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JXB Advance Access originally published online on August 9, 2006
Journal of Experimental Botany 2006 57(12):3109-3122; doi:10.1093/jxb/erl080
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© The Author [2006]. Published by Oxford University Press [on behalf of the Society for Experimental Biology]. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org

RESEARCH PAPER

Transcriptional profiling of sunflower plants growing under low temperatures reveals an extensive down-regulation of gene expression associated with chilling sensitivity

Tarek Hewezi1,2, Mathieu Léger1, Walid El Kayal3 and Laurent Gentzbittel1,*

1Laboratoire de Biotechnologies et Amélioration des Plantes, Ecole Nationale Supérieure Agronomique de Toulouse, Avenue de l'Agrobiopôle, BP 107, Auzeville Tolosane, F-31326 Castanet Tolosan, France
2National Research Center, Genetics and Cytology Department, Dokki, Cairo, Egypt
3Université Paul Sabatier: UMR 5546, ‘Surfaces Cellulaires et Signalisation chez les Végétaux’ Pôle de Biotechnologie Végétale, 24 Chemin de Borde Rouge, BP 42617 Auzeville, F-31326 Castanet-Tolosan, France

*To whom correspondence should be addressed. E-mail: gentz{at}ensat.fr

Received 21 March 2006; Accepted 6 June 2006


   Abstract
Top
 Abstract
Introduction
 Materials and methods
 Results and discussion
 Conclusion
 Supplementary data
 References
 
Being able to sow early to maximize the growing season and to escape drought stress has increased the importance of low-temperature tolerance in sunflower. Yet knowledge about the molecular basis of sunflower response to low temperature is still lacking. To address this issue, nylon microarrays containing >8000 putative unigenes were developed and used. Early- and late-flowering genotypes were sown at 15 °C and grown until the two-leaf stage when they were subjected to 7 °C until the four-leaf stage. The transcriptional profiles of low temperature-grown plants (15 °C and 7 °C) were compared with those grown under standard conditions (25 °C). Two-step ANOVA normalization and analysis models were used to identify the differentially expressed genes. A total of 108 cDNA clones having a P-value <10–3 were found to be differentially expressed between the low temperature-grown plants (15 °C and 7 °C) and their corresponding two-leaf- and four-leaf-stage controls across the two genotypes. About 90% of these genes were down-regulated. This includes genes potentially involved in the metabolism of carbohydrate and energy, protein synthesis, signal transduction, and transport function. Comparing gene expression profiles at 15 °C and 7 °C revealed that only four genes can be considered as differentially expressed, in both genotypes, suggesting that similar genetic programmes underlie the response of sunflower plants to these temperature regimes. The analysis also revealed that early- and late-flowering genotypes respond similarly to low-temperature tolerance as justified by the low number of genes showing a significant genotypextreatment interaction effect. It seems likely that the down-regulation and/or non-induction of genes having a critical role in low-temperature tolerance may be responsible for the sensitivity of sunflower plants to low-temperature tolerance. The results reported provide an initial characterization of the transcriptome activity of sunflower, as a chilling-sensitive plant under suboptimal temperatures, and could be of importance to reveal the potential differences between chilling-sensitive and chilling-tolerant species.

Key words: cDNA microarrays, chilling, global gene expression, Helianthus annuus L., low temperature


   Introduction
Top
 Abstract
 Introduction
Materials and methods
 Results and discussion
 Conclusion
 Supplementary data
 References
 
Chilling, which refers to low, but non-freezing temperatures, is one of the most important environmental factors affecting plant development and performance. Many tropical and subtropical plant species are considerably affected when exposed to low temperature during their life cycles. By contrast, it was found that many plants can increase their freezing tolerance after being exposed to a period of non-freezing temperatures, a phenomenon known as cold acclimation. Plants cope with low-temperature tolerance with a number of physiological and developmental changes. This includes, for example, reduction or cessation of plant growth, decreased water content and photosynthesis, and increased leaf thickness (Ristic and Ashworth, 1993; Uemura et al., 1995). Cellular responses to low temperature have been studied extensively at the molecular and biochemical levels in the model plant Arabidopsis thaliana and in a few other well-characterized plants. These responses include, for example, redistribution of calcium intracellular ion fluxes (Knight et al., 1996), changes in protein content (Marmiroli et al., 1986), and enzyme activity (Holaday et al., 1992). Significant induction of antioxidative enzymes such as catalase, ascorbate peroxidase, superoxide dismutase, and glutathione reductase were also observed after exposure to low temperatures (Xin and Browse, 2000). Alteration in membrane structure and lipid composition (Lyons and Raison, 1970), metabolic modifications (Trevanion et al., 1995), transient increases in abscisic acid (ABA) concentrations, accumulation of compatible osmolytes with cryoprotective properties (such as proline, betaine, polyols, and soluble sugars) have also been reported (Xin and Browse, 2000).

Extensive studies on plant response and acclimation to low temperatures have resulted in the cloning of many low temperatures-regulated genes from a variety of plant species and identification of their functional roles (Xin and Browse, 2000). These genes have been identified from different screenings, and have been given different terms such as COR for cold regulated, LTI for low-temperature induced, CAS for cold acclimation specific, and RD for responsive to desiccation (for a review see Xin and Browse, 2000; Browse and Xin, 2001). All of these groups are referred to as COR genes. Genetic and molecular dissection of COR genes has allowed the identification of pathways involved in low-temperature signalling. One of the well-studied pathways involves the rapid induction of CBF/DREB1 transcription factors which regulate the expression of COR genes by binding at the CRT (C-repeat)/DRE (dehydration-responsive element) domain (Shinozaki and Yamaguchi-Shinozaki, 2000; Thomashow, 2001). Components of the CBF cold-response pathway were found to be conserved in Brassica napus, wheat, and rye (Jaglo-Ottosen et al., 2001), which are all cold-acclimated plants, as well as in tomato (Jaglo-Ottosen et al., 2001; Zhang et al., 2004), a freezing-sensitive plant. The existence of multiple low-temperature regulatory pathways, in addition to the CBF cold-response pathway, has been supported by transcription profiling of about 8000 genes in transgenic Arabidopsis plants constitutively expressing the three members of the CBF family (Fowler and Thomashow, 2002). Microarray technology was successfully used to analyse gene expression patterns in response to biotic and abiotic stresses (Maleck et al., 2000; Fowler and Thomashow, 2002; Rabbani et al., 2003; Alignan et al., 2006). Recent expression profiling studies have revealed a large number of cold-regulated genes (Seki et al., 2001; Kreps et al., 2002; Lee and Lee, 2003). By contrast to the numerous studies describing global gene expression during cold acclimation and freezing tolerance, there are only a few examples describing the transcriptome profiles during acclimation to chilling temperatures (Provart et al., 2003). In all of these experiments, plants, at given developmental stages, were subjected to a period of low-temperature treatments ranging from 30 min to 1 week. However, much less is known about the cellular activities and signalling pathways during long-term acclimation to chilling temperatures.

Sunflower is one of the most important oil crops worldwide. Although it is adapted to a variety of environmental conditions (Beard and Geng, 1982), yield reduction was detected when normal spring sowing dates are delayed, or when plants are subjected to drought stress during the seed-filling period (Bange et al., 1998; de la Vega and Hall, 2002). It has been reported that growth of sunflower seedlings was inhibited to some degree when they were subjected to suboptimal temperatures (Bradlow, 1990). Thus, one of the central objectives of sunflower breeders is to maximize the duration of the growing season, thereby maximizing yields. An early sowing date could help sunflower plants avoid water-deficit stress which frequently takes place during the critical periods of plant development and seed filling. However, an early sowing date during early spring, which is characterized by a low and fluctuating temperature regime, has increased the importance of early-season low-temperature tolerance in sunflower. To address this issue, the sunflower's low-temperature tolerance must be known. To study changes in gene expression associated with two regimes of long-term low-temperature tolerance in sunflower plants, a cDNA microarray containing >8000 unigenes spotted onto nylon membrane was developed and used. Two genotypes were sown at 15 °C and grown until the one-pair-leaf stage when they were subjected to 7 °C until the two-pair-leaf stage. The transcriptome profiles of low temperature-grown seedlings (15 °C and 7 °C) were compared with those grown under standard conditions (25 °C). The objective was to identify stable low temperature-regulated genes that could be of practical importance in breeding programmes to develop early spring-grown sunflower genotypes.


   Materials and methods
Top
 Abstract
 Introduction
 Materials and methods
Results and discussion
 Conclusion
 Supplementary data
 References
 
Plant material and treatments
Two sunflower genotypes, Santiago II and Melody, showing different growth rate capacity were used in this study. For low-temperature treatments, seeds were grown in hydrated Jiffy-7 peat under controlled conditions, having 14 h day length, 80% relative humidity, 100 µE m–2 s–1 light intensity, and a temperature of 15 °C until germinating seedlings reached a two-leaf stage (about 50 d after sowing). The temperature was thereafter decreased to 7 °C until plants reached a four-leaf stage (about 70 d after sowing). Control treatments were performed under the same conditions described above except that temperatures were 25/20 °C light/dark. Plants at two- and four-leaf stages were harvested from both stressed and control treatments for RNA extraction and probe synthesis. Three independent biological samples for each treatment were used, each containing between 15 and 20 plants.

Determination of sunflower freezing tolerance
For cold acclimation, sunflower seedlings at the two-leaf stage were subjected to a short-day photoperiod (12 h) and reduced light intensity (45 µE m–2 s–1), with a decreasing temperature programme: 4 d at 15 °C followed by 12 d at 4 °C. Frost tolerance at –3 °C, –4 °C, and –5 °C was evaluated by measurements of electrolyte leakage, after freezing at 2.5 °C h–1. Ion leakage values, as a direct indicator of cell mortality, were used to compute the percentage of cell viability after freezing treatments compared with control (non-frozen leaf discs) as described by Leborgne et al. (1995).

Construction of sunflower cDNA microarrays
A total of 21 807 estimated sequence tags (ESTs) derived from different cDNA libraries, including embryos at different developmental stages, leaves, stems, and apices, as well as from previously described libraries (Tamborindeguy et al., 2004; Ben et al., 2005), were grouped in 8025 contigs using Phragment Assembly Program (PHRAP; University of Washington Genome Center) with a strict assembly criterion of >95% identity in a 40 bp overlap. For 1219 contigs, two non-overlapped ESTs at both 5' and 3' ends were selected. However, for the remaining 6806 contigs, only one EST at the 3' end was selected from each. Therefore, a total of 9244 ESTs representing 8025 putative unigenes was selected and amplified successfully. The size and quality of all PCR products were tested by agarose gel electrophoresis. PCR samples showing double bands were removed or replaced by another cDNA clone belonging to the same contig. The full list of the selected clones, as well as the positive and negative controls, is found in the supplementary data (see supplementary Table S1 at JXB online). The PCR products were concentrated by evaporation under the laminar flow hood for 24 h. The PCR products were then suspended in 40 µl of water to obtain a concentration of ~300–400 ng µl–1. Finally, the concentrated PCR products were arrayed onto Hybond N+, Amersham nylon membrane using the MicroGrid II (Biorobotics Ltd., Cambridge, UK) with 64 microarraying pins. A 13x13 gridding pattern and a distance of 0.325 mm between spots were used. The spotting was performed at the Centre de resources-Genotypage, Sequencage in Toulouse. To increase the reliability of signal, each PCR sample was arrayed twice in unadjusted spots to yield a total of 21 632 data points. After spotting, the nylon membranes were placed face up onto Whatman paper moistened with denaturation solution (1.5 M NaCl and 0.5 M NaOH) followed by neutralization solution (1.5 M NaCl and 1 M TRIS-HCl, pH 7.4) for 20 min each. The treated membranes were then dried at 80 °C for 2 h followed by UV crosslinking with a UV Stratalinker 1800. The quality of spotting was tested after oligonucleotide hybridization.

RNA isolation and probes labelling
The aerial parts of 15–20 plants, collected from the same treatment, were pooled for each RNA sample. Total RNA was extracted from the samples using the method described by Verwoerd et al. (1989). Single-stranded probes were synthesized from DNase-treated RNA using Advantage RT-for-PCR Kit (Ozyme, France). The reaction mixture containing 10 µg of total RNA and 40 pmol oligo (dT18) was heated at 70 °C for 2 min. Then, 8 µl of 5x reaction buffer, 2 µl of dNTP mix (0.625 mM dATP, 0.625 mM dTTP, 0.625 mM dGTP, and 0.625 µM dCTP), 4 µl of [{alpha}-33P]dCTP (40 µCi), 1 µl (1 unit) of RNase inhibitor, and 2 µl (400 units) of MMLV reverse transcriptase were added. The reaction was incubated at 42 °C for 1 h. An additional 200 units of MMLV reverse transcriptase was added and the mixture was incubated for another 60 min at 42 °C, followed by heating at 94 °C for 5 min to stop the synthesis reaction. To remove unincorporated labelled nucleotides, the radiolabelling reaction was purified by passing the reaction mixture through Probe Quant G-50 Micro Columns (Amersham). The purified radiolabelled cDNA was then used for hybridization. Hybridization was performed in a buffer containing 0.5% SDS, 5x SSC, 0.1% each of Ficoll 400, polyvinylpyrrolidone, and bovine albumin fraction, and 100 µg ml–1 of salmon sperm DNA (Sigma, France) at 65 °C for 24 h. Membranes were washed twice with buffer containing 0.1% SSC and 0.1% SDS at 65 °C for 15 min each. The membranes were then exposed to Fuji film imaging plates as a radioactive energy sensor. The radioactive intensity of the spots was captured using a bio-imaging analyser BAS-5000 (Fujifilm) with a density gradation of 16 bit pixel–1 at a resolution of 25 µm pixel–1. Signals and background quantification were performed using ArrayGauge V.1.3 (Fujifilm) and the numeric values assigned were used for statistical analysis.

Data normalization and ANOVA analysis
Analysis of variance (ANOVA) models were used both to estimate the relative gene expression level and to estimate other sources of variation in microarray data (Kerr et al., 2000; Wolfinger et al., 2001). A two-pass general linear model as described by Wolfinger et al. (2001) was performed to normalize the data and then to detect differentially expressed genes. The log10-transformed scores were subjected for all spot measures (yxijkl being the measured intensity for gene x subjected to low temperature treatments i in the genotype j for the spot k on array l) to a normalization model based on a three-way ANOVA of the form yxijkl=µ+Tri+Tmj+TrixTmj+Sl(TixTmj)+{varepsilon}xijkl where Tri is the treatment effect (15 °C, 7 °C and the corresponding controls, i.e. i=1, ... 4), Tmj is the genotype effect (Santiago II and Melody, i.e. j=1, 2), Sl is the membrane effect within a combination of factors and {varepsilon}xijk is the stochastic errors. The residuals from this model can be regarded as a crude indicator of the relative expression level and are referred to as ‘normalized expression levels’. The genes, for which the normalized expression levels of the two spots on a given slide are above the maximum of the empirical distribution of normalized expression levels for the control spots, are retained as ‘above background genes’. The gene-specific models were of the form rxijkl=Gx+GxxTri+GxxTmj+GxxTrixTmj+{varepsilon}xijklm where rxijkl is the normalized expression level of gene x. The GxxTri and GxxTmj effects quantify the overall variability of a gene as a function of the treatment or the genotype, respectively. The GxxTrixTmj interaction effect corresponds to the gene expression level in the two genotypes as a function of low-temperature treatments. A test for heterogeneous variances for the normalized expression levels among treatments was done using the Levene test for each gene model. The Bonferroni method was used to reduce errors conservatively due to multiple tests (at {alpha}=0.05 or 0.1). ‘Volcano plots’ of significance against magnitude of effects were drawn for each main effect. Computations were made on a PC running GNU/Linux (Suse 9.2, http://en.opensuse.org) and R 2.0.0 (http://www.r-project.org) statistical system.

Real-time RT-PCR
To confirm the results obtained from microarray experiments, the transcript abundance of 11 differentially expressed ESTs was tested. Gene-specific primers were designed using the Primer Express software, version 2.0 (Applied Biosystems, Courtaboeuf, France). Oligonucleotide primer sequences are shown in Table 1. First-strand cDNA was reverse transcribed from 5 µg of DNase-treated RNA as described before. The reaction was performed in a 20 µl volume containing 10 µl 2x Sybr Green Mastermix (Applied Biosystems), 300 nM of each primer, and 1 µl of 5-fold-diluted RT products. The PCR reactions were run in an ABI PRISM 7900HT sequence detection system (Applied Biosystems) using the following programme: 50 °C for 2 min, 95 °C for 10 min, and 40 cycles of 95 °C for 15 s and 60 °C for 1 min. Following PCR amplification, the reactions were subjected to a temperature ramp to create the dissociation curve, measured as changes in fluorescence measurements as a function of temperature, by which the non-specific products can be detected. The dissociation programme was 95 °C for 15 s, 60 °C for 15 s, followed by 20 min of slow ramp from 60 °C to 95 °C. Three replicates of each reaction were performed and ß-Actin (accession number AF282624), as a constitutively expressed gene, was used as an internal control to normalize the gene expression level. Quantifying the relative changes in gene expression was performed using the 2–{Delta}{Delta}CT method as described by Livak and Schmittgen (2001).


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  		Table 1 Oligonucleotide primers used for quantitative real-time RT-PCR

 

   Results and discussion
Top
 Abstract
 Introduction
 Materials and methods
 Results and discussion
Conclusion
 Supplementary data
 References
 
No cold acclimation is observed in sunflower after a chilling programme
The ability of sunflower plants to gain a frost tolerance after exposure to a period of low temperature is still poorly known. In order to investigate their cold acclimation capacity, sunflower plantlets were cultivated either under control conditions (25 °C) or under a specific chilling programme, then the leaf discs were exposed to freezing temperatures before the measurement of ion leakage. Evaluation of frost tolerance, at –3 °C, –4 °C, and –5 °C, was expressed as a value relative to the control (unfrozen discs). As shown in Fig. 1, there is no cold acclimation capacity observed at the three negative temperatures tested. Moreover, a gentle decrease in cell viabilities was observed in the treated plantlets when compared with the control (25 °C). For example, cell viability after a chilling programme decreased from 89% to 77% at –3 °C and –4 °C (Fig. 1). As expected, these results suggest that sunflower plants are non-acclimating plants under the experimental conditions of the study reported here.


Figure 1
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  		Fig. 1 Effect of freezing temperature on the relative viability of sunflower plantlets. Seedlings were grown at 25 °C (control conditions) or submitted to the chilling programme: 4 d at 15 °C followed by 12 d at 4 °C. At the end of this programme, leaf discs were frozen to different temperatures (–3 °C, –4 °C, and –5 °C) at a rate of 2.5 °C h–1. At –1 °C, an ice chip was added to the medium to promote ice nucleation and avoid erratic freezing and supercooling of the cells. Freezing tolerance was expressed as the percentage between the viability before and after the freezing test and given as the mean of five replicate measurements.

 
Global gene expression analysis
Seeds from early- (Santiago II) and late- (Melody) flowering genotypes were germinated and grown at a moderately low temperature (15 °C) until the two-leaf stage, and then the plants were transferred to 7 °C until the four-leaf stage. To avoid photoacclimation to high light which mimics photoacclimation to low temperature, sunflower plants were grown under 100 µE m–2 s–1 light intensity (see Materials and methods). Although the growth rate was affected in sunflower plants grown under low temperature conditions (15 °C and 7 °C), these plants displayed morphologies similar to those under standard growth conditions. Changes in the sunflower transcriptome in response to low-temperature tolerance were analysed in three biological samples collected from both treated and control plants at the two- and four-leaf stages. Twenty-four radio-labelled probes corresponding to two genotypesxfour treatments (two temperature regimes and their corresponding controls)xthree biological replications were performed. Gene expression values were measured as described in the Materials and methods. Over the range of non-normalized expression values, the correlation between the biological repeats was found to be very high (r2 ranges from 0.75 to 0.90) indicating that measurements of gene expression values are reproducible and that no artefactual difference is due to sample heterogeneities. The normalization of the data was performed using an ANOVA normalization model, according to the genotype and treatment effects that were found to be highly significant (data not shown). The residuals from this model, which represent the normalized expression values, were statistically analysed using a two-way analysis of variance method as described in the Materials and methods. This procedure allowed the effect of each factor across the entire experiment to be determined, as well as the interaction effects between the two factors.

Changes in mRNA abundance in response to low temperatures in sunflower include wide inhibition of primary metabolism-related genes
Since not all changes in transcriptional patterns are expected to be a direct consequence of low temperature treatments (15 °C and 7 °C), the identification of genes that exhibit significant variation in gene expression level between genotypes allows the comparison between the two low-temperature regimes and their corresponding controls to be potentially free of the genotype main effect. At a p-value cut-off of 10–3, 59 cDNA clones were identified showing exclusive genotype-specific variation in expression levels across all treatments, which are given as supplementary results (see supplementary Table S2 at JXB online). Similarly, 171 cDNA clones have been identified as showing an exclusive treatment main effect (genes whose expression levels differentiate significantly between at least two of the four treatments) (data not shown). In order to exclude the genes that exhibit significant differences between the two-leaf stage controls and the four-leaf stage controls from this list, two contrasts were carried out. The first contrast was performed to identify genes with significantly different expression patterns between the two low-temperature regimes on one hand, and their corresponding controls on the other hand. The second contrast was performed to identify the genes that show a significant difference between the two low-temperature treatments (15 °C and 7 °C). In the first contrast, a total of 150 cDNA clones were identified. These genes are presented as ‘volcano plots’ of significance against magnitude of effects in Fig. 2. Among these, 108 cDNA clones having a P-value <10–3 for the comparison between treatments, as well as for the comparison between low temperature-grown plants (15 °C and 7 °C) and their corresponding two-leaf and four-leaf stage controls across the two genotypes, have been considered as differentially expressed. These differentially expressed genes are represented as red or blue dots in Fig. 2. The majority of these genes (97) were down-regulated, while the remaining 11 clones were found to be induced in stressed plants. These results indicate clearly that the major part of the sunflower response to low growing temperatures involves gene down-regulation. These regulated genes are distributed throughout different functional categories and are provided in Table 2, together with their putative functions.


Figure 2
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  		Fig. 2 Volcano plot of significance against expression differences between low temperature (15 °C and 7 °C) and control (25 °C) treatments. For each gene, the negative log10 of the p-value from the gene model was plotted against the differences of normalized expression values between the low temperature-grown plants and their corresponding controls, as well as between the two low-temperature treatments (15 °C and 7 °C) across the two genotypes. Genes are indicated by dots with the highly significant ones toward the top. Red dots represent genes showing significant variations in transcript abundance between the low temperature-grown plants and controls. Blue dots represent genes showing significant variations in transcript abundance between 15 °C and 7 °C. Black dots represent genes showing significant variations in transcript abundance between the two-leaf stage controls and the four-leaf stage controls. The horizontal line denotes thresholds for P=10–3.

 

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  		Table 2 Long-term regulated genes in response to low temperatures

 
Careful examination of the putative functions of the differentially expressed genes highlighted that transcripts encoding proteins potentially involved in translation and protein synthesis were repressed. These include a collection of five ribosomal RNA genes, one tRNA synthetase, and a translation inhibitor protein. By contrast, a highly significant number of genes involved in protein biosynthesis was found to be up-regulated in Arabidopsis plants subjected to chilling temperature (13 °C) and down-regulated in chilling-sensitive mutants (Provart et al., 2003). The contrasting expression behaviour of protein biosynthesis-related genes in sunflower and Arabidopsis under low temperature may reflect the differences between chilling-resistant and chilling-sensitive plants. Many environmental factors have also been found to affect the expression of many genes involved in translation activity and protein synthesis in different plant species. This includes, for example, ultraviolet radiation (Casati and Walbot, 2003), low-oxygen stress (Morelli et al., 1998), nitrate uptake (Wang et al., 2004), salinity (Ozturk et al., 2002), and light conditions (Ma et al., 2001). Taken together, these results indicate that changes in growing temperatures could be one of several environmental factors contributing to changes in translation activity and protein synthesis.

The notion that low-temperature tolerance impairs protein structure and function justifies the importance of molecular chaperones, which accumulate under a wide range of stress conditions including low temperatures (Boston et al., 1996; Cui et al., 2005). Chaperones have a vital role in the folding and assembly of proteins during synthesis and in the elimination of malformed and damaged proteins. The inactivation and/or down-regulation of genes putatively involved in protein fate in the present study may be the fundamental cause of down-regulation of protein biosynthesis-related genes.

An interesting response of sunflower plants to low temperatures (15 °C and 7 °C) was also observed for genes potentially encoding glutamate:glyoxylate aminotransferase (GGT; EC 2.6.1.2 [EC] ) that were down-regulated. GGT is a key enzyme involved in glutamate metabolism and carbon fixation. The reduction of the transcription activity of these photorespiratory enzymes suggests that a shift occurs in glutamate metabolism and carbon fixation during low-temperature stress. The down-regulation of GGT-encoding genes was accompanied by the repression of a cDNA clone putatively encoding carbonic anhydrase, which catalyses the conversion of CO2 to Formula and plays a key role in CO2 fixation, the major function of photosynthesis. Among the down-regulated genes that encode products with predicted functions related to energy metabolism (26 genes), many clones potentially encoding components involved in photosynthesis such as photosystem proteins, chlorophyll-binding protein, Rubisco, and plastocyanin were found. Contrary to the results reported for Arabidopsis plants grown under low temperature, it was found that all differentially expressed genes related to energy metabolism were down-regulated in low temperature-grown plants relative to the control. This suggests that decreasing energy metabolism is one of the cellular processes associated with the sunflower response to decreased temperatures. Short-term exposure of chilling-sensitive and -tolerant species to low temperatures results in feedback-mediated down-regulation of photosynthesis and photosynthetic gene expression (Martino-Catt and Ort, 1992; Kreps and Simon, 1997). By contrast, when leaves of Arabidopsis and other cold-tolerant herbaceous plants develop at a low growth temperature (5 °C), they show a remarkable recovery of photosynthetic capacity which is the opposite of the response in cold-sensitive species (Holaday et al., 1992; Hurry et al., 1995; Strand et al., 1999). Contrary to sunflower, a chilling-sensitive plant, the increase of photosynthetic enzymes, as well as those involved in sucrose synthesis in chilling-tolerant plants, seems to be an adaptive response that enables these plants to maximize the production of sugars that may act in cryoprotection (Carpenter and Crowe, 1988). These results provide an important element regarding the differences between chilling-sensitive and -tolerant species.

Nine genes encoding products with predicted transport functions were identified as being repressed by low temperature treatments (15 °C and 7 °C) (Table 2). These are potentially involved in the transport of water, lipids, ions, cations, and electrons. Aquaporins are water-channel proteins which belong to intrinsic protein superfamilies that facilitate diffusion of water and other small molecules into the cell across membranes (Johansson et al., 2000; Chaumont et al., 2001). The down-regulation of aquaporin-encoding genes shows the failure of sunflower plants, growing under low temperature, to maintain cellular homeostasis. Low-temperature tolerance has been found to affect water-channel activity (Hertel and Steudle, 1997; Lee et al., 2005). Also, low temperatures can negatively affect electron transport by increasing membrane viscosity (Ensminger et al., 2006). The repression of the other genes involved in transport activity is consistent with the fact that low temperatures affect cellular metabolism and related processes, including inter- and intracellular transport.

Two cDNA clones putatively encoding lipid-transfer proteins (LTPs) with opposite expression patterns were identified as differentially expressed (Table 2). LTPs were isolated from different plant species and were found to be encoded by small multigene families in most plant species (Kader, 1996, 1997). Although LTPs were at first supposed to participate in membrane biogenesis, the biological function of the majority of plant LTPs remains unknown. Many studies suggested that they may be involved in plant response to biotic and abiotic stresses (Pearce et al., 1998; Blein et al., 2002; Wu and Burns, 2003). It is therefore possible that different gene family members account for the observed diversity in expression patterns under low-temperature tolerance, each one perhaps performing a different function. Because of the ability of LTPs to facilitate the transport of lipids in vitro from one membrane to another, these gene members could play different roles in the lipid-mediated processes under low-temperature tolerance.

Down-regulation of a putative lipoxygenase 2, suggests that jasmonate synthesis is significantly reduced. Several physiological roles have been described for jasmonic acid during plant development and in response to biotic and abiotic stresses (Creelman and Mullet, 1995). Similarly, expression of several genes encoding enzymes related to hormone biosynthesis was found to be affected by low temperatures in chilling-sensitive mutants of Arabidopsis (Provart et al., 2003).

On the other hand, only 11 genes exhibiting enhanced expression levels under low temperature treatments (15 °C and 7 °C), compared with controls, were identified as differentially expressed. However, the putative functions for eight of these up-regulated genes could not be assigned and annotated as ‘no hits or unknown’, and therefore may be of particular importance in future functional genomic investigations of sunflower tolerance to low temperature. The remaining three genes were found to encode proline-rich protein (PRPs) (two genes) and LTP. Genes encoding PRPs have not been identified as being regulated by low-temperature tolerance. However, an increase in PRP mRNA in response to water deficit has been observed (Creelman and Mullet, 1991; García-Gómez et al., 2000). It is well known that cell walls contain various types of proteins, including those highly enriched in proline residues (Cassab and Varner, 1988). Because PRPs are presumably insoluble in the cell wall matrix, it has been suggested that they play a role in structural strengthening (Cassab, 1998). García-Gómez et al. (2000) reported that PRPs interact with the plasma membrane through a specific protein, suggesting that PRPs may perform additional functions involving a contribution to the maintenance of a rigid adhesion of the plasma membrane to the cell wall. During development and environmental stress the composition and structure of the cell wall is continuously rearranged. It is therefore possible that PRPs participate in these processes and may have important biological functions during low-temperature stress. It may be important to mention that chilling treatment can induce drought stress especially in plants subjected to long-term low-temperature tolerance, where the roots are also chilled and hydraulic conductance through the roots could be severely reduced. Therefore, the induction of PRPs is not necessarily exclusively due to chilling stress, and induction of these genes as a result of chilling-induced drought stress cannot be excluded.

Similar genetic programmes underlie the response of sunflower plants to 15 °C and 7 °C stress
ANOVA analysis identified four ESTs exhibiting overall significant variations in transcript abundance between the two low temperature regimes (15 °C and 7 °C), irrespective of the genotype backgrounds. These clones are represented as blue points in the ‘volcano blot’ (Fig. 2) and potentially encode carbonic anhydrase, PRP, LTP, and ‘protein with non-significant similarity in databank’ (Table 3). The finding that the expression levels of the last three genes were induced by low-temperature treatments, and that the levels of induction were higher at 7 °C than at 15 °C, indicates that their mRNA accumulation is correlated with an increase in low-temperature tolerance. The biological function of LTPs in low-temperature tolerance remains to be elucidated. Some evidence suggests that a temperature sensor in higher plants may respond to plasma membrane fluidity, as in the case of cyanobacteria (Plieth et al., 1999; Orvar et al., 2000). Therefore, based on the reported functions of PRP and LTP in membrane fluidity, such roles of these proteins under low temperature can be expected. On the other hand, the low number of genes that are found to be differentially expressed between 15 °C and 7 °C suggests that similar genetic programmes underlie the response of sunflower plants to low-temperature stress.


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  		Table 3 Genes showing significant differences in transcriptional activity between 15 °C and 7 °C

 
Early and late genotypes respond similarly to low-temperature stress
The ANOVA interaction analysis, as a powerful tool to identify more complex gene expression patterns, was used to identify the putative difference between genotypes in response to low-temperature treatments. At a P-value cut-off of 10–3, eight cDNA clones showing significant genotypextreatment interactions were identified. The putative functions of four of these differentially expressed genes could not be assigned and annotated as ‘no hits or unknown’ (Table 4). However, the remaining four genes were found to encode fructose-1,6-bisphosphatase, DNA repair ATPase, calcium-binding EF-hand family protein, and 40S ribosomal protein. As shown in Table 4, the transcript abundance of five of these genes was repressed or unchanged under low-temperature tolerance compared with control; two genes were induced in both genotypes and one gene exhibited contrasting expression patterns under stress and control treatments in both genotypes. A transient increase in cytosolic Ca2+ has been observed as an early response of plant cells to low temperature and other abiotic stresses (Sanders et al., 1999; Knight, 2000). This increased Ca2+ is perceived by a variety of Ca2+-binding proteins. The up-regulation of a cDNA clone encoding a putative calcium-binding EF-hand family protein in both genotypes under low temperatures suggests the involvement of Ca2+-regulated processes in response to low temperature via the transduction of low temperature-induced signal, which can subsequently affect different aspects of cellular activities. The recovery of photosynthetic capacity in winter rye and Arabidopsis plants developed at low temperature was associated with an increase in the activity of key enzymes involved in sucrose biosynthesis (Strand et al., 1999). The down-regulation of a cDNA putatively encoding fructose-1,6-bisphosphatase (EC 3.1.3.11 [EC] ), a key enzyme of fructose and mannose metabolism, could, again, account for the sensitivity of the sunflower plant to low temperatures. Although the rate of development was found to be a good discriminator of cold tolerance during early phases of maize development (Lee et al., 2002), the present microarray analyses revealed that early-flowering (Santiago II) and late-flowering (Melody) genotypes respond similarly to low-temperature tolerance. Therefore, no clear relationship between growth rate and low-temperature tolerance in sunflower can be addressed. This may be due to selection pressures for the genetic programmes that ignore low-temperature tolerance.


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  		Table 4 Genes showing significant interaction between the two genotypes and the low-temperature treatments

 
Confirmation of gene expression patterns by quantitative real-time RT-PCR
To validate the present microarray data, the expression levels of 11 differentially expressed genes were tested by quantitative real-time RT-PCR. Estimated expression patterns by DNA microarray and real-time RT-PCR are compared in Table 5. In all cases, the transcript levels derived from the two methods are highly similar. Real time RT-PCR was also used to confirm the presence, in the present array, of different clones encoding members of the same gene family with different expression behaviours under low temperature conditions. Two putative LTPs, exhibiting contrasted expression profiles using microarray analysis, were examined by quantitative RT-PCR. The expression levels were also found to be similar to the levels of mRNA abundance obtained from the microarrays. These results, which validate the high specificity of hybridization signals obtained from the present array, demonstrate the possibility of differentiating between the expression profiles of different gene family members using 3'-end ESTs in EST-based microarray experiments.


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  		Table 5 Comparison of gene expression levels obtained by DNA microarray and real-time RT-PCR analysis for 11 differentially expressed genes

 

   Conclusion
Top
 Abstract
 Introduction
 Materials and methods
 Results and discussion
 Conclusion
Supplementary data
 References
 
To assess changes in gene expression associated with low growing-temperature stress during the early stage of sunflower development, the expression patterns of >8000 unigenes in two genotypes with contrasting flowering dates growing under two low temperature regimes were analysed. The results revealed that wide inhibition of transcriptional activity takes place during plant development under sub-optimal temperatures (15 °C and 7 °C). It is possible that the inhibition of these genes may only reflect responses to acclimate plant metabolism to growth under suboptimal temperatures. Such extensive down-regulation of gene expression was also found in Arabidopsis during cold acclimation (Fowler and Thomashow, 2002). The putative functions of about 38% of the differentially expressed genes could not be assigned and were annotated as ‘no hits’ or unknown. Among these non-annotated genes, seven cDNA clones were identified as being up-regulated under low temperature conditions, suggesting their potential importance in low-temperature tolerance. Identification of the functional role of these genes could shed light on new mechanisms by which plants can adjust the cellular processes to low growing-temperatures. The expression profiles derived from this study showed that early- and late-flowering genotypes respond similarly to low-temperature tolerance. Although it is well known that wild sunflowers are distributed over a range of latitudes, as far as is known the freezing tolerance of cultivated sunflower has not been published to date. The ability of different sunflower germplasms to tolerate low temperatures needs to be evaluated. The transcriptome analysis of such tolerant ecotypes could lead to new insights into the molecular basis of low-temperature tolerance in sunflower plants.

Comparison of the present results with the data set obtained from a microarray analysis of Arabidopsis plants subjected to chilling temperature (13 °C) (Provart et al., 2003) could reveal the potential differences between chilling-sensitive and chilling-insensitive plants. It was found that many of the known genes whose products are thought to be involved in low-temperature tolerance such as LTPs, aquaporin, chaperone, and sucrose metabolism-related genes were down-regulated in the present experiments. The expression level of many genes encoding, for example, fatty acid desaturase, antioxidant enzymes, cryoprotective proteins, and regulatory proteins were also not significantly induced. Thus, it is supposed that the down-regulation and/or non-induction of genes having important functions in low-temperature tolerance may be responsible for the sensitivity of sunflower plants to low-temperature tolerance. Similarly, Arabidopsis pollen, a cold-sensitive organ, was found to be unable to induce expression of genes important in cold acclimation after exposure to 0 °C for 72 h (Lee and Lee, 2003). The results reported here provide an initial characterization of the transcriptome activity of sunflower, a chilling-sensitive plant. These expression profiles could shed light on the similarities and dissimilarities between chilling-sensitive and -tolerant species in response to low-temperature tolerance.


   Supplementary data
Top
 Abstract
 Introduction
 Materials and methods
 Results and discussion
 Conclusion
 Supplementary data
References
 
Supplementary data (Table S1 which gives a full list of the clones spotted and their accession numbers and Table S2 which lists the genes which show a significant genotype main effect) can be found at JXB online.


   Acknowledgements
 
The Genoplante program (GOP-HG01 grant) is acknowledged for authorizing the use of sequences and cDNA clones for the construction of the microarray. We thank Cécile Donnadieu Tonon at ‘Centre de resources-Genotypage, Sequencage’ of Toulouse for advice and access to microarray equipment.


   References
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 Introduction
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