TY - JOUR
AU - Peng, Xinxiang
AB - Abstract Aluminium (Al) toxicity is a worldwide problem in agricultural practice. Based on evidence that Al resistance may be an inducible process and that rice is one of the most Al-resistant crops, the gene transcriptional responses to Al were investigated in two contrasting rice cultivars (resistant XN1 versus sensitive XX2) using differential display reverse transcription-PCR (DDRT-PCR) in combination with northern blotting analysis. A total of 37 genes were identified as differentially expressed, of which five have been previously known as Al regulated while the others are novel genes. Among the up-regulated genes, four encode ion transporters, two are involved in signal transduction, and five in the synthesis of cysteine and metallothionein. These could be members that are potentially involved in Al adaptation or resistance. On the other hand, the transcription of 17 genes was strongly inhibited under Al stress. These genes are associated with cytoskeletal dynamics and metabolism, and could be possible targets associated with Al toxicity. All of these differentially expressed genes may represent candidates that function in Al responses. The results suggest, at the transcriptional level, that cytoskeletal disruption may be associated with Al toxicity, whereas ion transport and sulphur metabolism could play major roles in Al adaptation or tolerance in rice. Al stress, gene expression, resistance, rice, toxicity Introduction Aluminium (Al) toxicity is one of the major agronomic problems in acid soils. Acid soils may account for as much as 50% of the world's potentially arable lands and, moreover, this problem is being aggravated due to the current extensive use of ammonium fertilizers and the phenomenon of ‘acid rain’ (von Uexkull and Mutert, 1995). The major symptom of Al toxicity is a rapid inhibition of root growth, which may directly translate into reduced plant vigour and yield (Rengel, 1992; Kochian et al., 2005). Some of the key features regarding the mechanistic basis for Al toxicity have been addressed (Kochian et al., 2004). Al inhibits root cell expansion and elongation and, if over the long term, cell division as well. Al can inhibit cytoskeletal dynamics, and interacts with both microtubules and actin filaments (Blancaflor et al., 1998; Sivaguru et al., 1999, 2003). The microtubules in elongating cells of wheat roots were shown to be depolymerized in response to Al (Sasaki et al., 1997). Al interference with the signal transduction pathway could also play a role in Al toxicity. For instance, Al exposure can alter cytosolic Ca2+ levels (Jones et al., 1998), and inhibits the enzyme phospholipase C (PLC) of the phosphoinositide pathway associated with Ca2+ signalling (Jones and Kochian, 1995; Ramos-Diaz et al., 2007). Of more general interest, Al elicits the production of reactive oxygen species (ROS), which could be involved in Al inhibition of root growth (Yamamoto et al., 2002). Plants have evolved mechanisms that enable them to tolerate toxic levels of Al, such that various species or genotypes display wide variations in their ability to cope with Al toxicity. Identifying the Al-resistant genes is a prerequisite for the molecular improvement of crop Al resistance. Over the past few decades, physiological studies have led to two proposed mechanisms for Al resistance. Al resistance can be mediated either via exclusion of Al from the root apex or via intracellular tolerance of Al transported into the plant symplasm (Kochian et al., 2005). While accumulation and exudation of organic acids have been widely accepted as the important players in both internal detoxification and exclusion mechanisms (Ryan et al., 2001; Kochian et al., 2004), other mechanisms have also recently been suggested in plants (Wenzl et al., 2001; Pineros et al., 2005; Yang et al., 2005; Deng et al., 2006). More intriguingly, Al resistance has been evidenced as an Al-inducible process (Kochian et al., 2004, 2005), pointing to the possibility that profiling the Al-responsive genes could permit the identification of factors important to Al resistance (Kochian et al., 2004). This assumption has been the driving force for a number of molecular investigations with various approaches. The availability of applicable techniques, such as differential display reverse transcription-PCR (DDRT-PCR), suppression subtractive hybridization (SSH), DNA microarray, and amplified fragment length polymorphism (AFLP), has provided researchers with essential tools to examine the gene transcriptional responses. Using these tools, a number of Al-responsive genes have been identified from the roots of wheat (Snowden and Gardner, 1993; Richards et al., 1994; Hamel et al., 1998; Hamilton et al., 2001; Sasaki et al., 2002, 2004), Arabidopsis (Richards et al., 1998; Sivaguru et al., 2003; Hoekenga et al., 2006), rye (Milla et al., 2002), tobacco (Ezaki et al., 1995, 1996), soybean (Ragland and Soliman, 1997; Ermolayev et al., 2003), pea (Brosché and Strid, 1999), sugarcane (Watt, 2003), and rice (Yu et al., 1998; Mao et al., 2004). Sasaki et al. (2004) identified a gene, ALMT1, which was involved in Al-activated malate exudation and increase of Al tolerance in tobacco cells. This may represent the identification of the first major Al-resistant gene in crop plants so far (Kochian et al., 2004). Rice is both a staple food crop and one of the most Al-tolerant crops (Ma et al., 2002), yet only a handful of Al-responsive genes have been identified. These include metallothionein II, xylose isomerase, phenylalanine ammonia-lyase, β-1,3-glucanase, quinine oxidoreductase, and elongation factor EF-2 (Yu et al., 1998; Mao et al., 2004). In this study, a highly Al-resistant rice cultivar XN1 (Xu et al., 2004; Yang et al., 2007) was used for a primary screen for both Al-induced and Al-suppressed genes. A comparison was then made with a susceptible cultivar in the gene expression profile. The DDRT-PCR approach in combination with northern blot analysis has identified a number of Al-responsive genes which could be major players in Al responses in rice. Materials and methods Plant cultivation and Al stress treatments Rice (Oryza sativa L.) cv. Xiangnuo 1 (XN1), which was previously identified and characterized as a highly Al-resistant genotype (Xu et al., 2004; Yang et al., 2007), was used as the plant material throughout the experiments. In the subsequent analysis, an Al-susceptible genotype Xiangzhongxian 2 (XX2) (Xu et al., 2004) was included for comparison in terms of the gene expression patterns. The seedlings were first grown for about 8 d in Kimura B complete nutrient solution (Yoshida et al., 1976) under greenhouse conditions (average temperature of 30 °C day/25 °C night, relative humidity 60–80%, photosynthetically active radiation 600–1000 μmol m−2 s−1, and photoperiod of 14 h day/10 h night), then at the four leaf stage seedlings were treated with Al3+ as follows: the seedlings were pre-grown in 0.5 mM CaCl2 solution (pH 4.2) overnight for root rinsing and acclimation, and then transferred into 0.5 mM CaCl2 solution containing 100 μM AlCl3 (pH 4.2). No addition of AlCl3 was used as the control. The 3–4 cm portions from root tips were sampled at 6, 12, and 24 h after Al treatment. Total RNA isolation Total RNA extraction was performed from rice roots according to Logemann et al. (1987). DNaseI (RNase free) was used to digest the trace amounts of chromosomal DNA contamination in RNA. Total RNA was dissolved in diethylpyrocarbonate (DEPC)-treated water and stored at –75 °C. RNA quality and quantity were assessed by denaturing RNA agarose gel electrophoresis (Sambrook et al., 1989) and spectrophotometric detection at 260 nm and 280 nm using a Heλios alpha spectrophotometer (Thermo Spectronic, Cambridge, UK). DDRT-PCR analysis DDRT-PCR was performed according to Liang et al. (1994) with some modifications. Thirteen-mer arbitrary primers (H-AP1–H-AP32) and anchored primers (AAGCT11A/C/G) as designed by GenHunter Corporation were applied. All PCRs were repeated twice using the same cDNA sample. Aliquots (3 μl each) of amplification products were resolved on a 6% denaturing polyacrylamide sequencing gel. DNA fragments were visualized by silver staining according to the silver sequence™ DNA sequencing system technical manual (Promega, Madison, WI, USA). The bands of interest were cut out and the gel slice was soaked in 100 μl of ddH2O for 10 min and boiled for 15 min. The DNA was precipitated with sodium acetate and glycogen according to the manufacturer's instructions. Cloning and sequencing of the differential fragments The Al-responsive fragments were amplified by PCR under the same conditions as used for the pre-amplification. The purified PCR products were ligated to pMD 18-T simple vectors. The clones containing recombinant plasmid vector DNA were sequenced by Shanghai Sangon Biological Engineering Technology & Services Co., Ltd. Northern blot analysis Total RNA (20 μg) was separated by electrophoresis on a 1% formaldehyde agarose gel followed by blotting onto Hybond-N nylon membranes (Amersham Pharmacia Biotech, Buckinghamshire, UK). Hybridization was conducted as described by Sambrook et al. (1989). DNA probes were labelled by a random primer DNA labelling kit (Takara, Dalian, PR China) using [α-32P]dCTP. The hybridization signal was detected and analysed by using the Molecular Imager FX system and Quantity One software (Bio-Rad, Hercules, CA, USA). Functional prediction of the gene fragments Database searches were conducted using the Blast Network service (NCBI, National Center for Biotechnology Information) (http://www.ncbi.nlm.nih.gov/BLAST/) and rice sequence database BLAST search (http://riceblast.dna.affrc.go.jp/). The sequence of each differential fragment was searched against all sequences in the non-redundant databases and in the expressed sequence tag (EST) database using the BLASTN program in turn. The sequences without significant homology were compared again by genomic sequence databases using the BLASTN program; significant homologies were further annotated at the web site (http://ricegaas.dna.affrc.go.jp/). The known genes were analysed by BLASTX and classified according to their putative function. Preparation of some other probes by RT-PCR for northern blot Twelve additional gene probes, which were involved in sulphur assimilation, were prepared through RT-PCR for northern blot analysis; these were the genes encoding cysteine synthase (CYS1, CYS2, CYS3, and CYS4), ATP sulphurylase (ATPS), 5′-adenosine-phosphosulphate reductase (APR2, APR3, APR5, and APR8), sulphite reductase (SR), sulphite oxidase (SO), and phytochelatin synthase (PCS). The primer sequences for amplification of these gene probes are listed in Table 1. Table 1. Primer sequences for amplification of some gene probes involved in sulphur assimilation Gene  GenBank accession no.  Forward (5′–3′)  Reverse (5′–3′)  Product (bp)  ATPS  AK099593  TGGGCTGCCTTATGTTGATG  CGACAGTTGATTCTGGGTTGA  383  APR2  XM_478340  CTCGTCAAGTGGAACCCC  GACGAAGGCGAGGAGCGAGT  648  APR3  AK059876  GCTGCTGTGCTCTTCTATGC  TTTCCTGC TCACAATCCC  325  APR5  AY739307  CTTTCCAACAATCGCTCAT  ATCCTGGTGAAGCAATCTG  319  APR8  AK100198  TAAAGAGTTGAACCTTCGCCACA  CACCCAGTGAAACAGAAGTAAACGA  677  SR  AK073969  ACTTGGCTATGGATA CGCT  CACAGTGGTAAGGCAGGAC  1090  CYS1  AF073695  GCCAAGGATGTCACCGAGTT  TGCCACCTGTCCCAATACC  538  CYS2  AF073696  ACAGGAGTGCCCTCAGAAT  CAGGTCCAGTCCACATAA AG  351  CYS3  AF073697  TGAGCATGGAAAGGAGGAT  GGACAGACGACAGGTAGCG  618  CYS4  AF073698  AGCCGACAAGTGGTAATCT  TCTACTTTGCCTGCCGTAT  307  SO  AB071966  AATGAGTAAGGTACGGAA  GCTACTATCTCAGCGTTT  744  PCS  AK065501  ACTCCTGATGGCTATGTTGC  GTCCTTGGAATCCTTACGC  1026  Gene  GenBank accession no.  Forward (5′–3′)  Reverse (5′–3′)  Product (bp)  ATPS  AK099593  TGGGCTGCCTTATGTTGATG  CGACAGTTGATTCTGGGTTGA  383  APR2  XM_478340  CTCGTCAAGTGGAACCCC  GACGAAGGCGAGGAGCGAGT  648  APR3  AK059876  GCTGCTGTGCTCTTCTATGC  TTTCCTGC TCACAATCCC  325  APR5  AY739307  CTTTCCAACAATCGCTCAT  ATCCTGGTGAAGCAATCTG  319  APR8  AK100198  TAAAGAGTTGAACCTTCGCCACA  CACCCAGTGAAACAGAAGTAAACGA  677  SR  AK073969  ACTTGGCTATGGATA CGCT  CACAGTGGTAAGGCAGGAC  1090  CYS1  AF073695  GCCAAGGATGTCACCGAGTT  TGCCACCTGTCCCAATACC  538  CYS2  AF073696  ACAGGAGTGCCCTCAGAAT  CAGGTCCAGTCCACATAA AG  351  CYS3  AF073697  TGAGCATGGAAAGGAGGAT  GGACAGACGACAGGTAGCG  618  CYS4  AF073698  AGCCGACAAGTGGTAATCT  TCTACTTTGCCTGCCGTAT  307  SO  AB071966  AATGAGTAAGGTACGGAA  GCTACTATCTCAGCGTTT  744  PCS  AK065501  ACTCCTGATGGCTATGTTGC  GTCCTTGGAATCCTTACGC  1026  View Large Results and discussion Identification of Al-responsive genes by DDRT-PCR and northern blotting DDRT-PCR has been widely used to isolate genes that are specifically expressed in particular types of cells or induced in cells by various stresses (Yamazaki and Saito, 2002). Here, a modified protocol was used to screen initially for Al-responsive genes from an Al-resistant cultivar XN1 that was identified previously (Xu et al., 2004). XN1 can grow well in a nutrient solution containing a concentration as high as 2 mM Al3+ that largely inhibits growth of the Al-sensitive cultivar (XX2) (Xu et al., 2004; Yang et al., 2007). More than 140 Al-responsive cDNA fragments were isolated from the roots. Sequencing showed that their sizes ranged from 141 bp to 624 bp and some of the cDNAs were detected repeatedly (Table 2). The possible functions of the isolated cDNAs were predicted through database searches. Based on either the predicted functions or their relevant expression patterns, 64 unique genes were selected for further analysis by northern blotting. The northern results confirmed that, out of the 64 chosen genes, 25 genes were drastically regulated by Al in a manner consistent with the results from DDRT-PCR. Six genes revealed an opposite Al response between the methods, and no differences were seen by northern blotting for 13 genes that were detected as differentially expressed by DDRT-PCR. Such inconsistency may have been caused either by the false positives of the DDRT-PCR approach or by the unspecificity of certain probes in the northern blotting (Table 2). The transcripts of the other 20 genes were not detectable by northern blot (Table 2). It is likely that the transcript levels for these genes are too low to be detected by the northern blotting. These genes include ABC transporter-like protein, putative nitrate transporter, Myb family transcription factor-like, alanine aminotransferase, NADP-dependent isocitrate dehydrogenase, putative enoyl-ACP reductase, putative NADH dehydrogenase, etc. More sensitive methods such as quantitative real-time PCR are needed to assess quantitatively the transcriptional response of these interesting genes. Table 2. Differential gene fragments initially screened from the Al-resistant XN1 by DDRT-PCR and northern blot verification Gene fragments  Size (bp)  Al-regulated trend (+/–)  R versus S  GenBank accession no.  Sequence identity (%)  Corresponding or related protein sequence  Abbreviation  Function category      DDRT-PCR  Northern blot              A3  187  +  +  R>S (Up)  AK073644  99  Protein phosphatase 2A homologues, catalytic domain  PP2A  Signal transduction  C12  220  –  NR    AK243656  100  Putative calcium-dependent protein kinase  CDPK    C45  272  –  NS    AK111555  99  Putative casein kinase 2 beta-4 subunit  CK2β4    G1  207  +  +  R>S (Up)  AK240876  99  Leucine-rich repeat family protein  LRR            R>S (Up)  AK122171  94  Leucine-rich repeat family protein  LRR    G2  209  +  +  R>S (Up)  AK240876  99  Leucine-rich repeat family protein  LRR            R>S (Up)  AK122171  94  Leucine-rich repeat family protein  LRR    G8  515  –  –  S>R (Down)  AK099348  99  Putative calreticulin precursor  CRT            S>R (Down)  AB021259  94  Putative calreticulin precursor  CRT            S>R (Down)  AK070712  86  Putative calreticulin precursor  CRT    G19  515  –  –  S>R (Down)  AK099348  99  Putative calreticulin precursor  CRT            S>R (Down)  AB021259  94  Putative calreticulin precursor  CRT            S>R (Down)  AK070712  86  Putative calreticulin precursor  CRT    G18  246  –  –  S>R (Down)  AK121587  100  Guanine nucleotide-binding protein beta subunit-like protein  GβL    C31  165  +  –  NC  CT830877  99  Synaptobrevin-like protein  SYBL    A26  226  +  +  R>S (Up)  AK070820  100  Phosphate translocator-like  PTL  Transport facilitation  A36  356  +  +  R>S (Up)  AK071480  100  Putative anion transporter  AT    C10  216  +  +  NC  AK101315  100  Putative system A transporter isoform 2  SAT2    C16  180  –  NS    AK060853  98  Putative transporter  TP    C57  333  +  NS    AK121164  99  ABC transporter-like protein  ABCTL    G5  522  –  NS    AK105635  99  Putative nitrate transporter  NT    G23  172  +  +  R≈S (Up)  AK119891  100  Potassium transporter 1  KT1    G26  173  +  +  R≈S (Up)  AK119891  98  Potassium transporter 1  KT1    G33  221  -  -  R≈S (Down)  CT855047  100  Putative sulphate transporter 1  ST1    A12  328  +  NR    AK243510  99  Putative acyl-coenzyme A oxidase 2, peroxisomal precursor  ACOX2  Cellular metabolism  A21  187  –  –  R>S (Down)  AK066907  100  Carbohydrate kinase-like  CARKL    A22  187  –  –  R>S (Down)  AK066907  98  Carbohydrate kinase-like  CARKL    A35  362  –  NS    AK070042  99  NADP-dependent isocitrate dehydrogenase  ICDH    A38  336  +  +  R≈S (Up)  AK243037  100  Putative glutamine synthetase root isozyme 5  GS5    C23  167  –  NS    AK070992  99  Putative enoyl-ACP reductase  ENR    C28  141  +  +  R>S (Up)  AK068638  100  Glycolate oxidase  GLO    C29  171  +  +  R>S (Up)  AK068638  99  Glycolate oxidase  GLO    C36  323  –  NS    AK072342  99  Putative NADH dehydrogenase  NDH    C38  536  –  NR    AK242951  99  Putative Mob1-like protein  Mob1              AK106431  99  Unknown protein      C62  310  +  –  NC  X15990  99  Cytochrome c oxidase subunit 1  COX1    G39  232  +  NS    AB007404  100  Alanine aminotransferase  ALT              AB007405  100  Alanine aminotransferase  ALT    G46  404  +  NR    AK242726  99  Alpha-rhamnosidase-like protein  Rha    G48  233  +  –  S>R (Down)  AK099387  99  Putative plastidic aldolase  ALD    G51  172  +  –  S>R (Down)  AK112014  100  Putative sterol-c5(6)-desaturase  SCD    A34  294  +  –  NC  Z26867  99  S-Adenosylmethionine synthetase1  SAMS1    A46  220  +  +  S≈R (Up)  AK241023  100  Putative metallothionein-like protein 1  MT1    G3  204  +  NR    AK058961  98  Putative cystathionine gamma synthase  CGS    G9  430  +  –  S>R (Down)  AK067958  100  Putative 5-methyltetrahydropteroyltriglutamate–homocysteine methyltransferase  MS    G52  174  +  +  NC  AK121519  99  Putative profilin  PFN  Cytokeleton  A45  442  –  –  S>R (Down)  AK101613  100  Actin  ACT    A8  310  +  +  NC  AK060789  99  Cationic peroxidase  CPOX  Stress  A25  263  +  +  NC  AK100973  100  Chitinase  CHI    G28  202  +  +  NC  AK100973  100  Chitinase  CHI    G29  263  +  +  NC  AK100973  100  Chitinase  CHI    A27  165  +  +  NC  AK105010  99  Stress-related protein-like protein  SRP    C17  283  +  NR    AK067262  100  Putative copper amine oxidase  CAO    C40  181  –  NR    AK103475  99  Putative hypersensitive-induced response protein  HIR1    G40  367  +  NR    AP008207  100  Putative hypersensitive-induced response protein  HIR2    G50  387  +  +  NC  AK061606  99  Pathogenesis-related protein 10  PR-10    A7  315  –  –  S≈R (Down)  AK105327  100  Putative ribosomal protein L21  RPL21  Others  A16  352  –  NR    AK100968  99  Putative eukaryotic translation initiation factor 4G  eIF4G    A40  314  –  NS    AK072358  98  F-box domain protein  F-Box    A43  277  –  NS    AK108764  98  PHD-finger family protein  PHDF    A44  281  +  NS    AK063278  98  Putative transposon protein, CACTA, En/Spm subclass  TPN    C13  340  +  NS    CT856635  99  Myb family transcription factor-like  Myb    C27  222  –  NS    AK099367  100  Putative RNA-binding protein  RNAB    C42  616  +  NR    AK107650  100  Receptor-like kinase Xa21-binding protein 3  RLK3    G7  396  –  –  NC  AK070267  98  Zinc finger protein-like  ZFPL1    C58  166  +  NS    AK071063  100  Zing finger protein-like  ZFPL2    G15  624  –  NS    AK102212  99  Putative glucosyltransferase  GTF    G35  213  –  NR    AK065228  100  Putative dnaK-type molecular chaperone precursor  DnaKC    G37  252  –  –  S≈R (Down)  AK119623  100  Mitochondrial chaperonin-60  CPN60    G44  282  +  +  NC  AK058360  99  Ubiquitin-conjugating enzyme  UBC    G47  376  +  NR    AK071581  100  DnaJ protein-like  DnaJL    G53  316  +  +  NC  AK066128  99  60S ribosomal protein L10-2  RPL10    C54  366  +  NS    AK108972  100  Unknown protein      C55  224  +  NS    AK108762  100  Unknown protein      C59  311  +  +  NC  AK100379  99  Unknown protein      G24  172  +  NS    AK066310  99  Unknown protein      A39  302  -  NS    NM_00105055  99  No      C24  260  +  NS    CT834936  98  No      C53  241  +  NR    CT835818  98  No      Gene fragments  Size (bp)  Al-regulated trend (+/–)  R versus S  GenBank accession no.  Sequence identity (%)  Corresponding or related protein sequence  Abbreviation  Function category      DDRT-PCR  Northern blot              A3  187  +  +  R>S (Up)  AK073644  99  Protein phosphatase 2A homologues, catalytic domain  PP2A  Signal transduction  C12  220  –  NR    AK243656  100  Putative calcium-dependent protein kinase  CDPK    C45  272  –  NS    AK111555  99  Putative casein kinase 2 beta-4 subunit  CK2β4    G1  207  +  +  R>S (Up)  AK240876  99  Leucine-rich repeat family protein  LRR            R>S (Up)  AK122171  94  Leucine-rich repeat family protein  LRR    G2  209  +  +  R>S (Up)  AK240876  99  Leucine-rich repeat family protein  LRR            R>S (Up)  AK122171  94  Leucine-rich repeat family protein  LRR    G8  515  –  –  S>R (Down)  AK099348  99  Putative calreticulin precursor  CRT            S>R (Down)  AB021259  94  Putative calreticulin precursor  CRT            S>R (Down)  AK070712  86  Putative calreticulin precursor  CRT    G19  515  –  –  S>R (Down)  AK099348  99  Putative calreticulin precursor  CRT            S>R (Down)  AB021259  94  Putative calreticulin precursor  CRT            S>R (Down)  AK070712  86  Putative calreticulin precursor  CRT    G18  246  –  –  S>R (Down)  AK121587  100  Guanine nucleotide-binding protein beta subunit-like protein  GβL    C31  165  +  –  NC  CT830877  99  Synaptobrevin-like protein  SYBL    A26  226  +  +  R>S (Up)  AK070820  100  Phosphate translocator-like  PTL  Transport facilitation  A36  356  +  +  R>S (Up)  AK071480  100  Putative anion transporter  AT    C10  216  +  +  NC  AK101315  100  Putative system A transporter isoform 2  SAT2    C16  180  –  NS    AK060853  98  Putative transporter  TP    C57  333  +  NS    AK121164  99  ABC transporter-like protein  ABCTL    G5  522  –  NS    AK105635  99  Putative nitrate transporter  NT    G23  172  +  +  R≈S (Up)  AK119891  100  Potassium transporter 1  KT1    G26  173  +  +  R≈S (Up)  AK119891  98  Potassium transporter 1  KT1    G33  221  -  -  R≈S (Down)  CT855047  100  Putative sulphate transporter 1  ST1    A12  328  +  NR    AK243510  99  Putative acyl-coenzyme A oxidase 2, peroxisomal precursor  ACOX2  Cellular metabolism  A21  187  –  –  R>S (Down)  AK066907  100  Carbohydrate kinase-like  CARKL    A22  187  –  –  R>S (Down)  AK066907  98  Carbohydrate kinase-like  CARKL    A35  362  –  NS    AK070042  99  NADP-dependent isocitrate dehydrogenase  ICDH    A38  336  +  +  R≈S (Up)  AK243037  100  Putative glutamine synthetase root isozyme 5  GS5    C23  167  –  NS    AK070992  99  Putative enoyl-ACP reductase  ENR    C28  141  +  +  R>S (Up)  AK068638  100  Glycolate oxidase  GLO    C29  171  +  +  R>S (Up)  AK068638  99  Glycolate oxidase  GLO    C36  323  –  NS    AK072342  99  Putative NADH dehydrogenase  NDH    C38  536  –  NR    AK242951  99  Putative Mob1-like protein  Mob1              AK106431  99  Unknown protein      C62  310  +  –  NC  X15990  99  Cytochrome c oxidase subunit 1  COX1    G39  232  +  NS    AB007404  100  Alanine aminotransferase  ALT              AB007405  100  Alanine aminotransferase  ALT    G46  404  +  NR    AK242726  99  Alpha-rhamnosidase-like protein  Rha    G48  233  +  –  S>R (Down)  AK099387  99  Putative plastidic aldolase  ALD    G51  172  +  –  S>R (Down)  AK112014  100  Putative sterol-c5(6)-desaturase  SCD    A34  294  +  –  NC  Z26867  99  S-Adenosylmethionine synthetase1  SAMS1    A46  220  +  +  S≈R (Up)  AK241023  100  Putative metallothionein-like protein 1  MT1    G3  204  +  NR    AK058961  98  Putative cystathionine gamma synthase  CGS    G9  430  +  –  S>R (Down)  AK067958  100  Putative 5-methyltetrahydropteroyltriglutamate–homocysteine methyltransferase  MS    G52  174  +  +  NC  AK121519  99  Putative profilin  PFN  Cytokeleton  A45  442  –  –  S>R (Down)  AK101613  100  Actin  ACT    A8  310  +  +  NC  AK060789  99  Cationic peroxidase  CPOX  Stress  A25  263  +  +  NC  AK100973  100  Chitinase  CHI    G28  202  +  +  NC  AK100973  100  Chitinase  CHI    G29  263  +  +  NC  AK100973  100  Chitinase  CHI    A27  165  +  +  NC  AK105010  99  Stress-related protein-like protein  SRP    C17  283  +  NR    AK067262  100  Putative copper amine oxidase  CAO    C40  181  –  NR    AK103475  99  Putative hypersensitive-induced response protein  HIR1    G40  367  +  NR    AP008207  100  Putative hypersensitive-induced response protein  HIR2    G50  387  +  +  NC  AK061606  99  Pathogenesis-related protein 10  PR-10    A7  315  –  –  S≈R (Down)  AK105327  100  Putative ribosomal protein L21  RPL21  Others  A16  352  –  NR    AK100968  99  Putative eukaryotic translation initiation factor 4G  eIF4G    A40  314  –  NS    AK072358  98  F-box domain protein  F-Box    A43  277  –  NS    AK108764  98  PHD-finger family protein  PHDF    A44  281  +  NS    AK063278  98  Putative transposon protein, CACTA, En/Spm subclass  TPN    C13  340  +  NS    CT856635  99  Myb family transcription factor-like  Myb    C27  222  –  NS    AK099367  100  Putative RNA-binding protein  RNAB    C42  616  +  NR    AK107650  100  Receptor-like kinase Xa21-binding protein 3  RLK3    G7  396  –  –  NC  AK070267  98  Zinc finger protein-like  ZFPL1    C58  166  +  NS    AK071063  100  Zing finger protein-like  ZFPL2    G15  624  –  NS    AK102212  99  Putative glucosyltransferase  GTF    G35  213  –  NR    AK065228  100  Putative dnaK-type molecular chaperone precursor  DnaKC    G37  252  –  –  S≈R (Down)  AK119623  100  Mitochondrial chaperonin-60  CPN60    G44  282  +  +  NC  AK058360  99  Ubiquitin-conjugating enzyme  UBC    G47  376  +  NR    AK071581  100  DnaJ protein-like  DnaJL    G53  316  +  +  NC  AK066128  99  60S ribosomal protein L10-2  RPL10    C54  366  +  NS    AK108972  100  Unknown protein      C55  224  +  NS    AK108762  100  Unknown protein      C59  311  +  +  NC  AK100379  99  Unknown protein      G24  172  +  NS    AK066310  99  Unknown protein      A39  302  -  NS    NM_00105055  99  No      C24  260  +  NS    CT834936  98  No      C53  241  +  NR    CT835818  98  No      ‘NR’ and ‘NS’ represents no response to Al or no signal detected, respectively; ‘R’ and ‘S’ represent the resistant or susceptible cultivar, respectively; ‘Up’ and ‘Down’ stand for the up- or down-regulated genes; ‘NC’ represents not comparable. View Large As shown in Table 2 and Fig. 1, there are several Al-regulated genes that are associated with sulphur acquisition and metabolism, such as ST1 (sulphate transporter 1), MS (5-methyltetrahydroteroyltriglutamate–homocysteine methyltransferase), SAMS1 (S-adenosylmethionine synthetase 1), and MT1 (metallothionein-like protein 1). It is possible that more genes in sulphur metabolism are also regulated during Al stress. An additional 12 genes involved in the sulphur metabolism pathway were chosen and their expression was independently analysed by northern blotting using gene-specific probes (Table 1). As shown in Fig. 2, among the 12 genes tested, six were shown to be Al responsive. ATPS (ATP sulphurylase) and APR3 (an isogene for adenosine 5′-phosphosulphate reductase) were up-regulated during Al treatment; CYS1 and CYS3 (isogenes for cysteine synthase) were induced at 6 h of Al treatment and then became non-different; APR2 and PCS (phytochelatin synthase) were highly suppressed by Al stress. Taken together with the previous 31 genes, a total of 37 genes were identified as Al responsive in this study, of which five have been previously known as Al regulated while the others are novel genes. Fig. 1. View largeDownload slide Al-induced differential expression of genes in rice cultivars with different Al sensitivities. ‘R’ and ‘S’ represents the resistant (XN1) or susceptible (XX2) genotype, respectively. CK and Al lanes correspond to control samples and Al-treated samples, respectively. rRNA shows the RNA integrity and uniform loading control. Al-regulated genes are grouped into six categories (a–f). (a) Genes related to signal transduction; (b) genes related to the cellular cytoskeleton; (c) genes related to transport facilitation; (d) genes related to cellular metabolism; (e) genes related to stress response; and (f) genes related to other functions. Refer to Table 2 for more detailed information on the genes. Fig. 1. View largeDownload slide Al-induced differential expression of genes in rice cultivars with different Al sensitivities. ‘R’ and ‘S’ represents the resistant (XN1) or susceptible (XX2) genotype, respectively. CK and Al lanes correspond to control samples and Al-treated samples, respectively. rRNA shows the RNA integrity and uniform loading control. Al-regulated genes are grouped into six categories (a–f). (a) Genes related to signal transduction; (b) genes related to the cellular cytoskeleton; (c) genes related to transport facilitation; (d) genes related to cellular metabolism; (e) genes related to stress response; and (f) genes related to other functions. Refer to Table 2 for more detailed information on the genes. Fig. 2. View largeDownload slide Northern blot analysis of selected genes related to sulphate metabolism (ATPS, ATP sulphurylase; APR, 5′-adenosine-phosphosulphate reductase; CYS, cysteine synthase; SO, sulphite oxidase; SR, sulphite reductase; PCS, phytochelatin synthase) in response to Al stress in the two contrasting genotypes. ‘R’ and ‘S’ represent the resistant or susceptible genotype, respectively. CK and Al lanes correspond to control and Al-stressed treatments. rRNA shows the RNA integrity and uniform loading control. Fig. 2. View largeDownload slide Northern blot analysis of selected genes related to sulphate metabolism (ATPS, ATP sulphurylase; APR, 5′-adenosine-phosphosulphate reductase; CYS, cysteine synthase; SO, sulphite oxidase; SR, sulphite reductase; PCS, phytochelatin synthase) in response to Al stress in the two contrasting genotypes. ‘R’ and ‘S’ represent the resistant or susceptible genotype, respectively. CK and Al lanes correspond to control and Al-stressed treatments. rRNA shows the RNA integrity and uniform loading control. Al-induced genes in relation to Al adaptation/resistance Al resistance has been evidenced as an inducible process (Kochian et al., 2004, 2005), suggesting that profiling the Al-induced genes may permit the identification of factors important to Al resistance (Kochian et al., 2004). By taking advantages of the unique Al-resistant rice cultivar XN1, a number of potentially important targets in Al responses have been identified (Figs 1, 2). Upon Al treatment, >20 genes were transcriptionally up-regulated in both cultivars. Among these up-regulated genes, 10 members (LRR, PP2A, PTL, AT, ATPS, APR3, SR, CYS1, CYS3, and GLO) were either more significantly Al induced or constitutively more abundant in the resistant XN1 than in the susceptible XX2. For instance, the Al-induced expression of both LRR (leucine-rich repeat family protein) and PP2A (protein phosphatase 2A) was more prominent in the resistant XN1, when compared with the susceptible XX2 (Fig. 1a). The LRR class of RLKs is thought to be engaged in protein–protein interactions (Trewavas, 2000). One example is RLK5, which is associated with a protein phosphatase (KAPP), and the RLK5 gene (i.e. Cf-9) is known to confer resistance against tomato mould (Trewavas, 2000). Provided that PP2A is a downstream effector to RLKs such as KAPP, the Al induction of both LRR and PP2A with genotypic difference may hint that the LRR-related signalling pathway could be activated and may play a role in Al adaptation or resistance. As shown in Fig. 1c, four genes (AT, PTL, KT1, and SAT2) that are involved in ion transport were induced by Al. AT was more significantly induced and PTL was constitutively more abundant in the resistant XN1. AT encodes an anion transporter that could function in exudation of anions, e.g. organic acids. Certain anion channels that were specifically activated by extracellular Al3+ were recently identified using the patch clamp technique with protoplasts isolated from root tips of Al-tolerant wheat (Ryan et al., 1997; Zhang et al., 2001) and maize (Kollmeier et al., 2001; Pineros et al., 2001, 2002). In an Al-tolerant maize line, an anion channel was identified to mediate Al-activated root citrate release (Ryan et al., 1997; Kollmeier et al., 2001). Sasaki et al. (2004) recently identified a gene, named ALMT1, via a subtractive hybridization approach from a pair of near-isogenic wheat lines differing at a single Al tolerance locus, and proved that this gene conferred an Al-activated malate exudation and Al resistance in plants. PTL encodes a phosphate translocator-like protein. Phosphate has been considered to be an important element in coping with Al toxicity (Pellet et al., 1996; Liao et al., 2005; Zheng et al., 2005). KT1 and SAT2 deserve to be addressed despite the fact both of them showed no discernible genotypic differences (Fig. 1c). KT1 and SAT2 encode a potassium transporter and a system A transporter, respectively, and are potential players in the overall high resistance of rice to Al. In Al3+-tolerant wheat, the presence of Al3+ activates both malate and K+ efflux from the root apices (Ryan et al., 1997). Zhang et al. (2001) reported that an outward-rectifying K+-current was activated by Al3+ in the Al3+-tolerant genotypes of wheat. These findings provide evidence that the sustained efflux of K+ from the root apices of Al3+-tolerant wheat genotypes is mediated by an Al3+-activated anion channel and an outward K+ channel in the plasma membranes of root cells. Consistently, Deng et al. (2006) found that overexpression of AtMGT1 (a magnesium transport protein) improved Al tolerance in plants. System A transporters are known to be involved in amino acid transport. Evidence has been provided indicating a possible involvement of metal-induced amino acids, particularly proline, in metal stress defence (Sharma and Dietz, 2006). Taken together, it is likely that the above four genes may function in rice Al resistance either for rice species or for the resistant cultivars. Five genes (ATPS, APR3, SR, CYS1, and CYS3) involved in sulphur assimilation were either more significantly Al induced or constitutively more abundant in the resistant XN1 (Fig. 2). Devi et al. (2003) showed that glutathione, a major product of sulphur metabolism, is related to Al resistance in tobacco suspension cells. Glutathione S-transferase (GST) and glutathione peroxidase (GPX) were also detected as being important players during Al stress (Ezaki et al., 1995; Richards et al., 1998; Milla et al., 2002). Cysteine synthase (CS) was recently identified as an Al-inducible protein in rice roots by a proteomic approach, and the response was validated by western blot, enzyme activity assay, and determination of glutathione (Yang et al., 2007). As also noticed earlier, MT1 encoding a metallothionein-like protein, a more downstream product of cysteine metabolism, was persistently up-regulated by Al despite no genotypic difference being detected (Fig. 1d). Similar results have been reported previously in various plants including rice (Snowden and Gardner, 1993; Yu et al., 1998). Since MT may play roles in both metal detoxification and antioxidation, the possibility exists that this peptide conferred the overall high resistance to Al for rice species. It is also interesting to note that a gene highly homologous to GLO (glycolate oxidase) was more highly induced by Al in the resistant XN1 (Fig. 1d). GLO is localized in the leaf peroxisomes and catalyses photorespiratory glycolate oxidation into glyoxylate with concomitant H2O2 release. The exact mechanism for potential involvement of GLO in Al adaptation will have to be determined. Al-inhibited genes and Al toxicity Al toxicity is characterized by a prompt inhibition of root growth. While the physiological mechanism of Al toxicity has been relatively well documented (Kochian et al., 2004), the molecular basis for Al toxicity remains far from clear. Al treatment transcriptionally suppressed a number of genes (Table 2; Fig. 1). For example, three genes (GβL, CRT, and SYBL) were significantly down-regulated by Al toxicity. GβLs are thought to be the receptors for activated protein kinase C (PKC) (Kwak et al., 1997), and PKC is known to be activated by DAG (diacylglycerol) in concert with Ca2+ (Trewavas, 2000). DAG and IP3 (inositol 1,4,5-triphosphate) are the products of PIP2 (phosphatidylinositol 4,5-bisphosphate) catalysed by PLC. CRT is a low-affinity Ca2+-binding protein and serves as a downstream component of IP3 signalling (Trewavas, 2000). SYBL has been reported to be functionally essential for certain small GTPases in yeasts and acts in the endoplasmic reticulum to Golgi transport (Ossig et al., 1991). The inhibition of these three genes (Fig. 1a) therefore could result in the disruption of the phosphoinositide pathway as associated with Ca2+ signalling during Al stress. Al inhibits IP3 signal transduction pathway associated with PLC activity (Jones and Kochian, 1995; Ramos-Diaz et al., 2007). PIP2 may be directly used as a regulator for profilin (PFN) which in turn regulates actin (ACT) (Trewavas, 2000). Both ACT and PFN were shown to be inhibited by Al in the two cultivars (Fig. 1b). Profilin, as an actin-binding protein, exerts regulatory effects on actin polymerization (Theriot and Mitchison, 1993). The polymerization and depolymerization of actin filaments provide cells with the ability to remodel the cytoskeleton rapidly in response to endogenous cues or external signals (Ramachandran et al., 2000). The expression level of PFN was rate limiting and critical for cell elongation. Reduction in the expression levels by 50% resulted in an elongation defect with no apparent impact on cell division (Ramachandran et al., 2000). It is likely that the above five genes (GβL, CRT, SYBL, ACT, and PFN) are functionally interconnected. Their consistent suppression upon Al treatment (Fig. 1a, b; Table 2) supports the previous notion that cytoskeletal dynamics as associated with the phosphoinositide signalling pathway is a potential target for Al phytotoxicity (Blancaflor et al., 1998; Sivaguru et al., 1999; Kochian et al., 2004). A number of Al-inhibited genes are associated with cellular metabolism. Four Al-inhibited genes are involved in sulphur acquisition and metabolism, i.e. ST1 (sulphate transporter 1), MS (5-methyltetrahydroteroyltriglutamate-homocysteine methyltransferase), SAMS1 (S-adenosylmethionine synthetase 1), and PCS (phytochelatin synthase) (Figs 1c, d, 2). MS and SAMS are two immediately neighbouring enzymes in the S-adenosylmethionine (SAM) pathway. MS catalyses methionine formation from homocysteine and then methionine is converted into SAM by SAMS catalysis. Consistent with this observation, Milla et al. (2002) reported a similar expression pattern for both SAMS and MS in response to Al stress in rye, and a recent proteomic analysis also revealed that SAMS protein was suppressed under Al toxicity in rice (Yang et al., 2007). In contrast, however, several genes involved in the synthesis of cysteine and MTs were up-regulated under Al stress, as described above (Table 2; Fig. 1d). Such a difference may indicate that the backbone pathway (cysteine synthesis) has to be activated in order to compensate the down-regulated branch pathway (i.e. the SAM-related cycle). Aldolase (ALD) and carbohydrate kinase (CARKL) are the key constituents in both the glycolytic pathway and the Calvin cycle. The inhibition of these two enzymes (Fig. 1d) may give rise to a blockage of carbohydrate turnover. In an aldolase-antisense transgenic rice plant, the root elongation rate was only half that of the wild type (Komatsu and Konishi, 2005), pointing to a possibility that ALD suppression may also be involved in Al-inhibited root growth. In summary, since XN1 and XX2 are two contrasting rice cultivars with different Al sensitivities, the identified Al-regulated gene expression profiles between the two cultivars will provide a good foundation to elucidate molecular mechanisms that are responsible for the sensitivity differences. The transcriptional regulation of these genes in responding to Al stress in this particular Al-resistant cultivar may provide important clues leading to the final identifications of genes that may be utilized to engineer Al-tolerant plants. Abbreviations Abbreviations APR 5′-adenosine-phosphosulphate reductase ATPS ATP sulphurylase CYS cysteine synthase PCS phytochelatin synthase SO sulphite oxidase SR sulphite reductase This work was supported by the Science and Technology Plans of Guangdong (No. 2004B50201017) and National Science Foundation of China (No. 30470152). 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TI - Identification of aluminium-responsive genes in rice cultivars with different aluminium sensitivities
JO - Journal of Experimental Botany
DO - 10.1093/jxb/erm110
DA - 2007-05-24
UR - https://www.deepdyve.com/lp/oxford-university-press/identification-of-aluminium-responsive-genes-in-rice-cultivars-with-Wq5a5LahQl
SP - 2269
EP - 2278
VL - 58
IS - 8
DP - DeepDyve
ER -