TY - JOUR
AU - Watt, Derek A.
AB - Abstract Suppression subtractive hybridization (SSH) technology was used to gain preliminary insights into gene expression induced by the phytotoxic aluminium species, Al3+, in sugarcane roots. Roots of hydroponically‐grown Saccharum spp. hybrid cv. N19 were exposed to 221 µM Al3+ at pH 4.1 for 24 h, a regime shown to inhibit root elongation by 43%, relative to unchallenged roots. Database comparisons revealed that, of a subset of 50 cDNAs ostensibly up‐regulated by the metal in the root tips, 14 possessed putative identities indicative of involvement in signalling events and the regulation of gene expression, while the majority (28) were of unknown function. All of the 50 cDNAs sequenced displayed significant similarity to uncharacterized plant expressed sequence tags (ESTs), approximately half (23) of which had been derived from other graminaceous crop species that had been subject to a variety of stresses. Analysis of the expression of 288 putative Al3+‐inducible genic fragments indicated higher levels of expression under oxidative (1 mM diamide for 4 h) rather than Al3+ stress. By deploying SSH, this study has provided an indication of the nature of genes expressed in sugarcane roots under Al3+ stress. It is anticipated that the information obtained will guide further exploration of the potential for manipulation of the Al tolerance characteristics of the crop. Key words: Aluminium, oxidative stress, sugarcane, suppression subtractive hybridization. Received 19 July 2002; Accepted 10 January 2003 Introduction The incidence and negative consequences of Al phytotoxicity on plant growth and crop production are of worldwide relevance and, consequently, have been the focus of numerous international research efforts (Taylor, 1991; Snowden and Gardner, 1993; Delhaize and Ryan, 1995; Kochian, 1995; Matsumoto, 2000). The effects of the metal on agricultural productivity are also of concern within the South African sugar industry where severe soil acidification has resulted from intensive sugarcane monocropping (Schroeder et al., 1994). Although current strategies used within the industry to alleviate the negative effects of soil acidity and by association Al phytotoxicity have met with some success (Schumann et al., 1999), they do not offer a sustainable solution for a number of agronomic, economic and environmental reasons. Hence, the exploitation and potential manipulation of Al tolerance characteristics of sugarcane, through the application of molecular technology, are increasingly viewed as desirable adjuncts to existing agronomic practices. However, fundamental to the deployment of these technologies is knowledge of the mechanisms through which sugarcane perceives and responds to such potentially harmful stimuli in the rhizosphere. Attempts to unravel the molecular mechanisms underlying the response of sugarcane to Al have been confined to the general data‐mining approach adopted within the Brazilian sugarcane Expressed Sequence Tag (EST) project, SUCEST (Drummond et al., 2001). However, studies on other graminaceous crops (Snowden and Gardner, 1993; Cruz‐Ortega et al., 1997; Hamel et al., 1998) and dicotyledonous species (Ezaki et al., 1995; Richards et al., 1998) have identified a number of genes expressed specifically as a consequence of a defined Al stress. Those investigations revealed that the metal induces the expression of diverse genes, including several involved in general plant stress‐responsive (Snowden and Gardner, 1993; Ezaki et al., 2000), pathogenesis (Cruz‐Ortega et al., 1997; Hamel et al., 1998) and anti‐oxidant (Richards et al., 1998) pathways. In instances where such Al‐induced ESTs have been used as transgenes, reduced susceptibility to both Al‐ and oxidative‐stresses has been demonstrated (Ezaki et al., 1999; Ezaki et al., 2000). Hence, given the diversity and apparently indiscriminate nature of Al‐responsive genes isolated to‐date (Richards et al., 1998), derivation of conclusions regarding the contributions of these individual determinants to overall Al tolerance is difficult. Detailed investigations into plant responses to agronomically important stresses, other than Al, have revealed that degree of tolerance may reside within variations in signalling pathways and gene regulatory mechanisms (Scheel and Wasternack, 2002). Hence, subsequent to the successful isolation of numerous genes with up‐regulated expression in response to such stresses, considerable effort has been expended on the discovery of proteins that regulate gene transcription, which may ultimately confer tolerance (Kirch et al., 2002; Xiong and Zhu, 2002). To date, however, investigations into signalling and regulatory pathways elicited by Al stress have been limited, possibly due to the challenges associated with the identification of genes involved in the perception of phytotoxic levels of Al in the rhizosphere and the consequent transmission of the stress response. In this regard, the advent of suppression subtractive hybridization (SSH) technology (Diatchenko et al., 1996) has provided plant physiologists with a powerful means to construct subtractive cDNA libraries enriched for rare transcripts, such as those involved in signalling and the regulation of gene expression. Towards the ultimate goal of elucidating the molecular responses of sugarcane to Al, SSH was used in the current study to capture and enrich rare transcripts expressed in root tips as a consequence of exposure to a demonstrably phytotoxic level of the metal. Insights into the nature of pathways operational under Al stress were gathered through the assignment of putative identities to a subset of these genic fragments through electronic database homology searches. In addition, the induction specificity of the isolated genic fragments was assessed by analysis of their expression under conditions of Al‐ and oxidative stress. These investigations aimed at establishing the nature of gene expression in sugarcane roots under Al phytotoxic conditions and the information obtained will permit more focused study of the Al tolerance characteristics of the crop. Materials and methods Plant material and growth conditions Entire transverse nodal culm sections, bearing a single intact axillary bud, of Saccharum spp. hybrid cv. N19 (N19) were planted to a depth of 1 cm in acid‐washed graded silica. To induce bud break and subsequent plantlet growth, water was supplied twice daily and supplemented weekly with nutrient medium (Hydroponic Nutrient Mix, Hygrotech Seeds [PTY] Ltd, Silverton, RSA) under glasshouse conditions (28±6 °C). After shoot emergence, plantlets were transferred to silica medium contained within 1.0 l volume pots and supplied with water and Long Ashton nutrients (Hewitt, 1966) by capillary action from a 20 l volume sump. Once the first population of metabolically active roots was established (approximately 5 weeks after bud break) the remaining portions of the original culm were excised and the plantlets introduced into a hydroponics system. Ten litre volume plastic buckets served as the basis of this system, with aeration and agitation of the medium by means of a diaphragm pump at approximately 0.5 l air delivered vessel–1 min–1. The growth medium was the Long Ashton formulation (Hewitt, 1966), modified to contain 2 mM NH4Cl, 0.09 mM Fe‐EDTA and 0.0033 mM CuSO4, at pH 5.5. To accommodate the plants, four holes of 2.5 cm diameter were cut in the lid of each vessel, through each of which a single 5‐week‐old plant was inserted and supported by a 5 cm wide Neoprene® collar. A 32 cm length of polycarbonate tubing (internal diameter 1.1 cm, external diameter 1.2 cm) with multiple perforations was inserted through the centre of each lid, which served to deliver air from the diaphragm pump. The four plants within each of 12 vessels were cultured for 4 weeks and supplied weekly with fresh nutrient medium. Twenty‐four hours prior to stress imposition, plants were supplied with fresh nutrient medium. Al3+ and oxidative stress: application and measurement of effects Challenge of roots with Al was conducted under conditions identical to those used in the hydroponic culture of plants, except that the nutrient medium was replaced with various concentrations of Al in 1 mM CaCl2. In the formulation of the medium for Al challenge, a 0.1 M AlCl3 stock was prepared by adding an appropriate amount of the chemical to polished water, acidified to a pH value of 3.0 with concentrated HCl (Hamel et al., 1998). Various volumes of this stock were added to 1 mM CaCl2 (pH 4.5) to give Al of concentrations 0, 0.05, 0.10, 0.25, 0.50, and 1.00 mM. The final pH value of these solutions was adjusted to 4.15 with concentrated HCl. The activity of the Al3+ ion at each concentration was determined by means of the ion speciation programme, MINTEQA2/PRODEFA2 (Allison et al., 1990). Plants exposed to 1 mM CaCl2 under identical conditions but in the absence of AlCl3 served as controls. Before exposure to the Al3+‐containing media, roots were rinsed three times with deionized water and blotted dry to remove traces of nutrient medium, after which the distal 10 mm region of each root was demarcated with indelible ink. Any increase in length of the tip of each root was measured after 24, 48, and 72 h and the average increase in root length for each treatment expressed as a relative root growth inhibition index (%RGI), calculated according to the equation cited by Hamel et al. (1998). The significance of the effects of the Al3+ treatments on retardation of root elongation was assessed by means of an unpaired student t‐test (SigmaPlot® version 4.0, Jandel Scientific). After measurement of root growth, the organs from three of the plants subjected to each treatment were separated and dried at 180 °C for 24 h. The Al content of roots, stems and leaves was determined by catechol violet dye colourimetry, following acid digestion (Wilson, 1984). Diamide [(CH3)2NCON=NCON(CH3)2] (Sigma), a thiol‐oxidizing compound (Kosower et al., 1969), was selected as agent for the imposition of oxidative stress on roots (Ezaki et al., 2000). Roots were exposed to 1 mM diamide for 4, 8, and 12 h, under conditions used for the Al challenge. After the elapse of each exposure period, roots were rinsed three times with deionized water, blotted dry and the distal portion (approximately 10 mm) of each root excised, and immediately frozen to –196 °C in liquid nitrogen. Total protein was extracted (Ibrahim and Cavia, 1975) from a portion of the harvested tips and quantified colourimetrically (Bradford, 1976). The effect of diamide on the roots was assessed through the determination of total reduced glutathione levels in a further portion of the root tips (Baker et al., 1990). The remaining root tips (approximately 2 g) were stored at –80 °C until required. cDNA synthesis and subtraction The protocol described by Carson and Botha (2000) was followed in the extraction of total RNA from approximately 2 g of frozen (–80 °C) root tips harvested from control plants and those challenged by Al3+ at a concentration and for a duration shown to have maximum inhibitory effect on root elongation. The total RNA preparations were further purified by selective binding and elution from silica‐gel‐based membranes (RNeasy Plant Mini Kit, Qiagen) prior to poly A+ RNA (mRNA) isolation by means of Dynabeads® Oligo (dT)25 (Dynal®), with final elution into a 10 µl volume. To increase the representation of 5′ ends within the final double‐stranded (ds) cDNA population, reverse transcription of mRNA and second strand synthesis reactions were facilitated by means of a SMART™ PCR cDNA Synthesis Kit (Clontech). A suppression subtractive hybridization (SSH) approach (Diatchenko et al., 1996) (PCR‐Select™ cDNA Subtraction Kit, Clontech) was adopted to isolate fragments of genes up‐regulated in root tips in response to Al3+ challenge. During subtraction, ds cDNA populations derived from control and Al3+‐challenged roots tips served as driver and tester cDNA, respectively. After cloning (pGEM®‐T Easy Vector System, Promega), 288 E. coli (strain JM 109) colonies containing recombinant plasmid vector DNA were selected randomly for further analysis. Array printing, querying and analysis The cDNA inserts, which were to serve as probes in the reverse northern hybridization analyses, were amplified directly from each of the 288 bacterial clones by means of the PCR and vector‐specific primers (pGEM®‐T Easy Vector System, Promega). To determine approximate insert size and verify the specificity and efficiency of PCR amplification, aliquots (2 µl) of the amplified PCR products were fractionated by means of standard agarose gel electrophoresis. Following this verification, amplicons were denatured by the addition of NaOH to a final concentration of 0.2 N, heating to 65 °C for 30 min (Cairney et al., 1999) and quenching on ice. Aliquots (0.2 µl) of the denatured PCR products, representing approximately 20 ng of probe DNA, were transferred in triplicate to 150–100 mm portions of positively‐charged nylon membrane (Hybond™‐N+, Amersham Pharmacia Biotech) with a 96 pin replicator (V&P Scientific, San Diego, Ca). The amplified cDNAs were deposited in a 3×3 format with a single blank row and column intervening amongst each array unit. Once printed, the membranes were dried under a stream of filtered air for 2 h and the denatured probe cDNA cross‐linked to the membrane with short‐wavelength ultra‐violet radiation (120 000 mJ cm–2 for 2 min). The membranes were stored desiccated at room temperature until required. The mRNA populations that served as template for the production of driver and tester cDNA for SSH reactions, as well as those isolated from diamide challenged and control root tips, were used to synthesize target total cDNA populations for array querying. The target cDNA was synthesized and labelled with [α‐33P] dATP (AEC Amersham) by means of the Advantage PCR system (Clontech), using single‐strand (ss) cDNA generated by SMART technology (SMART™ PCR cDNA Synthesis Kit, Clontech), according to the principle described by Cairney et al. (1999). The labelled target was purified from unincorporated dNTPs with NucTrap® Probe Purification Columns (Stratagene), and heated to 100 °C for 5 min, with subsequent quenching to 0 °C, immediately prior to array querying. The cDNA probes on the arrays and the 33P‐labelled target cDNA populations were allowed to hybridize overnight under conditions identical to those described by Carson et al. (2002). Used for array querying were target cDNA populations derived from Al3+‐ and diamide‐treated roots, as well those from prepared from the roots of plants in two experimental controls. Each querying event was repeated twice. After array washing (Carson et al., 2002), the hybridization patterns were captured through exposure of the membranes for 18 h to high‐resolution phosphor screens with subsequent laser scanning (Cyclone™ Storage Phosphor System, Packard Bioscience). Array images were analysed using QuantArray® Microarray Analysis Software (Version 3.0, Packard Bioscience), which permitted the quantification of comparative intensity of hybridization amongst probes and target cDNAs derived from root tips in the aluminium and diamide treatments, relative to their respective controls. The software also generated quality measures for each querying event, including spot diameter and intensity, background and signal to noise ratios. Using a threshold of 20% above local backgrounds, poorly hybridized spots were eliminated from the data set, as were cases in which the relative hybridization intensities for triplicate spots varied from each other by more that 30% (Kurth et al., 2002). Northern and cDNA Southern hybridization analysis Size fractionation of total RNA (12 µg) under denaturing conditions and subsequent transfer and immobilization onto nylon support membranes were conducted essentially according to the method developed by Ingelbrecht et al. (1998). The only deviation involved the inclusion of 0.45 M formaldehyde in the electrophoretic tank buffer to avoid the formation of formaldehyde gradients during fractionation (Tsang et al., 1993). Labelling of the probe cDNA with [α‐32P] dCTP (AEC Amersham), hybridization and subsequent visualization procedures were as described by Carson et al. (2002). In certain instances, cDNA Southern hybridization was used as an alternative to northern analysis. In these cases, the method of Jaakola et al. (2001) was used, although for the purpose of this study, the target cDNA population was synthesized by means of the Advantage PCR system (Clontech), using ss cDNA generated by a SMART™ PCR cDNA Synthesis Kit (Clontech). DNA sequencing and sequence data analysis Selected inserts within purified (QIAprep® Spin Miniprep Kit, Qiagen) recombinant plasmid DNA were sequenced by dye terminator cycle chemistry (BigDye Terminator Cycle Sequencing Kit, Applied Biosystems) and automated capillary electrophoresis (ABI Prism 310 Genetic Analyser, Applied Biosystems). The universal reverse primer was used to generate single‐pass partial sequences. After removal of vector and ambiguous sequences (Sequence Navigator, Applied Biosystems), comparative sequence analysis was conducted with the BLASTx and BLASTn algorithms (Altschul et al., 1997) against the National Centre for Biotechnological Information (NCBI) non‐redundant protein and nucleotide Expressed Sequence Tag (dbEST) databases, respectively. Matches were considered significant when the E values were below 10–5 and the PAM120 similarity scores were above 80 (Newman et al., 1994). Results Assessment of sensitivity to Al3+ stress. To determine the level and duration of exposure for maximal phytotoxic effect of the octahedral hexahydrate species of Al (Al(H2O)63+), commonly abbreviated as Al3+ (Kochian, 1995), sugarcane roots were exposed to concentrations of AlCl3 ranging from 0 to 1 mM at pH 4.15 for 1, 2 and 3 d. As sugarcane is reportedly more tolerant of Al than other graminaceous crops (Hetherington et al., 1986), the upper limits of concentration and exposure period used in this investigation were extended beyond those reported for other studies (Hamel et al., 1998; Ezaki et al., 2000). The activity of Al3+ in the media was calculated by means of the ion speciation program, MINTEQA2/PRODEFA2, which indicated that the phytotoxic Al3+ species was present at levels only 11% lower than the molar concentrations of the metal (results not shown). At the lowest concentration tested (45 µM), Al3+ stimulated relative root elongation by between 6% and 14%, an effect that was consistent over the entire duration of the assay (Fig. 1A). However, at 88 µM Al3+, the stimulatory effect was reversed and root elongation was inhibited by 10‐15%, when compared to the unexposed plants. This symptom of phytotoxicity was exacerbated by higher concentrations of the metal, reaching an apparent maximum of 43% relative root growth inhibition at 221 µM Al3+, a trend that was maintained over the three exposure periods assessed. Over the entire higher concentration range (221–897 µM Al3+), relative root elongation was reduced on average by between 36–46%. The Al content of roots, stems and leaves was determined in plants that had been challenged with the selected concentration range of Al3+ for 24 h. This shorter challenge period was chosen because the effect of the metal on root elongation was shown not to increase significantly upon further exposure (Fig. 1A). Under these conditions, Al accumulated to levels significantly higher in the roots than in the aerial parts of the plant, regardless of the concentration of the metal within the challenge medium (Fig. 1B). After exposure to the metal, roots contained between 230 and 322 µmol Al g–1 dry weight, while the aerial portions of the plants contained approximately 8‐fold less (14–51 µmol g–1 dry weight). However, despite measures to remove free Al3+ from the apoplasm, it is possible that metal adsorbed to the cell walls may have accounted for a proportion of the levels measured in the roots. Identification of Al3+‐ responsive genes Genes responsive to Al3+ challenge were captured through the construction of a subtractive cDNA library from mRNA isolated from unexposed root tips and those exposed to 221 µM Al3+ for 24 h. An SSH approach was adopted due the capacity of the technology to enrich specifically for rare transcripts, thereby substantially reducing the number of genic fragments required to obtain a representation of the changes in gene expression occurring in response to external and internal stimuli. Furthermore, as the intent of this study was to catalogue genes up‐regulated by exposure to the metal, only forward subtractions were performed, in which cDNA derived from control and challenged root tips served as driver and tester populations, respectively. Assessment of subtraction efficiency by means of reverse northern hybridization analysis of the 288 fragments isolated revealed that 182 were up‐regulated by Al3+ (results not shown). Results of such array analyses further served as the basis for the selection of 50 cDNAs with the most obvious Al3+‐inducible expression patterns for further characterization. This subset of ostensibly Al‐responsive cDNAs was subjected to sequence determinations with subsequent homology searches against the NCBI non‐redundant protein and Expressed Sequence Tag (dbEST) databases (Table 1). Over half (28 out of 50) of the cDNAs sequenced were of unknown function, either demonstrating no similarity to genes lodged in the data base or being homologous to genes encoding unknown or hypothetical proteins. However, analysis of the putative identities assigned to the remaining 22 sequences provided additional evidence of the potential of the SSH technology to enrich for rare transcripts, in that the majority (13 out of 22) appeared to be direct or indirect participants in the regulation of gene expression (clones 1E9, 1F9, 1G7, 1G12, 2C7, and 3C2) and signalling (clones 1C1, 1E10, 1H12, 2B11, 2G4, 2G11, and 3G8), rather than basic metabolic events (clones 1D5, 1D12, 1F7, and 2C9) (Table 1). Interestingly, four sequences displayed similarity to genes involved in vesicular trafficking and membrane transport (clones 2A2, 2G9, 3A1, and 3G10). Although caution should be exercized in their interpretation, such functional categorizations may serve to illustrate general trends in gene expression under particular circumstances. In this study, it is also of note that only a limited degree of redundancy (two out of 50) (clones 1F7 and 2C9) was apparent amongst the genic fragments isolated, suggesting that effective normalization between abundant and rare transcripts had occurred during subtraction. All of the cDNAs sequenced displayed significant similarity to sequences contained within the dbEST (Table 1). A number (18 out of 50) of these ESTs were derived from Sorghum spp. that had been subject to biotic and a variety of abiotic stresses. Further identity matches (five out of 50) were obtained to cDNAs induced by disease or cold in other graminaceous crop species, namely, Oryza sativa, Triticum aestivum and Zea mays. To verify expression inducibility, three of the isolated ESTs (clones 1F9, 1E10 and 1H12) were subjected to further hybridization analysis. Due to the propensity of SSH to capture rare transcripts, either conventional northern or cDNA Southern hybridization was deployed, the latter being used when increased detection sensitivity was demanded. For the three cDNAs assessed, an Al3+‐responsive expression pattern was confirmed (Fig. 2). These data, together with those obtained regarding the efficiency of SSH, indicate that the technology effectively captured a representation of Al3+‐responsive genes. Although this investigation fulfilled the objective of providing an insight into the nature of genes responsive to the metal in sugarcane roots, characterization of an increased number of genic fragments would be required for a detailed dissection of the molecular mechanisms operating under the stress. Determination of responses common to Al3+ and oxidative stress Determination of possible pluralities in induction of expression of the isolated genic fragments required the imposition of the additional stress under conditions similar to those used during Al challenge. To this end, Al3+ in the challenge medium was replaced with 1 mM diamide, a compound known to impose severe oxidative stress on biological material. The effect of this superoxide generator on sugarcane roots was assessed through the monitoring of levels of reduced glutathione (GSH) after 4, 8 and 24 h of exposure (Table 2). The GSH content of the tips of oxidatively stressed roots increased from an initial concentration of 4.1 to 13.8 µmol g–1 total protein after 4 h of exposure, with the latter level being approximately 46‐fold that measured in the control (0.3 µmol g–1 total protein) for the same period. After this sharp rise, the levels of GSH subsequently declined to 6.5 and 6.1 µmol g–1 total protein after 8 and 24 h of exposure to diamide, respectively. The concentration of GSH in the root tips of control (6.0 µmol g–1 total protein) and stressed (6.1 µmol g–1 total protein) root tips reached similar levels after 24 h, although these remained elevated relative to the initial level of 4.1 µmol per g–1 total protein (Table 2). The observed increase in GSH content of roots upon exposure to diamide is a pattern not without precedent, in that increased rates of GSH synthesis have been reported in plants subjected to either oxidative (Xiang and Oliver, 1998) or low, non‐freezing temperatures (Kocsy et al., 2000) and are believed to fulfil a detoxification function. In such cases, this response has been attributed to the induction of adenosine 5′‐phosphate reductase and γ‐glutamylcysteine synthetase, which are the key enzymes of cysteine and GSH synthesis (Kocsy et al., 2001). After the initial rise in GSH content of the diamide‐treated roots, a decline was observed until, after 24 h, levels in the challenged and control roots were similar (c. 6.0 µmol g–1 total protein) (Table 2). Furthermore, a substantial fluctuation in GSH levels in the control roots was observed over the 24 h diamide challenge period, possibly indicating a diurnal response (Table 2). Circadian rhythms in mRNA levels have been reported for genes encoding several enzymes involved in cysteine synthesis, cysteine being a precursor for glutathione synthesis (Leustek, 2002). Hence, the observed response of root GSH levels to diamide challenge, during which maximal levels were reached after 4 h of exposure, and the similar levels after 24 h in both challenged and control roots precluded the choice of 24 h exposure period, as was used for Al3+ challenge. As the perturbation of root metabolism by 1 mM diamide, as reflected by variations in GSH content, was most apparent after 4 h of exposure (Table 2), it was under this experimental regime that the expression of the putative Al3+‐responsive genic fragments was examined. To accomplish this, arrays of the 288 genic fragments, enriched for Al3+‐induced sequences through SSH, were queried with 33P‐labelled total cDNA populations derived from root tips of sugarcane plants that had been subject to conditions imposing quantified levels Al3+ (Fig. 1A) and oxidative (Table 2) stress. The hybridization patterns resulting from these query events were analysed with software (QuantArray® Microarray Analysis Software) that facilitated comparison of relative hybridization intensity to each genic fragment amongst the two target and control total cDNA populations. When arrays were queried with total cDNA populations originating from unstressed roots, a hybridization signal was detected for only 78 of the 288 (27%) cDNA probes on the membrane (Fig. 3A), confirming initial estimates of the subtraction efficiency of SSH. Of the remaining 210 probes to which species within the control total cDNA populations did not hybridize, 92 (32%) and 6 (2%) emitted signal exclusively upon querying with total cDNA populations derived from diamide and Al3+ challenged root tips, respectively. By contrast, hybridization of species common to both the Al3+‐ and oxidative‐stress derived targets occurred to 29% (83 out of 288) of the probes (Fig. 3A). Considerable variation in relative hybridization intensity was detected for these apparently dual Al3+‐ and oxidative‐stress inducible genic fragments (Fig. 3B). When the data were expressed as the proportion of the total hybridization signal contributed by the Al‐challenge derived target relative to that by the diamide target, it was apparent that expression of the putative Al‐inducible genes was generally higher under conditions of oxidative than Al3+ stress. In 34% (28 out of 83) of such cases, expression under conditions of Al3+ stress, relative to that detected under oxidative stress, was very low (0.0–0.2) (Fig. 3B). Similarly, for the remainder of the genic fragments within this category, 28% (23 out of 83) and 38% (32 out of 83) displayed low (0.2–0.4) to approximately equivalent (0.4–0.6) relative expression levels, respectively, under Al3+ stress. In no instances did expression under Al3+ stress substantially exceed that under oxidative stress. Furthermore, the results of these reverse northern hybridization studies indicated that the three ESTs with confirmed Al3+‐induced expression patterns (1F9, 1E10 and 1H12) (Fig. 2) were responsive to both Al3+ and oxidative stress, with one (1F9) demonstrating substantially higher expression under the latter. Discussion Sugarcane is susceptible to the negative effects of Al3+ The two primary progenitor species to modern sugarcane cultivars, namely, S. officinarum and S. spontaneum, are reported to have different degrees of tolerance to Al3+, with the latter being the more susceptible (Landell, 1989). However, commercial genotypes (Saccharum spp hybrids) are generally regarded as tolerant of Al (Hetherington et al., 1986): a phenotype that may have been inadvertently selected in the extensive breeding that has culminated in modern cultivars (Drummond et al., 2001). Nevertheless, despite this apparently high degree of tolerance, the extent and severity of soil acidification that arises from sugarcane husbandry, particularly on sandy soils under intensive cultivation (Schroeder et al., 1994), suggests that even slight susceptibility to the metal may result in perceptible economic losses. In fact, exposure to 221 µM Al3+ resulted in a relative inhibition of root elongation by approximately 43% in N19 (Fig. 1A), a cultivar rated within the South African sugar industry as tolerant of the metal and hence, widely grown on acid soils. On sandy, acidic soils within the industry, Al concentrations of between 2 and 5 mM have been reported (Turner et al., 1992), although the proportion of phytotoxic species prevailing under such conditions is unclear. Hence, given the observed susceptibility of a tolerant cultivar to Al3+ (Fig. 1A) and the severity of soil acidification within the industry, it is likely that Al phytotoxicity accounts for substantial yield losses. When compared to Al3+ dose–response studies conducted on other plant species (Hamel et al., 1998; Ezaki et al., 2000), the results of this investigation revealed notable differences and similarities amongst wheat, Arabidopsis and sugarcane. A similar incapacity of Al3+ to curtail root elongation completely (Fig. 1A) has been reported for wheat (Hamel et al., 1998). In that study, a maximum RGI of 70% was observed above threshold concentrations of 50 µM and 500 µM Al3+ for susceptible (cv. Frederick) and tolerant (cv. Atlas‐66) wheat genotypes, respectively. For both the current investigation and that of Hamel et al. (1998), it is unlikely that the observed plateaus in RGI were due to saturation in the chemical availability of the phytotoxic Al3+ species above the threshold concentrations, as the challenge media were formulated to deliver specific levels of the phytotoxic Al3+ ion according to the predictions of ion speciation software (MINTEQA2/PRODEFA2) (Allison et al., 1990). Hence, it is reasonable to assume that the persistent root elongation at high Al3+ does not reflect an experimental limitation but rather a capacity to tolerate the metal. In this regard, recent work conducted on wheat near‐isogenic lines demonstrated that genetic variation in Al tolerance resides at multiple loci that segregate independently (Tang et al., 2002). Consequently, allelic inheritance at more than one locus may contribute to variations in tolerance, including low‐level tolerance in genotypes characterized as susceptible. In contrast to sugarcane (Fig. 1A), a complete cessation of root growth at 800 µM Al3+ was observed in Arabidopsis (Ezaki et al., 2000). Despite this difference, the performance of an Al‐tolerant Arabidopis ecotype (Ler‐0) (Ezaki et al., 2000) and sugarcane cv. N19 (Fig. 1A) were similar in the lower Al3+ concentration range of 200–221 µM, where inhibition was between 40% and 50%. Thus, given the apparent sensitivity of this reportedly tolerant sugarcane cultivar to the negative effects of Al3+ and the potential diversity of tolerance characteristics within sugarcane germplasm (Landell, 1989), the manipulation of Al3+ tolerance through the application of molecular technologies would appear to be a viable strategy. Nature of Al3+‐responsive gene expression in sugarcane In the light of the increasing body of evidence suggesting that the degree of plant tolerance to abiotic and biotic stress resides in variations within signalling events and the regulation of gene expression (Scheel and Wasternack, 2002), it seems likely that the same may hold true for Al3+‐induced stress. Thus, the success of attempts to manipulate the genetically complex trait of Al3+ tolerance (Aniol and Gustafson, 1984; Berzonsky, 1992) may depend on the availability of comprehensive information regarding the way in which plants perceive and respond to harmful levels of the metal in the rhizosphere. Previous attempts to identify Al3+‐induced genes in roots have been successful, in that several research groups have isolated and characterized cDNAs that show up‐regulated expression in response to exposure to the metal (Snowden and Gardner, 1993; Snowden et al., 1995; Cruz‐Ortega et al., 1997; Hamel et al., 1998). However, due to the objectives of those studies and approaches used, rare transcripts, such as those participating in cell signalling and the regulation of gene expression, were not targeted. Consequently, in an attempt to address this apparent gap in knowledge, the current investigation deployed SSH to capture and subsequently enrich such rare transcripts, with a view to isolating those involved in the perception and transmission of Al3+‐induced stress signals. Examination of the putative identities and characteristics assigned to 21 of the cDNAs synthesized from the isolated transcripts supports the general success of the approach (Table 1) in that, of these sequences, 13 were assigned putative functions associated either directly or indirectly with cell regulatory and signalling events. However, the majority of the isolated cDNAs (28 out of 50) demonstrated no homology to sequences lodged in the international electronic data bases, against which the searches were conducted and may represent either novel or unique genes involved in the response of sugarcane to the imposed stress. Also of particular note were the strong associations observed amongst the Al3+‐responsive cDNAs captured from sugarcane root tips and ESTs derived from stressed maize, rice and sorghum (Table 1), supporting prior evidence of substantial overlap in the way in which plants perceive and respond to diverse abiotic stressors (Snowden et al., 1995; Ezaki et al., 2000). Apparent commonalities exist between Al3+‐ and oxidative‐stress induced gene expression in sugarcane The existence of a relationship between Al3+ phytotoxicity and oxidative stress has been inferred from the identity of genes up‐regulated in response to challenge by the metal (Ezaki et al., 1996; Hamel et al., 1998; Richards et al., 1998). This link may emanate from the capacity of Al3+ to facilitate an Fe‐mediated free radical chain reaction at the plasmalemma (Gutteridge et al., 1985). Hence, to assess whether the transcripts captured by SSH in this study were responsive to oxidative stress, comparative expression analysis was conducted under conditions of Al3+ and oxidative stress. According to scientific convention, the physiological effects of Al3+ and the oxidative agent, diamide, on roots were assessed through quantification of root elongation (Fig. 1A) and GSH content (Table 2), respectively. Challenge periods of 24 h and 4 h facilitated the detection of significant effects of Al3+ and diamide, respectively, and, hence, roots subjected to these conditions served as material for reverse northern hybridization analyses. Of the transcripts not detectable in unstressed root tips, the vast majority (175 out of 210: 83%) displayed higher expression in response to oxidative than Al3+ stress, with 53% (92 out of 175) of these emitting undetectable hybridization signal upon querying with total cDNA populations derived from Al3+‐challenged root tips (Fig. 3). This apparent anomaly within the expression profiles may have resulted from differences between the severity of stress imposed on roots by Al3+ and diamide, as the stress regimes employed were selected according to detectable effects of the stressors on the roots rather than on gene expression data. The six genic fragments identified by reverse northern hybridization analysis as being expressed exclusively upon Al3+ challenge (Fig. 3) are worthy of further investigation as they may provide insights into possible divergence between the Al3+ and oxidative stress responsive pathways. Nevertheless, the results of this study clearly demonstrated that the vast majority of the genes represented by the transcripts captured from sugarcane root tips were responsive to both Al3+ and oxidative stress. This investigation has provided insights into the nature and induction behaviour of Al3+‐reponsive genes in sugarcane roots and represents the first study specifically to target rare transcripts, such as those participating in cell signalling and the regulation of gene expression, elicited in roots in response to challenge by a demonstrably phytotoxic level of the metal. The presumed identities of a subset of the genic fragments isolated indicated that Al3+‐stress results in the up‐regulation of genes involved in regulatory events. Furthermore, the patterns of Al3+‐ and oxidative‐stress‐induced gene expression observed are in accordance with evidence from other studies, indicating that parallels exist in the way in which roots respond to different abiotic stresses. These results will guide future exploration of the potential for manipulating the Al3+‐tolerance status of this important tropical crop: approaches that will focus on the contributions of cell signalling and regulatory events to the tolerance phenotype. Acknowledgements I thank Drs Barbara Huckett, Deborah Carson and Stuart Rutherford for invaluable advice and encouragement and Alistair McCormick for his technical contributions to the study. The manuscript was subject to critical evaluation by Professor Paula Watt and Dr Barbara Huckett, for which I am truly grateful, as am I for the helpful comments provided by two anonymous reviewers. View largeDownload slide Fig. 1. Relative root elongation and Al3+ accumulation in sugarcane as a consequence of Al3+ challenge. Roots of hydroponically‐grown plants were exposed to various concentrations of Al3+ in 1 mM CaCl2 at a pH value of 4.15 for 24 h, after which the effects of the challenge on (A) root elongation and (B) levels of the metal in roots, stems and leaves were assessed. Root growth inhibition was calculated as a percentage of the elongation of the terminal 1 cm portion of roots exposed to Al3+ relative to that of unchallenged root tips (mean ±SE, n=16). Values not significantly different (0.01 significance level) share the same alphabetical character while those significantly different do not. View largeDownload slide Fig. 1. Relative root elongation and Al3+ accumulation in sugarcane as a consequence of Al3+ challenge. Roots of hydroponically‐grown plants were exposed to various concentrations of Al3+ in 1 mM CaCl2 at a pH value of 4.15 for 24 h, after which the effects of the challenge on (A) root elongation and (B) levels of the metal in roots, stems and leaves were assessed. Root growth inhibition was calculated as a percentage of the elongation of the terminal 1 cm portion of roots exposed to Al3+ relative to that of unchallenged root tips (mean ±SE, n=16). Values not significantly different (0.01 significance level) share the same alphabetical character while those significantly different do not. View largeDownload slide Fig. 2. Al3+‐responsive expression of selected cDNAs. Confirmation of expression patterns was facilitated by means of northern (A) and cDNA Southern hybridization (B, C) analyses. The lowest panel (D), representing rRNA, serves to illustrate equal loading of 12 µg total RNA for northern analysis (A). Size fractionated total cDNA populations (1 µg) (SMART™ PCR cDNA Synthesis Kit, Clontech) were used as alternatives to total RNA in cDNA Southern analyses (B, C). View largeDownload slide Fig. 2. Al3+‐responsive expression of selected cDNAs. Confirmation of expression patterns was facilitated by means of northern (A) and cDNA Southern hybridization (B, C) analyses. The lowest panel (D), representing rRNA, serves to illustrate equal loading of 12 µg total RNA for northern analysis (A). Size fractionated total cDNA populations (1 µg) (SMART™ PCR cDNA Synthesis Kit, Clontech) were used as alternatives to total RNA in cDNA Southern analyses (B, C). View largeDownload slide Fig. 3. Comparative analysis of relative expression levels of Al3+‐responsive genes under Al3+ and oxidative stress. Comparison of the relative hybridization signal strength, relative to the controls, for each probe after querying with each of the two target total cDNA populations (+Al3+ and +diamide) was facilitated by means of QuantArray® MicroArray Analysis Software (Version 3.0, Packard Biosciences). (A) The inner pie chart indicates the percentage of presumed Al3+‐responsive clones to which species within the total cDNA population derived from unstressed root tips did (+C) or did not hybridize (–C). The outer circumference panel details the percentage of probes hybridizing to cDNA species within each of the three total populations: diamide‐ (D only) or Al3+‐challenge‐derived (Al only), or a combination thereof (Al+D; C+D; C+Al; C+Al+D). (B) Proportion contributed to total signal by hybridization of species within Al3+‐ and diamide‐derived total cDNA populations for clones showing up‐regulated expression in response to both Al3+ and oxidative stress. Proportions were calculated by dividing hybridization signal contributed by Al3+ by the total signal value. View largeDownload slide Fig. 3. Comparative analysis of relative expression levels of Al3+‐responsive genes under Al3+ and oxidative stress. Comparison of the relative hybridization signal strength, relative to the controls, for each probe after querying with each of the two target total cDNA populations (+Al3+ and +diamide) was facilitated by means of QuantArray® MicroArray Analysis Software (Version 3.0, Packard Biosciences). (A) The inner pie chart indicates the percentage of presumed Al3+‐responsive clones to which species within the total cDNA population derived from unstressed root tips did (+C) or did not hybridize (–C). The outer circumference panel details the percentage of probes hybridizing to cDNA species within each of the three total populations: diamide‐ (D only) or Al3+‐challenge‐derived (Al only), or a combination thereof (Al+D; C+D; C+Al; C+Al+D). (B) Proportion contributed to total signal by hybridization of species within Al3+‐ and diamide‐derived total cDNA populations for clones showing up‐regulated expression in response to both Al3+ and oxidative stress. Proportions were calculated by dividing hybridization signal contributed by Al3+ by the total signal value. Table 1. Putative identities and characteristics of selected sequences expressed in the root tips of Saccharum spp. hybrid cv. N19 as a consequence of challenge by 250 µM Al3+ at pH 4.1 for 24 h Clone reference  cDNA size (bp)  BLASTx  BLASTn (dbEST)      Corresponding or related protein sequence  E‐value  Sequence identity (%)  Accession number  Characteristics of cDNA  E‐value  Sequence identity (%)  Accession number  1A3  146  No significant similarity  –  –  –  Zea mays, pathogen‐induced  9×10–6  91  BG836703  1A11  173  No significant similarity  –  –  –  Sorghum bicolor, water‐stressed  1×10–9  97  BE638185  1B2  366  No significant similarity  –  –  –  S. bicolor, pathogen‐induced  5×10–29  88  BE594873  1B6  212  No significant similarity  –  –  –  S. bicolor, water‐stressed  1×10–11  86  BE592729  1B12  355  No significant similarity  –  –  –  Triticum aestivum, cold‐induced  1×10–11  88  BF200586  1C1  461  Digitalis lanata Acyl‐CoA binding protein  3×10–36  86  AJ249833  S. bicolor, pathogen‐induced  1×10–163  92  BE367649  1D3  329  No significant similarity  –  –  –  Z. mays, stressed root  5×10–51  104  AI855319  1D5  367  Z. mays adenine nucleotide translocator   1×10–28  72  X15711  S. bicolor, pathogen‐induced  1×10–139  96  BE600734  1D12  168  Capsicum annuum TMV‐induced protein  2×10–18  60  AF242731  S. bicolor, pathogen‐induced   3×10–20  87  BE594885  1E2  354  No significant similarity  –  –  –  Oryza sativa, pathogen‐induced  7×10–7  60  AW070097  1E3  172  Z. mays cDNA clone MEST41‐B08  2×10–22  98  BG842882  Z. mays, inbred tassel  9×10–60  93  AI939876  1F3  358  No significant similarity  –  –  –  S. bicolor, dark‐grown seedling  1×10–64  127  BE358013  1E9  549  Arabidopsis thaliana probable RNA binding protein  4×10–31  92  T49019  S. bicolor, light‐grown seedling  1×10–168  96  AW287250  1E10  384  S. bicolor serine/threonine kinase  1×10–30  51  AP002482  S. bicolor, pathogen‐induced  1×10–40  93  BE599698  1F7  370  Nicotiana glutinosa 60S ribosomal protein  8×10–16  88  NGU23784  S. bicolor, water‐stressed  1×10–122  95  AW677661  1F9  373  Z. mays probable histone deacetylase  4×10–40  90  P56521  Z. mays, cold‐stressed  1×10–129  92  BG320015  1G2  346  A. thaliana hypothetical protein F9D16.100  6×10–30  92  T05595  S. bicolor, water‐stressed  1×10–142  89  AW745310  1G7  377  Z. mays probable histone deacetylase  2×10–24  81  P56521  S. bicolor, pathogen‐induced  1×10–116  94  BE599391  1G12  556  Homo sapiens SWI/SNF gene  2×10–19  90  AF109733  O. sativa, panicle at flowering stage  6×10–52  89  C72606  1H5  477  No significant similarity  –  –  –  O. sativa, root  1×10–12  83  AU032267  1H6  381  No significant similarity  –  –  –  Z. mays, inbred tassel  9×10–60  93  AI939876  1H12  207  O. sativa RAS‐related protein RGP1  4×10–16  83  P25766  S. bicolor, pathogen‐induced  2×10–77  94  BE595980  2A2  479  Z. mays kinesin heavy chain (KIN15)  1×10–169  601  AF272759  Z. mays, tassel primordium  1×10–167  595  BU098549  2A4  389  No significant similarity  –  –  –  Triticum aestivum, cold‐stress induced  3×10–45  188  BQ282541  2A12  424  No significant similarity  –  –  –  S. bicolor, pathogen‐induced  4×10–78  297  BM329690  2B3  288  No significant similarity  –  –  –  Z. mays, Unigene II   1×10–22  113  BI992021  2B4  389  No significant similarity  –  –  –  Z. mays, cDNA clone MEST286‐D05 3′  3×10–76  291  BM348090  2B11  486  Z. mays calnexin  3×10–10  61  T03251  S. propinquum, floral‐induced meristem 1 (FM1)  0.0  781  BF585670  2C7  316  O. sativa putative G‐box binding protein  2×10–35  147  AAL76334  S. bicolor, pathogen‐induced 1 (PI1)      BE363888  2C9  313  O. sativa putative 60S ribosomal protein L37a  2×10–7  55  AP003335  S. bicolor, water‐stressed 1 (WS1)  1×10–68  266  BE363812  2E2  216  No significant similarity  –  –  –  Z. mays, root cDNA  1×10–15  90  AW054220  2E3  281  No significant similarity  –  –  –  S. bicolor, pathogen‐induced 1 (PI1)  2×10–8  66  BE599251  2E7  304  No significant similarity  –  –  –  Z. mays, mixed tissue  8×10–11  74  BM381305  2F3  293  No significant similarity  –  –  –  S. bicolor, dark‐grown 1 (DG1)  2×10–61  289  AW922283  2F10  420  No significant similarity  –  –  –  O. sativa, callus  4×10–8  66  D22024  2G4  500  O. sativa 24‐methylene lophenol C24(1) methyltransferase  5×10–5  48  AAC34989  S. bicolor, pathogen‐induced (PI1)  1×10–115  420  BE597306  2G6  225  No significant similarity  –  –  –  S. bicolor water‐stressed 1 (WS1)  1×10–64  252  AW745885  2G9  305  A. thaliana putative ABC transporter  1×10–14  79  AY086511  S. bicolor embryo 1 (EM1)  2×10–92  345  BG739317  2G11  531  A. thaliana putative amine oxidase  4×10–27  297  AC006224  O. sativa genomic DNA, chromosome 4  2×10–63  250  AL606652  2H5  340  No significant similarity  –  –  –  S. bicolor immature panicle 1 (IP1)   4×10–57  115  BI1351176  3A1  421  Z. mays actin related protein  7×10–19  77  AJ223200  Z. mays, cold‐stressed  1×10–127  460  BG319679  3C2  370  A. thaliana RING‐H2 finger protein RHF1a  3×10–12  71  NP_193158  S. bicolor, immature panicle 1 (IP1)  4×10–47  115  BI351176  3D9  116  No significant similarity  –  –  –  S. bicolor water‐stressed 1 (WS1)  1×10–23  115  AW745885  3E10  421  O. sativa unknown protein zwh13.1  2×10–17  89  CAB55397  Z. mays mRNA sequence CL36095_1  4×10–85  321  AY109821  3F5  350  A. thaliana similar to unknown protein emb|CAB89322  1×10–22  105  BAB10214  S. propinquum floral‐induced meristem 1 (FM1)  8×10–15  88  BF481893  3G8  487  A. thaliana GTP‐binding protein (RAB1Y)  9×10–32  132  AAF79660  S. bicolor immature pannicle 1 (IP1)  1×10–168  599  BI211750  3G9  514  O. sativa genomic DNA, chromosome 4  2×10–17  89  AL117264  Z. mays PCO085208 mRNA sequence  1×10–107  394  AY105682  3G10  501  A. thaliana γ‐soluble NSF attachment protein  5×10–23  90  AF177990  Z. mays CL36095_1 mRNA sequence  1×10–162  577  AY109821  3H3  502  A. thaliana hypothetical protein  5×10–38  125  NP_176310  S. propinquum Rhizome2 (RHIZ2)  0.0  718  BG102656  3H8  348  No significant similarity  –  –  –  Z. mays Unigene II  2×10–18  100  BI993147  Clone reference  cDNA size (bp)  BLASTx  BLASTn (dbEST)      Corresponding or related protein sequence  E‐value  Sequence identity (%)  Accession number  Characteristics of cDNA  E‐value  Sequence identity (%)  Accession number  1A3  146  No significant similarity  –  –  –  Zea mays, pathogen‐induced  9×10–6  91  BG836703  1A11  173  No significant similarity  –  –  –  Sorghum bicolor, water‐stressed  1×10–9  97  BE638185  1B2  366  No significant similarity  –  –  –  S. bicolor, pathogen‐induced  5×10–29  88  BE594873  1B6  212  No significant similarity  –  –  –  S. bicolor, water‐stressed  1×10–11  86  BE592729  1B12  355  No significant similarity  –  –  –  Triticum aestivum, cold‐induced  1×10–11  88  BF200586  1C1  461  Digitalis lanata Acyl‐CoA binding protein  3×10–36  86  AJ249833  S. bicolor, pathogen‐induced  1×10–163  92  BE367649  1D3  329  No significant similarity  –  –  –  Z. mays, stressed root  5×10–51  104  AI855319  1D5  367  Z. mays adenine nucleotide translocator   1×10–28  72  X15711  S. bicolor, pathogen‐induced  1×10–139  96  BE600734  1D12  168  Capsicum annuum TMV‐induced protein  2×10–18  60  AF242731  S. bicolor, pathogen‐induced   3×10–20  87  BE594885  1E2  354  No significant similarity  –  –  –  Oryza sativa, pathogen‐induced  7×10–7  60  AW070097  1E3  172  Z. mays cDNA clone MEST41‐B08  2×10–22  98  BG842882  Z. mays, inbred tassel  9×10–60  93  AI939876  1F3  358  No significant similarity  –  –  –  S. bicolor, dark‐grown seedling  1×10–64  127  BE358013  1E9  549  Arabidopsis thaliana probable RNA binding protein  4×10–31  92  T49019  S. bicolor, light‐grown seedling  1×10–168  96  AW287250  1E10  384  S. bicolor serine/threonine kinase  1×10–30  51  AP002482  S. bicolor, pathogen‐induced  1×10–40  93  BE599698  1F7  370  Nicotiana glutinosa 60S ribosomal protein  8×10–16  88  NGU23784  S. bicolor, water‐stressed  1×10–122  95  AW677661  1F9  373  Z. mays probable histone deacetylase  4×10–40  90  P56521  Z. mays, cold‐stressed  1×10–129  92  BG320015  1G2  346  A. thaliana hypothetical protein F9D16.100  6×10–30  92  T05595  S. bicolor, water‐stressed  1×10–142  89  AW745310  1G7  377  Z. mays probable histone deacetylase  2×10–24  81  P56521  S. bicolor, pathogen‐induced  1×10–116  94  BE599391  1G12  556  Homo sapiens SWI/SNF gene  2×10–19  90  AF109733  O. sativa, panicle at flowering stage  6×10–52  89  C72606  1H5  477  No significant similarity  –  –  –  O. sativa, root  1×10–12  83  AU032267  1H6  381  No significant similarity  –  –  –  Z. mays, inbred tassel  9×10–60  93  AI939876  1H12  207  O. sativa RAS‐related protein RGP1  4×10–16  83  P25766  S. bicolor, pathogen‐induced  2×10–77  94  BE595980  2A2  479  Z. mays kinesin heavy chain (KIN15)  1×10–169  601  AF272759  Z. mays, tassel primordium  1×10–167  595  BU098549  2A4  389  No significant similarity  –  –  –  Triticum aestivum, cold‐stress induced  3×10–45  188  BQ282541  2A12  424  No significant similarity  –  –  –  S. bicolor, pathogen‐induced  4×10–78  297  BM329690  2B3  288  No significant similarity  –  –  –  Z. mays, Unigene II   1×10–22  113  BI992021  2B4  389  No significant similarity  –  –  –  Z. mays, cDNA clone MEST286‐D05 3′  3×10–76  291  BM348090  2B11  486  Z. mays calnexin  3×10–10  61  T03251  S. propinquum, floral‐induced meristem 1 (FM1)  0.0  781  BF585670  2C7  316  O. sativa putative G‐box binding protein  2×10–35  147  AAL76334  S. bicolor, pathogen‐induced 1 (PI1)      BE363888  2C9  313  O. sativa putative 60S ribosomal protein L37a  2×10–7  55  AP003335  S. bicolor, water‐stressed 1 (WS1)  1×10–68  266  BE363812  2E2  216  No significant similarity  –  –  –  Z. mays, root cDNA  1×10–15  90  AW054220  2E3  281  No significant similarity  –  –  –  S. bicolor, pathogen‐induced 1 (PI1)  2×10–8  66  BE599251  2E7  304  No significant similarity  –  –  –  Z. mays, mixed tissue  8×10–11  74  BM381305  2F3  293  No significant similarity  –  –  –  S. bicolor, dark‐grown 1 (DG1)  2×10–61  289  AW922283  2F10  420  No significant similarity  –  –  –  O. sativa, callus  4×10–8  66  D22024  2G4  500  O. sativa 24‐methylene lophenol C24(1) methyltransferase  5×10–5  48  AAC34989  S. bicolor, pathogen‐induced (PI1)  1×10–115  420  BE597306  2G6  225  No significant similarity  –  –  –  S. bicolor water‐stressed 1 (WS1)  1×10–64  252  AW745885  2G9  305  A. thaliana putative ABC transporter  1×10–14  79  AY086511  S. bicolor embryo 1 (EM1)  2×10–92  345  BG739317  2G11  531  A. thaliana putative amine oxidase  4×10–27  297  AC006224  O. sativa genomic DNA, chromosome 4  2×10–63  250  AL606652  2H5  340  No significant similarity  –  –  –  S. bicolor immature panicle 1 (IP1)   4×10–57  115  BI1351176  3A1  421  Z. mays actin related protein  7×10–19  77  AJ223200  Z. mays, cold‐stressed  1×10–127  460  BG319679  3C2  370  A. thaliana RING‐H2 finger protein RHF1a  3×10–12  71  NP_193158  S. bicolor, immature panicle 1 (IP1)  4×10–47  115  BI351176  3D9  116  No significant similarity  –  –  –  S. bicolor water‐stressed 1 (WS1)  1×10–23  115  AW745885  3E10  421  O. sativa unknown protein zwh13.1  2×10–17  89  CAB55397  Z. mays mRNA sequence CL36095_1  4×10–85  321  AY109821  3F5  350  A. thaliana similar to unknown protein emb|CAB89322  1×10–22  105  BAB10214  S. propinquum floral‐induced meristem 1 (FM1)  8×10–15  88  BF481893  3G8  487  A. thaliana GTP‐binding protein (RAB1Y)  9×10–32  132  AAF79660  S. bicolor immature pannicle 1 (IP1)  1×10–168  599  BI211750  3G9  514  O. sativa genomic DNA, chromosome 4  2×10–17  89  AL117264  Z. mays PCO085208 mRNA sequence  1×10–107  394  AY105682  3G10  501  A. thaliana γ‐soluble NSF attachment protein  5×10–23  90  AF177990  Z. mays CL36095_1 mRNA sequence  1×10–162  577  AY109821  3H3  502  A. thaliana hypothetical protein  5×10–38  125  NP_176310  S. propinquum Rhizome2 (RHIZ2)  0.0  718  BG102656  3H8  348  No significant similarity  –  –  –  Z. mays Unigene II  2×10–18  100  BI993147  View Large Table 2. Effect of diamide on reduced glutathione (GSH) levels in sugarcane roots Levels of GSH were determined in root tips exposed to 1 mM of diamide for 4, 8 and 24 h (n=3, ±SE). Duration of exposure (h)  GSH concentration (µmol g–1 total protein)    0 mM diamide  1 mM diamide  0  4.1±0.5  4.1±0.5  4  0.3±0.1  13.8±1.2  8  2.2±0.9  6.5±0.8  24  6.0±0.5  6.1±0.8  Duration of exposure (h)  GSH concentration (µmol g–1 total protein)    0 mM diamide  1 mM diamide  0  4.1±0.5  4.1±0.5  4  0.3±0.1  13.8±1.2  8  2.2±0.9  6.5±0.8  24  6.0±0.5  6.1±0.8  View Large References Allison JD , Brown DS, Novo‐Gradac KJ. 1991. MINTEQA2/PRODEFA2: a geochemical assessment model for environmental system. Version 3.0 user manual. Athens, Georgia, USA: United States Environmental Protection Agency. Google Scholar Altschul SF , Madden TL, Schäffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ. 1997. Gapped BLAST and PSI‐BLAST: a new generation of protein database search programs. 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TI - Aluminium‐responsive genes in sugarcane: identification and analysis of expression under oxidative stress
JF - Journal of Experimental Botany
DO - 10.1093/jxb/erg128
DA - 2003-04-01
UR - https://www.deepdyve.com/lp/oxford-university-press/aluminium-responsive-genes-in-sugarcane-identification-and-analysis-of-WNj3cYuPHS
SP - 1163
EP - 1174
VL - 54
IS - 385
DP - DeepDyve
ER -