The whole-genomic gene-expression changes of maize (Zea mays L.) plants in response to water-deficit stress at the heading stage have not been previously studied. The present work utilized a maize oligonucleotide array (‘57K’, ~57000 sequences; http://www.maizearray.org/) representing more than 30000 unique genes, to profile transcriptome changes in maize leaves subjected to 1d (day) and 7d water-deficit stress. After 1d and 7d water-stress treatment, 195 and 1008 differential genes were identified respectively. One-third of 1d-water-stress-induced genes had known or putative functions in various cellular signalling pathways, indicating that signal-transduction-related genes play important roles in the early responses of maize leaves to water stress. The 7d-stress-regulated genes were involved in a broad range of cellular and biochemical activities. The most notable genes may function in compatible osmolyte metabolism, particularly in proline, sucrose, trehalose and raffinose metabolism in the leaves. The present study provided a valuable starting point for further elucidation of molecular mechanisms in the drought tolerance of maize plants.

INTRODUCTION

Among the various abiotic stresses, drought or water deficit is the most severe limiting factor of plant growth and production. Maize is one of the most important cereal crops and suffers from serious water-deficit stress in cultivated areas worldwide [1]. To ensure their own survival and the prosperity of their offspring, plants have evolved a range of strategies to cope with water stress. One common mechanism is the accumulation of compatible solutes, low-molecular-mass highly soluble compounds that are non-toxic at high concentrations. The compatible solutes accumulate differently among plant species and include amino acids, such as proline, sugars, such as RFOs (raffinose family oligosaccharides), sucrose and trehalose, and sugar alcohols [2]. Understanding the molecular mechanism of the responses of plants to water-deficit stress may provide new strategies to improve the stress tolerance of agriculturally important plants [3].

It has been shown that the protective mechanisms of plants in response to stress are regulated by alterations in the expression levels of stress-responsive genes. Therefore a global assessment of gene expression is needed to understand the response at the genome-wide level. Microarrays provide an analytical tool by which thousands of genes can be studied at one time, and cDNA microarray has been used to monitor global gene expression in response to water stress in maize plants. Zinselmeier et al. [4] used cDNA microarrays to monitor expression of 384 maize genes in response to shade stress, and used oligonucleotide microarray to examine expression of 1502 genes in response to water stress. Yu and Setter [5] monitored gene expression in developing maize endosperm and placenta/pedicel tissues during water deficit and re-watering using cDNA microarray slides containing approx. 2500 unique cDNAs from the immature maize ear. Zheng et al. [6] successfully isolated 174 ESTs (expressed sequence tags) in the response of maize seedlings to water stress using SSH (suppression subtraction hybridization) and cDNA macroarray. Jia et al. [7] identified 79 genes up-regulated by water stress in maize seedlings using a maize macroarray of 2073 full-length cDNAs. Andjelkovic and Thompson [8] used a macroarray to analyse expression profiles of 2500 clones in the maize kernel during water and salt stress, and identified 20 dehydration and salt-inducible genes, and 37 induced solely by salt stress and 26 specifically dehydration-induced genes. These studies provide an insight into the transcriptomes involved in responses to water stress and contribute to our understanding of the function of the responsive genes in maize.

Periods of soil water deficit can occur at any time during the crop season, but maize is particularly sensitive to water stress around flowering time. At this time, the stress usually causes remarkable yield loss [9]. Heading time, which is just before tassel flowering, is one of the most important stages during which maize productivity is affected severely if plants encounter water stress. However, the molecular mechanism of the response to water stress at this stage has not been fully understood. To advance our understanding of maize plants response to water-deficit stress at the crucial development stage, we adopted a genomic approach to monitor the transcriptome change of maize leaves under water-deficit conditions, using the ‘57K’ oligonucleotide microarray slides (http://www.maizearray.org/), and a large number of genes responded to water deficit were found.

MATERIALS AND METHODS

Plant materials and stress treatments

The maize (Zea mays L.) inbred line DH4866 was used in the present study. Plants were grown in flowerpots containing field soil under natural conditions. When the tassel spread out of the uppermost leaf, some plants were treated with drought stress for 7d (days), and others were left under normal-watered conditions as controls. In the period of the stress, the plants were watered every day to maintain a similar water-deficiency state by adjusting water supply, according to the osmotic potential of the fully expanded leaf of the plants measured at 8:00 h each day. The maize flag leaves were harvested after 24 h (1d) and 168 h (7d) of stress treatment, frozen in liquid nitrogen immediately and stored at −80°C for further analysis. Unstressed plants as controls were harvested at the same time as the stressed plants. One sample consisted of the leaves from three independent plants under the same conditions.

Microarray experiments and data analysis

Slides of the maize oligonucleotide array (version 1.9) were obtained from the Maize Oligonucleotide Array Project (University of Arizona, Tucson, AZ, U.S.A.; http://www.maizearray.org/). The microarray used in the present study contained 57452 maize 70-mer oligonucleotides [the sequences containing 70-mer oligonucleotides were designated by TIGR ID (http://www.tigr.org/), e.g. TM00026383, sequence information is available at http://www.maizearray.org/], representing >30000 identifiable unique maize genes. Two technical replicates (dye-swap experiments) for each biological sample from two independent treatments were performed.

Total RNA was isolated from the frozen samples as described previously [10]. For each sample, 100 μg of total RNA was transcribed into cDNA and fluorescently labelled with Cy3 and Cy5 dyes using the SuperScript indirect cDNA labelling system (Invitrogen) according to the manufacturer's instructions. The Cy3 and Cy5 labels were swapped between sample and control cDNA to minimize any possible impact of inequalities in DNA incorporation and photobleaching of the fluorescent dyes. Hybridizations were performed according to the protocols described by the Maize Oligonucleotide Array Project.

Data acquisition and analysis were performed on a GenePix 4000B scanner with GenePix 6.0 software (Axon Instruments). Signal values were initially normalized during the image scanning process to adjust the average ratios between two channels. The overall intensity of the hybridized slide was then normalized by GenePix 6.0 software. Those spots flagged as ‘bad’ or ‘not found’ by GenePix were removed from further data analysis and only those spots that showed fluorescent intensity levels above the 1.5-fold background (local) in each channel were input into the FiRe software for further analysis [11]. Signal values for each spot on the slide were calculated, using the median intensity of pixels minus the median local background for each channel. The normalization of Cy3 and Cy5 fluorescence intensity was performed by adjusting the total fluorescence intensities of the two images. These adjusted values were used to determine differential gene expression (stressed/control ratio) for each spot. Only those transcripts with a stressed/control ratio ≤0.5 or ≥2.0 in each experiment were considered to be differentially expressed. To remove redundant transcripts we used the following criteria: (1) transcripts with their top hit in the NRAA (non-redundant amino acid) database (BLAST) are the same, and (2) they are in the identical contig using CAP3 DNA sequence analysis programme [12].

Expression validation by real-time PCR

The expression profiles obtained from microarray hybridizations were further validated by real-time RT (reverse transcriptase)-PCR. DNase-treated total RNA (500 ng) from the maize leaves of controls or samples that were subjected to water-deficit stress for 1d and 7d was used for the synthesis of first-strand cDNA for real-time RT-PCR using the RT reagent kit (TAKARA) according to the manufacturer's instructions. Real-time RT-PCR experiments were performed on a Chromo 4™ continuous fluorescence detector (MJ Research) with the SYBR® RT-PCR kit (TAKARA), in a 10 μl reaction volume, which contained 5 μl of SYBR® Green I PCR mix, 0.2 μl of each forward and reverse primer, 1 μl of diluted cDNA template and appropriate amounts of sterile double-distilled water. Amplification conditions were: 2 min at 95°C; 40 cycles of 15 s at 95°C, 30 s at 58°C and 30 s at 72°C. Fold changes of RNA transcripts were calculated by the 2−ΔΔCt method [12a] using 18S ribosomal RNA (forward primer, GAAACGGCTACCACATCCA; reverse primer, CACCAGACTTGCCCTCCA) as the internal control. The genes selected for validation included six up-regulated and four down-regulated transcripts in response to water stress. The clones whose expression was validated were: TM00015224 (TIGR ID) (forward, GCTGTAGGGAATGCTGGGT; reverse, CACGGCTTGGTATTTCTGTG); TM00015929 (forward, AGGTCCTGAGCAAAATCCC; reverse, CTACAGCAGTAGCCGAGACG); TM00019036 (forward, GTTGTGCGACGAGGGTGA; reverse, GATGCCGATTGGAGAGATTT); TM00023565: (forward, ACGAACTGTGTAGACGATTGCT; reverse, GGAGCGGCACCTACATCA); TM00023596 (forward, CACCGAAGAAAGCAAAGAAGT; reverse: CACGGACATTATCCAGCAGA); TM00035829 (forward, CGTTCTATGGGCTCGCAC; reverse, TGGACGCTGGAGATTATGG); TM00000350 (forward, GGAGCAGCAATGGCATCT; reverse, ACGAGGAGGGTCCTGTAGG); TM00026418 (forward, ACCCATCCATTCATTTCCTC; reverse: GTCAGAGTTTGGTTTGCGAA); TM00042197 (forward, AGGTCCTC GTGGTCATTGG; reverse, TGCCTTAGCCCTAGTTTTTCA); and TM00048364 (forward, CAACGATCACGGATGTGACTA; reverse: TCTGAAGAAGGCGGACGA). The experiments were repeated three times.

RESULTS AND DISCUSSION

Characterization of stress treatments

In the present study, the middle part of the top fully expanded leaves of the plants under water-stress treatment, as well as that of the control, were taken to measure the leaf osmotic potential at different times using a micro-osmometer (Fiske®). During the water stress, the leaf osmotic potential of the stressed plants was held at −0.4 to −0.5 MPa, whereas the osmotic potential was −0.2 to −0.25 MPa in the leaves of the control plants at 8:00 h. Also there were visible signs of water deficiency, such as leaf rolling during the daytime, although at night the rolled leaves spread out. Maize plants were stress-treated at the beginning of the heading stage. After 7d of water deficiency, the plants began to enter the flowering stage.

Microarray analysis of transcriptomic changes in leaves by water stress

The global gene expression profiles of the maize leaves under short-term (1d) and long-term (7d) water-deficit stress were examined using a whole-genome microarray. The genes that have at least a 2-fold change of the expression between control and treatment were selected. In total, we identified 102 up-regulated genes and 93 down-regulated genes in the 1d water-stress experiment, and 332 up-regulated and 676 down-regulated genes in the 7d experiment. Among them, 22 genes were commonly up-regulated and 37 genes were commonly down-regulated in both treatments (Figure 1). The results showed that gene expression changes were significantly different under the 1d (short-term) and 7d (long-term) water-deficit conditions.

Venn diagram showing the number of differentially expressed genes up- (A) or down- (B) regulated by water stress in either or both treatments (1d and 7d stress) of maize leaves

Figure 1
Venn diagram showing the number of differentially expressed genes up- (A) or down- (B) regulated by water stress in either or both treatments (1d and 7d stress) of maize leaves

The genes with a ratio (stressed/control) of more than 2-fold in each experiment were identified as differential changes.

Figure 1
Venn diagram showing the number of differentially expressed genes up- (A) or down- (B) regulated by water stress in either or both treatments (1d and 7d stress) of maize leaves

The genes with a ratio (stressed/control) of more than 2-fold in each experiment were identified as differential changes.

Verification of microarray data

We further used a real-time quantitative RT-PCR to confirm the expression changes of transcripts identified by the microarray analysis. Six up-regulated and four down-regulated genes were selected. Three independent biological replicates were performed. The results showed that levels of transcripts of all of these ten genes in samples under water-deficit stress for 1d and 7d were changed, compared with the controls, which were consistent with the microarray results (Table 1).

Table 1
Verification of microarray results by real-time PCR

Total RNAs from the maize leaves of controls and plants subjected to water-deficit stress for 1d and 7d were used for the synthesis of the first-strand cDNA for real-time PCR analysis. The ratios are the stressed/control plants. The results are expressed as the means±S.E.M. for three independent biological replicates.

Ratio of real-time PCRRatio of microarray
TIGR IDAnnotation1d stress7d stress1d stress7d stress
TM00015224 Putative zinc finger transcription factor 2.88±0.50 2.71±0.41 2.48 3.78 
TM00015929 Putative reticulon 3.41±0.44 3.83±0.48 3.79 4.43 
TM00019036 Protein phosphatase 2C-like protein 2.57±0.36 3.49±0.43 3.38 5.39 
TM00023565 Putative lipid transfer protein 2.32±0.33 2.75±0.36 2.63 3.79 
TM00023596 Putative ribosomal protein L19 3.15±0.50 2.67±0.39 2.41 2.77 
TM00035829 Putative seed imbibition protein 5.89±0.83 6.09±0.65 3.99 9.74 
TM00000350 Fructose-bisphosphate aldolase 0.41±0.07 0.39±0.06 0.35 0.37 
TM00026418 Neutral/alkaline invertase 2 0.28±0.03 0.23±0.03 0.37 0.22 
TM00042197 Carbonate dehydratase 0.45±0.07 0.48±0.05 0.44 0.46 
TM00048364 Putative β-amylase 0.31±0.06 0.43±0.05 0.27 0.41 
Ratio of real-time PCRRatio of microarray
TIGR IDAnnotation1d stress7d stress1d stress7d stress
TM00015224 Putative zinc finger transcription factor 2.88±0.50 2.71±0.41 2.48 3.78 
TM00015929 Putative reticulon 3.41±0.44 3.83±0.48 3.79 4.43 
TM00019036 Protein phosphatase 2C-like protein 2.57±0.36 3.49±0.43 3.38 5.39 
TM00023565 Putative lipid transfer protein 2.32±0.33 2.75±0.36 2.63 3.79 
TM00023596 Putative ribosomal protein L19 3.15±0.50 2.67±0.39 2.41 2.77 
TM00035829 Putative seed imbibition protein 5.89±0.83 6.09±0.65 3.99 9.74 
TM00000350 Fructose-bisphosphate aldolase 0.41±0.07 0.39±0.06 0.35 0.37 
TM00026418 Neutral/alkaline invertase 2 0.28±0.03 0.23±0.03 0.37 0.22 
TM00042197 Carbonate dehydratase 0.45±0.07 0.48±0.05 0.44 0.46 
TM00048364 Putative β-amylase 0.31±0.06 0.43±0.05 0.27 0.41 

Functional classification of the responding genes

According to the functional categories of the Arabidopsis proteins, the differentially expressed genes after 1d and 7d water-deficit stress were classified into several function categories (Figure 2). Over one-third of the differentially expressed genes were functionally unknown, whereas the others were related to metabolism, signal transduction, defence, transcription, transport and subcellular localization etc. Under 1d stress, the biggest three function groups of those induced genes were involved in signal transduction, metabolism and defence. The largest three function groups of those repressed genes were metabolism, energy and subcellular localization. In contrast, under 7d stress, the largest three function groups of the induced genes were metabolism, defence and transcription, whereas the largest three function groups of the repressed genes were involved in metabolism, energy and transport. The data revealed that the metabolism-related genes differentially expressed in controls and samples subjected to water-deficit stress were prominent in the leaves of maize plants at the heading stage.

Functional classification of differentially expressed genes up- (A) or down- (B) regulated by 1d water stress, and up- (C) or down- (D) regulated by 7d stress

Figure 2
Functional classification of differentially expressed genes up- (A) or down- (B) regulated by 1d water stress, and up- (C) or down- (D) regulated by 7d stress
Figure 2
Functional classification of differentially expressed genes up- (A) or down- (B) regulated by 1d water stress, and up- (C) or down- (D) regulated by 7d stress

Signal-transduction-related genes induced by short-term stress

Among the 102 genes up-regulated by short-term water stress, approx. one-third of 56 annotated genes had functions involved in various signal transduction pathways (Table 2). It is noteworthy that the TM00044933, a gene encoding a putative PX (Phox homology)-domain-containing protein, showed an induction ratio of 13.24 by microarray hybridization experiments. A putative PH (pleckstrin homology)-domain-containing protein (TM00017922) was also significantly induced by short-term stress. PIs (phosphoinositides) are phosphorylated derivatives of PtdIns, which regulate many cellular and physiological processes. The PH domain mediates the action of PtdIns(3,4)P2, PtdIns(4,5)P2 and PtdIns(3,4,5)P3, whereas the PX domain is a structural domain capable of interacting with PIs, such as PtdIns(3)P and others [such as PtdIns(3,4)P2, PtdIns(3,5)P2 and PtdIns(4,5)P3] [1315]. The PX-domain-containing proteins involved in cell signalling include PI3Ks (PI 3-kinases), CISK (cytokine-independent survival kinase) and the FISH (containing five Src homology 3 domains) adaptor protein [16]. The PH domain has been found to be present in a multitude of proteins involved in cellular signalling, such as PKB (protein kinase B), PDK1 (PI-dependent kinase 1) and BTK (Bruton's tyrosine kinase) [17,18]. The up-regulated expression of the PX-domain-containing protein and PH-domain-containing protein may indicate that the PI signalling pathway plays an important role in early responses of maize to water stress.

Table 2
Signal-transduction-related genes induced by short-term stress

A ratio for stressed/control of ≤0.5 or ≥2 is considered as a differential change. The sequence information for the TIGR ID is available from the Maize Oligonucleotide Array Project. The top hit is the GenBank® accession number for the top match in the non-redundant amino acid database.

TIGR IDTop hitAnnotationStressed/control ratio
TM00044933 BAB10207 PX-domain-containing protein (Arabidopsis thaliana13.24 
TM00017922 ABF96033 PH-domain-containing protein-like (Oryza sativa2.64 
TM00001754 BAD61465 Putative receptor serine/threonine kinase PR5K (O. sativa2.86 
TM00010454 BAD07521 Putative serine/threonine protein kinase Mak (O. sativa3.84 
TM00012680 BAD28646 Putative CBL-interacting protein kinase (O. sativa2.62 
TM00013901 ABA95233 Auxin-repressed protein-like protein ARP1 (O. sativa3.12 
TM00019036 AAT39223 Putative protein phosphatase 2C (O. sativa3.38 
TM00023073 AAS98512 Putative protein kinase (O. sativa3.04 
TM00023449 AAY41186 Coronatine-insensitive 1 (O. sativa2.32 
TM00024368 BAD07891 Putative serine/threonine protein kinase Mak (O. sativa4.15 
TM00024369 BAD07520 Putative serine/threonine protein kinase Mak (O. sativa2.86 
TM00024495 CAB40376 Adenosine kinase (Zea mays2.53 
TM00025065 BAA19553 Protein cdc2 kinase (O. sativa3.18 
TM00025250 AAP52712 RING zinc-finger protein (O. sativa7.24 
TM00026517 AAR87222 Putative gibberellin-regulated protein (O. sativa5.38 
TM00028000 AAT44303 Putative protein phosphatase 2C ABI2 (O. sativa2.83 
TM00043924 AAK82535 VirB2-interacting protein (A. thaliana3.88 
TM00056066 AAS76635 Auxin-repressed protein-like protein (Nicotiana tabacum2.87 
TIGR IDTop hitAnnotationStressed/control ratio
TM00044933 BAB10207 PX-domain-containing protein (Arabidopsis thaliana13.24 
TM00017922 ABF96033 PH-domain-containing protein-like (Oryza sativa2.64 
TM00001754 BAD61465 Putative receptor serine/threonine kinase PR5K (O. sativa2.86 
TM00010454 BAD07521 Putative serine/threonine protein kinase Mak (O. sativa3.84 
TM00012680 BAD28646 Putative CBL-interacting protein kinase (O. sativa2.62 
TM00013901 ABA95233 Auxin-repressed protein-like protein ARP1 (O. sativa3.12 
TM00019036 AAT39223 Putative protein phosphatase 2C (O. sativa3.38 
TM00023073 AAS98512 Putative protein kinase (O. sativa3.04 
TM00023449 AAY41186 Coronatine-insensitive 1 (O. sativa2.32 
TM00024368 BAD07891 Putative serine/threonine protein kinase Mak (O. sativa4.15 
TM00024369 BAD07520 Putative serine/threonine protein kinase Mak (O. sativa2.86 
TM00024495 CAB40376 Adenosine kinase (Zea mays2.53 
TM00025065 BAA19553 Protein cdc2 kinase (O. sativa3.18 
TM00025250 AAP52712 RING zinc-finger protein (O. sativa7.24 
TM00026517 AAR87222 Putative gibberellin-regulated protein (O. sativa5.38 
TM00028000 AAT44303 Putative protein phosphatase 2C ABI2 (O. sativa2.83 
TM00043924 AAK82535 VirB2-interacting protein (A. thaliana3.88 
TM00056066 AAS76635 Auxin-repressed protein-like protein (Nicotiana tabacum2.87 

Osmolyte-metabolism-related genes responded to long-term stress

The osmolyte-metabolism-related genes responding to long-term water stress in maize leaves are listed in Table 3. The genes encoding P5CS (Δ1-pyrroline-5-carboxylate synthetase) and P5CR (Δ1-pyrroline 5-carboxylate reductase) were induced, and a putative ProDH (proline dehydrogenase) gene was repressed in leaves following long-term water stress. In plants, as well as in all eukaryotes, proline is synthesized from glutamate and ornithine, and the glutamate pathway is predominant in plants subjected to water shortage and nitrogen starvation [19]. Proline is synthesized from glutamate via P5C (Δ1-pyrroline-S-carboxylate) by two successive reductions, which are catalysed by P5CS and P5CR. ProDH is a mitochondrial enzyme involved in the first step of the conversion of proline back into glutamate (Figure 3A). The accumulation of proline in dehydrated plants is caused both by the activation of the biosynthesis of proline and by the inactivation of the degradation of proline [20]. Many studies have demonstrated that the manipulation of genes involved in the biosynthesis of low-molecular-mass metabolites, such as proline, improves tolerance to drought and salinity in a number of crops [21,22].

Table 3
Long-term stress-responsive genes involved in proline, sucrose, trehalose and raffinose metabolism pathways according to the KEGG pathway database (http://www.genome.jp/kegg/pathway.html)

A ratio for stressed/control of ≤0.5 or ≥2 is considered as a differential change. The sequence information for the TIGR ID is available from the Maize Oligonucleotide Array Project. The top hit is the GenBank® accession number for the top match in the non-redundant amino acid database. The data for tassel and ear are from a previous study [36]. Inv, invertase.

Stressed/control ratio
TIGR IDTop hitAnnotationLeafTasselEar
Proline metabolism      
 TM00025596 BAB64280 Putative P5CS (Oryza sativa8.79 0.43 1.91 
 TM00024573 AAY45745 P5CR (Zea mays2.36 1.34 1.34 
 TM00027872 ABB47966 ProDH (O. sativa0.30 1.42 0.57 
Sucrose metabolism      
 TM00003743 AAA68209 Sus1 (Z. mays0.39 0.23 0.49 
 TM00013609 AAA33515 Sus2 (Z. mays0.19 0.19 0.40 
 TM00026383 AAM89473 Sus3 (Z. mays3.66 7.86 8.57 
 TM00035504 BAA88904 Putative sucrose synthase (Citrus unshiu3.75 4.90 8.57 
 TM00037218 AAL27096 Putative sucrose synthase (Z. mays3.69 5.68 8.80 
 TM00026347 AAP59436 Soluble acid invertase (Saccharum hybrid cultivar) 3.13 1.71 0.42 
 TM00002884 BAD54740 Putative neutral Inv (O. sativa0.23 1.70 0.85 
 TM00026418 AAV28810 Neutral/alkaline Inv2 (O. sativa0.22 3.40 0.99 
 TM00046703 AAO25633 Putative neutral Inv (O. sativa0.42 0.99 1.06 
Trehalose metabolism      
 TM00024468 BAB56048 Putative TPS homologue (O. sativa0.45 1.32 1.19 
 TM00012094 AAT78804 Putative TPP (O. sativa0.38 0.91 1.01 
 TM00046962 BAD25928 Putative trehalose-phosphatase B (O. sativa0.49 0.72 0.61 
 TM00002153 AAP54665 Putative trehalase (O. sativa2.47 2.09 4.29 
Raffinose metabolism      
 TM00041665 AAP68981 UDP-glucose-4-epimerase (Z. mays2.03 4.35 1.00 
 TM00026736 AAO48782 Galactinol synthase 3 (Z. mays2.31 3.88 1.10 
 TM00037414 CAB77245 Putative raffinose synthase (O. sativa5.83 4.61 2.01 
 TM00028501 AAP53373 Putative INPS (O. sativa2.23 3.78 0.74 
Stressed/control ratio
TIGR IDTop hitAnnotationLeafTasselEar
Proline metabolism      
 TM00025596 BAB64280 Putative P5CS (Oryza sativa8.79 0.43 1.91 
 TM00024573 AAY45745 P5CR (Zea mays2.36 1.34 1.34 
 TM00027872 ABB47966 ProDH (O. sativa0.30 1.42 0.57 
Sucrose metabolism      
 TM00003743 AAA68209 Sus1 (Z. mays0.39 0.23 0.49 
 TM00013609 AAA33515 Sus2 (Z. mays0.19 0.19 0.40 
 TM00026383 AAM89473 Sus3 (Z. mays3.66 7.86 8.57 
 TM00035504 BAA88904 Putative sucrose synthase (Citrus unshiu3.75 4.90 8.57 
 TM00037218 AAL27096 Putative sucrose synthase (Z. mays3.69 5.68 8.80 
 TM00026347 AAP59436 Soluble acid invertase (Saccharum hybrid cultivar) 3.13 1.71 0.42 
 TM00002884 BAD54740 Putative neutral Inv (O. sativa0.23 1.70 0.85 
 TM00026418 AAV28810 Neutral/alkaline Inv2 (O. sativa0.22 3.40 0.99 
 TM00046703 AAO25633 Putative neutral Inv (O. sativa0.42 0.99 1.06 
Trehalose metabolism      
 TM00024468 BAB56048 Putative TPS homologue (O. sativa0.45 1.32 1.19 
 TM00012094 AAT78804 Putative TPP (O. sativa0.38 0.91 1.01 
 TM00046962 BAD25928 Putative trehalose-phosphatase B (O. sativa0.49 0.72 0.61 
 TM00002153 AAP54665 Putative trehalase (O. sativa2.47 2.09 4.29 
Raffinose metabolism      
 TM00041665 AAP68981 UDP-glucose-4-epimerase (Z. mays2.03 4.35 1.00 
 TM00026736 AAO48782 Galactinol synthase 3 (Z. mays2.31 3.88 1.10 
 TM00037414 CAB77245 Putative raffinose synthase (O. sativa5.83 4.61 2.01 
 TM00028501 AAP53373 Putative INPS (O. sativa2.23 3.78 0.74 

Modulation of genes encoding enzymes involved in proline (A), and sucrose, trehalose and raffinose (B) metabolism by water stress

Figure 3
Modulation of genes encoding enzymes involved in proline (A), and sucrose, trehalose and raffinose (B) metabolism by water stress

Genes differentially modulated by water stress are shown in italics. The biochemical and physiological pathways were classified according to the KEGG database (http://www.genome.jp/kegg/). P5CDH, Δ1-pyrroline-5-carboxylate dehydrogenase; Inv, invertase; UGE, UDP-glucose-4-epimerase; GolS3, galactinol synthase 3; RafS, raffinose synthase; IMPA, inositol monophosphatase.

Figure 3
Modulation of genes encoding enzymes involved in proline (A), and sucrose, trehalose and raffinose (B) metabolism by water stress

Genes differentially modulated by water stress are shown in italics. The biochemical and physiological pathways were classified according to the KEGG database (http://www.genome.jp/kegg/). P5CDH, Δ1-pyrroline-5-carboxylate dehydrogenase; Inv, invertase; UGE, UDP-glucose-4-epimerase; GolS3, galactinol synthase 3; RafS, raffinose synthase; IMPA, inositol monophosphatase.

Interestingly, we found that expression of Sus3 (sucrose synthase 3) was up-regulated in maize exposed to 7d stress, whereas Sus1 and Sus2 were down-regulated (Table 3). It is well known that sucrose metabolism is involved in responses to environmental stresses in many plant species. Sucrose cannot be used directly for metabolic processes, but must be cleaved into hexoses before entering into the carbohydrate metabolism pathway. The only known enzymatic pathway of sucrose cleavage in plants is catalysed by invertases (yielding glucose and fructose) and sucrose synthases (yielding fructose and UDP-glucose) (Figure 3B). The different members of the maize Sus family of enzymes showed different expression patterns in the present study. An analysis of their sequence information showed that Sus3 is more similar to dicot SuSy than to Sus1 and Sus2 of maize, and it is possible that maize Sus3 represents the ancestral form of SuSy (sucrose synthase) [23]. In addition to the up-regulation of Sus3, a soluble acid invertase gene was also induced, whereas three neutral/alkaline invertase genes were repressed by water stress in leaves (Table 3). Acid invertases are also called β-fructofuranosidases, because they hydrolyse sucrose and other β-fructose-containing oligosaccharides [24]. Unlike acid invertase, neutral/alkaline invertases appear to be sucrose-specific [25]. The sequences of neutral/alkaline invertases are different from acid invertase, and have been found only in photosynthetic bacteria and plants. Neutral/alkaline invertases are mostly accumulated in the cytoplasm, but their function is still largely unknown. In our present study, neutral/alkaline invertases were down-regulated under water-deficit stress in leaves (Tables 1 and 3), and some of them were shown to be repressed rapidly under water-deficit stress, and then were maintained in the repression situation. The finding was similar to previous reports that, under low-oxygen and cold-stress conditions, a shift from invertase to sucrose synthase occurs during low-oxygen adjustment and cold acclimation [26,27]. The repressed neutral/alkaline invertases may cause more sucrose to enter the sucrose synthase reaction, facilitating the direct supply for the rapid abiotic stress-induced biosynthesis of compatible polysaccharides in maize leaves.

Several genes encoding key enzymes functioning in raffinose metabolism were up-regulated by water stress in maize leaves (Table 3 and Figure 3B), including UGE (UDP-glucose-4-epimerase), GolS3 (galactinol synthase 3) and RafS (raffinose synthase). A INPS (myo-inositol-1-phosphate synthase) gene was also up-regulated by stress. In contrast, both a putative TPS (trehalose-6-phosphate synthase) gene and a putative TPP (trehalose phosphatase) gene for the biosynthesis of trehalose were significantly down-regulated in leaves under water-deficit conditions. However, a putative trehalase gene involved in the trehalose degradative pathway was up-regulated by the stress (Table 3).

RFO sugars, such as raffinose and galactinol, play important roles during maize seed development and maturation [28]. Overexpression of drought-inducible galactinol synthase genes in transgenic Arabidopsis plants enhanced drought tolerance, because of the accumulation of galactinol and raffinose [29]. In addition to galactinol synthase, INPS is another enzyme that may control the levels of galactinol and raffinose. INPS diverts carbon from glucose-6-phosphate into myo-inositol-1-phosphate, and myo-inositol-1-phosphate is then used to produce myo-inositol, the precursor of galactinol. Antisense INPS transformants have greatly reduced levels of myo-inositol, galactinol and raffinose in potato leaves [30]. Transgenic plants that overexpress DREB1A/CBF3 (dehydration response element B1A/C-repeat binding factor 3) are tolerant of drought and cold stress, and accumulate more galactinol and raffinose than wild-type plants [31,32]. In our present study, several key genes involved in the raffinose biosynthetic pathway were notably up-regulated in maize leaves under water-deficit stress (Table 3 and Figure 3B). These findings suggested that galactinol and raffinose may play an important role as osmoprotectants in leaves under water stress. Trehalose is a disaccharide comprising two molecules of glucose. The best-known and most widely distributed pathway of trehalose biosynthesis is a two-step process, consisting of the conversion of UDP-glucose and glucose-6-phosphate into trehalose-6-phosphate by TPS and, subsequently, dephosphorylation by TPP [33]. Functions of trehalose as a stress protectant or compatible solute have been described in many organisms [34]. However, it is unlikely that trehalose in higher plants has these functions, because of its low abundance [35]. In the present study, TPS and TPP were down-regulated, whereas trehalase, which broke down trehalose to glucose, was up-regulated by water stress. As a result it is unlikely that trehalose acts as an osmoprotectant in maize leaves under drought conditions.

Recently, we have monitored gene expression changes in the developing immature tassels and ears after 7d water-deficit stress using the maize whole-genome oligonucleotide microarray [36]. In this study, the same microarray was used to identify the gene expression profile in maize leaves under water stress. We are interested in comparing the expression changes of genes, particularly the genes involved in compatible osmolyte metabolism in leaves and the productive organs under long-term water stress. The osmolyte-metabolism-related genes that are expressed differentially in leaves, tassels and ears are shown in Table 3. The results show that proline-metabolism-related genes represented different expression patterns in maize leaves and the productive organs. In leaves, both P5CS and P5CR were up-regulated and ProDH was down-regulated at a significant level by water stress. In ears, expression of P5CS was induced, and proDH was repressed, but the transcription level of both genes changed less than 2-fold. However, P5CS was down-regulated in tassels under water-deficit treatment. These differences showed that proline plays a role as an osmoprotectant in vegetative organs, but is not so important in productive organs under water-deficit conditions. A group of genes involved in the raffinose synthesis pathway were up-regulated both in leaves and in tassels, suggesting that raffinose may play an important role as osmoprotectants in these organs during water stress. It should be noted that expression of Sus3 was up-regulated, whereas maize Sus1 and Sus2 were down-regulated in leaves, tassels and ears by water stress. The result showed that sucrose metabolism in different organs may give the same response to stress as when plants encounter water stress.

The previous studies by Zheng et al. [6] and Jia et al. [7] focused on maize vegetative organs for expression profiling under water-stress conditions. The present study used maize leaves to monitor the transcriptome changes induced by water stress, therefore we were interested in comparing our work with the two previous studies [6,7] to examine any consensus responses to water stress from these investigations. In our present work and previous studies [6,7], a number of genes were identified as being up-regulated by water-deficit treatment, but only a small part of them were common. This may be attributed to the differences in plant growth conditions and the age of sampling, degrees of stress treatment, maize genotypes and experimental methods. The products of common stress-inducible genes include carbohydrate-metabolism-related proteins, detoxification enzymes, lipid-transfer proteins, ribosomal proteins, signal transduction and transcription factors (Table 4). Carbohydrates are necessary in living cells not only as the source of carbon and energy, but also as osmotic agents during plant stress responses [37]. Detoxification enzymes, such as glutathione transferase, are thought to be involved in protecting cells from active oxygen radicals. Lipid-transfer proteins may have a function in repairing stress-induced damage of membranes or changes in the lipid composition of membranes, perhaps to regulate the permeability to toxic ions and the fluidity of the membrane [38,39]. Ribosomal proteins stabilize the structure of ribosomes and are involved in controlling protein synthesis. Altered relative abundance of ribosomal proteins may lead to enhance translational efficiency in water-stressed plants. Signal transduction and transcription factors involved in regulating gene expression probably function in stress responses, such as CBL-interacting protein kinase 16, 14-3-3-like protein, putative WD-40 repeat protein, C2-domain-containing protein and RING-H2 zinc-finger protein.

Table 4
Genes with similar functions or names are commonly up-regulated in maize under water-deficit conditions in the present and previous [6,7] studies

GST, glutathione transferase.

Previous studies
Protein categoryPresent study[6][7]
Carbohydrate metabolism Putative alcohol dehydrogenase (TIGR ID TM00017814) Alcohol dehydrogenase 1 (Adh1) Cinnamyl alcohol dehydrogenase 
 Allyl alcohol dehydrogenase (TM00029691) Alcohol dehydrogenase 2-N – 
 INPS (TM00028501) INPS  
 Ribulose-phosphate 3-epimerase (TM00057320) – D-Ribulose-5-phosphate 3-epimerase 
Detoxification enzyme GST 29 protein (TM00040653) GST7 protein GST7 protein 
 Putative GST (TM00015070) – – 
Lipid-transfer protein Non-specific lipid-transfer protein 2 precursor (TM00040001) – Non-specific lipid-transfer protein B precursor 
 Putative lipid-transfer protein (TM00023565) – – 
Proline-rich protein Proline-rich protein (TM00036403) – Proline-rich protein (APG-like) 
Nucleic-acid-binding protein Nucleic-acid-binding protein (TM00036079) Nucleic-acid-binding protein – 
RNA-binding protein Putative RNA-binding protein (TM00043485) Putative RNA-binding protein – 
Protein synthesis 60S Ribosomal protein L11 (TM00025791) 60S Ribosomal protein L11A 60S Ribosomal protein L12 
 60S Ribosomal protein L7a (TM00024710) 60 Ribosomal protein-like 60S Ribosomal protein L13a-4 
 60S Ribosomal protein L30 (TM00025536) Ribosomal S15 protein 60S Ribosomal protein L27a-3 
 60S Ribosomal protein L39 (TM00039655) Ribosomal protein L5 50S Ribosomal protein L32 
 40S Ribosomal protein s24 (TM00041842) Ribosomal protein S29-like 60S Ribosomal protein L36 
 – – Ribosomal protein L7Ae-like 
 – – 40S Ribosomal protein s10-b 
 – – 40S Ribosomal protein s15a 
 – – 40S Ribosomal protein s6 
Signal transduction CBL-interacting protein kinase 16 (TM00022188) CBL-interacting protein kinase 16 – 
 14-3-3-like protein (TM00036703) – 14-3-3-like protein GF14 ω 
 14-3-3-like protein (TM00013540) – – 
Transcription factor Putative WD-40 repeat protein (TM00043520) Putative WD-40 repeat protein – 
 C2-domain-containing protein-like (TM00057330) – C2-domain-containing protein-like 
 RING-H2 zinc-finger protein (TM00020240) – RING-H2 zinc-finger protein 
 Putative RING-H2 zinc-finger protein (TM00002756) – – 
Previous studies
Protein categoryPresent study[6][7]
Carbohydrate metabolism Putative alcohol dehydrogenase (TIGR ID TM00017814) Alcohol dehydrogenase 1 (Adh1) Cinnamyl alcohol dehydrogenase 
 Allyl alcohol dehydrogenase (TM00029691) Alcohol dehydrogenase 2-N – 
 INPS (TM00028501) INPS  
 Ribulose-phosphate 3-epimerase (TM00057320) – D-Ribulose-5-phosphate 3-epimerase 
Detoxification enzyme GST 29 protein (TM00040653) GST7 protein GST7 protein 
 Putative GST (TM00015070) – – 
Lipid-transfer protein Non-specific lipid-transfer protein 2 precursor (TM00040001) – Non-specific lipid-transfer protein B precursor 
 Putative lipid-transfer protein (TM00023565) – – 
Proline-rich protein Proline-rich protein (TM00036403) – Proline-rich protein (APG-like) 
Nucleic-acid-binding protein Nucleic-acid-binding protein (TM00036079) Nucleic-acid-binding protein – 
RNA-binding protein Putative RNA-binding protein (TM00043485) Putative RNA-binding protein – 
Protein synthesis 60S Ribosomal protein L11 (TM00025791) 60S Ribosomal protein L11A 60S Ribosomal protein L12 
 60S Ribosomal protein L7a (TM00024710) 60 Ribosomal protein-like 60S Ribosomal protein L13a-4 
 60S Ribosomal protein L30 (TM00025536) Ribosomal S15 protein 60S Ribosomal protein L27a-3 
 60S Ribosomal protein L39 (TM00039655) Ribosomal protein L5 50S Ribosomal protein L32 
 40S Ribosomal protein s24 (TM00041842) Ribosomal protein S29-like 60S Ribosomal protein L36 
 – – Ribosomal protein L7Ae-like 
 – – 40S Ribosomal protein s10-b 
 – – 40S Ribosomal protein s15a 
 – – 40S Ribosomal protein s6 
Signal transduction CBL-interacting protein kinase 16 (TM00022188) CBL-interacting protein kinase 16 – 
 14-3-3-like protein (TM00036703) – 14-3-3-like protein GF14 ω 
 14-3-3-like protein (TM00013540) – – 
Transcription factor Putative WD-40 repeat protein (TM00043520) Putative WD-40 repeat protein – 
 C2-domain-containing protein-like (TM00057330) – C2-domain-containing protein-like 
 RING-H2 zinc-finger protein (TM00020240) – RING-H2 zinc-finger protein 
 Putative RING-H2 zinc-finger protein (TM00002756) – – 

In conclusion, we have identified hundreds of water-deficit stress responsive genes in maize leaves at the heading stage. The products of these genes are not only involved in stress tolerance, but also in the regulation of gene expression and signal transduction in the stress response. Investigating the function of these genes may contribute to the understanding of the molecular mechanisms of stress tolerance and the responses of higher plants, as well as improving the stress tolerance of crops by gene manipulation. Although the functions of many identified genes remain unknown, overexpression and RNA interference studies may be useful for determining the putative functions in the future. The information obtained in the present study will help the development of approaches to manipulate the genes to improve tolerance and yield of maize plants.

Abbreviations

     
  • d

    day

  •  
  • INPS

    myo-inositol-1-phosphate synthase

  •  
  • P5CR

    Δ1-pyrroline 5-carboxylate reductase

  •  
  • P5CS

    Δ1-pyrroline-5-carboxylate synthetase

  •  
  • PH

    pleckstrin homology

  •  
  • PI

    phosphoinositide

  •  
  • ProDH

    proline dehydrogenase

  •  
  • PX

    Phox homology

  •  
  • RFO

    raffinose family oligosaccharide

  •  
  • RT

    reverse transcriptase

  •  
  • Sus

    sucrose synthase

  •  
  • TPP

    trehalose phosphatase

  •  
  • TPS

    trehalose-6-phosphate synthase

We thank Dr Dapeng Zhang (Department of Biology, University of Ottawa, Ottawa, ON, Canada) for his critical reading of the manuscript. This work was supported by the National High Technology Research and Development Program of China (863 Program; no. 2007AA10Z175) and the Natural Science Foundation of China (no. 30771127).

References

References
Grant
 
R. F.
Jackson
 
B. S.
Kiniry
 
J. R.
Arkin
 
G. F.
 
Water deficit timing effects on yield components in maize
Agron. J.
1989
, vol. 
81
 (pg. 
61
-
65
)
Seki
 
M.
Umezawa
 
T.
Urano
 
K.
Shinozaki
 
K.
 
Regulatory metabolic networks in drought stress responses
Curr. Opin. Plant Biol.
2007
, vol. 
10
 (pg. 
296
-
302
)
Xiong
 
L.
Schumaker
 
K. S.
Zhu
 
J. K.
 
Cell signal during cold, drought, and salt stress
Plant Cell
2002
, vol. 
14
 (pg. 
S165
-
S183
)
Zinselmeier
 
C.
Sun
 
Y.
Helentjaris
 
T.
Beatty
 
M.
Yang
 
S.
Smith
 
H.
Habben
 
J.
 
The use of gene expression profiling to dissect the stress sensitivity of reproductive development in maize
Field Crops Res.
2002
, vol. 
75
 (pg. 
111
-
121
)
Yu
 
L. X.
Setter
 
T. L.
 
Comparative transcriptional profiling of placenta and endosperm in developing maize kernels in response to water deficit
Plant Physiol.
2003
, vol. 
131
 (pg. 
568
-
582
)
Zheng
 
J.
Zhao
 
J. F.
Tao
 
Y. Z.
Wang
 
J. H.
Liu
 
Y. J.
Fu
 
J. J.
Jin
 
Y.
Gao
 
P.
Zhang
 
J. P.
Bai
 
Y. F.
Wang
 
G. Y.
 
Isolation and analysis of water stress induced genes in maize seedlings by subtractive PCR and cDNA macroarray
Plant Mol. Biol.
2004
, vol. 
55
 (pg. 
807
-
823
)
Jia
 
J. P.
Fu
 
J. J.
Zheng
 
J.
Zhou
 
X.
Huai
 
J. L.
Wang
 
J. H.
Wang
 
M.
Zhang
 
Y.
Chen
 
X. P.
Zhang
 
J. P.
, et al 
Annotation and expression profile analysis of 2073 full-length cDNAs from stress-induced maize (Zea mays L) seedlings
Plant J.
2006
, vol. 
48
 (pg. 
710
-
727
)
Andjelkovic
 
V.
Thompson
 
R.
 
Changes in gene expression in maize kernel in response to water and salt stress
Plant Cell Rep.
2006
, vol. 
25
 (pg. 
71
-
79
)
Betran
 
F. J.
Beck
 
D.
Banziger
 
M.
Edmeades
 
G. O.
 
Genetic analysis of inbred and hybrid grain yield under stress and nonstress environments in tropical maize
Crop Sci.
2003
, vol. 
43
 (pg. 
807
-
817
)
McCarty
 
D. R.
 
A simple method for extraction of RNA from maize tissues
Maize Genet. Coop. News Lett.
1986
, vol. 
60
 pg. 
61
 
Garcion
 
C.
Applimath
 
F. R. I.
Metraux
 
J. P.
 
FiRe and microarray: a fast answer to burning questions
Trends Plant Sci.
2006
, vol. 
11
 (pg. 
320
-
322
)
Huang
 
X.
Madan
 
A.
 
CAP3: a DNA sequence assembly program
Genome Res.
1999
, vol. 
9
 (pg. 
868
-
877
)
12a
Livak
 
K. J.
Schmittgen
 
T. D.
 
Analysis of relative gene expression data using real-time quantitative PCR and the 2−ΔΔCT method
Methods
2001
, vol. 
25
 (pg. 
402
-
408
)
Dowler
 
S.
Currie
 
R. A.
Campbell
 
D. G.
Deak
 
M.
Kular
 
G.
Downes
 
C. P.
Alessi
 
D. R.
 
Identification of pleckstrin-homology-domain-containing proteins with novel phosphoinositide-binding specificities
Biochem. J.
2000
, vol. 
351
 (pg. 
19
-
31
)
Song
 
X.
Xu
 
W.
Zhang
 
A.
Huang
 
G.
Liang
 
X.
Virbasius
 
J. V.
Czech
 
M. P.
Zhou
 
G. W.
 
Phox homology domains specifically bind phosphatidylinositol phosphates
Biochemistry
2001
, vol. 
40
 (pg. 
8940
-
8944
)
Yu
 
J. W.
Lemmon
 
M. A.
 
All phox homology (PX) domains from Saccharomyces cerevisiae specifically recognize phosphatidylinositol 3-phosphate
J. Biol. Chem.
2001
, vol. 
276
 (pg. 
44179
-
44184
)
Seet
 
L. F.
Hong
 
W. J.
 
The Phox (PX) domain proteins and membrane traffic
Biochim. Biophys. Acta 1761
2006
(pg. 
878
-
896
)
Lemmon
 
M. A.
Ferguson
 
K. M.
 
Signal-dependent membrane targeting by pleckstrin homology (PH) domains
Biochem. J.
2000
, vol. 
350
 (pg. 
1
-
18
)
Vanhaesebroeck
 
B.
Leevers
 
S. J.
Khatereh
 
A.
Timms
 
J.
Katso
 
R.
Driscoll
 
P. C.
Woscholski
 
R.
Parker
 
P. J.
Waterfield
 
M. D.
 
Synthesis and function of 3-phosphorylated inositol lipids
Annu. Rev. Biochem.
2001
, vol. 
70
 (pg. 
535
-
602
)
Delauney
 
A. J.
Verma
 
D. P. S.
 
Proline biosynthesis and osmoregulation in plants
Plant J.
1993
, vol. 
4
 (pg. 
215
-
223
)
Kiyosue
 
T.
Yoshiba
 
Y.
Yamaguchi-Shinozaki
 
K.
Shinozaki
 
K.
 
A nuclear gene encoding mitochondrial proline dehydrogenase, an enzyme involved in proline metabolism, is upregulated by proline but downregulated by dehydration in Arabidopsis
Plant Cell
1996
, vol. 
8
 (pg. 
1323
-
1335
)
Molinari
 
H. B. C.
Marur
 
C. J.
Bespalhok
 
J. C.
Kobayashi
 
A. K.
Pileggi
 
M.
Leite
 
R. P.
Pereira
 
L. F. P.
Vieira
 
L. G. E.
 
Osmotic adjustment in transgenic citrus rootstock Carrizo citrange (Citrus sinensis Osb×Poncirus trifoliate L. Raf) overproducing proline
Plant Sci.
2004
, vol. 
167
 (pg. 
1375
-
1381
)
Vendruscolo
 
E. C. G.
Schuster
 
I.
Pileggi
 
M.
Scapim
 
C. A.
Molinari
 
H. B. C.
Marur
 
C. J.
Vieira
 
L. G. E.
 
Stress-induced synthesis of proline confers tolerance to water deficit in transgenic wheat
J. Plant Physiol.
2007
, vol. 
164
 (pg. 
1367
-
1376
)
Carlson
 
S. J.
Chourey
 
P. S.
Helentjaris
 
T.
Datta
 
R.
 
Gene expression studies on developing kernels of maize sucrose synthase (SuSy) mutants show evidence for a third SuSy gene
Plant Mol. Biol.
2002
, vol. 
49
 (pg. 
15
-
29
)
Sturm
 
A.
 
Invertases. Primary structures, functions, and roles in plant development and sucrose partitioning
Plant Physiol.
1999
, vol. 
121
 (pg. 
1
-
7
)
Vargas
 
W.
Cumino
 
A.
Salerno
 
G. L.
 
Cyanobacterial alkaline/neutral invertases. Origin of sucrose hydrolysis in the plant cytosol?
Planta
2003
, vol. 
216
 (pg. 
951
-
960
)
Zeng
 
Y.
Wu
 
Y.
Avigne
 
W. T.
Koch
 
K. E.
 
Rapid repression of maize invertases by low oxygen. Invertase/sucrose synthase balance, sugar signaling potential, and seedling survival
Plant Physiol.
1999
, vol. 
121
 (pg. 
599
-
608
)
Hannah
 
M. A.
Heyer
 
A. G.
Hincha
 
D. K.
 
A global survey of gene regulation during cold acclimation in Arabidopsis thaliana
PLoS Genet.
2005
, vol. 
1
 (pg. 
179
-
196
)
Brenac
 
P.
Horbowicz
 
M.
Downer
 
S. M.
Dickerman
 
A. M.
Smith
 
M. E.
Obendorf
 
R. L.
 
Raffinose accumulation related to desiccation tolerance during maize (Zea mays L) seed development and maturation
J. Plant Physiol.
1997
, vol. 
150
 (pg. 
481
-
488
)
Taji
 
T.
Ohsumi
 
C.
Iuchi
 
S.
Seki
 
M.
Kasuga
 
M.
Kobayashi
 
M.
Yamaguchi-Shinozaki
 
K.
Shinozaki
 
K.
 
Important roles of drought- and cold-inducible genes for galactinol synthase in stress tolerance in Arabidopsis thaliana
Plant J.
2002
, vol. 
29
 (pg. 
417
-
426
)
Keller
 
R.
Brearley
 
C. A.
Trethewey
 
R. N.
Muller-Rober
 
B.
 
Reduced inositol content and altered morphology in transgenic potato plants inhibited for 1D-myo-inositol 3-phosphate synthase
Plant J.
1998
, vol. 
16
 (pg. 
403
-
410
)
Avonce
 
N.
Leyman
 
B.
Mascorro-Gallardo
 
J. O.
Van Dijck
 
P.
Thevelein
 
J. M.
Iturriaga
 
G.
 
The Arabidopsis trehalose-6-P synthase AtTPS1 gene is a regulator of glucose, abscisic acid, and stress signaling
Plant Physiol.
2004
, vol. 
136
 (pg. 
3649
-
3659
)
Valliyodan
 
B.
Nguyen
 
H. T.
 
Understanding regulatory networks and engineering for enhanced drought tolerance in plants
Curr. Opin. Plant Biol.
2006
, vol. 
9
 (pg. 
189
-
195
)
Goddijn
 
O. J. M.
van Dun
 
K.
 
Trehalose metabolism in plants
Trends Plant Sci.
1999
, vol. 
4
 (pg. 
315
-
319
)
Elbein
 
A. D.
Pan
 
Y. T.
Pastuszak
 
I.
Carroll
 
D.
 
New insights on trehalose: a multifunctional molecule
Glycobiology
2003
, vol. 
13
 (pg. 
17
-
27
)
Grennan
 
A. K.
 
The role of trehalose biosynthesis in plants
Plant Physiol.
2007
, vol. 
144
 (pg. 
3
-
5
)
Zhuang
 
Y. L.
Ren
 
G. J.
Yue
 
G. D.
Li
 
Z. X.
Qu
 
X.
Hou
 
G. H.
Zhu
 
Y.
Zhang
 
J. R.
 
Effects of water-deficit stress on the transcriptomes of developing immature ear and tassel in maize
Plant Cell Rep.
2007
, vol. 
26
 (pg. 
2137
-
2147
)
Cushman
 
J. C.
Bohnert
 
H. J.
 
Genomic approaches to plant stress tolerance
Curr. Opin. Plant Biol.
2000
, vol. 
3
 (pg. 
117
-
124
)
Torres-Schumann
 
S.
Godoy
 
J. A.
Pintor-Toro
 
J. A.
 
A probable lipid transfer protein gene is induced by NaCl in stems of tomato plants
Plant Mol. Biol.
1992
, vol. 
18
 (pg. 
749
-
757
)
Holmberg
 
N.
Bülow
 
L.
 
Improving stress tolerance in plants by gene transfer
Trends Plant Sci.
1998
, vol. 
3
 (pg. 
61
-
66
)

Author notes

1

These authors contributed equally to this work.

The expression data reported are available in the NCBI Gene Expression Omnibus (GEO) database under the GSE series accession number GSE10596.