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RESEARCH PAPER |
Antisense-mediated suppression of C-hordein biosynthesis in the barley grain results in correlated changes in the transcriptome, protein profile, and amino acid composition
1Department of Genetics and Biotechnology, Faculty of Agricultural Sciences, University of Aarhus, Research Centre Flakkebjerg, DK-4200 Slagelse, Denmark
2Center for Biological Sequence Analysis, BioCentrum, Technical University of Denmark, Building 208, DK-2800 Kgs. Lyngby, Denmark
* To whom correspondence should be addressed. E-mail: eva.vincze{at}agrsci.dk
Received 9 August 2007; Accepted 19 September 2007
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Abstract |
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Antisense- or RNAi-mediated suppression of the biosynthesis of nutritionally inferior storage proteins is a promising strategy for improving the amino acid profile of seeds. However, the potential pleiotropic effects of this on interconnected pathways and the agronomic quality traits need to be addressed. In the current study, a transcriptomic analysis of an antisense C-hordein line of barley was performed, using a grain-specific cDNA array. The C-hordein antisense line is characterized by marked changes in storage protein and amino acid profiles, while the seed weight is within the normal range and no external morphological irregularities were observed. The results of the transcriptome analysis showed excellent correlation with data on changes in the relative proportions of storage proteins and amino acid composition. The antisense line had a lower C-hordein level and down-regulated transcript encoding C-hordein. The production of the S-rich B/
- and D-hordeins was increased and significantly higher steady-state expression levels of the corresponding genes were observed. The increased synthesis of S-rich hordeins appeared to increase the demand for sulphur and the S-rich amino acids (cysteine and methionine), resulting in an up-regulation of key genes in the appropriate biosynthetic pathways. This study demonstrated the utility of the grain-specific cDNA microarray analysis to detect perturbations induced by antisense suppression of plant processes. Key words: cDNA microarray, gene silencing, genetically modified (GM) crop, Hordeum vulgare, storage proteins, transcriptome
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Introduction |
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TopAbstractIntroductionMaterials and methodsResults and discussionSupplementary dataReferences |
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Today, cereals provide a significant proportion of human and animal diets. However, the grains of most cereals species have a number of nutritional shortcomings. A primary problem is the low levels of essential amino acids (AAs), such as lysine and threonine in wheat and barley, while maize has a shortage of lysine and tryptophan. These deficiencies can primarily be attributed to the abundance of the major storage proteins, the prolamins. In barley, these are called hordeins and in maize, zeins, and they typically account for >50% of the storage proteins. In the last few years, an additional problem relating to the AA composition of cereals has gained significance. Barley and maize are used extensively as animal feed, and as the prolamins possess a high amount of non-essential AAs, namely glutamine and proline, that are not utilized, the excess nitrogen excreted in the urine makes a significant contribution to the environmental nitrogen load.
A large number of classical mutagenesis and gene technology approaches have been explored with a view to improving the AA content of seeds of a wide range of species (Munck, 1992; Hunter et al., 2002; Galili et al., 2005, and references therein). Although significant increases in lysine content have been achieved, other drawbacks have been reported such as reduced yield and seed viability. In maize, these problems have been solved by the introduction of so-called modifier genes (Gibbon and Larkins, 2005), but in other cereals such as barley, it has not yet been possible to generate agronomically competitive high-lysine cultivars (Munck, 1992).
At present, one of the most promising strategies for improving the protein nutritional value appears to be by altering the relative proportions of the major storage protein families by antisense or RNAi technology (Kohno-Murase et al., 1995; Maruta et al., 2002; Segal et al., 2003; Huang et al., 2004). Recently, Lange et al. (2007) reported the generation of a number of lines with altered storage protein composition by integrating an antisense construct of the C-hordein genes into the barley genome. It was found that the antisense strategy resulted in a partial suppression of the genes targeted, while the seed weight of the transgenic lines grown in a greenhouse was within the normal range and no external morphological irregularities were observed. By contrast, the conventional high lysine mutants are readily identifiable by their shrunken kernels and enlarged embryos. The lines described by Lange et al. (2007) had altered AA and storage protein profiles. The general pattern was a reduction in the amount of hordeins with a relative suppression of C-hordein and a comparable increase in the amount of B-hordein and glutelins. These changes were accompanied by a decrease in proline, glutamine, and phenylalanine, in agreement with the high amounts of these three AAs in C-hordein (Lange et al., 2007).
Microarray-based transcriptome analysis is a powerful tool for the global analysis of gene expression in response to perturbations of plant processes and development by mutation or transformation. Microarray analyses of several high-lysine maize mutants have thus started to create the foundation for improved understanding of the effect of single mutations on the intricate regulatory mechanisms and the interconnections of pathways in the maize grain (Hunter et al., 2002). Studies of transgenic wheat have shown that it is possible to develop lines expressing additional copies of high molecular weight glutenins or lines that express a heterologous phytase gene that are substantially equivalent to the conventional varieties (Gregersen et al., 2005; Shewry et al., 2007, and references therein). Similarly, studies in Arabidopsis have revealed that gene silencing by RNAi does not, per se, have an effect on the expression of the rest of the genome (Aelbrecht et al., 2006). However, when perturbing and modulating regulatory mechanisms or metabolic pathways by transformation, pleiotropic effects will invariably follow as interconnected pathways will also be affected. Microarray analysis in these cases is very powerful for elucidating and evaluating changes in metabolism and the putative effects of these changes on the properties of the transgenic line.
In the present study, microarray analyses were used to compare the transcriptome of a transgenic barley line containing an antisense C-hordein gene (Lange et al., 2007) with the parental wild type, cv. Golden Promise. A custom-made cDNA array for developing grains of barley was prepared where a comprehensive set of genes known to be involved in nitrogen mobilization, transport, and AA metabolism was collated. The changes in the transcriptome, combined with the AA and HPLC analyses reported by Lange et al. (2007), allowed the effects of suppressing C-hordein biosynthesis on the relative proportions of the different storage proteins, as well as the interconnecting pathways, to be illustrated and, thereby, increased insight into the intricate regulatory pathways of the developing barley grain to be gained.
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Materials and methods |
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Plant material for cDNA microarray analysis
The wild-type barley (Hordeum vulgare cv. Golden Promise) and the transgenic AsHorC line number 5, which was selected because of its optimal storage protein and AA composition with respect to feed application (Lange et al., 2007), were grown in pots in a greenhouse under a cycle of 16 h illumination and 8 h darkness at 23 °C and 18 °C, respectively. Individual spikes were tagged at pollination and developing grains were harvested at 10.00 hours, 20 d after pollination (DAP). The grains were still green at this stage of harvesting, corresponding to Zadoks code 85 (Zadoks et al., 1974) (data not shown). The grains were frozen in liquid nitrogen immediately after sampling and stored at –80 °C until RNA extraction was performed. The same batch of developing seeds was used for the current microarray analysis and real-time RT-PCR, and the AA and HPLC analyses were as performed by Lange et al. (2007).
Construction of barley cDNA microarrays
A set of 1035 cDNA probes was assembled from the two EST libraries of Clemson University Genomics Institute (termed HVSMEi and HVSMEk). These libraries contain 
13 000 ESTs from testa/pericarp and developing barley spike (20 DAP) tissues (http://www.genome.clemson.edu/projects/barley/). Primarily, genes involved in nitrogen mobilization, transport, and AA metabolism were selected, but the array was supplemented with genes encoding transcription factors as well as genes of major significance for carbon and lipid metabolism, to assess the interconnections between the basic metabolic pathways during grain filling; 52 hypothetical genes were included as well (see Table S1 in Supplementary data available at JXB online).
Individual pBluescript SK (-) EST clones were transferred to a microtitre well containing 150 µl of LB medium in 96-well plates (Greiner Bio-one) and grown at 30 °C on a shaker at 220 rpm overnight. Colony PCR was performed using 1.5 µl of the resulting broth to amplify the EST insert. This was achieved using 0.5 µl (10 U µl–1) of 50x BD Advantage 2 Polymerase Mix and 5 µM of each optimized primer (forward primer: 5'-CGC GCG TAA TAC GAC TCA CT-3’; reverse primer: 5'CGC GCA ATT AAC CCT CAC TA-3’) in 50 µl of reaction buffer (5 µl of 10x BD AdvantageTM 2 SA PCR buffer containing 100 mM TRIS–HCl (pH 8.5), 500 mM KCl, 20 mM MgCl2; 0.3 mM each dNTP). The PCRs were performed in a Peltier thermal Cycler (PTC-225; VWR International) with the following thermal cycle: 3 min denaturation at 95 °C, followed by 35 cycles of 30 s at 95 °C, 1 min at 55 °C, 3 min at 72 °C, and a final extension of 10 min at 72 °C. The qualities of the PCR products were checked in a 1% agarose gel. The PCR products were purified and desalted in a PCR microtitre plate in the following way: a size exclusion column was prepared in each well of the microtitre plate by first creating a hole in the bottom of each well and then adding a glass bead and 200 µl of Sepharose CL-6B (Sigma). The eluate from the column was collected by centrifugation for 5 min at 2797 g. Twenty microlitres of each PCR product was vacuum-dried and dissolved in 8 µl of 50% dimethyl sulphoxide (Sigma D8418) resulting in a DNA concentration range of 250–400 ng µl–1. The probes were spotted onto SuperchipTM poly-L-lysine slides (Erie Scientific Company, USA) using a Qarray mini-microarray spotter (Genetix) with 16 pins. Probes were spotted in three subgrids across the slide, providing three technical replicates per hybridization. After air-drying overnight at room temperature, the DNA was cross-linked to the slide by UV irradiation at 250 mJ (Stratalinker, Stratagene). The slides were stored in the dark at room temperature until hybridization.
RNA isolation and labelling of target material
Three biological samples were collected from a transgenic line and the non-transgenic parental cv. Golden Promise. Each biological sample consisted of three whole grains selected from the mid-section of the spike from three independent barley plants. Whole grains were ground in liquid nitrogen prior to the RNA extraction. One hundred and eighty milligrams of plant material was obtained and mRNA was extracted using-Dynabeads (610-05; Dynal, N) according to the manufacturer's protocol. The synthesis of first- and second-strand cDNA and labelling with Cyanine3/Cyanine5 were performed according to Eisen and Brown (1999).
Hybridization, scanning, and data analysis
The hybridization protocol was performed according to Eisen and Brown (1999) with modifications as follows: the slide was first heat treated for 20 min at 80 °C to avoid comet tails of the spots and, thereafter, blocked in succinic anhydride to inactivate free lysine groups and minimize background (Eisen and Brown, 1999). After blocking, the slides were incubated for 3 min in boiling water and rinsed twice in 96% EtOH. Excess EtOH was removed by centrifuging the slides in 50 ml tubes at 1860 g for 8 min. The dry slides were placed in a dust-free hybridization chamber (MWG) on a heating block at 45 °C, and a lifter slip (25x 60I-2-4789; Erie Scientific Company, USA) was placed on the slides covering the spotted area. Fifty picromoles of both Cy3- and Cy5-labelled cDNA solutions were combined and vacuum dried at 30 °C, followed by adding 5 µl of ddH2O and 45 µl of cover slip-hybridization solution (MWG). The hybridization solution was denatured for 4 min at 95 °C and centrifuged for 5 s. The solution was immediately added to all four corners of the lifter slip, allowing the fluid to be distributed without air bubbles. One hundred microlitres of Solution II (0.5x SSC, 50% formamide) was added to the incubation chamber, which was then closed and incubated for 16 h in the dark at 42 °C. After the incubation period the lifter slip was removed by soaking the slide in solution I (2x SSC, 0.1% SDS, pre-heated to 50 °C). The slide was then washed in fresh solution I, subjected to vigorous stirring for 10 min, followed by two washes in wash II (0.1x SSC, 0.1% SDS, pre-heated to 50 °C) for 10 min, and three washes in 0.1x SSC for 1 min. Finally, the slide was dipped 10 times in 0.01x SSC, 10 times in 96% EtOH, and immediately thereafter vacuum dried in a 50 ml tube while being centrifuged at 1860 g for 8 min.
Dye swap was not performed, as a paired sample design was used in order to avoid masking the gene expression data by dye biases (Dobbin et al., 2003). Three hybridization experiments were performed with three individual biological samples (biological replicates). The transgenic RNA samples were labelled with Cyanine3 and Golden Promise with Cyanine5. The array design included three spots for each probe (technical replicates). Data acquisition and analysis were performed on an arrayWoRx microarray scanner (BioChipReader, Applied Precision, USA) using the arrayWoRx 2.0 software suite. The spots on each individual slide were quantified using a well-defined grid.
Pre-processing of microarray data and identification of differential expression
The microarray data were normalized using the non-linear Qspline algorithm (Workman et al., 2002) that also compensates for dye-specific effects. The differences in expression between the transgenic plants and the parental variety, Golden Promise, were quantified using a one-way analysis of variance (ANOVA). For the purpose of this ANOVA, the technical and biological replicates were treated as equal and independent observations, which would normally not be a valid assumption since the variance between biological replicates would be much higher than that between technical replicates. However, in the case of the present data the variance observed between the technical replicates was comparable with that between the biological replicates—although still less than that observed between the transgenic and parental lines (data not shown).
The 207 most-significant genes from the ANOVA, corresponding to 20% of the total, were extracted into a high confidence set and used for further analysis. All together, 139 genes had a P-value of <0.05 (Table S2 in Supplementary data available at JXB online), while all of the 207 genes were identified at the P <0.1 significance level (the extended list is available on request). In order to prevent the loss of important information from significant differentially expressed genes exhibiting low intensity signals under one or more conditions, no level of arbitrary threshold value for gene expression was used prior to normalization and statistical analysis (Li et al., 2002).
Alignment (BLAST)
Since very little annotation currently exists for barley proteins, a sequence alignment was performed to obtain putative functional information. For each probe on the array, the corresponding target sequences were aligned at the protein level against the Swiss-Prot protein database (Swiss-Prot: http://www.expasy.org/) using blastx (Altschul et al., 1990). For each target sequence, putative annotation was assigned only from the best alignment hit, and the alignment identity was recorded (Table S1 in Supplementary data available at JXB online).
Real-time RT-PCR expression analysis
Total RNA was isolated from a pool of six individual grains from the midrib of six independent barley spikes using a FastRNA Pro Green Kit (Bio101, Systems, France) and resuspended in 50 µl of DEPC-treated water, according to the manufacturer's manual. The diluted RNA was measured on a GeneQuant II DNA/RNA calculator (Pharmacia Biotech, Piscataway, NJ, USA). For each sample, 2 µg of total RNA was used for first-strand cDNA synthesis. To the RNA was added 500 ng (500 ng µl–1) of a random hexamer primer mix (Fermentas, Germany), and the volume was adjusted to 11 µl. The mixture was heated for 10 min at 70 °C and cooled on ice while adding 4 µl of 5x first-strand buffer (Invitrogen GmbH, Karlsruhe, Germany), 1 µl of RNase GuardTM porcine RNase inhibitor (30 U µl–1), 2 µl of DTT (0.1 M), and 1 µl of dNTPs (10 mM each dNTP), followed by incubation for 2 min at 42 °C. Before incubation for 1.5 h at 42 °C, 1 µl of Superscript II reverse transcriptase (Invitrogen GmbH) was added. After incubation the mixture was diluted to 200 µl, of which 1 µl was used as a template for each real-time RT-PCR.
A real-time RT-PCR was carried out in a total volume of 10 µl using 5 µl of Power SYBR Green master mix (Applied Biosystems, Foster City, CA, USA), 500 nM forward and reverse primer (Table S3 in Supplementary data available at JXB online), 1 µl of cDNA template, and MilliQ H2O up to 10 µl. Reactions were loaded onto 384-well plates and performed in an AB7900HT sequence detection system (Applied Biosystems) programmed with the following thermal profile set-up: one cycle at 50 °C for 2 min; one cycle at 95 °C for 2 min; 40 cycles at 95 °C for 15 s and 60 °C for 1 min. The primer sets were designed using Primer Express software (Applied Biosystems) and built within the microarray probe region to assure an identical expression tendency. To investigate the specificity of each primer set (Table S3 in Supplementary data available at JXB online) a dissociation curve analysis was implemented. Each gene of interest was normalized to a housekeeping gene, Actin, in the sample of the control line, Golden Promise, and the transgenic line. The Ct value was obtained for each specific gene in the control line Golden Promise and the transgenic line followed by a quality check and relative expression calculation for each gene using the software REST©, according to Pfaffl et al. (2002). Herein, the expression ratio results were tested for significance by a pair-wise fixed reallocation randomization test.
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Results and discussion |
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TopAbstractIntroductionMaterials and methodsResults and discussionSupplementary dataReferences |
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The developing grain-specific microarray
A custom-made cDNA microarray was constructed with 1035 cDNA probes, primarily derived from the Clemson University cDNA libraries, generated from developing barley grains. This array, which is referred to as a grain-specific microarray, contains a comprehensive set of genes involved in nitrogen mobilization, transport, and AA metabolism. In addition, to assess regulatory networks and interconnections between the basic metabolic pathways in the grain, a number of genes encoding transcription factors, as well as selected genes associated with carbon and lipid metabolism, was included.
The aim was to illustrate the effects of the suppression of C-hordein biosynthesis on the relative proportions of the different storage proteins, as well as the interconnecting pathways, and thereby gain increased insight into the intricate regulatory pathways of the developing barley grain. The developmental stage of 20 DAP was chosen because storage product accumulation occurs exclusively in the latter phase of grain development (Rahman et al., 1984; Sørensen et al., 1989; Shewry and Halford, 2002). The transgenic line and its parental cv. Golden Promise were compared at the transcriptome level by studying a selected set of genes encoding AA and storage protein synthesis in the maturing barley grain at the most relevant time. The raw data files of the microarray experiments performed can be obtained from the ArrayExpress microarray repository at the European Bioinformatics Institute (EBI) (http://www.ebi.ac.uk/arrayexpress/) accession number: E-MEXP-1000 supplemented with annotations of the probes used in the experiment.
The analysis of the array revealed 139 differentially expressed genes showing statistical significance at a probability of P <0.05 (Table S2 in Supplementary data available at JXB online). Sets of up- and down-regulated genes involved in AA metabolism and photosynthesis are shown in Tables 1 and 2, respectively. The chosen annotated genes of interest were ranked in relation to significance levels; they belonged to the P <0.05 group when it was not stated otherwise. A visualization of the effects, namely the down-regulation of the C-hordein gene and the relative changes in steady-state mRNA levels associated with the other storage proteins and AA metabolic pathways described by Lange et al. (2007), is presented in Fig. 1. This diagrammatic representation of the relative changes provides a visual confirmation and extension of the changes in protein and AA profile reported by Lange et al. (2007) and illustrates the trends obtained.
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) or decreases (
). Closed triangles, changes in gene expression studied by cDNA microarray (P <0.05); open triangles, changes in protein and amino acid levels (Storage proteins
Lange et al. (2007) reported that the hordein fraction was reduced from 52.3% to 41.3% of the combined amounts of albumins, prolamins, and glutelins in the antisense line compared with cv. Golden Promise. The changes in the relative proportions of the hordein fractions were also reported; higher contents of D- and
/B-hordein (7.0% versus 4.9%, and 60.6% versus 58.5%) were observed in the transgenic line (Lange et al., 2007). By contrast, the C-hordein content was reduced to 31.1% in the transgenic line compared with 35.4% in the donor variety Golden Promise (Lange et al., 2007). The relative content of albumin/globulin of the transgenic line was slightly lower than in Golden Promise (8.6% versus 9.2%), while the relative glutelin content increased (50.1% versus 38.5%).
The microarray data indicated a down-regulation of the transcription of C- and D-hordein-encoding genes, while there was an up-regulation of B- and -hordein genes (Fig. 1, Tables 1, 2). In addition, there was an up-regulation of the gene encoding barley prolamine-binding factor (BPBF) (Fig. 1, Table 1), a transcription factor that regulates B-hordein genes (Mena et al., 1998). The array results were confirmed by real-time RT-PCR (Table 3). The C-hordein transcription was thus down-regulated by a factor of 5.7. It was also found that the transcription of the barley homologue of the rice glutelin gene was up-regulated (Fig. 1, Table 1), correlating with the increased glutelin content of the transgenic line, while the transcription of the globulin storage protein gene was down-regulated (Fig.1, Table 2), corresponding to the decreased albumin/globulin content of the transgenic line (Lange et al., 2007).
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Sulphur-containing proteins and amino acids
The AA analyses of the transgenic line indicated a 12% increase in methionine and an 18% increase in cysteine content compared with the donor variety (Lange et al. 2007). In the present microarray experiments, several genes, including sulphite reductase, catalase, S-adenosylmethionine synthetase 1 (SAM-S1), as well as genes encoding metallothionein-like protein and puroindolines (Fig. 1, Table 1), were found to be up-regulated within the connected pathways of these AAs. Sulphite reductase (EC 1.8.7.1) catalyses the reduction of sulphite to sulphide, whereafter cysteine is generated by cysteine synthase from sulphide and o-acetylserine. Methionine is generated three steps downstream of the cysteine synthesis. Methionine is converted to S-methylmethionine by a reversible reaction catalysed by S-adenosylmethionine synthetase 1 (SAM-S1, EC 2.5.1.6 [EC] ). The up-regulation of the SAMS-1-encoding gene was confirmed by real-time RT-PCR (Table 3). Within the cell, SAM is an important metabolite serving as a major methyl group donor for numerous trans-methylation reactions (Boerjan et al., 1994). In addition, SAM is the precursor of ethylene, polyamines, and nicotianamine (Moffatt and Weretilnyk, 2001). SAM-S1 is also proposed to be involved during drought-stress-induced betaine biosynthesis (Hanson et al., 1995).
Genes involved in cysteine biosynthesis did not show any significant differential regulation in the comparison between cv. Golden Promise and the antisense barley line. The production of cysteine may have peaked earlier, followed by the up-regulation of genes encoding glutathione S-transferase III (EC 2.5.1.1 [EC] 8; GST), which was also overexpressed in the transgenic line (Fig. 1, Table 1). This enzyme has many functions in plants and is inducible by pathogens and dehydration (Taylor et al., 1990) as well as detoxification relating to herbicide resistance (Frear and Swanson, 1970). It can bind directly to auxins (Zetti et al., 1994) and catalyses the formation of anthocyanins (Alfenito et al., 1998). A second gene from the glutathione pathway encoding glutathione reductase (EC 1.8.1.7 [EC] ), which reduces oxidized glutathione (GSSG) to GSH, was down-regulated (Fig. 1, Table 2). GSH is described as a key factor in plant defence mechanisms and S metabolism (Noctor et al., 2002). GSH is also known for its transport function of reduced non-protein sulphur in higher plants (Rennenberg, 1995), an activity that increases during grain development (Tea et al., 2005).
Genes coding the cysteine- and tryptophan-rich hordoindolines (puroindolines), which are assumed to confer hardness to the endosperm by binding to starch grain, were up-regulated in the transgenic line (Clarke and Wilde, 1994; Gautier et al., 1994, 2000; Amoroso et al., 2004). The hordoindolines are mainly expressed in the endosperm, and only a low level of expression is detectable in the aleurone layer from 14 to 40 days after anthesis (Darlington et al., 2001).
The altered regulatory network of the ‘aspartate family’ pathway
The lysine and threonine content of the transgenic line increased by 15% and 9%, respectively. In the lysine pathway, it was found that the gene encoding diaminoepimelate epimerase 2 (DAP2) was up-regulated (Fig. 1, Table 1). DAP2 (EC 5.1.1.7) catalyses the isomerization of L,L- to D,L-meso-diaminopimelate in the biosynthetic pathway leading from aspartate to lysine. The genes encoding the lysine-rich serine proteinase inhibitor (chymotrypsin-subtilisin inhibitor 2A; CI-2A), the barley alpha-amylase inhibitor, and the trypsin/factor XIIA factor were all up-regulated (Fig. 1, Table 1). These inhibitor proteins act as regulators of endogenous proteinases, but also have been suggested to have a protective role against insects and putatively function as storage proteins. CI-2A was the only up-regulated gene for which the array data and the real-time RT-PCR data differed, with a 1.7-fold up-regulation versus a 2.3-fold down-regulation (Table 3). This could result from the high specificity of the primer set compared with the longer probe (<450 bp) of the array. The array probe of CI-2A could theoretically cross-hybridize to related gene family members such as CI-1A and CI-1B.
The glutamine, proline, and asparagine pathways
The AA measurements revealed a 6% reduction in glutamine/glutamate, a 12% reduction of proline, and a 13% increase in the asparagine/aspartate level (Lange et al., 2007). Interestingly, proline biosynthesis-related genes were not affected in the transgenic line. However, it was found that the gene encoding the key enzyme of proline biosynthesis (Szoke et al. 1992), pyrroline-5-carboxylate synthetase (P5CS; EC 2.7.2.11
[EC]
), exhibits a high level of expression at 10 DAP (M Hansen, unpublished results).
Down-regulation of genes encoding mitochondrial glutamate dehydrogenase 2 (GDH; EC 1.4.1.3) and glutamine synthetase 1 (GS1; EC 6.3.1.2) was observed (Fig. 1, Table 2). The GS down-regulation was in the significance range of P <0.1. Both GS and GDH are involved in glutamine/glutamate metabolic pathways (Miflin and Habash, 2002; Purnell et al., 2005; Kichey et al., 2006).
The increased asparagine/aspartate level in the transgenic line may correlate with the increased glutelin protein level, as this storage protein is characterized by high asparagine/aspartate and lysine content (Shewry, 1993; Lange et al., 2007). Contrary to expectation, the asparagine synthetase (AS; EC 6.3.5.4) gene was found to be down-regulated at P <0.1 (Fig. 1, Table 2). Genes encoding AS are known to be light-repressed, while their transcripts accumulate to high levels in darkness (Lea et al., 2007, and references therein). As the grains were harvested at 10.00 hours this could explain the results, but further experiments are needed to confirm the actual expression pattern of the AS genes in the transgenic line.
The aromatic pathway leading to phenylpropanoid production
In the transgenic line phenylalanine content was reduced by 6%. For the aromatic phenylalanine biosynthetic pathway, the gene encoding prephenate dehydratase (PDT; EC 4.2.1.51
[EC]
), which converts prephenate to phenylpyruvate, was found to be down-regulated (Table 2). However, PDT has not been characterized in higher plants, although the compound is used for phenylalanine production in bacteria (Haslam, 1993).
A gene encoding histidinol dehydrogenase (EC 1.1.1.23 [EC] ), which is involved in the biosynthetic pathway of the aromatic AAs and correlated with the increased level of histidine (9%) (Lange et al., 2007), was up-regulated (Table 1). This bifunctional enzyme catalyses the sequential NAD-dependent oxidations of L-histidinol to L-histidinaldehyde and then to L-histidine (Bürger and Görisch, 1981).
Antisensing C-hordein biosynthesis affects interconnecting pathways
This study illustrates that gene expression profiling with cDNA microarrays is a valuable tool for evaluating the pleiotropic effects of selectively inhibiting C-hordein biosynthesis. It is apparent that the inhibition of the genes encoding this specific group of storage proteins has an effect on a number of other pathways. The lower amount of C-hordein was correlated with the transcriptional down-regulation of the C-hordeins. A prominent effect on the entire pathway that generates sulphur-rich AAs, methionine, and cysteine was also found from the aspartate family pathway. This increase may be triggered by an up-regulation of B-hordein biosynthesis, possibly relating to an increase in the BPBF transcription factor, a positive regulator of B-hordein genes. The reduced synthesis of C-hordeins probably redirected the production of S-rich storage proteins, e.g. B- and -hordein. This may have caused an up-regulation of other genes encoding S-rich proteins as well (Fig. 1, Table 1). Furthermore, the transgenic line has an increased lysine level, together with a higher content of the lysine-rich storage protein, glutelin (Lange et al., 2007). In agreement with this, a transcriptional up-regulation of lysine-rich proteins, including barley homologue of rice glutelin, was found.
The up-regulation of the genes encoding SAM-S and MT3 can be correlated with the increased methionine and cysteine AA content (Lange et al., 2007), as well as with the accumulation of GSSG, and the subsequent formation of polymeric protein–glutathione mixed sulphide (Tea et al., 2005). During this process, one molecule of GSH is regenerated and used as a template by GSTIII; this could explain the significant down-regulation of GR and up-regulation of GSTIII (Tables 1, 2).
In general, there appears to be good agreement between the gene expression data and protein and AA analyses. It is apparent from the transcriptomics and protein and AA analysis data that the down-regulation of C-hordein leads to alterations in a range of metabolic pathways in the developing barley grain. However, the alterations did not appear to have any negative impact, such as growth retardation, as seen in transgenic studies in Arabidopsis (Zhu and Gallili, 2003), and in canola and soybean (Falco et al., 1995), or extensive phenotypic effects as seen in maize and barley high-lysine mutants. Further studies and field trial experiments will reveal whether the antisense C-hordein approach will be useful for improving the nutritional value of the barley grain and for reducing the environmental nitrogen load.
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Supplementary data |
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TopAbstractIntroductionMaterials and methodsResults and discussionSupplementary dataReferences |
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The supplementary data, which can be found at JXB on line, consist of three tables.
Table 1. The list of the 1035 genes spotted on the array.
Table2. Significantly regulated genes from the developing grain-specific microarray. The 139 genes (P <0.05) are described with a specific library name from Clemson University (http://www.genome.clemson.edu/projects/barley/).
Table 3. Specific primers used for real-time RT-PCR.
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Acknowledgements |
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We would like to thank KB Nellerup and OB Hansen for their excellent technical support. This work was supported by a grant (93S-943-F07-00047) from The Danish Directorate for Food, Fisheries and Agri Business.
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