient for food production. Oat, ranking sixth in the world’s cereal production, contains valuable nutritional compounds and can withstand poor soil conditions. Our aim was to investigate root transcriptional and metabolic responses of oat grown under P-deficient and P-sufficient conditions. We conducted a hydroponic experiment and measured root morphology and organic anion exudation, and analysed changes in the transcriptome and metabolome. Oat roots showed enhanced citrate and malate exudation after 4 weeks of P deficiency. After 10 d of P deficiency, we identified 9371 differentially expressed transcripts with a 2-fold or greater change (P<0.05): 48 sequences predicted to be involved in organic anion biosynthesis and efflux were consistently up-regulated; 24 up-regulated transcripts in oat were also found to be up-regulated upon P starvation in rice and wheat under similar conditions. Phosphorylated metabolites (i.e. glucose-6-phosphate, myo-inositol phosphate) were reduced dramatically, while citrate and malate, some sugars and amino acids increased slightly in P-deficient oat roots. Our data are consistent with a strategy of increased organic anion efflux and a shift in primary metabolism in response to P deficiency in oat. Metabolome, oat (Avena sativa L.), organic anions, phosphorus deficiency, plant roots, RNA-seq Introduction Oat (Avena sativa L.) is one of the most important food and feed crops in the world. It contains various nutritional and health-promoting compounds such as avenanthramides, vitamin E and β-glucans (Gutierrez-Gonzalez et al., 2013; Gutierrez-Gonzalez & Garvin, 2016), which have been suggested to have various health-promoting effects (Alminger and Eklund-Jonsson, 2008; Nazare et al., 2009; Whitehead et al., 2014; Valeur et al., 2016). In addition, oat can withstand poor soil conditions, e.g. acidic soils (Hill 1931; Stewart and McDougall, 2014), and is widely cultivated in temperate climates. In order to feed the rapidly growing world population, we need to secure sustainable food production worldwide. Phosphorus (P) is a key macronutrient with significant impact on plant growth and productivity. However, the P available to plants in soils is often low due to the complexes that P forms with soil minerals and compounds (Vance et al., 2003; Lynch, 2011). In addition, the P resources (mainly phosphate rock) are limited, non-renewable and geographically unevenly distributed (Cordell & White, 2015). Understanding the mechanisms of P mobilization and uptake, and improving P acquisition efficiency, particularly in staple cereal food crops, is important for food security and sustainable future food production (Vance et al., 2003; Faucon et al., 2015). Plants have evolved various adaptive strategies to cope with P deficiency in nature. Examples are morphological responses such as changes in root architecture (Hermans et al., 2006; Lynch, 2011), physiological adaptations such as secreted organic anions and acid phosphatases (Hedley et al., 1982; Hoffland et al., 1989; Jones 1998; Gahoonia et al., 2000; Ryan et al., 2001; Lambers et al., 2006; Cheng et al., 2014; Pang et al., 2015; Wang et al., 2016), biochemical responses to optimize utilization of internal P such as replacement of P lipids with non-P lipids (Chiou & Lin, 2011; Plaxton & Tran, 2011; Faucon et al., 2015; Lambers et al., 2015), molecular responses such as induced expression of high-affinity phosphate transporters (Wu et al., 2013; Zhang et al., 2014), and symbiotic responses such as root colonization with mycorrhizal fungi (Smith et al., 2003; Sawers et al., 2017). Multiple genes and mechanisms are required to improve plant tolerance to P deficiency. Thousands of plant genes that are differentially expressed in response to P deficiency have been identified in various plant species including Arabidopsis, potato, rice, wheat, and white lupin (Misson et al., 2005; Hammond et al., 2011; Oono et al., 2011, 2013; O’Rourke et al., 2013). Regulatory components identified include transcription factors, SPX domain-containing proteins, plant hormones, microRNAs, protein modifiers, and epigenetic modifications (Lin et al., 2009; Panigrahy et al., 2009; Yang & Finnegan, 2010; Chiou & Lin, 2011; Wu et al., 2013; Zhang et al., 2014). The gene regulatory networks that are necessary to sense and respond to P deficiency are complex and differ in different plant species. For Poaceae species, the molecular mechanisms associated with P uptake, translocation, and remobilization are well elucidated in rice (Panigrahy et al., 2009; Oono et al., 2013; Wu et al., 2013). Plant roots play an essential role in P uptake. To promote P uptake upon reduced P availability, most species allocate more biomass to roots, increase root length, and develop more and longer root hairs and secondary roots (Hermans et al., 2006; Lambers et al., 2006; Lynch, 2011; Lambers et al., 2015). Accordingly, research has focused on mechanisms regulating root architecture, especially by phytohormones such as auxin (see reviews by Lin et al., 2009; Panigrahy et al., 2009; Chiou and Lin, 2011; Lynch, 2011). However, only very few candidate genes associated with changes in root architecture under P deficiency have been isolated (e.g. AtLPR1, AtLPR2, AtPDR2, and OsMYB4P; Péret et al., 2014). A rice quantitative trait locus (QTL), Pup1, encoding a protein kinase that confers tolerance to P deficiency, is the only phosphorus-related QTL currently available for marker-assisted breeding programs (Gamuyao et al., 2012; Péret et al., 2014). Root exuded organic anions are also considered to be important in mobilizing soil P and enhancing P uptake. However, there is little information on the molecular mechanisms involved in organic acid biosynthesis and efflux under P deficiency. Despite the importance of oat, limited research has been carried out on its adaptation to P starvation. Wang et al. (2016) found that oat showed an increased root mass/total biomass ratio, high percentage of root colonization by arbuscular mycorrhizal fungi, large amounts of rhizosphere organic anions, and efficient P uptake in low P availability soils. These findings paved the way for our current study on the molecular mechanisms underlying P deficiency responses in oat roots, and the genes and metabolites involved. Here we compare gene expression and metabolome profiles of oat roots exposed to P-sufficient and -deficient conditions. The objectives were to: (i) identify differentially expressed transcripts in oat roots in response to P deficiency, particular focusing on up-regulated transcripts associated with organic anion biosynthesis and exudation; (ii) discover conserved responsive genes in rice, wheat, and oat, and transcripts unique for oat; and (iii) assess differential metabolite accumulation in response to P deficiency and the transcriptional program triggered by it. The overarching goal was to identify candidate genes that may be active in oat adaptation to P deficiency and that may be useful to future breeding and genetic engineering efforts towards oat improvement. Materials and methods Plant growth and harvest Seeds of the oat cultivar ‘BELINDA’ were germinated and grown hydroponically in full strength nutrient medium (Wang et al., 2015) in the greenhouse at the Norwegian University of Life Sciences. Fourteen days after sowing, seedlings were transferred to the same medium supplemented with 100 μM (P100) or 1 μM (P1) KH2PO4, and pH adjusted to 5.8 ± 0.2. Plants were grown under a photoperiod of 16 h light and 8 h dark at a light intensity of 200 ± 20 μmol m−2 s−1 and 50–75% relative humidity, with a temperature of 25 °C/16 °C (day/night). The nutrient solution was replaced every third day. Ten days post-treatment, four root samples (representing four independent biological replications) from both P100- and P1-treated plants were collected for RNA extraction and analysis as described by Oono et al. (2011). These were mixed samples containing the root cap zone, elongation zone, and a part of the maturation zone. These eight root samples, together with another eight samples (four from P1 and four from P100) were used for root metabolome analysis. When roots were sampled for RNA and metabolite extraction, they were quickly washed and the water was removed, after which they were immediately placed in liquid nitrogen. Additionally, eight plants (two treatments, four replicates) were used for studies of root morphology, root organic anions and biomass determinations after 4 weeks of different P treatments. All the plants were in vegetative growth phase, with tillers but before heading. Root released organic anions, root morphology and biomass determination For root exudate collection, briefly, whole root systems of intact plants were carefully washed with deionized water to remove the nutrient solution. The whole root system was then placed into ultrapure Milli-Q water (Millipore, Billerica, MA, USA; the volume varied from 50 to 150 ml depending on the size of the roots) in a container to collect root exudates (Khorassani et al., 2011; Wang et al., 2015). Afterwards, Micropur (0.01 g L−1, Katadyn Products, Kemptthal, Switzerland) was added to the solution to inhibit the activity of microorganisms (Cheng et al., 2014). The collected root exudates were analysed by liquid chromatography–triple quadrupole mass spectrometry (LC-MS/MS), as described in a previous study (Wang et al. 2015). Root-released organic anions were collected and analysed after plants had been grown hydroponically under P1 or P100 for 2 and 4 weeks. After 4 weeks, the total number of green leaves and senesced leaves was recorded. For root morphology determination, WinRHIZO (Epson 1680, WinRHIZO Pro2003b, Regent Instruments Inc., Quebec, Canada) was used to measure root length, number of lateral roots and root surface area. Shoot and root dry weight (DW) were measured separately after oven-drying for 48 h at 65 °C. Shoot P concentrations were subsequently determined by inductively coupled plasma atomic emission spectroscopy (Wang et al., 2015). RNA extraction and quality control Total RNA was extracted using a Spectrum™ Plant Total RNA Kit (Sigma-Aldrich, St Louis, MO, USA) and genomic DNA was removed using On-column DNase I digest kit (Sigma-Aldrich). RNA quantity and quality were assessed by a NanoDrop spectrophotometer (NanoDrop Technologies, Wilmington, DE, USA) and Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). RNA samples with RIN (RNA integrity number) scores greater than 9.0 were used for RNA-Seq. Eight independent root cDNA libraries were prepared according to Illumina’s TruSeq® RNA Sample Preparation v2 Guide, and 125-bp paired-end reads were sequenced using an Illumina HiSeq 2500 sequencer (Illumina, San Diego, CA, USA) at the Norwegian Sequencing Centre (www.sequencing.uio.no). Sequence processing and analysis A total of 215087481 paired-end short read sequences were quality checked, trimmed and de novo assembled using CLC Genomics Workbench v9.01 (Qiagen, Aarhus, Denmark), generating 207 017 contigs, with a maximum contig length of 13319 nt, a minimum contig length of 200 nt, and a mean contig length of 801 nt (Table 1). Gene expression was calculated and normalized using reads per kb per million reads (RPKM). Differential expression between P1 and P100 was analysed by Student’s t-test and up-/down-regulation of genes was considered to be significant if ≥2-fold (P<0.05). Totally, 41679 transcripts were filtered out and selected to be de novo oat root transcriptome (dnORT), used as a reference for further analysis. The dnORT sequences were a combination of the differentially expressed transcripts and other transcripts with RPKM≥1.5 regardless of P treatments. These sequences were annotated using Blast2Go (Conesa et al., 2005) and MapMan (Thimm et al., 2004). RNA sequencing raw data were deposited in the GeneBank Sequence Read Archive (SRA) database under bioproject identifier PRJNA355647. Table 1. Transcriptome statistics Total number of reads 215087481 Assembled contigs 207017 Minimum length (nt) 200 Maximum length (nt) 13319 Mean length (nt) 801 Contigs larger than 1000 nt 9631 Up-regulated contigs 7817 Down-regulated contigs 1554 Annotated contigs 41679 Total number of reads 215087481 Assembled contigs 207017 Minimum length (nt) 200 Maximum length (nt) 13319 Mean length (nt) 801 Contigs larger than 1000 nt 9631 Up-regulated contigs 7817 Down-regulated contigs 1554 Annotated contigs 41679 nt, nucleotides. View Large Table 1. Transcriptome statistics Total number of reads 215087481 Assembled contigs 207017 Minimum length (nt) 200 Maximum length (nt) 13319 Mean length (nt) 801 Contigs larger than 1000 nt 9631 Up-regulated contigs 7817 Down-regulated contigs 1554 Annotated contigs 41679 Total number of reads 215087481 Assembled contigs 207017 Minimum length (nt) 200 Maximum length (nt) 13319 Mean length (nt) 801 Contigs larger than 1000 nt 9631 Up-regulated contigs 7817 Down-regulated contigs 1554 Annotated contigs 41679 nt, nucleotides. View Large Real-time quantitative reverse transcription PCR analysis First-strand cDNA was synthesized from 1.0 µg RNA using iScriptTM Adv cDNA kit for real-time quantitative reverse transcription PCR (qRT-PCR; Bio-Rad, USA). The qRT-PCR reactions were carried out on a CFX96TM real-time system (Bio-Rad) using SsoAdvancedTM Universal SYBR® Green Supermix (Bio-Rad, USA) with transcript-specific primers (shown in Supplementary Table S5 at JXB online). Ten nanograms of cDNA were used as template in a 20 µl qPCR reaction with 0.8 µM primers. After initial denaturing at 95 °C for 5 min, the reaction was followed by 40 cycles at 95 °C for 15 s, 61 °C for 15 s, and 72 °C for 45 s. The expression of endogenous reference genes EF1α (Elongation factor 1α; Kemen et al., 2014) and β-actin was used to normalize the expression level estimated by the Δ∆Cq method provided by CFX Manager 3.1 (Bio-Rad). Four biological replicates of each treatment and three technical replicates of each sample were applied in the analysis. The qPCR data were represented as fold change (P1 mean value: P100 mean value) derived from relative normalized expression level from four biological replicates and further compared with RNA-seq results (P1 RPKM means/P100 RPKM means). R software (version 3.2.2) and one-way ANOVA were used to examine significant differences between P1 and P100 treatments. Heat maps were generated in Heml 1.0: Heatmap illustrator as described by Deng et al. (2014). Root metabolite extraction Eight replicate samples each of roots from plants grown under P1 and P100 conditions were sampled. Frozen samples (with water content varying between 95.3% and 96.6%) of 100 mg (±10%) root were ground to homogeneity (2 min, 30 Hz; Grinding Mill MM310; Retsch, Germany) under freezing conditions. To each sample was added 360 μl precooled (−20 °C) extraction buffer (300 μl methanol, 30 μl 2 mg ml−1 nonadecanoic acid methylester in chloroform, 30 μl 0.2 mg ml−1 [13C]sorbitol in methanol) and samples shaken for 15 min, 70 °C, 1000 rpm (Thermomixer Comfort, Eppendorf, Germany). Samples were cooled to room temperature, added to 200 μl CHCl3, and further shaken for 5 min, 37 °C, 1000 rpm. To each sample was added 400 μl H2O and, following vortexing, samples were centrifuged (5 min, 20 800 g) to facilitate phase separation. Finally, 160 μl of the upper, polar phase was aliquoted and dried overnight by Speed Vac. Gas chromatography–mass spectrometry metabolite profiling and identification Prior to gas chromatography–electron impact–time of flight mass spectrometry (GC-EI/TOF-MS) analysis, metabolites were methoxyaminated and trimethylsilylated. Briefly, addition of 40 µl MeOX (40 mg ml−1 methoxyaminhydrochloride in pyridine), samples were shaken (1.5 h, 30 °C) followed by addition of 80 µl BSTFA mixture (70 µl N,O-bis(trimethylsilyl)trifluoroacetamide+10 µl alkane mix; n-alkanes: C10, C12, C15, C18, C19, C22, C28, C32, and C36), and further shaken (30 min, 37 °C). GC-MS was undertaken using an Agilent CP9013 column in an Agilent 6890N24 gas chromatograph, coupled to a Pegasus III, similar to that previously described (Wagner et al., 2003; Erban et al., 2007; Dethloff et al., 2014). Measurements were undertaken both splitless and split (1/30) from an injection volume of 1 µl, with bulk metabolites reaching the upper detection limit in split-less measurements evaluated from split data. Retention indices were calibrated based on added n-alkanes (Strehmel et al., 2008). Chromatograms were visually controlled, baseline corrected, and exported in NetCDF format using ChromaTOF. Further data processing and compound identification were performed with TagFinder (Luedemann et al., 2008) and by matching to the Golm Metabolome Database (GMD, http://gmd.mpimpgolm.mpg.de/;Kopka et al., 2005; Schauer et al., 2005) and the NIST08 database (http://www.nist.gov/srd/mslist.htm). Manually supervised metabolite annotation and quantification were undertaken with the requirement of at least three specific quantitative mass fragments per compound, and a retention index deviation <1.0%. Data were normalized to sample fresh weight, the internal [13C6]sorbitol, and represented relative to the mean value of P100 samples per analyte. Principal component analysis and statistical analysis Principal component analysis (PCA) was carried out using the program R. Data were normalized to the median of the P100 samples and subsequently subjected to logarithmic (log2) transformation. Missing values were not replaced with zero or a constant value. Statistical testing was performed using the t test in multiple experiment viewer MeV (Saeed et al., 2006), based on log2-transformed data, followed by Mann–Whitney false discovery rate (FDR) correction at α<0.05, due to non-normal distribution (as shown by PCA analysis) of the metabolite data. Results Plant growth, root morphology and root-released organic anion analysis The plant phenotype and root-released organic anions were examined to study the effects of P deficiency on oat growth and root exudates under hydroponic conditions. After 4 weeks of growth under two different P regimes (1 and 100 μM KH2PO4), a drastic reduction of shoot P concentration was observed in plants grown under P-deficient conditions (P1) compared with P100 (0.90 versus 6.35 mg g−1). Oat plants subjected to P1 treatment showed on average a 55% reduction in the total number of leaves, 44% more senescent leaves (number of senescent leaves: number of total leaves), 68% less shoot dry biomass, and 96% greater root mass ratio (root dry biomass: total dry biomass) than P100 plants as shown in Fig. 1A–D. Moreover, P1-treatment plants showed shorter total root length (25%), lower root surface area (27%) and more lateral roots (14%) than P100 plants (Fig. 2A–C). Furthermore, after 4 weeks, compared with P100-treated plants, which showed no detectable root-released organic anions, P1 roots had higher exudation rates of citrate and malate, 927 and 81 nmol h−1 g−1 root dry weight (DW), respectively, as shown in Fig. 2D. By contrast, no organic anions were detected in either P1 or P100 root exudates collected after 2 weeks’ treatment. Fig. 1. View largeDownload slide Plant growth response to P1 and P100 treatments. (A) Total leaves, (B) senescent leaves, (C) shoot dry weight, and (D) root mass ratio. Error bars indicate SE (n=4). Significant differences are indicated (***P<0.001). Fig. 1. View largeDownload slide Plant growth response to P1 and P100 treatments. (A) Total leaves, (B) senescent leaves, (C) shoot dry weight, and (D) root mass ratio. Error bars indicate SE (n=4). Significant differences are indicated (***P<0.001). Fig. 2. View largeDownload slide Oat root response to P1 and P100 treatments. (A) Root length, (B) root surface area, (C) number of root tips, and (D) root-released organic anions. Error bars indicate SE (n=4). Significant differences are indicated (ns, not significant; ***P<0.001). Fig. 2. View largeDownload slide Oat root response to P1 and P100 treatments. (A) Root length, (B) root surface area, (C) number of root tips, and (D) root-released organic anions. Error bars indicate SE (n=4). Significant differences are indicated (ns, not significant; ***P<0.001). Transcriptome analysis of root response to P deficiency Approximately 9.4% of the dnORT transcripts could not be assigned to any Blastx hits (E-value>1E-3) as shown in Supplementary Fig. S1. The Blastx top hit species were: Brachypodium distachyon (22%), Hordeum vulgare subsp. vulgare (17%), Aegilops tauschii (15%), Triticum urartu (10%), and Oryza sativa japonica group (4%) (Supplementary Fig. S2). Functional gene ontology (GO) classification of dnORT sequences suggested that the biological process was mainly represented by the term ‘cellular and metabolic processes’, and the most represented GO subcategories within the cellular component main term were ‘cell or cell part’ and ‘membrane or membrane part’. When the sequences were categorized according to the molecular function main term, 10699 transcripts corresponded to ‘binding category’ and 10522 sequences to ‘catalytic activity’ (Supplementary Fig. S3). Putative functions (with InterProScan) were predicted for 62% of the sequences (Supplementary Fig. S4). In total, 9371 transcripts (7817 up-regulated, 1554 down-regulated) were differentially expressed in response to P deficiency as shown in Table 1. Gene ontology (GO) categories showed that up-regulated transcripts under P deficiency were categorized into more than 40 groups, such as oxidation–reduction process, transmembrane transport, carbohydrate metabolic process, response to osmotic stress, biosynthetic process, pyruvate metabolism, tricarboxylic acid cycle, acid phosphatase, and CCAAT-binding complex (Fig. 3). Fig. 3. View largeDownload slide Functional annotation of up-regulated sequences based on gene ontology (GO) categorization. y-Axis indicates the category, x-axis the percentage of transcripts in a category. Fig. 3. View largeDownload slide Functional annotation of up-regulated sequences based on gene ontology (GO) categorization. y-Axis indicates the category, x-axis the percentage of transcripts in a category. Reciprocal tblastx (E<1E-10) analysis showed that 24 oat transcripts that were up-regulated in P1 matched the conserved responsive genes previously found up-regulated in both rice and wheat (Oono et al., 2013) as listed in Table 2. We also found 25 unique responsive transcripts (between 308 and 1672 nt) in oat roots that were up-regulated more than 2-fold (P<0.001, P1 RPKM means>5), without any blast hits in currently available databases, i.e. they seem to be exclusively expressed in oat (Supplementary Table S1). Table 2. Conserved responsive transcripts found in oat, wheat, and rice under P deficiency dnORT ID Rice proteins Wheat_proteins (TRIAE_CS42) P1 RPKM P100 RPKM Fold change P1/P100 Gene Gene annotation Contig000022 Os05t0137400-01 1AS_TGACv1_020885_ AA0080310.2.1 107.9 48.1 2.2 Similar to aspartic protease precursor Contig000835 Os05t0387200-01 1DL_TGACv1_061485_ AA0196630.2.1 13.5 1.7 8.0 SQD1 Sulphite: UDP-glucose sulfotransferase Contig010807 Os10t0500600-01 1DL_TGACv1_062297_ AA0212030.5.1 48.3 22.6 2.1 Zinc finger, C2H2-like domain containing protein Contig011660 Os07t0100300-02 2AL_TGACv1_094153_ AA0293430.1.1 17.4 1.3 13.4 Glycosyl transferase, group 1 domain containing protein Contig009578 Os10t0100500-01 2AS_TGACv1_113238_ AA0353330.1.1 61.3 11.4 5.4 Serine/threonine protein kinase-related domain containing protein Contig001778 Os07t0622200-01 2AS_TGACv1_113290_ AA0354140.2.1 71.8 68.0 1.1 Similar to M-160-u1_1 Contig009737 Os07t0630400-01 2BS_TGACv1_146583_ AA0468610.1.1 5.2 1.1 4.8 OsRNS1 Ribonuclease T2 family protein Contig005229 Os04t0555300-01 2DL_TGACv1_158105_ AA0509380.4.1 41.6 9.1 4.6 Similar to glycerol 3-phosphate permease Contig019750 Os04t0652700-01 2DL_TGACv1_158583_ AA0522480.2.1 4.8 1.2 4.0 Similar to nuclease PA3 Contig061747 Os01t0128200-01 3AS_TGACv1_210696_ AA0677330.2.1 4.0 1.4 2.8 Similar to nuclease I Contig013859 Os01t0897200-04 3B_TGACv1_224141_ AA0792910.2.1 68.9 21.8 3.2 OsRNS2 Ribonuclease 2 precursor Contig004306 Os06t0115600-01 4AL_TGACv1_289135_ AA0965550.1.1 76.7 53.6 1.4 Similar to CYCLOPS Contig026884 Os08t0299400-01 4AL_TGACv1_289998_ AA0980080.1.1 13.9 0.0 MGD MGDG synthase type A Contig003298 Os03t0238600-01 4AS_TGACv1_308481_ AA1028160.1.1 273.2 54.6 5.0 PAP Similar to purple APase Contig007532 Os09t0553200-01 5AL_TGACv1_374888_ AA1211020.2.1 504.8 181.3 2.8 UGPase UDP-glucose pyrophosphorylase Contig003667 Os09t0478300-01 5AL_TGACv1_376126_ AA1232370.2.1 17.7 7.5 2.4 Conserved hypothetical protein Contig026720 Os12t0554500-00 5AS_TGACv1_393365_ AA1271860.2.1 11.6 0.1 167.7 Lipase, class 3 family protein Contig116061 Os09t0379900-02 5BL_TGACv1_404442_ AA1299920.1.1 1.6 0.6 2.5 Endo-1,3(4)-β-glucanase 2 like Contig073770 Os08t0433200-01 5BL_TGACv1_404654_ AA1307490.1.1 28.0 5.4 5.1 Conserved hypothetical protein Contig007245 Os09t0315700-01 5BL_TGACv1_407230_ AA1354660.1.1 58.1 20.4 2.9 Phosphoenolpyruvate carboxylase family protein Contig000670 Os02t0809800-01 6BL_TGACv1_501820_ AA1620890.2.1 70.5 22.9 3.1 PHO1:H2 Root-to-shoot inorganic phosphate (Pi) transfer Contig000259 Os06t0178900-01 7BS_TGACv1_592527_ AA1939830.5.1 184.6 82.2 2.2 Vacuolar H+-pyrophosphatase Contig027611 Os05t0489900-01 U_TGACv1_641100_ AA2085080.2.1 13.9 6.4 2.2 Calcium/calmodulin-dependent protein kinase Contig044047 Os09t0321200-00 U_TGACv1_642666_ AA2121200.1.1 0.9 0.1 11.0 Similar to carotenoid cleavage dioxygenase dnORT ID Rice proteins Wheat_proteins (TRIAE_CS42) P1 RPKM P100 RPKM Fold change P1/P100 Gene Gene annotation Contig000022 Os05t0137400-01 1AS_TGACv1_020885_ AA0080310.2.1 107.9 48.1 2.2 Similar to aspartic protease precursor Contig000835 Os05t0387200-01 1DL_TGACv1_061485_ AA0196630.2.1 13.5 1.7 8.0 SQD1 Sulphite: UDP-glucose sulfotransferase Contig010807 Os10t0500600-01 1DL_TGACv1_062297_ AA0212030.5.1 48.3 22.6 2.1 Zinc finger, C2H2-like domain containing protein Contig011660 Os07t0100300-02 2AL_TGACv1_094153_ AA0293430.1.1 17.4 1.3 13.4 Glycosyl transferase, group 1 domain containing protein Contig009578 Os10t0100500-01 2AS_TGACv1_113238_ AA0353330.1.1 61.3 11.4 5.4 Serine/threonine protein kinase-related domain containing protein Contig001778 Os07t0622200-01 2AS_TGACv1_113290_ AA0354140.2.1 71.8 68.0 1.1 Similar to M-160-u1_1 Contig009737 Os07t0630400-01 2BS_TGACv1_146583_ AA0468610.1.1 5.2 1.1 4.8 OsRNS1 Ribonuclease T2 family protein Contig005229 Os04t0555300-01 2DL_TGACv1_158105_ AA0509380.4.1 41.6 9.1 4.6 Similar to glycerol 3-phosphate permease Contig019750 Os04t0652700-01 2DL_TGACv1_158583_ AA0522480.2.1 4.8 1.2 4.0 Similar to nuclease PA3 Contig061747 Os01t0128200-01 3AS_TGACv1_210696_ AA0677330.2.1 4.0 1.4 2.8 Similar to nuclease I Contig013859 Os01t0897200-04 3B_TGACv1_224141_ AA0792910.2.1 68.9 21.8 3.2 OsRNS2 Ribonuclease 2 precursor Contig004306 Os06t0115600-01 4AL_TGACv1_289135_ AA0965550.1.1 76.7 53.6 1.4 Similar to CYCLOPS Contig026884 Os08t0299400-01 4AL_TGACv1_289998_ AA0980080.1.1 13.9 0.0 MGD MGDG synthase type A Contig003298 Os03t0238600-01 4AS_TGACv1_308481_ AA1028160.1.1 273.2 54.6 5.0 PAP Similar to purple APase Contig007532 Os09t0553200-01 5AL_TGACv1_374888_ AA1211020.2.1 504.8 181.3 2.8 UGPase UDP-glucose pyrophosphorylase Contig003667 Os09t0478300-01 5AL_TGACv1_376126_ AA1232370.2.1 17.7 7.5 2.4 Conserved hypothetical protein Contig026720 Os12t0554500-00 5AS_TGACv1_393365_ AA1271860.2.1 11.6 0.1 167.7 Lipase, class 3 family protein Contig116061 Os09t0379900-02 5BL_TGACv1_404442_ AA1299920.1.1 1.6 0.6 2.5 Endo-1,3(4)-β-glucanase 2 like Contig073770 Os08t0433200-01 5BL_TGACv1_404654_ AA1307490.1.1 28.0 5.4 5.1 Conserved hypothetical protein Contig007245 Os09t0315700-01 5BL_TGACv1_407230_ AA1354660.1.1 58.1 20.4 2.9 Phosphoenolpyruvate carboxylase family protein Contig000670 Os02t0809800-01 6BL_TGACv1_501820_ AA1620890.2.1 70.5 22.9 3.1 PHO1:H2 Root-to-shoot inorganic phosphate (Pi) transfer Contig000259 Os06t0178900-01 7BS_TGACv1_592527_ AA1939830.5.1 184.6 82.2 2.2 Vacuolar H+-pyrophosphatase Contig027611 Os05t0489900-01 U_TGACv1_641100_ AA2085080.2.1 13.9 6.4 2.2 Calcium/calmodulin-dependent protein kinase Contig044047 Os09t0321200-00 U_TGACv1_642666_ AA2121200.1.1 0.9 0.1 11.0 Similar to carotenoid cleavage dioxygenase View Large Table 2. Conserved responsive transcripts found in oat, wheat, and rice under P deficiency dnORT ID Rice proteins Wheat_proteins (TRIAE_CS42) P1 RPKM P100 RPKM Fold change P1/P100 Gene Gene annotation Contig000022 Os05t0137400-01 1AS_TGACv1_020885_ AA0080310.2.1 107.9 48.1 2.2 Similar to aspartic protease precursor Contig000835 Os05t0387200-01 1DL_TGACv1_061485_ AA0196630.2.1 13.5 1.7 8.0 SQD1 Sulphite: UDP-glucose sulfotransferase Contig010807 Os10t0500600-01 1DL_TGACv1_062297_ AA0212030.5.1 48.3 22.6 2.1 Zinc finger, C2H2-like domain containing protein Contig011660 Os07t0100300-02 2AL_TGACv1_094153_ AA0293430.1.1 17.4 1.3 13.4 Glycosyl transferase, group 1 domain containing protein Contig009578 Os10t0100500-01 2AS_TGACv1_113238_ AA0353330.1.1 61.3 11.4 5.4 Serine/threonine protein kinase-related domain containing protein Contig001778 Os07t0622200-01 2AS_TGACv1_113290_ AA0354140.2.1 71.8 68.0 1.1 Similar to M-160-u1_1 Contig009737 Os07t0630400-01 2BS_TGACv1_146583_ AA0468610.1.1 5.2 1.1 4.8 OsRNS1 Ribonuclease T2 family protein Contig005229 Os04t0555300-01 2DL_TGACv1_158105_ AA0509380.4.1 41.6 9.1 4.6 Similar to glycerol 3-phosphate permease Contig019750 Os04t0652700-01 2DL_TGACv1_158583_ AA0522480.2.1 4.8 1.2 4.0 Similar to nuclease PA3 Contig061747 Os01t0128200-01 3AS_TGACv1_210696_ AA0677330.2.1 4.0 1.4 2.8 Similar to nuclease I Contig013859 Os01t0897200-04 3B_TGACv1_224141_ AA0792910.2.1 68.9 21.8 3.2 OsRNS2 Ribonuclease 2 precursor Contig004306 Os06t0115600-01 4AL_TGACv1_289135_ AA0965550.1.1 76.7 53.6 1.4 Similar to CYCLOPS Contig026884 Os08t0299400-01 4AL_TGACv1_289998_ AA0980080.1.1 13.9 0.0 MGD MGDG synthase type A Contig003298 Os03t0238600-01 4AS_TGACv1_308481_ AA1028160.1.1 273.2 54.6 5.0 PAP Similar to purple APase Contig007532 Os09t0553200-01 5AL_TGACv1_374888_ AA1211020.2.1 504.8 181.3 2.8 UGPase UDP-glucose pyrophosphorylase Contig003667 Os09t0478300-01 5AL_TGACv1_376126_ AA1232370.2.1 17.7 7.5 2.4 Conserved hypothetical protein Contig026720 Os12t0554500-00 5AS_TGACv1_393365_ AA1271860.2.1 11.6 0.1 167.7 Lipase, class 3 family protein Contig116061 Os09t0379900-02 5BL_TGACv1_404442_ AA1299920.1.1 1.6 0.6 2.5 Endo-1,3(4)-β-glucanase 2 like Contig073770 Os08t0433200-01 5BL_TGACv1_404654_ AA1307490.1.1 28.0 5.4 5.1 Conserved hypothetical protein Contig007245 Os09t0315700-01 5BL_TGACv1_407230_ AA1354660.1.1 58.1 20.4 2.9 Phosphoenolpyruvate carboxylase family protein Contig000670 Os02t0809800-01 6BL_TGACv1_501820_ AA1620890.2.1 70.5 22.9 3.1 PHO1:H2 Root-to-shoot inorganic phosphate (Pi) transfer Contig000259 Os06t0178900-01 7BS_TGACv1_592527_ AA1939830.5.1 184.6 82.2 2.2 Vacuolar H+-pyrophosphatase Contig027611 Os05t0489900-01 U_TGACv1_641100_ AA2085080.2.1 13.9 6.4 2.2 Calcium/calmodulin-dependent protein kinase Contig044047 Os09t0321200-00 U_TGACv1_642666_ AA2121200.1.1 0.9 0.1 11.0 Similar to carotenoid cleavage dioxygenase dnORT ID Rice proteins Wheat_proteins (TRIAE_CS42) P1 RPKM P100 RPKM Fold change P1/P100 Gene Gene annotation Contig000022 Os05t0137400-01 1AS_TGACv1_020885_ AA0080310.2.1 107.9 48.1 2.2 Similar to aspartic protease precursor Contig000835 Os05t0387200-01 1DL_TGACv1_061485_ AA0196630.2.1 13.5 1.7 8.0 SQD1 Sulphite: UDP-glucose sulfotransferase Contig010807 Os10t0500600-01 1DL_TGACv1_062297_ AA0212030.5.1 48.3 22.6 2.1 Zinc finger, C2H2-like domain containing protein Contig011660 Os07t0100300-02 2AL_TGACv1_094153_ AA0293430.1.1 17.4 1.3 13.4 Glycosyl transferase, group 1 domain containing protein Contig009578 Os10t0100500-01 2AS_TGACv1_113238_ AA0353330.1.1 61.3 11.4 5.4 Serine/threonine protein kinase-related domain containing protein Contig001778 Os07t0622200-01 2AS_TGACv1_113290_ AA0354140.2.1 71.8 68.0 1.1 Similar to M-160-u1_1 Contig009737 Os07t0630400-01 2BS_TGACv1_146583_ AA0468610.1.1 5.2 1.1 4.8 OsRNS1 Ribonuclease T2 family protein Contig005229 Os04t0555300-01 2DL_TGACv1_158105_ AA0509380.4.1 41.6 9.1 4.6 Similar to glycerol 3-phosphate permease Contig019750 Os04t0652700-01 2DL_TGACv1_158583_ AA0522480.2.1 4.8 1.2 4.0 Similar to nuclease PA3 Contig061747 Os01t0128200-01 3AS_TGACv1_210696_ AA0677330.2.1 4.0 1.4 2.8 Similar to nuclease I Contig013859 Os01t0897200-04 3B_TGACv1_224141_ AA0792910.2.1 68.9 21.8 3.2 OsRNS2 Ribonuclease 2 precursor Contig004306 Os06t0115600-01 4AL_TGACv1_289135_ AA0965550.1.1 76.7 53.6 1.4 Similar to CYCLOPS Contig026884 Os08t0299400-01 4AL_TGACv1_289998_ AA0980080.1.1 13.9 0.0 MGD MGDG synthase type A Contig003298 Os03t0238600-01 4AS_TGACv1_308481_ AA1028160.1.1 273.2 54.6 5.0 PAP Similar to purple APase Contig007532 Os09t0553200-01 5AL_TGACv1_374888_ AA1211020.2.1 504.8 181.3 2.8 UGPase UDP-glucose pyrophosphorylase Contig003667 Os09t0478300-01 5AL_TGACv1_376126_ AA1232370.2.1 17.7 7.5 2.4 Conserved hypothetical protein Contig026720 Os12t0554500-00 5AS_TGACv1_393365_ AA1271860.2.1 11.6 0.1 167.7 Lipase, class 3 family protein Contig116061 Os09t0379900-02 5BL_TGACv1_404442_ AA1299920.1.1 1.6 0.6 2.5 Endo-1,3(4)-β-glucanase 2 like Contig073770 Os08t0433200-01 5BL_TGACv1_404654_ AA1307490.1.1 28.0 5.4 5.1 Conserved hypothetical protein Contig007245 Os09t0315700-01 5BL_TGACv1_407230_ AA1354660.1.1 58.1 20.4 2.9 Phosphoenolpyruvate carboxylase family protein Contig000670 Os02t0809800-01 6BL_TGACv1_501820_ AA1620890.2.1 70.5 22.9 3.1 PHO1:H2 Root-to-shoot inorganic phosphate (Pi) transfer Contig000259 Os06t0178900-01 7BS_TGACv1_592527_ AA1939830.5.1 184.6 82.2 2.2 Vacuolar H+-pyrophosphatase Contig027611 Os05t0489900-01 U_TGACv1_641100_ AA2085080.2.1 13.9 6.4 2.2 Calcium/calmodulin-dependent protein kinase Contig044047 Os09t0321200-00 U_TGACv1_642666_ AA2121200.1.1 0.9 0.1 11.0 Similar to carotenoid cleavage dioxygenase View Large Furthermore, as shown in Fig. 4 and Supplementary Tables S2 and S3, among the 7817 up-regulated transcripts, 128 transcripts were annotated as transcription factors (TFs), 57 sequences were assigned as acid phosphatases, and 18 as phosphate transporters. In addition, there were two sequences similar to SIZ1, namely SPX domain-containing proteins and PHO1 (which transfers P from roots to shoots), and one sequence was annotated as PHO2. Transcripts associated with auxin responses that regulate root development, and with disease and fungus responses, were also detected, as shown in Supplementary Table S4. Fig. 4. View largeDownload slide Heat map of expression profiling of up-regulated transcription factors (TFs) and selected known genes related to P deficiency. P1-induced up-regulated (P<0.05) TFs (A) and sequences assigned to APases, phosphate transporters (PHT), SPX protein, SIZ1, and PHO1 (B). Note that transcripts with RPKM<3 are presented in Supplementary Tables S1 and S2. The color bar indicates the expression levels [represented as log2 (RPKM means)]; red indicates high expression level and blue indicates low expression level. Fig. 4. View largeDownload slide Heat map of expression profiling of up-regulated transcription factors (TFs) and selected known genes related to P deficiency. P1-induced up-regulated (P<0.05) TFs (A) and sequences assigned to APases, phosphate transporters (PHT), SPX protein, SIZ1, and PHO1 (B). Note that transcripts with RPKM<3 are presented in Supplementary Tables S1 and S2. The color bar indicates the expression levels [represented as log2 (RPKM means)]; red indicates high expression level and blue indicates low expression level. Up-regulated transcripts associated with root-released organic anions The citric acid and glyoxylate cycles play important roles in synthesis of organic acids in plant tissues. To see if biosynthesis of organic acids could be altered by P deficiency, we mapped the annotated transcripts to genes involved in the citric acid and glyoxylate cycles. Our analysis revealed that 38 up-regulated transcripts identified under P1 treatment represent enzyme-encoding genes putatively involved in the citric acid and glyoxylate cycles (Fig. 5A, B; Supplementary Table S5). In addition, organic anions were mainly exuded through plasma membrane-located transporters. Hence, we further found 10 sequences that were associated with organic anion efflux transporters, including the MATE efflux family (transporters that transport a broad range of substrates such as organic anions, plant hormones, and secondary metabolites), citrate transporter (CT), and aluminium-activated malate transporter (ALMT) (Fig. 5C; Supplementary Table S5). Fig. 5. View largeDownload slide Up-regulated sequences associated with organic anion production and efflux under P deficiency (P1). Schematic representation of metabolic pathways (A) including citric acid and glyoxylate cycles related to organic anion production that was up-regulated (P<0.05) under P1 (B) and up-regulated organic anion transporters responsive to P deficiency (C). The color bar indicates the expression levels [represented as log2(RPKM means)]; red indicates high expression level, blue indicates low expression level, and black indicates RPKM=0. Fig. 5. View largeDownload slide Up-regulated sequences associated with organic anion production and efflux under P deficiency (P1). Schematic representation of metabolic pathways (A) including citric acid and glyoxylate cycles related to organic anion production that was up-regulated (P<0.05) under P1 (B) and up-regulated organic anion transporters responsive to P deficiency (C). The color bar indicates the expression levels [represented as log2(RPKM means)]; red indicates high expression level, blue indicates low expression level, and black indicates RPKM=0. RNA-seq validation by qRT-PCR To assess whether differentially expressed transcripts could be confirmed by an alternative method, 14 transcripts were selected and analysed by qRT-PCR using primers listed in Supplementary Table S6. Transcripts known to be up-regulated in response to phosphate starvation, i.e. PHO2, PAP3, RNS1 (RNase), PHO1, and SPX, were confirmed by qRT-PCR and showed similar expression patterns to those analysed by RNA-seq. Additionally, the expression of transcripts involved in root organic anion synthesis, such as malate synthase–isocitrate lyase (MSIL), phosphoenolpyruvate carboxylase (PEPC), citrate synthase (CS), L-malate dehydrogenase (LMD), NADP-dependent malate dehydrogenase (NADP-MD), and efflux transporters such as ALMT and MATE, was also investigated by qRT-PCR. Among 14 transcripts evaluated by qRT-PCR, the trend of changes in 11 (79%) was consistent with the RNA-seq data (Fig. 6). Fig. 6. View largeDownload slide Expression of candidate known genes related to low P stress, and up-regulated transcripts associated with organic anion production and efflux under P1 as determined using RNA-Seq and qRT-PCR. Fourteen genes were selected and analysed using qRT-PCR for both P1 and P100 treatments. Transcript expression levels were normalized using the internal controls β-actin and EF1α (see ‘Materials and methods’). Relative expression values were calculated based on means of four biological replicates (with three technical replicates) under P1 and P100 treatments. Transcripts with statistically insignificant (P>0.05) changes in expression compared with P100 roots are denoted as ns. Fold changes based on RPKM values derived from RNA-seq are plotted on the same graph. The transcript IDs for each gene are listed in Supplementary Table S5. Fig. 6. View largeDownload slide Expression of candidate known genes related to low P stress, and up-regulated transcripts associated with organic anion production and efflux under P1 as determined using RNA-Seq and qRT-PCR. Fourteen genes were selected and analysed using qRT-PCR for both P1 and P100 treatments. Transcript expression levels were normalized using the internal controls β-actin and EF1α (see ‘Materials and methods’). Relative expression values were calculated based on means of four biological replicates (with three technical replicates) under P1 and P100 treatments. Transcripts with statistically insignificant (P>0.05) changes in expression compared with P100 roots are denoted as ns. Fold changes based on RPKM values derived from RNA-seq are plotted on the same graph. The transcript IDs for each gene are listed in Supplementary Table S5. Metabolome analyses To assess the effects of gene expression in oat roots on overall metabolism, non-biased metabolite profiling of oat roots was performed using GC-MS. We detected and identified 82 metabolites in oat roots subjected to P1 and P100, as shown in Supplementary Table S7. Table 3 lists those metabolites that are significantly different (P<0.05, t test in MeV) between the P1 and P100 treatments as well as the P1/P100 response ratios (based on non-transformed data) and FDR correction (based on log2-transformed data). The primary metabolites were amino acids, organic acids, polyhydroxy acids, sugars, phosphates, polyols, and N-compounds. Most of the metabolites showed a response ratio lower than 1, indicating a decrease in P1 roots; only eight metabolites were increased in P1 roots (Table 3; Supplementary Table S7). Table 3. Known metabolites identified by GC-MS in oat roots from P1- and P100-treated plants with P<0.05 Class Metabolite Response ratio P1/P100 P Organic acids 2-Hydroxy-glutaric acid 0.10 0.0023 2-Oxo-glutaric acid 0.08 0.0117 Pantothenic acid 0.69 0.0118 Pyruvic acid 0.17 0.0101 Succinic acid 0.32 0.0063 Amino acids 4-Amino-butanoic acid 0.81 0.0209 Methionine 0.25 0.0253 Valine 0.35 0.0460 N-compounds 5-Methylthio-adenosine 0.22 0.0087 Putrescine 0.29 0.0063 Spermidine 0.56 0.0446 Phenylpropanoids 4-Hydroxy-cinnamic acid 0.75 0.0372 Phosphates Ethanolaminephosphate 0.30 0.0404 Fructose-6-phosphate 0.43 0.0063 Glucose-6-phosphate 0.19 0.0011 Glycerophosphoglycerol 0.27 0.0367 Mannose-6-phosphate 0.22 0.0011 myo-Inositol phosphate 0.25 0.0016 Phosphoric acid 0.28 7.8E-4 Phosphoric acid monomethyl ester 0.41 0.0118 Glucose-6-phosphate 0.20 0.0034 Polyhydroxy Acids Lyxonic acid 0.48 0.0039 Ribonic acid 0.45 0.0087 Polyols Arabitol 0.56 0.0087 myo-Inositol 0.84 0.0157 Ribitol 0.49 0.0157 Sugars Sucrose 0.47 0.0357 Xylose 0.65 0.0209 Glucopyranose 0.27 0.0016 Maltose 0.53 0.0207 Class Metabolite Response ratio P1/P100 P Organic acids 2-Hydroxy-glutaric acid 0.10 0.0023 2-Oxo-glutaric acid 0.08 0.0117 Pantothenic acid 0.69 0.0118 Pyruvic acid 0.17 0.0101 Succinic acid 0.32 0.0063 Amino acids 4-Amino-butanoic acid 0.81 0.0209 Methionine 0.25 0.0253 Valine 0.35 0.0460 N-compounds 5-Methylthio-adenosine 0.22 0.0087 Putrescine 0.29 0.0063 Spermidine 0.56 0.0446 Phenylpropanoids 4-Hydroxy-cinnamic acid 0.75 0.0372 Phosphates Ethanolaminephosphate 0.30 0.0404 Fructose-6-phosphate 0.43 0.0063 Glucose-6-phosphate 0.19 0.0011 Glycerophosphoglycerol 0.27 0.0367 Mannose-6-phosphate 0.22 0.0011 myo-Inositol phosphate 0.25 0.0016 Phosphoric acid 0.28 7.8E-4 Phosphoric acid monomethyl ester 0.41 0.0118 Glucose-6-phosphate 0.20 0.0034 Polyhydroxy Acids Lyxonic acid 0.48 0.0039 Ribonic acid 0.45 0.0087 Polyols Arabitol 0.56 0.0087 myo-Inositol 0.84 0.0157 Ribitol 0.49 0.0157 Sugars Sucrose 0.47 0.0357 Xylose 0.65 0.0209 Glucopyranose 0.27 0.0016 Maltose 0.53 0.0207 FDR correction with α<0.05 is indicated by the P value shown in bold. View Large Table 3. Known metabolites identified by GC-MS in oat roots from P1- and P100-treated plants with P<0.05 Class Metabolite Response ratio P1/P100 P Organic acids 2-Hydroxy-glutaric acid 0.10 0.0023 2-Oxo-glutaric acid 0.08 0.0117 Pantothenic acid 0.69 0.0118 Pyruvic acid 0.17 0.0101 Succinic acid 0.32 0.0063 Amino acids 4-Amino-butanoic acid 0.81 0.0209 Methionine 0.25 0.0253 Valine 0.35 0.0460 N-compounds 5-Methylthio-adenosine 0.22 0.0087 Putrescine 0.29 0.0063 Spermidine 0.56 0.0446 Phenylpropanoids 4-Hydroxy-cinnamic acid 0.75 0.0372 Phosphates Ethanolaminephosphate 0.30 0.0404 Fructose-6-phosphate 0.43 0.0063 Glucose-6-phosphate 0.19 0.0011 Glycerophosphoglycerol 0.27 0.0367 Mannose-6-phosphate 0.22 0.0011 myo-Inositol phosphate 0.25 0.0016 Phosphoric acid 0.28 7.8E-4 Phosphoric acid monomethyl ester 0.41 0.0118 Glucose-6-phosphate 0.20 0.0034 Polyhydroxy Acids Lyxonic acid 0.48 0.0039 Ribonic acid 0.45 0.0087 Polyols Arabitol 0.56 0.0087 myo-Inositol 0.84 0.0157 Ribitol 0.49 0.0157 Sugars Sucrose 0.47 0.0357 Xylose 0.65 0.0209 Glucopyranose 0.27 0.0016 Maltose 0.53 0.0207 Class Metabolite Response ratio P1/P100 P Organic acids 2-Hydroxy-glutaric acid 0.10 0.0023 2-Oxo-glutaric acid 0.08 0.0117 Pantothenic acid 0.69 0.0118 Pyruvic acid 0.17 0.0101 Succinic acid 0.32 0.0063 Amino acids 4-Amino-butanoic acid 0.81 0.0209 Methionine 0.25 0.0253 Valine 0.35 0.0460 N-compounds 5-Methylthio-adenosine 0.22 0.0087 Putrescine 0.29 0.0063 Spermidine 0.56 0.0446 Phenylpropanoids 4-Hydroxy-cinnamic acid 0.75 0.0372 Phosphates Ethanolaminephosphate 0.30 0.0404 Fructose-6-phosphate 0.43 0.0063 Glucose-6-phosphate 0.19 0.0011 Glycerophosphoglycerol 0.27 0.0367 Mannose-6-phosphate 0.22 0.0011 myo-Inositol phosphate 0.25 0.0016 Phosphoric acid 0.28 7.8E-4 Phosphoric acid monomethyl ester 0.41 0.0118 Glucose-6-phosphate 0.20 0.0034 Polyhydroxy Acids Lyxonic acid 0.48 0.0039 Ribonic acid 0.45 0.0087 Polyols Arabitol 0.56 0.0087 myo-Inositol 0.84 0.0157 Ribitol 0.49 0.0157 Sugars Sucrose 0.47 0.0357 Xylose 0.65 0.0209 Glucopyranose 0.27 0.0016 Maltose 0.53 0.0207 FDR correction with α<0.05 is indicated by the P value shown in bold. View Large PCA analysis of metabolite data using all 82 known metabolites as well as 22 alternative metabolites and 39 mass spectral metabolite tags (MSTs) indicated that PC1 nicely defines the difference between two groups and represents about 35.8% of the variation (Fig. 7). However, some overlap in the samples can be seen and high variation within the samples of the same group can be observed, which probably suggests different levels of P deficiency in oat roots and that some P100-treated plants might be suffering P deficiency due to rapid depletion of P in the solution. After FDR correction, only five metabolites showed significant differences between P1 and P100 roots: phosphoric acid, mannose-6-phosphate, glucose-6-phosphate, glucopyranose, and myo-inositol phosphate, which indicated that the central metabolism might be stable in oat roots after 10 d of P deficiency. Regarding the organic acids, all identified organic acids showed P1/P100 ratios lower than 1 except for citric and malic acids, which showed P1/P100 ratios of 1.08 and 1.23, respectively (Table 3; and Supplementary Table S7). Fig. 7. View largeDownload slide Principal component (PC) scores of metabolic variances in oat roots (n=8 × 2). Oat plants were grown in P1 (circles) and P100 (triangles) solutions for 10 d. Fig. 7. View largeDownload slide Principal component (PC) scores of metabolic variances in oat roots (n=8 × 2). Oat plants were grown in P1 (circles) and P100 (triangles) solutions for 10 d. Discussion Phosphorus (P) deficiency severely limits plant growth and productivity. This is especially important for sustainable staple cereal crop production in the future. Understanding the molecular mechanisms underlying root and root-secreted organic anion responses to P deficiency in oat, one of the main cereal crops of the world, is of high interest for optimizing future production. Oono et al. (2011, 2013) concluded that the greatest number of responsive transcripts was observed in roots at 10 d after P deficiency in rice and wheat, while the plant’s morphological and physiological responses to P deficiency become prominent at around 30 d of P starvation (Oono et al., 2011; Cheng et al., 2014; Wang et al., 2015). Hence, we studied transcriptome and metabolome at different time points from root morphology and exudates (i.e. 10 d for RNA and metabolome samples and 2 or 4 weeks for root exudates). Our gene expression and metabolome profiles represent early to mid-term responses, while the others were mainly long-term P deficiency responses. Our physiological analysis did not detect any organic anion exudation after 2 weeks of P-deficient and under P-sufficient conditions in oat. This might be due to (i) the extracted organic anions being below the detection limit, (ii) the inevitably present microorganisms metabolizing the low amounts of organic anions due to the non-sterile root environment (Kuijken et al., 2015), and/or (iii) the root-released organic anions being affected by the plant developmental stage (Watt and Evans, 1999; Aulakh et al., 2001; Wang et al., 2017). Following 4 weeks of P deficiency, under similar growth and sampling conditions, exudation rate of citrate was higher for root of oat than for other species such as canola, rice, cabbage, carrot, barley, soybean, and potato (Gahoonia et al., 2000; Aulakh et al., 2001; Dechassa and Schenk, 2004; Ligaba et al., 2004; Liang et al., 2013; Wang et al., 2015), as well as white lupin (Watt and Evans, 1999; Wang et al., 2007; Cheng et al., 2014), which is to our current knowledge the most efficient species using root-secreted citrate to cope with P deficiency (Cheng et al., 2011). Additionally, the high exudation rate of citrate by oat roots under P1 treatment corresponded well with our greenhouse experiment using clay-loam agricultural soils (Wang et al., 2016). Therefore, exudation of citrate appeared to be a late response to P starvation in oat. Given that production and exudation of organic anions is a more carbon-costly process for plants than other pathways (e.g. the production of root hairs and lateral roots) (Lynch, 2007; Whipps, 1990), it might be economical to release organic anions only at a later stage of P deficiency. Transcripts encoding PEPC and malate synthase from a glyoxylate-like cycle, which are involved in organic anion production, as well as sequences assigned to citrate and malate efflux transporters, were detected in the transcriptome of white lupin cluster roots under low P stress (O’Rourke et al., 2013). By contrast, such transcripts were not reported in wheat, rice, Arabidopsis, or potato (Misson et al., 2005; Hammond et al., 2011; Oono et al., 2011, 2013), probably due to these plants exhibiting a low exudation rate of organic anions under P deficiency (Neumann and Roemheld, 1999; Narang et al., 2000; Aulakh et al., 2001; Wang et al., 2015). In P-starved oat roots, we identified 38 up-regulated transcripts encoding almost all the enzymes associated with the citric acid and glyoxylate cycles except for fumarase and α-ketoglutarate dehydrogenase. Moreover, a transcript annotated as malate synthase–isocitrate lyase (MSIL) was highly expressed (>40-fold) under the P1 compared with the P100 treatment, suggesting an important role of the glyoxylate cycle in organic anion production in oat. This gene is of interest and might be used to improve P uptake in other species using genetic engineering. Exudation of organic anions may also lead to alteration of gene expression of enzymes involved in organic acid metabolism, but this is unlikely to be the case in the current study since no organic anion exudation was yet detected when we sampled RNA. In white lupin, enhanced levels of citrate were observed in roots (2.2-fold) and cluster roots (7.6-fold) after 22 d of P deficiency, whereas after 14 d of P deficiency the changes were 1.4- and 3.5-fold, respectively (Müller et al., 2015), suggesting that changes in the metabolome mainly occurred after long-term P deficiency. Our oat root metabolome analysis indicated that most organic acids showed a general reduction after 10 d of P deficiency, which corresponded well with common bean roots after 21 d of low-P treatment (Hernández et al., 2007), while slight (but not significant) increases in citric and malic acids were detected in our study. Previous studies have suggested that biosynthesis and exudation of organic anions is associated with enhanced expression of genes encoding PEPC, malate dehydrogenase, citrate synthase, and transporters such as ALMT and MATE (Johnson et al., 1994; de la Fuente et al., 1997; Koyama et al., 1999; Watt and Evans, 1999; Delhaize et al., 2009; Wang et al., 2013). However, interpretation of links between gene expression and organic anion biosynthesis and exudation should be done with caution, because enhanced gene expression does not necessarily result in enhanced enzyme levels (and enzyme activities). Also, other cellular conditions caused by P deficiency can affect endogenous enzyme function (Ryan et al., 2001). Additionally, although a number of studies have shown associations between organic anion efflux and internal concentrations (Hoffland et al., 1989; Neumann and Roemheld, 1999), internal concentrations of organic anions are unlikely to directly regulate organic anion efflux in P-deficient plants (Keerthisinghe et al., 1998; Watt and Evans, 1999; Ryan et al., 2001). Rather, transporters are likely to be the most important regulators of organic anion exudation (Ryan et al., 2001). We identified 10 up-regulated transcripts encoding MATE and ALMT family members, and other citrate and malate transporters. While higher expression of transporter-encoding genes may increase the number of transporters per cell, the expression of these transcripts was not high (0.66–16.66 RPKM), and enhanced transcript accumulation cannot be assumed to equal increased protein abundance. Furthermore, efflux is determined by both abundance and activity, with regulation of the latter still largely unknown. Among the known genes expressed in P deficiency, a highly conserved PHR1–IPS1–miRNA399–PHO2 signalling cascade has been elucidated in Arabidopsis and rice (Lin et al., 2009; Oono et al., 2013). PHR1 (PHR2 in rice) is a MYB-type transcription factor, acting as a key factor in regulating downstream P-deficiency-responsive gene expression. Both AtPHR1 and OsPHR2 were not very responsive to P deficiency, but their overexpression activated the expression of a number of P-starvation-induced genes even under P-sufficient conditions (Rubio et al., 2001; Zhou et al., 2008). We did not identify any transcript annotated as PHR1 or PHR2 in our dnORT database. We detected up-regulated SPX, PHO2, RNS1, and SIZ1 in oat. SPX may inhibit the expression of PHR1, and SIZ1 facilitates sumoylation of PHR1 and thereby regulates the post-translational modification of PHR1 (Miura et al., 2005; Chiou & Lin, 2011; Wu et al., 2013), which likely explains why we could not detect differentially expressed PHR1 in oat and suggests that the PHR1–IPS1–miRNA399–PHO2 signalling cascade is likely also conserved in oat. In our study, we also detected many CCAAT-box binding transcription factors, including nuclear factor (NF) Y subunits NF-YA, NF-YB and NF-YC, which respond to P deficiency in oat. CCAAT-box transcription factors, in particular NFYA-B1, play essential roles in root development and P uptake in wheat (Qu et al., 2015). Our previous study also found that root morphology, rhizosphere bacteria and root-colonizing mycorrhizal fungi were involved in the response to low P availability in oat (Wang et al., 2016). The current study identified about 30 up-regulated transcripts associated with auxin responses, which might regulate root morphology, more than 60 transcripts involved in disease response, and nine involved in responses to fungal infection. Additionally, 24 up-regulated transcripts under P deficiency found in the present study had been reported previously in rice and wheat (Oono et al. 2011, 2013), suggesting that these genes are valuable indicators of P deficiency in cereal crops. Another 25 unique transcripts in oat that were up-regulated more than 2-fold under P deficiency were identified. These will be studied further to investigate their roles related to P uptake in oat, in order to facilitate future improvements in oat production. The current study used hydroponics for plant culture. Hydroponics as a root environment are known to influence root architecture, in particular root elongation due to reduced mechanical impedance in the absence of solids (Bengough et al., 2011). Previous studies have suggested that root exudation by plants grown in hydroponics is different from root exudation by plants grown in soil (Neumann et al., 2009; Wang et al., 2015, 2016). Nevertheless, the elimination of other variables such as impact of soil particles and soil microorganisms favors use of hydroponics in root exudation studies (Gahoonia et al., 2000; Aulakh et al., 2001; Dechassa and Schenk, 2004; Ligaba et al., 2004; Cheng et al., 2014). In addition, RNA-seq analysis also benefits from removal of the influence of these variables on gene expression, in that hydroponics make the extraction of high quality root RNA easier. In summary, our current study demonstrated that oat roots show a high exudation rate of citrate and malate at later stages of P deficiency, and identified a number of candidate genes with various predicated functions that might be involved in adaptation of oat plants to P deficiency. These results provide new insights into the molecular mechanisms underpinning root responses to P deficiency and the release of organic anions by P-starved oat roots. Moreover, our study improves our understanding of plant adaptation to low P availability. The identified candidate genes offer potential for future marker-assisted breeding programs and genetic engineering (e.g. genome editing) efforts to generate P-efficient genotypes to contribute to future sustainable oat production. Supplementary data Supplementary data are available at JXB online. Fig. S1. Data distribution of Blastx hits of dnORT sequences. Fig. S2. The Blastx top-hit species distribution of dnORT sequences. Fig. S3. Functional gene onthology (GO) classification of dnORT sequences. Fig. S4. Putative functions (with InterProScan) distribution of dnORT sequences. Table S1. Unique P responsive transcripts found in oat. Table S2. Up-regulated transcription factors under P deficiency. Table S3. Up-regulated transcripts predicted to be acid phosphatases (APases), phosphate transporters and other known genes related to P deficiency. Table S4. Up-regulated transcripts associated with auxin responses, disease responses and responses to fungal infection under P deficiency. Table S5. Up-regulated transcripts associated with organic anion production and efflux under P deficiency. Table S6. Primers used in the present study. Table S7. GC-MS metabolite profiles. Author Contributions YW contributed to the experimental design, sample preparation, plant biomass and root morphology measurements, data analyses, and manuscript writing; JLC conceived the study, contributed to the experimental design, and revised the manuscript; EL conducted the sequence trimming, de novo assembly, annotation, and helped with the data analyses; RB designed the metabolite profiling; TA-M and AE conducted metabolite measurements; and LP helped with the qRT-PCR experiment. All authors approved the manuscript. Acknowledgements This study was supported by the strategic institute program (SIS) on ‘Opportunities for sustainable use of phosphorus in food production’ at the Norwegian Institute of Bioeconomy Research (NIBIO). The authors thank Marit Almvik and Monica Skogen for their kind help with LC-MS/MS and RNA sample preparation, respectively. We are grateful to Prof. Nicholas Clarke for linguistic correction and to the Norwegian Sequencing Centre, Oslo, Norway, for library preparation and sequencing. The Norwegian Sequencing Centre, a national technology platform hosted by the University of Oslo and supported by the ‘Functional Genomics’ and ‘Infrastructure’ programs of the Research Council of Norway and the South-eastern Regional Health Authorities, provided the sequencing service. We thank Ines Fehrle and Joachim Kopka (both from Max Planck Institute of Molecular Plant Physiology, Germany) for their excellent technical assistance and support in analysis of oat metabolites. 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Transcriptome and metabolome analyses provide insights into root and root-released organic anion responses to phosphorus deficiency in oat

Journal of Experimental Botany , Volume Advance Article (15) – May 11, 2018

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Abstract

Abstract Roots and root-released organic anions play important roles in uptake of phosphorus (P), an essential macronutrient for food production. Oat, ranking sixth in the world’s cereal production, contains valuable nutritional compounds and can withstand poor soil conditions. Our aim was to investigate root transcriptional and metabolic responses of oat grown under P-deficient and P-sufficient conditions. We conducted a hydroponic experiment and measured root morphology and organic anion exudation, and analysed changes in the transcriptome and metabolome. Oat roots showed enhanced citrate and malate exudation after 4 weeks of P deficiency. After 10 d of P deficiency, we identified 9371 differentially expressed transcripts with a 2-fold or greater change (P<0.05): 48 sequences predicted to be involved in organic anion biosynthesis and efflux were consistently up-regulated; 24 up-regulated transcripts in oat were also found to be up-regulated upon P starvation in rice and wheat under similar conditions. Phosphorylated metabolites (i.e. glucose-6-phosphate, myo-inositol phosphate) were reduced dramatically, while citrate and malate, some sugars and amino acids increased slightly in P-deficient oat roots. Our data are consistent with a strategy of increased organic anion efflux and a shift in primary metabolism in response to P deficiency in oat. Metabolome, oat (Avena sativa L.), organic anions, phosphorus deficiency, plant roots, RNA-seq Introduction Oat (Avena sativa L.) is one of the most important food and feed crops in the world. It contains various nutritional and health-promoting compounds such as avenanthramides, vitamin E and β-glucans (Gutierrez-Gonzalez et al., 2013; Gutierrez-Gonzalez & Garvin, 2016), which have been suggested to have various health-promoting effects (Alminger and Eklund-Jonsson, 2008; Nazare et al., 2009; Whitehead et al., 2014; Valeur et al., 2016). In addition, oat can withstand poor soil conditions, e.g. acidic soils (Hill 1931; Stewart and McDougall, 2014), and is widely cultivated in temperate climates. In order to feed the rapidly growing world population, we need to secure sustainable food production worldwide. Phosphorus (P) is a key macronutrient with significant impact on plant growth and productivity. However, the P available to plants in soils is often low due to the complexes that P forms with soil minerals and compounds (Vance et al., 2003; Lynch, 2011). In addition, the P resources (mainly phosphate rock) are limited, non-renewable and geographically unevenly distributed (Cordell & White, 2015). Understanding the mechanisms of P mobilization and uptake, and improving P acquisition efficiency, particularly in staple cereal food crops, is important for food security and sustainable future food production (Vance et al., 2003; Faucon et al., 2015). Plants have evolved various adaptive strategies to cope with P deficiency in nature. Examples are morphological responses such as changes in root architecture (Hermans et al., 2006; Lynch, 2011), physiological adaptations such as secreted organic anions and acid phosphatases (Hedley et al., 1982; Hoffland et al., 1989; Jones 1998; Gahoonia et al., 2000; Ryan et al., 2001; Lambers et al., 2006; Cheng et al., 2014; Pang et al., 2015; Wang et al., 2016), biochemical responses to optimize utilization of internal P such as replacement of P lipids with non-P lipids (Chiou & Lin, 2011; Plaxton & Tran, 2011; Faucon et al., 2015; Lambers et al., 2015), molecular responses such as induced expression of high-affinity phosphate transporters (Wu et al., 2013; Zhang et al., 2014), and symbiotic responses such as root colonization with mycorrhizal fungi (Smith et al., 2003; Sawers et al., 2017). Multiple genes and mechanisms are required to improve plant tolerance to P deficiency. Thousands of plant genes that are differentially expressed in response to P deficiency have been identified in various plant species including Arabidopsis, potato, rice, wheat, and white lupin (Misson et al., 2005; Hammond et al., 2011; Oono et al., 2011, 2013; O’Rourke et al., 2013). Regulatory components identified include transcription factors, SPX domain-containing proteins, plant hormones, microRNAs, protein modifiers, and epigenetic modifications (Lin et al., 2009; Panigrahy et al., 2009; Yang & Finnegan, 2010; Chiou & Lin, 2011; Wu et al., 2013; Zhang et al., 2014). The gene regulatory networks that are necessary to sense and respond to P deficiency are complex and differ in different plant species. For Poaceae species, the molecular mechanisms associated with P uptake, translocation, and remobilization are well elucidated in rice (Panigrahy et al., 2009; Oono et al., 2013; Wu et al., 2013). Plant roots play an essential role in P uptake. To promote P uptake upon reduced P availability, most species allocate more biomass to roots, increase root length, and develop more and longer root hairs and secondary roots (Hermans et al., 2006; Lambers et al., 2006; Lynch, 2011; Lambers et al., 2015). Accordingly, research has focused on mechanisms regulating root architecture, especially by phytohormones such as auxin (see reviews by Lin et al., 2009; Panigrahy et al., 2009; Chiou and Lin, 2011; Lynch, 2011). However, only very few candidate genes associated with changes in root architecture under P deficiency have been isolated (e.g. AtLPR1, AtLPR2, AtPDR2, and OsMYB4P; Péret et al., 2014). A rice quantitative trait locus (QTL), Pup1, encoding a protein kinase that confers tolerance to P deficiency, is the only phosphorus-related QTL currently available for marker-assisted breeding programs (Gamuyao et al., 2012; Péret et al., 2014). Root exuded organic anions are also considered to be important in mobilizing soil P and enhancing P uptake. However, there is little information on the molecular mechanisms involved in organic acid biosynthesis and efflux under P deficiency. Despite the importance of oat, limited research has been carried out on its adaptation to P starvation. Wang et al. (2016) found that oat showed an increased root mass/total biomass ratio, high percentage of root colonization by arbuscular mycorrhizal fungi, large amounts of rhizosphere organic anions, and efficient P uptake in low P availability soils. These findings paved the way for our current study on the molecular mechanisms underlying P deficiency responses in oat roots, and the genes and metabolites involved. Here we compare gene expression and metabolome profiles of oat roots exposed to P-sufficient and -deficient conditions. The objectives were to: (i) identify differentially expressed transcripts in oat roots in response to P deficiency, particular focusing on up-regulated transcripts associated with organic anion biosynthesis and exudation; (ii) discover conserved responsive genes in rice, wheat, and oat, and transcripts unique for oat; and (iii) assess differential metabolite accumulation in response to P deficiency and the transcriptional program triggered by it. The overarching goal was to identify candidate genes that may be active in oat adaptation to P deficiency and that may be useful to future breeding and genetic engineering efforts towards oat improvement. Materials and methods Plant growth and harvest Seeds of the oat cultivar ‘BELINDA’ were germinated and grown hydroponically in full strength nutrient medium (Wang et al., 2015) in the greenhouse at the Norwegian University of Life Sciences. Fourteen days after sowing, seedlings were transferred to the same medium supplemented with 100 μM (P100) or 1 μM (P1) KH2PO4, and pH adjusted to 5.8 ± 0.2. Plants were grown under a photoperiod of 16 h light and 8 h dark at a light intensity of 200 ± 20 μmol m−2 s−1 and 50–75% relative humidity, with a temperature of 25 °C/16 °C (day/night). The nutrient solution was replaced every third day. Ten days post-treatment, four root samples (representing four independent biological replications) from both P100- and P1-treated plants were collected for RNA extraction and analysis as described by Oono et al. (2011). These were mixed samples containing the root cap zone, elongation zone, and a part of the maturation zone. These eight root samples, together with another eight samples (four from P1 and four from P100) were used for root metabolome analysis. When roots were sampled for RNA and metabolite extraction, they were quickly washed and the water was removed, after which they were immediately placed in liquid nitrogen. Additionally, eight plants (two treatments, four replicates) were used for studies of root morphology, root organic anions and biomass determinations after 4 weeks of different P treatments. All the plants were in vegetative growth phase, with tillers but before heading. Root released organic anions, root morphology and biomass determination For root exudate collection, briefly, whole root systems of intact plants were carefully washed with deionized water to remove the nutrient solution. The whole root system was then placed into ultrapure Milli-Q water (Millipore, Billerica, MA, USA; the volume varied from 50 to 150 ml depending on the size of the roots) in a container to collect root exudates (Khorassani et al., 2011; Wang et al., 2015). Afterwards, Micropur (0.01 g L−1, Katadyn Products, Kemptthal, Switzerland) was added to the solution to inhibit the activity of microorganisms (Cheng et al., 2014). The collected root exudates were analysed by liquid chromatography–triple quadrupole mass spectrometry (LC-MS/MS), as described in a previous study (Wang et al. 2015). Root-released organic anions were collected and analysed after plants had been grown hydroponically under P1 or P100 for 2 and 4 weeks. After 4 weeks, the total number of green leaves and senesced leaves was recorded. For root morphology determination, WinRHIZO (Epson 1680, WinRHIZO Pro2003b, Regent Instruments Inc., Quebec, Canada) was used to measure root length, number of lateral roots and root surface area. Shoot and root dry weight (DW) were measured separately after oven-drying for 48 h at 65 °C. Shoot P concentrations were subsequently determined by inductively coupled plasma atomic emission spectroscopy (Wang et al., 2015). RNA extraction and quality control Total RNA was extracted using a Spectrum™ Plant Total RNA Kit (Sigma-Aldrich, St Louis, MO, USA) and genomic DNA was removed using On-column DNase I digest kit (Sigma-Aldrich). RNA quantity and quality were assessed by a NanoDrop spectrophotometer (NanoDrop Technologies, Wilmington, DE, USA) and Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). RNA samples with RIN (RNA integrity number) scores greater than 9.0 were used for RNA-Seq. Eight independent root cDNA libraries were prepared according to Illumina’s TruSeq® RNA Sample Preparation v2 Guide, and 125-bp paired-end reads were sequenced using an Illumina HiSeq 2500 sequencer (Illumina, San Diego, CA, USA) at the Norwegian Sequencing Centre (www.sequencing.uio.no). Sequence processing and analysis A total of 215087481 paired-end short read sequences were quality checked, trimmed and de novo assembled using CLC Genomics Workbench v9.01 (Qiagen, Aarhus, Denmark), generating 207 017 contigs, with a maximum contig length of 13319 nt, a minimum contig length of 200 nt, and a mean contig length of 801 nt (Table 1). Gene expression was calculated and normalized using reads per kb per million reads (RPKM). Differential expression between P1 and P100 was analysed by Student’s t-test and up-/down-regulation of genes was considered to be significant if ≥2-fold (P<0.05). Totally, 41679 transcripts were filtered out and selected to be de novo oat root transcriptome (dnORT), used as a reference for further analysis. The dnORT sequences were a combination of the differentially expressed transcripts and other transcripts with RPKM≥1.5 regardless of P treatments. These sequences were annotated using Blast2Go (Conesa et al., 2005) and MapMan (Thimm et al., 2004). RNA sequencing raw data were deposited in the GeneBank Sequence Read Archive (SRA) database under bioproject identifier PRJNA355647. Table 1. Transcriptome statistics Total number of reads 215087481 Assembled contigs 207017 Minimum length (nt) 200 Maximum length (nt) 13319 Mean length (nt) 801 Contigs larger than 1000 nt 9631 Up-regulated contigs 7817 Down-regulated contigs 1554 Annotated contigs 41679 Total number of reads 215087481 Assembled contigs 207017 Minimum length (nt) 200 Maximum length (nt) 13319 Mean length (nt) 801 Contigs larger than 1000 nt 9631 Up-regulated contigs 7817 Down-regulated contigs 1554 Annotated contigs 41679 nt, nucleotides. View Large Table 1. Transcriptome statistics Total number of reads 215087481 Assembled contigs 207017 Minimum length (nt) 200 Maximum length (nt) 13319 Mean length (nt) 801 Contigs larger than 1000 nt 9631 Up-regulated contigs 7817 Down-regulated contigs 1554 Annotated contigs 41679 Total number of reads 215087481 Assembled contigs 207017 Minimum length (nt) 200 Maximum length (nt) 13319 Mean length (nt) 801 Contigs larger than 1000 nt 9631 Up-regulated contigs 7817 Down-regulated contigs 1554 Annotated contigs 41679 nt, nucleotides. View Large Real-time quantitative reverse transcription PCR analysis First-strand cDNA was synthesized from 1.0 µg RNA using iScriptTM Adv cDNA kit for real-time quantitative reverse transcription PCR (qRT-PCR; Bio-Rad, USA). The qRT-PCR reactions were carried out on a CFX96TM real-time system (Bio-Rad) using SsoAdvancedTM Universal SYBR® Green Supermix (Bio-Rad, USA) with transcript-specific primers (shown in Supplementary Table S5 at JXB online). Ten nanograms of cDNA were used as template in a 20 µl qPCR reaction with 0.8 µM primers. After initial denaturing at 95 °C for 5 min, the reaction was followed by 40 cycles at 95 °C for 15 s, 61 °C for 15 s, and 72 °C for 45 s. The expression of endogenous reference genes EF1α (Elongation factor 1α; Kemen et al., 2014) and β-actin was used to normalize the expression level estimated by the Δ∆Cq method provided by CFX Manager 3.1 (Bio-Rad). Four biological replicates of each treatment and three technical replicates of each sample were applied in the analysis. The qPCR data were represented as fold change (P1 mean value: P100 mean value) derived from relative normalized expression level from four biological replicates and further compared with RNA-seq results (P1 RPKM means/P100 RPKM means). R software (version 3.2.2) and one-way ANOVA were used to examine significant differences between P1 and P100 treatments. Heat maps were generated in Heml 1.0: Heatmap illustrator as described by Deng et al. (2014). Root metabolite extraction Eight replicate samples each of roots from plants grown under P1 and P100 conditions were sampled. Frozen samples (with water content varying between 95.3% and 96.6%) of 100 mg (±10%) root were ground to homogeneity (2 min, 30 Hz; Grinding Mill MM310; Retsch, Germany) under freezing conditions. To each sample was added 360 μl precooled (−20 °C) extraction buffer (300 μl methanol, 30 μl 2 mg ml−1 nonadecanoic acid methylester in chloroform, 30 μl 0.2 mg ml−1 [13C]sorbitol in methanol) and samples shaken for 15 min, 70 °C, 1000 rpm (Thermomixer Comfort, Eppendorf, Germany). Samples were cooled to room temperature, added to 200 μl CHCl3, and further shaken for 5 min, 37 °C, 1000 rpm. To each sample was added 400 μl H2O and, following vortexing, samples were centrifuged (5 min, 20 800 g) to facilitate phase separation. Finally, 160 μl of the upper, polar phase was aliquoted and dried overnight by Speed Vac. Gas chromatography–mass spectrometry metabolite profiling and identification Prior to gas chromatography–electron impact–time of flight mass spectrometry (GC-EI/TOF-MS) analysis, metabolites were methoxyaminated and trimethylsilylated. Briefly, addition of 40 µl MeOX (40 mg ml−1 methoxyaminhydrochloride in pyridine), samples were shaken (1.5 h, 30 °C) followed by addition of 80 µl BSTFA mixture (70 µl N,O-bis(trimethylsilyl)trifluoroacetamide+10 µl alkane mix; n-alkanes: C10, C12, C15, C18, C19, C22, C28, C32, and C36), and further shaken (30 min, 37 °C). GC-MS was undertaken using an Agilent CP9013 column in an Agilent 6890N24 gas chromatograph, coupled to a Pegasus III, similar to that previously described (Wagner et al., 2003; Erban et al., 2007; Dethloff et al., 2014). Measurements were undertaken both splitless and split (1/30) from an injection volume of 1 µl, with bulk metabolites reaching the upper detection limit in split-less measurements evaluated from split data. Retention indices were calibrated based on added n-alkanes (Strehmel et al., 2008). Chromatograms were visually controlled, baseline corrected, and exported in NetCDF format using ChromaTOF. Further data processing and compound identification were performed with TagFinder (Luedemann et al., 2008) and by matching to the Golm Metabolome Database (GMD, http://gmd.mpimpgolm.mpg.de/;Kopka et al., 2005; Schauer et al., 2005) and the NIST08 database (http://www.nist.gov/srd/mslist.htm). Manually supervised metabolite annotation and quantification were undertaken with the requirement of at least three specific quantitative mass fragments per compound, and a retention index deviation <1.0%. Data were normalized to sample fresh weight, the internal [13C6]sorbitol, and represented relative to the mean value of P100 samples per analyte. Principal component analysis and statistical analysis Principal component analysis (PCA) was carried out using the program R. Data were normalized to the median of the P100 samples and subsequently subjected to logarithmic (log2) transformation. Missing values were not replaced with zero or a constant value. Statistical testing was performed using the t test in multiple experiment viewer MeV (Saeed et al., 2006), based on log2-transformed data, followed by Mann–Whitney false discovery rate (FDR) correction at α<0.05, due to non-normal distribution (as shown by PCA analysis) of the metabolite data. Results Plant growth, root morphology and root-released organic anion analysis The plant phenotype and root-released organic anions were examined to study the effects of P deficiency on oat growth and root exudates under hydroponic conditions. After 4 weeks of growth under two different P regimes (1 and 100 μM KH2PO4), a drastic reduction of shoot P concentration was observed in plants grown under P-deficient conditions (P1) compared with P100 (0.90 versus 6.35 mg g−1). Oat plants subjected to P1 treatment showed on average a 55% reduction in the total number of leaves, 44% more senescent leaves (number of senescent leaves: number of total leaves), 68% less shoot dry biomass, and 96% greater root mass ratio (root dry biomass: total dry biomass) than P100 plants as shown in Fig. 1A–D. Moreover, P1-treatment plants showed shorter total root length (25%), lower root surface area (27%) and more lateral roots (14%) than P100 plants (Fig. 2A–C). Furthermore, after 4 weeks, compared with P100-treated plants, which showed no detectable root-released organic anions, P1 roots had higher exudation rates of citrate and malate, 927 and 81 nmol h−1 g−1 root dry weight (DW), respectively, as shown in Fig. 2D. By contrast, no organic anions were detected in either P1 or P100 root exudates collected after 2 weeks’ treatment. Fig. 1. View largeDownload slide Plant growth response to P1 and P100 treatments. (A) Total leaves, (B) senescent leaves, (C) shoot dry weight, and (D) root mass ratio. Error bars indicate SE (n=4). Significant differences are indicated (***P<0.001). Fig. 1. View largeDownload slide Plant growth response to P1 and P100 treatments. (A) Total leaves, (B) senescent leaves, (C) shoot dry weight, and (D) root mass ratio. Error bars indicate SE (n=4). Significant differences are indicated (***P<0.001). Fig. 2. View largeDownload slide Oat root response to P1 and P100 treatments. (A) Root length, (B) root surface area, (C) number of root tips, and (D) root-released organic anions. Error bars indicate SE (n=4). Significant differences are indicated (ns, not significant; ***P<0.001). Fig. 2. View largeDownload slide Oat root response to P1 and P100 treatments. (A) Root length, (B) root surface area, (C) number of root tips, and (D) root-released organic anions. Error bars indicate SE (n=4). Significant differences are indicated (ns, not significant; ***P<0.001). Transcriptome analysis of root response to P deficiency Approximately 9.4% of the dnORT transcripts could not be assigned to any Blastx hits (E-value>1E-3) as shown in Supplementary Fig. S1. The Blastx top hit species were: Brachypodium distachyon (22%), Hordeum vulgare subsp. vulgare (17%), Aegilops tauschii (15%), Triticum urartu (10%), and Oryza sativa japonica group (4%) (Supplementary Fig. S2). Functional gene ontology (GO) classification of dnORT sequences suggested that the biological process was mainly represented by the term ‘cellular and metabolic processes’, and the most represented GO subcategories within the cellular component main term were ‘cell or cell part’ and ‘membrane or membrane part’. When the sequences were categorized according to the molecular function main term, 10699 transcripts corresponded to ‘binding category’ and 10522 sequences to ‘catalytic activity’ (Supplementary Fig. S3). Putative functions (with InterProScan) were predicted for 62% of the sequences (Supplementary Fig. S4). In total, 9371 transcripts (7817 up-regulated, 1554 down-regulated) were differentially expressed in response to P deficiency as shown in Table 1. Gene ontology (GO) categories showed that up-regulated transcripts under P deficiency were categorized into more than 40 groups, such as oxidation–reduction process, transmembrane transport, carbohydrate metabolic process, response to osmotic stress, biosynthetic process, pyruvate metabolism, tricarboxylic acid cycle, acid phosphatase, and CCAAT-binding complex (Fig. 3). Fig. 3. View largeDownload slide Functional annotation of up-regulated sequences based on gene ontology (GO) categorization. y-Axis indicates the category, x-axis the percentage of transcripts in a category. Fig. 3. View largeDownload slide Functional annotation of up-regulated sequences based on gene ontology (GO) categorization. y-Axis indicates the category, x-axis the percentage of transcripts in a category. Reciprocal tblastx (E<1E-10) analysis showed that 24 oat transcripts that were up-regulated in P1 matched the conserved responsive genes previously found up-regulated in both rice and wheat (Oono et al., 2013) as listed in Table 2. We also found 25 unique responsive transcripts (between 308 and 1672 nt) in oat roots that were up-regulated more than 2-fold (P<0.001, P1 RPKM means>5), without any blast hits in currently available databases, i.e. they seem to be exclusively expressed in oat (Supplementary Table S1). Table 2. Conserved responsive transcripts found in oat, wheat, and rice under P deficiency dnORT ID Rice proteins Wheat_proteins (TRIAE_CS42) P1 RPKM P100 RPKM Fold change P1/P100 Gene Gene annotation Contig000022 Os05t0137400-01 1AS_TGACv1_020885_ AA0080310.2.1 107.9 48.1 2.2 Similar to aspartic protease precursor Contig000835 Os05t0387200-01 1DL_TGACv1_061485_ AA0196630.2.1 13.5 1.7 8.0 SQD1 Sulphite: UDP-glucose sulfotransferase Contig010807 Os10t0500600-01 1DL_TGACv1_062297_ AA0212030.5.1 48.3 22.6 2.1 Zinc finger, C2H2-like domain containing protein Contig011660 Os07t0100300-02 2AL_TGACv1_094153_ AA0293430.1.1 17.4 1.3 13.4 Glycosyl transferase, group 1 domain containing protein Contig009578 Os10t0100500-01 2AS_TGACv1_113238_ AA0353330.1.1 61.3 11.4 5.4 Serine/threonine protein kinase-related domain containing protein Contig001778 Os07t0622200-01 2AS_TGACv1_113290_ AA0354140.2.1 71.8 68.0 1.1 Similar to M-160-u1_1 Contig009737 Os07t0630400-01 2BS_TGACv1_146583_ AA0468610.1.1 5.2 1.1 4.8 OsRNS1 Ribonuclease T2 family protein Contig005229 Os04t0555300-01 2DL_TGACv1_158105_ AA0509380.4.1 41.6 9.1 4.6 Similar to glycerol 3-phosphate permease Contig019750 Os04t0652700-01 2DL_TGACv1_158583_ AA0522480.2.1 4.8 1.2 4.0 Similar to nuclease PA3 Contig061747 Os01t0128200-01 3AS_TGACv1_210696_ AA0677330.2.1 4.0 1.4 2.8 Similar to nuclease I Contig013859 Os01t0897200-04 3B_TGACv1_224141_ AA0792910.2.1 68.9 21.8 3.2 OsRNS2 Ribonuclease 2 precursor Contig004306 Os06t0115600-01 4AL_TGACv1_289135_ AA0965550.1.1 76.7 53.6 1.4 Similar to CYCLOPS Contig026884 Os08t0299400-01 4AL_TGACv1_289998_ AA0980080.1.1 13.9 0.0 MGD MGDG synthase type A Contig003298 Os03t0238600-01 4AS_TGACv1_308481_ AA1028160.1.1 273.2 54.6 5.0 PAP Similar to purple APase Contig007532 Os09t0553200-01 5AL_TGACv1_374888_ AA1211020.2.1 504.8 181.3 2.8 UGPase UDP-glucose pyrophosphorylase Contig003667 Os09t0478300-01 5AL_TGACv1_376126_ AA1232370.2.1 17.7 7.5 2.4 Conserved hypothetical protein Contig026720 Os12t0554500-00 5AS_TGACv1_393365_ AA1271860.2.1 11.6 0.1 167.7 Lipase, class 3 family protein Contig116061 Os09t0379900-02 5BL_TGACv1_404442_ AA1299920.1.1 1.6 0.6 2.5 Endo-1,3(4)-β-glucanase 2 like Contig073770 Os08t0433200-01 5BL_TGACv1_404654_ AA1307490.1.1 28.0 5.4 5.1 Conserved hypothetical protein Contig007245 Os09t0315700-01 5BL_TGACv1_407230_ AA1354660.1.1 58.1 20.4 2.9 Phosphoenolpyruvate carboxylase family protein Contig000670 Os02t0809800-01 6BL_TGACv1_501820_ AA1620890.2.1 70.5 22.9 3.1 PHO1:H2 Root-to-shoot inorganic phosphate (Pi) transfer Contig000259 Os06t0178900-01 7BS_TGACv1_592527_ AA1939830.5.1 184.6 82.2 2.2 Vacuolar H+-pyrophosphatase Contig027611 Os05t0489900-01 U_TGACv1_641100_ AA2085080.2.1 13.9 6.4 2.2 Calcium/calmodulin-dependent protein kinase Contig044047 Os09t0321200-00 U_TGACv1_642666_ AA2121200.1.1 0.9 0.1 11.0 Similar to carotenoid cleavage dioxygenase dnORT ID Rice proteins Wheat_proteins (TRIAE_CS42) P1 RPKM P100 RPKM Fold change P1/P100 Gene Gene annotation Contig000022 Os05t0137400-01 1AS_TGACv1_020885_ AA0080310.2.1 107.9 48.1 2.2 Similar to aspartic protease precursor Contig000835 Os05t0387200-01 1DL_TGACv1_061485_ AA0196630.2.1 13.5 1.7 8.0 SQD1 Sulphite: UDP-glucose sulfotransferase Contig010807 Os10t0500600-01 1DL_TGACv1_062297_ AA0212030.5.1 48.3 22.6 2.1 Zinc finger, C2H2-like domain containing protein Contig011660 Os07t0100300-02 2AL_TGACv1_094153_ AA0293430.1.1 17.4 1.3 13.4 Glycosyl transferase, group 1 domain containing protein Contig009578 Os10t0100500-01 2AS_TGACv1_113238_ AA0353330.1.1 61.3 11.4 5.4 Serine/threonine protein kinase-related domain containing protein Contig001778 Os07t0622200-01 2AS_TGACv1_113290_ AA0354140.2.1 71.8 68.0 1.1 Similar to M-160-u1_1 Contig009737 Os07t0630400-01 2BS_TGACv1_146583_ AA0468610.1.1 5.2 1.1 4.8 OsRNS1 Ribonuclease T2 family protein Contig005229 Os04t0555300-01 2DL_TGACv1_158105_ AA0509380.4.1 41.6 9.1 4.6 Similar to glycerol 3-phosphate permease Contig019750 Os04t0652700-01 2DL_TGACv1_158583_ AA0522480.2.1 4.8 1.2 4.0 Similar to nuclease PA3 Contig061747 Os01t0128200-01 3AS_TGACv1_210696_ AA0677330.2.1 4.0 1.4 2.8 Similar to nuclease I Contig013859 Os01t0897200-04 3B_TGACv1_224141_ AA0792910.2.1 68.9 21.8 3.2 OsRNS2 Ribonuclease 2 precursor Contig004306 Os06t0115600-01 4AL_TGACv1_289135_ AA0965550.1.1 76.7 53.6 1.4 Similar to CYCLOPS Contig026884 Os08t0299400-01 4AL_TGACv1_289998_ AA0980080.1.1 13.9 0.0 MGD MGDG synthase type A Contig003298 Os03t0238600-01 4AS_TGACv1_308481_ AA1028160.1.1 273.2 54.6 5.0 PAP Similar to purple APase Contig007532 Os09t0553200-01 5AL_TGACv1_374888_ AA1211020.2.1 504.8 181.3 2.8 UGPase UDP-glucose pyrophosphorylase Contig003667 Os09t0478300-01 5AL_TGACv1_376126_ AA1232370.2.1 17.7 7.5 2.4 Conserved hypothetical protein Contig026720 Os12t0554500-00 5AS_TGACv1_393365_ AA1271860.2.1 11.6 0.1 167.7 Lipase, class 3 family protein Contig116061 Os09t0379900-02 5BL_TGACv1_404442_ AA1299920.1.1 1.6 0.6 2.5 Endo-1,3(4)-β-glucanase 2 like Contig073770 Os08t0433200-01 5BL_TGACv1_404654_ AA1307490.1.1 28.0 5.4 5.1 Conserved hypothetical protein Contig007245 Os09t0315700-01 5BL_TGACv1_407230_ AA1354660.1.1 58.1 20.4 2.9 Phosphoenolpyruvate carboxylase family protein Contig000670 Os02t0809800-01 6BL_TGACv1_501820_ AA1620890.2.1 70.5 22.9 3.1 PHO1:H2 Root-to-shoot inorganic phosphate (Pi) transfer Contig000259 Os06t0178900-01 7BS_TGACv1_592527_ AA1939830.5.1 184.6 82.2 2.2 Vacuolar H+-pyrophosphatase Contig027611 Os05t0489900-01 U_TGACv1_641100_ AA2085080.2.1 13.9 6.4 2.2 Calcium/calmodulin-dependent protein kinase Contig044047 Os09t0321200-00 U_TGACv1_642666_ AA2121200.1.1 0.9 0.1 11.0 Similar to carotenoid cleavage dioxygenase View Large Table 2. Conserved responsive transcripts found in oat, wheat, and rice under P deficiency dnORT ID Rice proteins Wheat_proteins (TRIAE_CS42) P1 RPKM P100 RPKM Fold change P1/P100 Gene Gene annotation Contig000022 Os05t0137400-01 1AS_TGACv1_020885_ AA0080310.2.1 107.9 48.1 2.2 Similar to aspartic protease precursor Contig000835 Os05t0387200-01 1DL_TGACv1_061485_ AA0196630.2.1 13.5 1.7 8.0 SQD1 Sulphite: UDP-glucose sulfotransferase Contig010807 Os10t0500600-01 1DL_TGACv1_062297_ AA0212030.5.1 48.3 22.6 2.1 Zinc finger, C2H2-like domain containing protein Contig011660 Os07t0100300-02 2AL_TGACv1_094153_ AA0293430.1.1 17.4 1.3 13.4 Glycosyl transferase, group 1 domain containing protein Contig009578 Os10t0100500-01 2AS_TGACv1_113238_ AA0353330.1.1 61.3 11.4 5.4 Serine/threonine protein kinase-related domain containing protein Contig001778 Os07t0622200-01 2AS_TGACv1_113290_ AA0354140.2.1 71.8 68.0 1.1 Similar to M-160-u1_1 Contig009737 Os07t0630400-01 2BS_TGACv1_146583_ AA0468610.1.1 5.2 1.1 4.8 OsRNS1 Ribonuclease T2 family protein Contig005229 Os04t0555300-01 2DL_TGACv1_158105_ AA0509380.4.1 41.6 9.1 4.6 Similar to glycerol 3-phosphate permease Contig019750 Os04t0652700-01 2DL_TGACv1_158583_ AA0522480.2.1 4.8 1.2 4.0 Similar to nuclease PA3 Contig061747 Os01t0128200-01 3AS_TGACv1_210696_ AA0677330.2.1 4.0 1.4 2.8 Similar to nuclease I Contig013859 Os01t0897200-04 3B_TGACv1_224141_ AA0792910.2.1 68.9 21.8 3.2 OsRNS2 Ribonuclease 2 precursor Contig004306 Os06t0115600-01 4AL_TGACv1_289135_ AA0965550.1.1 76.7 53.6 1.4 Similar to CYCLOPS Contig026884 Os08t0299400-01 4AL_TGACv1_289998_ AA0980080.1.1 13.9 0.0 MGD MGDG synthase type A Contig003298 Os03t0238600-01 4AS_TGACv1_308481_ AA1028160.1.1 273.2 54.6 5.0 PAP Similar to purple APase Contig007532 Os09t0553200-01 5AL_TGACv1_374888_ AA1211020.2.1 504.8 181.3 2.8 UGPase UDP-glucose pyrophosphorylase Contig003667 Os09t0478300-01 5AL_TGACv1_376126_ AA1232370.2.1 17.7 7.5 2.4 Conserved hypothetical protein Contig026720 Os12t0554500-00 5AS_TGACv1_393365_ AA1271860.2.1 11.6 0.1 167.7 Lipase, class 3 family protein Contig116061 Os09t0379900-02 5BL_TGACv1_404442_ AA1299920.1.1 1.6 0.6 2.5 Endo-1,3(4)-β-glucanase 2 like Contig073770 Os08t0433200-01 5BL_TGACv1_404654_ AA1307490.1.1 28.0 5.4 5.1 Conserved hypothetical protein Contig007245 Os09t0315700-01 5BL_TGACv1_407230_ AA1354660.1.1 58.1 20.4 2.9 Phosphoenolpyruvate carboxylase family protein Contig000670 Os02t0809800-01 6BL_TGACv1_501820_ AA1620890.2.1 70.5 22.9 3.1 PHO1:H2 Root-to-shoot inorganic phosphate (Pi) transfer Contig000259 Os06t0178900-01 7BS_TGACv1_592527_ AA1939830.5.1 184.6 82.2 2.2 Vacuolar H+-pyrophosphatase Contig027611 Os05t0489900-01 U_TGACv1_641100_ AA2085080.2.1 13.9 6.4 2.2 Calcium/calmodulin-dependent protein kinase Contig044047 Os09t0321200-00 U_TGACv1_642666_ AA2121200.1.1 0.9 0.1 11.0 Similar to carotenoid cleavage dioxygenase dnORT ID Rice proteins Wheat_proteins (TRIAE_CS42) P1 RPKM P100 RPKM Fold change P1/P100 Gene Gene annotation Contig000022 Os05t0137400-01 1AS_TGACv1_020885_ AA0080310.2.1 107.9 48.1 2.2 Similar to aspartic protease precursor Contig000835 Os05t0387200-01 1DL_TGACv1_061485_ AA0196630.2.1 13.5 1.7 8.0 SQD1 Sulphite: UDP-glucose sulfotransferase Contig010807 Os10t0500600-01 1DL_TGACv1_062297_ AA0212030.5.1 48.3 22.6 2.1 Zinc finger, C2H2-like domain containing protein Contig011660 Os07t0100300-02 2AL_TGACv1_094153_ AA0293430.1.1 17.4 1.3 13.4 Glycosyl transferase, group 1 domain containing protein Contig009578 Os10t0100500-01 2AS_TGACv1_113238_ AA0353330.1.1 61.3 11.4 5.4 Serine/threonine protein kinase-related domain containing protein Contig001778 Os07t0622200-01 2AS_TGACv1_113290_ AA0354140.2.1 71.8 68.0 1.1 Similar to M-160-u1_1 Contig009737 Os07t0630400-01 2BS_TGACv1_146583_ AA0468610.1.1 5.2 1.1 4.8 OsRNS1 Ribonuclease T2 family protein Contig005229 Os04t0555300-01 2DL_TGACv1_158105_ AA0509380.4.1 41.6 9.1 4.6 Similar to glycerol 3-phosphate permease Contig019750 Os04t0652700-01 2DL_TGACv1_158583_ AA0522480.2.1 4.8 1.2 4.0 Similar to nuclease PA3 Contig061747 Os01t0128200-01 3AS_TGACv1_210696_ AA0677330.2.1 4.0 1.4 2.8 Similar to nuclease I Contig013859 Os01t0897200-04 3B_TGACv1_224141_ AA0792910.2.1 68.9 21.8 3.2 OsRNS2 Ribonuclease 2 precursor Contig004306 Os06t0115600-01 4AL_TGACv1_289135_ AA0965550.1.1 76.7 53.6 1.4 Similar to CYCLOPS Contig026884 Os08t0299400-01 4AL_TGACv1_289998_ AA0980080.1.1 13.9 0.0 MGD MGDG synthase type A Contig003298 Os03t0238600-01 4AS_TGACv1_308481_ AA1028160.1.1 273.2 54.6 5.0 PAP Similar to purple APase Contig007532 Os09t0553200-01 5AL_TGACv1_374888_ AA1211020.2.1 504.8 181.3 2.8 UGPase UDP-glucose pyrophosphorylase Contig003667 Os09t0478300-01 5AL_TGACv1_376126_ AA1232370.2.1 17.7 7.5 2.4 Conserved hypothetical protein Contig026720 Os12t0554500-00 5AS_TGACv1_393365_ AA1271860.2.1 11.6 0.1 167.7 Lipase, class 3 family protein Contig116061 Os09t0379900-02 5BL_TGACv1_404442_ AA1299920.1.1 1.6 0.6 2.5 Endo-1,3(4)-β-glucanase 2 like Contig073770 Os08t0433200-01 5BL_TGACv1_404654_ AA1307490.1.1 28.0 5.4 5.1 Conserved hypothetical protein Contig007245 Os09t0315700-01 5BL_TGACv1_407230_ AA1354660.1.1 58.1 20.4 2.9 Phosphoenolpyruvate carboxylase family protein Contig000670 Os02t0809800-01 6BL_TGACv1_501820_ AA1620890.2.1 70.5 22.9 3.1 PHO1:H2 Root-to-shoot inorganic phosphate (Pi) transfer Contig000259 Os06t0178900-01 7BS_TGACv1_592527_ AA1939830.5.1 184.6 82.2 2.2 Vacuolar H+-pyrophosphatase Contig027611 Os05t0489900-01 U_TGACv1_641100_ AA2085080.2.1 13.9 6.4 2.2 Calcium/calmodulin-dependent protein kinase Contig044047 Os09t0321200-00 U_TGACv1_642666_ AA2121200.1.1 0.9 0.1 11.0 Similar to carotenoid cleavage dioxygenase View Large Furthermore, as shown in Fig. 4 and Supplementary Tables S2 and S3, among the 7817 up-regulated transcripts, 128 transcripts were annotated as transcription factors (TFs), 57 sequences were assigned as acid phosphatases, and 18 as phosphate transporters. In addition, there were two sequences similar to SIZ1, namely SPX domain-containing proteins and PHO1 (which transfers P from roots to shoots), and one sequence was annotated as PHO2. Transcripts associated with auxin responses that regulate root development, and with disease and fungus responses, were also detected, as shown in Supplementary Table S4. Fig. 4. View largeDownload slide Heat map of expression profiling of up-regulated transcription factors (TFs) and selected known genes related to P deficiency. P1-induced up-regulated (P<0.05) TFs (A) and sequences assigned to APases, phosphate transporters (PHT), SPX protein, SIZ1, and PHO1 (B). Note that transcripts with RPKM<3 are presented in Supplementary Tables S1 and S2. The color bar indicates the expression levels [represented as log2 (RPKM means)]; red indicates high expression level and blue indicates low expression level. Fig. 4. View largeDownload slide Heat map of expression profiling of up-regulated transcription factors (TFs) and selected known genes related to P deficiency. P1-induced up-regulated (P<0.05) TFs (A) and sequences assigned to APases, phosphate transporters (PHT), SPX protein, SIZ1, and PHO1 (B). Note that transcripts with RPKM<3 are presented in Supplementary Tables S1 and S2. The color bar indicates the expression levels [represented as log2 (RPKM means)]; red indicates high expression level and blue indicates low expression level. Up-regulated transcripts associated with root-released organic anions The citric acid and glyoxylate cycles play important roles in synthesis of organic acids in plant tissues. To see if biosynthesis of organic acids could be altered by P deficiency, we mapped the annotated transcripts to genes involved in the citric acid and glyoxylate cycles. Our analysis revealed that 38 up-regulated transcripts identified under P1 treatment represent enzyme-encoding genes putatively involved in the citric acid and glyoxylate cycles (Fig. 5A, B; Supplementary Table S5). In addition, organic anions were mainly exuded through plasma membrane-located transporters. Hence, we further found 10 sequences that were associated with organic anion efflux transporters, including the MATE efflux family (transporters that transport a broad range of substrates such as organic anions, plant hormones, and secondary metabolites), citrate transporter (CT), and aluminium-activated malate transporter (ALMT) (Fig. 5C; Supplementary Table S5). Fig. 5. View largeDownload slide Up-regulated sequences associated with organic anion production and efflux under P deficiency (P1). Schematic representation of metabolic pathways (A) including citric acid and glyoxylate cycles related to organic anion production that was up-regulated (P<0.05) under P1 (B) and up-regulated organic anion transporters responsive to P deficiency (C). The color bar indicates the expression levels [represented as log2(RPKM means)]; red indicates high expression level, blue indicates low expression level, and black indicates RPKM=0. Fig. 5. View largeDownload slide Up-regulated sequences associated with organic anion production and efflux under P deficiency (P1). Schematic representation of metabolic pathways (A) including citric acid and glyoxylate cycles related to organic anion production that was up-regulated (P<0.05) under P1 (B) and up-regulated organic anion transporters responsive to P deficiency (C). The color bar indicates the expression levels [represented as log2(RPKM means)]; red indicates high expression level, blue indicates low expression level, and black indicates RPKM=0. RNA-seq validation by qRT-PCR To assess whether differentially expressed transcripts could be confirmed by an alternative method, 14 transcripts were selected and analysed by qRT-PCR using primers listed in Supplementary Table S6. Transcripts known to be up-regulated in response to phosphate starvation, i.e. PHO2, PAP3, RNS1 (RNase), PHO1, and SPX, were confirmed by qRT-PCR and showed similar expression patterns to those analysed by RNA-seq. Additionally, the expression of transcripts involved in root organic anion synthesis, such as malate synthase–isocitrate lyase (MSIL), phosphoenolpyruvate carboxylase (PEPC), citrate synthase (CS), L-malate dehydrogenase (LMD), NADP-dependent malate dehydrogenase (NADP-MD), and efflux transporters such as ALMT and MATE, was also investigated by qRT-PCR. Among 14 transcripts evaluated by qRT-PCR, the trend of changes in 11 (79%) was consistent with the RNA-seq data (Fig. 6). Fig. 6. View largeDownload slide Expression of candidate known genes related to low P stress, and up-regulated transcripts associated with organic anion production and efflux under P1 as determined using RNA-Seq and qRT-PCR. Fourteen genes were selected and analysed using qRT-PCR for both P1 and P100 treatments. Transcript expression levels were normalized using the internal controls β-actin and EF1α (see ‘Materials and methods’). Relative expression values were calculated based on means of four biological replicates (with three technical replicates) under P1 and P100 treatments. Transcripts with statistically insignificant (P>0.05) changes in expression compared with P100 roots are denoted as ns. Fold changes based on RPKM values derived from RNA-seq are plotted on the same graph. The transcript IDs for each gene are listed in Supplementary Table S5. Fig. 6. View largeDownload slide Expression of candidate known genes related to low P stress, and up-regulated transcripts associated with organic anion production and efflux under P1 as determined using RNA-Seq and qRT-PCR. Fourteen genes were selected and analysed using qRT-PCR for both P1 and P100 treatments. Transcript expression levels were normalized using the internal controls β-actin and EF1α (see ‘Materials and methods’). Relative expression values were calculated based on means of four biological replicates (with three technical replicates) under P1 and P100 treatments. Transcripts with statistically insignificant (P>0.05) changes in expression compared with P100 roots are denoted as ns. Fold changes based on RPKM values derived from RNA-seq are plotted on the same graph. The transcript IDs for each gene are listed in Supplementary Table S5. Metabolome analyses To assess the effects of gene expression in oat roots on overall metabolism, non-biased metabolite profiling of oat roots was performed using GC-MS. We detected and identified 82 metabolites in oat roots subjected to P1 and P100, as shown in Supplementary Table S7. Table 3 lists those metabolites that are significantly different (P<0.05, t test in MeV) between the P1 and P100 treatments as well as the P1/P100 response ratios (based on non-transformed data) and FDR correction (based on log2-transformed data). The primary metabolites were amino acids, organic acids, polyhydroxy acids, sugars, phosphates, polyols, and N-compounds. Most of the metabolites showed a response ratio lower than 1, indicating a decrease in P1 roots; only eight metabolites were increased in P1 roots (Table 3; Supplementary Table S7). Table 3. Known metabolites identified by GC-MS in oat roots from P1- and P100-treated plants with P<0.05 Class Metabolite Response ratio P1/P100 P Organic acids 2-Hydroxy-glutaric acid 0.10 0.0023 2-Oxo-glutaric acid 0.08 0.0117 Pantothenic acid 0.69 0.0118 Pyruvic acid 0.17 0.0101 Succinic acid 0.32 0.0063 Amino acids 4-Amino-butanoic acid 0.81 0.0209 Methionine 0.25 0.0253 Valine 0.35 0.0460 N-compounds 5-Methylthio-adenosine 0.22 0.0087 Putrescine 0.29 0.0063 Spermidine 0.56 0.0446 Phenylpropanoids 4-Hydroxy-cinnamic acid 0.75 0.0372 Phosphates Ethanolaminephosphate 0.30 0.0404 Fructose-6-phosphate 0.43 0.0063 Glucose-6-phosphate 0.19 0.0011 Glycerophosphoglycerol 0.27 0.0367 Mannose-6-phosphate 0.22 0.0011 myo-Inositol phosphate 0.25 0.0016 Phosphoric acid 0.28 7.8E-4 Phosphoric acid monomethyl ester 0.41 0.0118 Glucose-6-phosphate 0.20 0.0034 Polyhydroxy Acids Lyxonic acid 0.48 0.0039 Ribonic acid 0.45 0.0087 Polyols Arabitol 0.56 0.0087 myo-Inositol 0.84 0.0157 Ribitol 0.49 0.0157 Sugars Sucrose 0.47 0.0357 Xylose 0.65 0.0209 Glucopyranose 0.27 0.0016 Maltose 0.53 0.0207 Class Metabolite Response ratio P1/P100 P Organic acids 2-Hydroxy-glutaric acid 0.10 0.0023 2-Oxo-glutaric acid 0.08 0.0117 Pantothenic acid 0.69 0.0118 Pyruvic acid 0.17 0.0101 Succinic acid 0.32 0.0063 Amino acids 4-Amino-butanoic acid 0.81 0.0209 Methionine 0.25 0.0253 Valine 0.35 0.0460 N-compounds 5-Methylthio-adenosine 0.22 0.0087 Putrescine 0.29 0.0063 Spermidine 0.56 0.0446 Phenylpropanoids 4-Hydroxy-cinnamic acid 0.75 0.0372 Phosphates Ethanolaminephosphate 0.30 0.0404 Fructose-6-phosphate 0.43 0.0063 Glucose-6-phosphate 0.19 0.0011 Glycerophosphoglycerol 0.27 0.0367 Mannose-6-phosphate 0.22 0.0011 myo-Inositol phosphate 0.25 0.0016 Phosphoric acid 0.28 7.8E-4 Phosphoric acid monomethyl ester 0.41 0.0118 Glucose-6-phosphate 0.20 0.0034 Polyhydroxy Acids Lyxonic acid 0.48 0.0039 Ribonic acid 0.45 0.0087 Polyols Arabitol 0.56 0.0087 myo-Inositol 0.84 0.0157 Ribitol 0.49 0.0157 Sugars Sucrose 0.47 0.0357 Xylose 0.65 0.0209 Glucopyranose 0.27 0.0016 Maltose 0.53 0.0207 FDR correction with α<0.05 is indicated by the P value shown in bold. View Large Table 3. Known metabolites identified by GC-MS in oat roots from P1- and P100-treated plants with P<0.05 Class Metabolite Response ratio P1/P100 P Organic acids 2-Hydroxy-glutaric acid 0.10 0.0023 2-Oxo-glutaric acid 0.08 0.0117 Pantothenic acid 0.69 0.0118 Pyruvic acid 0.17 0.0101 Succinic acid 0.32 0.0063 Amino acids 4-Amino-butanoic acid 0.81 0.0209 Methionine 0.25 0.0253 Valine 0.35 0.0460 N-compounds 5-Methylthio-adenosine 0.22 0.0087 Putrescine 0.29 0.0063 Spermidine 0.56 0.0446 Phenylpropanoids 4-Hydroxy-cinnamic acid 0.75 0.0372 Phosphates Ethanolaminephosphate 0.30 0.0404 Fructose-6-phosphate 0.43 0.0063 Glucose-6-phosphate 0.19 0.0011 Glycerophosphoglycerol 0.27 0.0367 Mannose-6-phosphate 0.22 0.0011 myo-Inositol phosphate 0.25 0.0016 Phosphoric acid 0.28 7.8E-4 Phosphoric acid monomethyl ester 0.41 0.0118 Glucose-6-phosphate 0.20 0.0034 Polyhydroxy Acids Lyxonic acid 0.48 0.0039 Ribonic acid 0.45 0.0087 Polyols Arabitol 0.56 0.0087 myo-Inositol 0.84 0.0157 Ribitol 0.49 0.0157 Sugars Sucrose 0.47 0.0357 Xylose 0.65 0.0209 Glucopyranose 0.27 0.0016 Maltose 0.53 0.0207 Class Metabolite Response ratio P1/P100 P Organic acids 2-Hydroxy-glutaric acid 0.10 0.0023 2-Oxo-glutaric acid 0.08 0.0117 Pantothenic acid 0.69 0.0118 Pyruvic acid 0.17 0.0101 Succinic acid 0.32 0.0063 Amino acids 4-Amino-butanoic acid 0.81 0.0209 Methionine 0.25 0.0253 Valine 0.35 0.0460 N-compounds 5-Methylthio-adenosine 0.22 0.0087 Putrescine 0.29 0.0063 Spermidine 0.56 0.0446 Phenylpropanoids 4-Hydroxy-cinnamic acid 0.75 0.0372 Phosphates Ethanolaminephosphate 0.30 0.0404 Fructose-6-phosphate 0.43 0.0063 Glucose-6-phosphate 0.19 0.0011 Glycerophosphoglycerol 0.27 0.0367 Mannose-6-phosphate 0.22 0.0011 myo-Inositol phosphate 0.25 0.0016 Phosphoric acid 0.28 7.8E-4 Phosphoric acid monomethyl ester 0.41 0.0118 Glucose-6-phosphate 0.20 0.0034 Polyhydroxy Acids Lyxonic acid 0.48 0.0039 Ribonic acid 0.45 0.0087 Polyols Arabitol 0.56 0.0087 myo-Inositol 0.84 0.0157 Ribitol 0.49 0.0157 Sugars Sucrose 0.47 0.0357 Xylose 0.65 0.0209 Glucopyranose 0.27 0.0016 Maltose 0.53 0.0207 FDR correction with α<0.05 is indicated by the P value shown in bold. View Large PCA analysis of metabolite data using all 82 known metabolites as well as 22 alternative metabolites and 39 mass spectral metabolite tags (MSTs) indicated that PC1 nicely defines the difference between two groups and represents about 35.8% of the variation (Fig. 7). However, some overlap in the samples can be seen and high variation within the samples of the same group can be observed, which probably suggests different levels of P deficiency in oat roots and that some P100-treated plants might be suffering P deficiency due to rapid depletion of P in the solution. After FDR correction, only five metabolites showed significant differences between P1 and P100 roots: phosphoric acid, mannose-6-phosphate, glucose-6-phosphate, glucopyranose, and myo-inositol phosphate, which indicated that the central metabolism might be stable in oat roots after 10 d of P deficiency. Regarding the organic acids, all identified organic acids showed P1/P100 ratios lower than 1 except for citric and malic acids, which showed P1/P100 ratios of 1.08 and 1.23, respectively (Table 3; and Supplementary Table S7). Fig. 7. View largeDownload slide Principal component (PC) scores of metabolic variances in oat roots (n=8 × 2). Oat plants were grown in P1 (circles) and P100 (triangles) solutions for 10 d. Fig. 7. View largeDownload slide Principal component (PC) scores of metabolic variances in oat roots (n=8 × 2). Oat plants were grown in P1 (circles) and P100 (triangles) solutions for 10 d. Discussion Phosphorus (P) deficiency severely limits plant growth and productivity. This is especially important for sustainable staple cereal crop production in the future. Understanding the molecular mechanisms underlying root and root-secreted organic anion responses to P deficiency in oat, one of the main cereal crops of the world, is of high interest for optimizing future production. Oono et al. (2011, 2013) concluded that the greatest number of responsive transcripts was observed in roots at 10 d after P deficiency in rice and wheat, while the plant’s morphological and physiological responses to P deficiency become prominent at around 30 d of P starvation (Oono et al., 2011; Cheng et al., 2014; Wang et al., 2015). Hence, we studied transcriptome and metabolome at different time points from root morphology and exudates (i.e. 10 d for RNA and metabolome samples and 2 or 4 weeks for root exudates). Our gene expression and metabolome profiles represent early to mid-term responses, while the others were mainly long-term P deficiency responses. Our physiological analysis did not detect any organic anion exudation after 2 weeks of P-deficient and under P-sufficient conditions in oat. This might be due to (i) the extracted organic anions being below the detection limit, (ii) the inevitably present microorganisms metabolizing the low amounts of organic anions due to the non-sterile root environment (Kuijken et al., 2015), and/or (iii) the root-released organic anions being affected by the plant developmental stage (Watt and Evans, 1999; Aulakh et al., 2001; Wang et al., 2017). Following 4 weeks of P deficiency, under similar growth and sampling conditions, exudation rate of citrate was higher for root of oat than for other species such as canola, rice, cabbage, carrot, barley, soybean, and potato (Gahoonia et al., 2000; Aulakh et al., 2001; Dechassa and Schenk, 2004; Ligaba et al., 2004; Liang et al., 2013; Wang et al., 2015), as well as white lupin (Watt and Evans, 1999; Wang et al., 2007; Cheng et al., 2014), which is to our current knowledge the most efficient species using root-secreted citrate to cope with P deficiency (Cheng et al., 2011). Additionally, the high exudation rate of citrate by oat roots under P1 treatment corresponded well with our greenhouse experiment using clay-loam agricultural soils (Wang et al., 2016). Therefore, exudation of citrate appeared to be a late response to P starvation in oat. Given that production and exudation of organic anions is a more carbon-costly process for plants than other pathways (e.g. the production of root hairs and lateral roots) (Lynch, 2007; Whipps, 1990), it might be economical to release organic anions only at a later stage of P deficiency. Transcripts encoding PEPC and malate synthase from a glyoxylate-like cycle, which are involved in organic anion production, as well as sequences assigned to citrate and malate efflux transporters, were detected in the transcriptome of white lupin cluster roots under low P stress (O’Rourke et al., 2013). By contrast, such transcripts were not reported in wheat, rice, Arabidopsis, or potato (Misson et al., 2005; Hammond et al., 2011; Oono et al., 2011, 2013), probably due to these plants exhibiting a low exudation rate of organic anions under P deficiency (Neumann and Roemheld, 1999; Narang et al., 2000; Aulakh et al., 2001; Wang et al., 2015). In P-starved oat roots, we identified 38 up-regulated transcripts encoding almost all the enzymes associated with the citric acid and glyoxylate cycles except for fumarase and α-ketoglutarate dehydrogenase. Moreover, a transcript annotated as malate synthase–isocitrate lyase (MSIL) was highly expressed (>40-fold) under the P1 compared with the P100 treatment, suggesting an important role of the glyoxylate cycle in organic anion production in oat. This gene is of interest and might be used to improve P uptake in other species using genetic engineering. Exudation of organic anions may also lead to alteration of gene expression of enzymes involved in organic acid metabolism, but this is unlikely to be the case in the current study since no organic anion exudation was yet detected when we sampled RNA. In white lupin, enhanced levels of citrate were observed in roots (2.2-fold) and cluster roots (7.6-fold) after 22 d of P deficiency, whereas after 14 d of P deficiency the changes were 1.4- and 3.5-fold, respectively (Müller et al., 2015), suggesting that changes in the metabolome mainly occurred after long-term P deficiency. Our oat root metabolome analysis indicated that most organic acids showed a general reduction after 10 d of P deficiency, which corresponded well with common bean roots after 21 d of low-P treatment (Hernández et al., 2007), while slight (but not significant) increases in citric and malic acids were detected in our study. Previous studies have suggested that biosynthesis and exudation of organic anions is associated with enhanced expression of genes encoding PEPC, malate dehydrogenase, citrate synthase, and transporters such as ALMT and MATE (Johnson et al., 1994; de la Fuente et al., 1997; Koyama et al., 1999; Watt and Evans, 1999; Delhaize et al., 2009; Wang et al., 2013). However, interpretation of links between gene expression and organic anion biosynthesis and exudation should be done with caution, because enhanced gene expression does not necessarily result in enhanced enzyme levels (and enzyme activities). Also, other cellular conditions caused by P deficiency can affect endogenous enzyme function (Ryan et al., 2001). Additionally, although a number of studies have shown associations between organic anion efflux and internal concentrations (Hoffland et al., 1989; Neumann and Roemheld, 1999), internal concentrations of organic anions are unlikely to directly regulate organic anion efflux in P-deficient plants (Keerthisinghe et al., 1998; Watt and Evans, 1999; Ryan et al., 2001). Rather, transporters are likely to be the most important regulators of organic anion exudation (Ryan et al., 2001). We identified 10 up-regulated transcripts encoding MATE and ALMT family members, and other citrate and malate transporters. While higher expression of transporter-encoding genes may increase the number of transporters per cell, the expression of these transcripts was not high (0.66–16.66 RPKM), and enhanced transcript accumulation cannot be assumed to equal increased protein abundance. Furthermore, efflux is determined by both abundance and activity, with regulation of the latter still largely unknown. Among the known genes expressed in P deficiency, a highly conserved PHR1–IPS1–miRNA399–PHO2 signalling cascade has been elucidated in Arabidopsis and rice (Lin et al., 2009; Oono et al., 2013). PHR1 (PHR2 in rice) is a MYB-type transcription factor, acting as a key factor in regulating downstream P-deficiency-responsive gene expression. Both AtPHR1 and OsPHR2 were not very responsive to P deficiency, but their overexpression activated the expression of a number of P-starvation-induced genes even under P-sufficient conditions (Rubio et al., 2001; Zhou et al., 2008). We did not identify any transcript annotated as PHR1 or PHR2 in our dnORT database. We detected up-regulated SPX, PHO2, RNS1, and SIZ1 in oat. SPX may inhibit the expression of PHR1, and SIZ1 facilitates sumoylation of PHR1 and thereby regulates the post-translational modification of PHR1 (Miura et al., 2005; Chiou & Lin, 2011; Wu et al., 2013), which likely explains why we could not detect differentially expressed PHR1 in oat and suggests that the PHR1–IPS1–miRNA399–PHO2 signalling cascade is likely also conserved in oat. In our study, we also detected many CCAAT-box binding transcription factors, including nuclear factor (NF) Y subunits NF-YA, NF-YB and NF-YC, which respond to P deficiency in oat. CCAAT-box transcription factors, in particular NFYA-B1, play essential roles in root development and P uptake in wheat (Qu et al., 2015). Our previous study also found that root morphology, rhizosphere bacteria and root-colonizing mycorrhizal fungi were involved in the response to low P availability in oat (Wang et al., 2016). The current study identified about 30 up-regulated transcripts associated with auxin responses, which might regulate root morphology, more than 60 transcripts involved in disease response, and nine involved in responses to fungal infection. Additionally, 24 up-regulated transcripts under P deficiency found in the present study had been reported previously in rice and wheat (Oono et al. 2011, 2013), suggesting that these genes are valuable indicators of P deficiency in cereal crops. Another 25 unique transcripts in oat that were up-regulated more than 2-fold under P deficiency were identified. These will be studied further to investigate their roles related to P uptake in oat, in order to facilitate future improvements in oat production. The current study used hydroponics for plant culture. Hydroponics as a root environment are known to influence root architecture, in particular root elongation due to reduced mechanical impedance in the absence of solids (Bengough et al., 2011). Previous studies have suggested that root exudation by plants grown in hydroponics is different from root exudation by plants grown in soil (Neumann et al., 2009; Wang et al., 2015, 2016). Nevertheless, the elimination of other variables such as impact of soil particles and soil microorganisms favors use of hydroponics in root exudation studies (Gahoonia et al., 2000; Aulakh et al., 2001; Dechassa and Schenk, 2004; Ligaba et al., 2004; Cheng et al., 2014). In addition, RNA-seq analysis also benefits from removal of the influence of these variables on gene expression, in that hydroponics make the extraction of high quality root RNA easier. In summary, our current study demonstrated that oat roots show a high exudation rate of citrate and malate at later stages of P deficiency, and identified a number of candidate genes with various predicated functions that might be involved in adaptation of oat plants to P deficiency. These results provide new insights into the molecular mechanisms underpinning root responses to P deficiency and the release of organic anions by P-starved oat roots. Moreover, our study improves our understanding of plant adaptation to low P availability. The identified candidate genes offer potential for future marker-assisted breeding programs and genetic engineering (e.g. genome editing) efforts to generate P-efficient genotypes to contribute to future sustainable oat production. Supplementary data Supplementary data are available at JXB online. Fig. S1. Data distribution of Blastx hits of dnORT sequences. Fig. S2. The Blastx top-hit species distribution of dnORT sequences. Fig. S3. Functional gene onthology (GO) classification of dnORT sequences. Fig. S4. Putative functions (with InterProScan) distribution of dnORT sequences. Table S1. Unique P responsive transcripts found in oat. Table S2. Up-regulated transcription factors under P deficiency. Table S3. Up-regulated transcripts predicted to be acid phosphatases (APases), phosphate transporters and other known genes related to P deficiency. Table S4. Up-regulated transcripts associated with auxin responses, disease responses and responses to fungal infection under P deficiency. Table S5. Up-regulated transcripts associated with organic anion production and efflux under P deficiency. Table S6. Primers used in the present study. Table S7. GC-MS metabolite profiles. Author Contributions YW contributed to the experimental design, sample preparation, plant biomass and root morphology measurements, data analyses, and manuscript writing; JLC conceived the study, contributed to the experimental design, and revised the manuscript; EL conducted the sequence trimming, de novo assembly, annotation, and helped with the data analyses; RB designed the metabolite profiling; TA-M and AE conducted metabolite measurements; and LP helped with the qRT-PCR experiment. All authors approved the manuscript. Acknowledgements This study was supported by the strategic institute program (SIS) on ‘Opportunities for sustainable use of phosphorus in food production’ at the Norwegian Institute of Bioeconomy Research (NIBIO). The authors thank Marit Almvik and Monica Skogen for their kind help with LC-MS/MS and RNA sample preparation, respectively. We are grateful to Prof. Nicholas Clarke for linguistic correction and to the Norwegian Sequencing Centre, Oslo, Norway, for library preparation and sequencing. The Norwegian Sequencing Centre, a national technology platform hosted by the University of Oslo and supported by the ‘Functional Genomics’ and ‘Infrastructure’ programs of the Research Council of Norway and the South-eastern Regional Health Authorities, provided the sequencing service. We thank Ines Fehrle and Joachim Kopka (both from Max Planck Institute of Molecular Plant Physiology, Germany) for their excellent technical assistance and support in analysis of oat metabolites. 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Published: May 11, 2018

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