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Keywords:

  • abscisic acid (ABA);
  • anhydrobiosis;
  • dehydration stress;
  • desiccation tolerance;
  • moss;
  • Physcomitrella patens;
  • transcriptional profiling

Summary

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods and Materials
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information
  • • 
    Dehydration tolerance was an adaptive trait necessary for the colonization of land by plants, and remains widespread among bryophytes: the nearest extant relatives of the first land plants. A genome-wide analysis was undertaken of water-stress responses in the model moss Physcomitrella patens to identify stress-responsive genes.
  • • 
    An oligonucleotide microarray was used for transcriptomic analysis of Physcomitrella treated with abscisic acid (ABA), or subjected to osmotic, salt and drought stress. Bioinformatic analysis of the Physcomitrella genome identified the responsive genes, and a number of putative stress-related cis-regulatory elements.
  • • 
    In protonemal tissue, 130 genes were induced by dehydration, 56 genes by ABA, but only 10 and eight genes, respectively, by osmotic and salt stress. Fifty-one genes were induced by more than one treatment. Seventy-six genes, principally encoding chloroplast proteins, were drought down-regulated. Many ABA- and drought-responsive genes are homologues of angiosperm genes expressed during drought stress and seed development. These ABA- and drought-responsive genes include those encoding a number of late embryogenesis abundant (LEA) proteins, a ‘DREB’ transcription factor and a Snf-related kinase homologous with the Arabidopsis ABA signal transduction component ‘OPEN STOMATA 1’.
  • • 
    Evolutionary capture of conserved stress-regulatory transcription factors by the seed developmental pathway probably accounts for the seed-specificity of desiccation tolerance among angiosperms.

Introduction

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods and Materials
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

The green plants constitute one of the major classes of eukaryotes on the planet, comprising approx. 500 000 species. Phylogenetic and palaeobotanic evidence suggests that the present variety of land plants diversified from a single colonization of the land during the mid-Ordovician period (c. 480 million yr ago; Kenrick & Crane, 1997). Fundamental to the success of plants in colonizing a terrestrial habitat is the acquisition of adaptations to an uncertain supply of water. The currently dominant taxa among the land plants – the tracheophytes – display numerous anatomical adaptations to the terrestrial environment, including ramifying root systems to scavenge water from the substratum, extensive vascular tissues for its delivery throughout the plant, and stomates, cuticles and lignin that restrict evaporative loss, whilst facilitating gas exchange, and providing mechanical strength. By contrast, the first plants to assume a terrestrial lifestyle lacked these adaptations and must, necessarily, have exhibited a variety of biochemical and physiological mechanisms to ensure their survival during times of drought (Oliver et al., 2005).

Most bryophytes retain the property of vegetative desiccation tolerance, in the form of anhydrobiotic survival, and occupy niches characterized by frequent cycles of dehydration and rehydration (Dilks & Proctor, 1974). In the evolution of the vascular plants, this property has been lost, in favour of the adaptations associated with added complexity and increased diversity. True desiccation tolerance, in the form of anhydrobiotic survival, has become restricted to the protection of metabolically quiescent reproductive propagules: spores and pollen (sometimes) and seeds (usually) (Oliver et al., 2000). In only a few remarkable species (termed ‘resurrection plants’) has vegetative desiccation tolerance re-evolved within the tracheophyte phylogeny (Ingram & Bartels, 1996; Bartels, 2005).

Nevertheless, many processes characteristic of the early stages of embryonic desiccation tolerance may be recognized within water-stressed vegetative tissues. These include the early accumulation of compatible osmolytes, and of potentially stabilizing compounds such as proline, glycine-betaine, polyhydric alcohols and disaccharides (Bianchi et al., 1991; Ishitani et al., 1995; Yoshiba et al., 1995; McKue & Hanson, 1996). ABA coordinates these stress responses, mediating physiological processes such as stomatal closure (an immediate response to restrict evaporative water loss), osmolyte accumulation, and also the synthesis of stress-related proteins, including late embryogenesis abundant (LEA) and heat shock proteins (HSPs), as well as compounds associated with the scavenging of reactive oxygen species that are implicated in desiccation-related membrane damage (Leopold et al., 1991; Ingram & Bartels, 1996; Hoekstra et al., 2001).

The molecular responses to dehydration in higher plants have been studied by genome-wide microarray analysis of gene expression processes in the model angiosperm, A. thaliana, resulting in the identification of several hundred individual genes whose expression is induced by dehydration stress, salinity stress and cold stress, as well as an additional subset of c. 150 genes expressed during the recovery from these stresses. The identification of groups of coregulated genes has enabled the identification of common sequence motifs among the promoters of these genes, and the identification of the transcription factors that regulate their expression (Seki et al., 2002; Oono et al., 2003; Shinozaki et al., 2003).

Since dehydration tolerance is an ancient evolutionary adaptation within the plant kingdom, it is of clear interest to determine the extent to which common genetic mechanisms leading to dehydration stress and desiccation tolerance have been conserved, and to identify the processes by which the phenomenon of desiccation tolerance has become developmentally restricted within the higher plant lineages. For the desiccation-tolerant moss Tortula ruralis, the ability to survive rapid and complete desiccation appears to rely on an ABA-independent, constitutive mechanism supported by the induction of a repair-associated gene set upon rehydration (Oliver, 1991; Oliver et al., 2004, 2005). Such a mechanism is not universal among bryophytes, however, and in the dehydration-resistant, but desiccation-sensitive, moss Physcomitrella patens, ABA-related induction of stress-related gene products, clearly homologous with higher-plant stress-related genes, is associated with the response to, and survival of, both dehydration stress (Knight et al., 1995; Machuka et al., 1999; Frank et al., 2005; Kamisugi & Cuming, 2005; Oldenhof et al., 2006), and of freezing tolerance (Minami et al., 2003; Takezawa & Minami, 2004; Oldenhof et al., 2006).

The developing genomic resources available for Physcomitrella have been exploited, using an oligonucleotide microarray to identify a larger set of genes expressed in response to ABA and water stress in a near relative of the earliest land plants. A number of genes whose stress-related expression is conserved between moss and angiosperms were identified. Analysis of the putative promoter regions of these genes identifies a number of potential cis-acting elements similar to those identified in stress-induced genes of higher plants. A number of GC-rich sequence elements were also identified that appear significantly over-represented in the promoters of the induced gene set, and that represent candidates for further functional characterization.

Methods and Materials

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods and Materials
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Plant material

Physcomitrella patens ssp. patens (Hedwig) ecotype ‘Gransden 2004’ was propagated in culture as described by Knight et al. (2002). Protonemal tissue was subcultured at weekly intervals on cellophane overlays on solid BCD medium containing 5 mm ammonium tartrate. Treatment with abscisic acid and osmotic stressing agents was applied to protonemal (largely chloronemal) tissue, 6 d following subculture: the cellophane overlays were transferred on to filter paper soaked with liquid BCD medium containing 5 mm ammonium tartrate and additional supplements: cis-trans ABA was added to a final concentration of 10−5 m; mannitol was added at a final concentration of 10% (w/v) and NaCl at a final concentration of 0.3 m. Tissue was incubated for 2 h before harvesting. For dehydration treatments, the cellophane-grown moss was transferred directly to the plastic base of a 9 cm Petri dish by inverting the cellophane and peeling it away from the protonemal tissue. Dishes were placed without lids in desiccators containing saturated NaCl to provide an atmosphere of relative humidity = 75% (Young, 1967). The extent of fresh-weight loss by the tissue was monitored by weighing the dishes at intervals following the onset of treatment. Tissue was harvested and squeezed dry before freezing in liquid nitrogen and storage at –70°C before RNA isolation.

Microarray analysis

Total RNA was isolated from moss tissue by aqueous phenol extraction, as described by Knight et al. (2002). Two replicate samples for each treatment were extracted and the quality of RNA samples was monitored in two ways. First, equivalence of stress-induced gene expression between replicate samples was checked by RNA gel blot hybridization using a cDNA probe corresponding to a transcript previously known to be induced by all four stress treatments (PpLEA-2: AW497323). Second, integrity of the RNA was determined on an Agilent 2100 bioanalyser using an RNA 6000 LabChip kit. An Agilent-certified microarray service lab (MOgene, LC, St. Louis, MO, USA) was used to perform the microarray experiments. Gene-specific 60-base oligomers were printed on to glass slides by Agilent Technologies Inc. RNA samples (2.5 µg) were labelled using the ULS-Cy 3/5 ULS aRNA Labelling Kit (product no. EA-006, Kreatech Biotechnology, San Diego, CA, USA). As a quality control, a dye swap for labelling RNA samples was performed. Once the samples were labelled with reciprocal Cy fluorescent dyes, equal amounts (1 µg) of samples were combined in nuclease-free water and processed using the Gene Expression Hybridization Kit (product no. 5188-5242, Agilent, Palo Alto, CA, USA). The sample was then placed between the Agilent backing slide and the microarray chip, sealed in the hybridization chamber and set to hybridize for 17 h in a 60°C rotating hybridization oven. Upon completion, the slides were washed sequentially in 6 × SSC (0.9 m NaCl, 90 mm Na-acetate, pH 7.0) buffer at room temperature, then 0.1 × SSC (0.15 m NaCl, 15 mm Na-acetate, pH 7.0) on ice. Slides were then dried using nitrogen gas and placed in holders, and scanned using the DNA Microarray Scanner (no. G2565BA, Agilent) with the Agilent Scan Control software. The fluorescent intensities of each feature were extracted using the Feature Extraction Software with default parameters (version 9.1, Agilent). The raw intensity data then were loge-transformed for normalization before anova (mixed model) analysis. When the raw intensities of both Cy3 and Cy5 channels were below 150 (typical background intensity is 40) and the signal-to-background ratio below 2, the genes were removed from further analysis. Log ratios among different samples and the P-values were calculated using the mixed model (Wolfinger et al., 2001). A gene was considered as a significant change in gene expression based on the twofold cutoff with P-values < 0.05.

RNA blot hybridization

RNA gel blot hybridization was used to identify individual transcripts using a subset of selected cDNA probes as indicated. Probes were isolated by restriction enzyme digestion of EST clones, for labelling. Gel electrophoresis, blotting, probe synthesis, hybridization and detection were carried out as previously described (Kamisugi & Cuming, 2005).

Gene identification

The genomic sequences corresponding to individual microarray features were retrieved from the Physcomitrella genome sequence assembly, version 1 (http://genome.jgi-psf.org/Phypa1_1/Phypa1_1.home.html) using blast searches (Altschul et al., 1990). The repeat-masked genome assembly was searched with the sequences of the EST contigs from which the microarray oligonucleotides were designed, using the blastn tool, following their retrieval from NIBB Physcobase (http://moss.nibb.ac.jp). Gene models were selected, where possible, by alignment with cDNA sequences. Where cDNA sequences were incomplete, the intron and exon sequences determined by the gene prediction software were manually curated following pairwise comparison between the translated Physcomitrella genomic assembly and the polypeptide sequence of the closest plant homologues using blastx and tblastn alignment, and the gene models annotated. Cis-acting sequences previously identified in promoters of higher plant genes were identified in 1 kb lengths of Physcomitrella DNA sequence located immediately 5′- to the gene coding sequence using the PlantCARE search tool (Lescot et al., 2002: http://bioinformatics.psb.ugent.be/webtools/plantcare/html/). Hexameric sequence motifs that were relatively over-represented in the promoters of the ABA- and stress-induced gene set were determined by using the tair motif finder software (http://arabidopsis.org/tools/bulk/motiffinder/index.jsp).

Gene retrieval

Gene models for all the features up- and down-regulated in this study can be retrieved from the Physcomitrella Genome Browser v1.1 using the protein ID number assigned to each chip feature in Tables S1 and S2 (Supplementary material), as follows: (i) go to http://genome.jgi-psf.org/Phypa1_1/Phypa1_1.home.html and select ‘Search’; (ii) scroll down to ‘Gene models’ and select ‘Protein id’ in the drop-down menu; (iii) enter the ID number and click ‘Search models’– results are returned as ‘Model search results’; (iv) clicking on ‘Model ID’ links to the gene model page (gene and transcript sequence, polypeptide sequence, annotation details).

Results

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods and Materials
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Microarray analysis

The microarray for Physcomitrella was designed based on the 22 895 cDNA contigs obtained from Physcobase (http://moss.nibb.ac.jp). These represented the total available publicly accessible EST set generated by the Leeds University Physcomitrella EST programme and the National Institute for Basic Biology (Nishiyama et al., 2003). The 3′ region in each contig was targeted for computational generation of 60-base oligomers. Among 190 784 oligomers generated, 21 939 were selected based on melting temperature (Tm) range, the number of Gs, complexity such as repeats and simple sequences, RNA secondary structure and uniqueness based on blast score. The blast was performed against the Dec-01-03 version of nucleotide sequences downloaded from NCBI (http://www.ncbi.nlm.nih.gov). The E-value cutoff used was 1E−06 using blastn. These oligomers were fabricated on the chip. Because the cDNA contigs from which these oligonucleotides were designed have since undergone several revisions, each feature on the chip has been denoted by a GenBank accession number assigned to a representative cDNA clone. These will be further denoted by a gene model accession number when the genomic sequences are released via GenBank. Initial microarray experiments compared transcripts induced by ABA-treated protonemal tissue with protonemal tissue incubated in hormone-free medium. Tissue was treated with 10−5 m ABA for 2 h before harvest. The principal effect of ABA treatment was to cause the appearance of new transcripts (Fig. 1): 60 features indicated significant (twofold or greater) up-regulation, by comparison with only four features whose corresponding transcript abundances fell by the same amount.

image

Figure 1. Microarray analysis of abscisic acid (ABA)-regulated genes. A dot-matrix plot of the signal intensities of each feature on the microarray chip for Cy3-labelled ABA-treated probe (Intensity 2) vs Cy5-labelled control probe (Intensity 1), plotted on a log10 scale. The two red lines indicate the values at which genes are twofold up- or down-regulated. Red data points are indicated as up-regulated by the Agilent software, and green data points as down-regulated. Only those genes indicated as outside the twofold threshold of change in expression were analysed in detail.

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Because of the interrelationship between ABA and drought, osmotic and salt stresses, a further series of analyses was undertaken of transcript abundance in protonemal tissue subjected to these treatments. Salt stress resulted from incubation in the presence of 0.3 m NaCl, whilst osmotic stress resulted from incubation in the presence of 10% mannitol. Each of these treatments was applied for 2 h before harvest of tissue. Drought stress was applied by controlled drying of tissue in an atmosphere of 75% relative humidity. Tissue was harvested at intervals (Fig. 2) and monitored for induction of a candidate stress-related transcript (the PpLea-2 gene product: feature 15287 on the microarray), and for viability following rehydration. Figure 2(a) shows the rate of water loss by individual batches of protonemal tissue over a period of 24 h, and Fig. 2(b) indicates the accumulation of the PpLea-2 transcript in tissue harvested at progressive stages of dehydration, detected by northern blot hybridization. Tissue dehydrated to 84% water loss was able to resume normal growth following rehydration. Tissue dehydrated to 90% water loss or greater was unviable. There was a general (but inexact) correspondence between the extent of water loss and the accumulation of the PpLea-2 transcript, and, significantly, RNA extracted from highly dehydrated tissue (95% fresh weight loss) had undergone some degradation (Fig. 2b).

image

Figure 2. Dehydration of moss Physcomitrella protonemal tissue. (a) Time-course of dehydration of protonemal tissue. Water loss was determined from three replicate plates for each time point except 24 h (six replicate plates). (b) RNA gel blot hybridization of mRNA isolated from tissue dehydrated to different extents: following blot transfer, the blot was hybridized with a cDNA probe corresponding to the group 2 late embryogenesis abundant (LEA) protein gene, PpLEA-2 (chip feature 15287: EST clone AW497323). The autoradiograph and the corresponding filter stained with methylene blue is shown so that unequal loading of RNA can be taken into account. The region of the filter shown contains the 18SrRNA (topmost band) and fragments derived from 23S and 16S chloroplast rRNA. Tracks contain: 1, control RNA; 2, 8% water loss; 3, 11% water loss; 4, 16% water loss; 5, 30% water loss; 6, 60% water loss; 7, 95% water loss.

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Messenger RNA derived from tissue that had undergone c. 84% fresh weight loss was used to generate the hybridization probe for microarray analysis. The results of this analysis are summarized in Fig. 3, with further detail provided in Tables S1 and S2. The complete datasets have been deposited in ArrayExpress (Array A-MEXP-646; Experiment E-TABM-225). Drought treatment resulted in the largest number of up-regulated transcripts being detected, with 134 features identified as indicating twofold up-regulation or greater. Osmotic stress (11 features) and salt stress (nine features) were less effective in inducing the accumulation of new transcripts. Drought treatment also resulted in the largest number of down-regulated transcripts (84 features). Because the features on the chip were based on EST sequences clustered in 2003, subsequent genomic analysis has identified that, in some cases, the oligonucleotides correspond to different regions of the same gene. Consequently, the number of genes represented by these features is slightly fewer than the number of chip features.

image

Figure 3. Genes up- and down-regulated by abscisic acid (ABA) and stress treatments. Transcripts exhibiting significant changes (> twofold) in abundance following 2 h treatment with 10−5 m ABA (ABA), 2 h incubation on 10% mannitol (mannitol), 2 h incubation on 0.3 m NaCl (salt) and dehydration to 84% fresh weight loss (drought). Numbers in brackets indicate the numbers of genes, where some chip features correspond to different sequences within the same transcript.

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There is considerable overlap between the sets of genes regulated by the different treatments, with 49 of the 56 ABA-up-regulated genes also showing increased expression in response to at least one other treatment. Four genes were induced by all four treatments, and seven by three of the treatments. Of the smaller numbers of genes induced in response to salt- and mannitol-induced osmotic stress, all but one were also up-regulated by one or more additional treatment. The single gene expressed only in response to salt treatment (feature 2398) encodes a glutathione-S-tranferase most similar to the product of an Arabidopsis gene annotated as ‘ERD’ (early response to dehydration). Of the larger number of ABA- and drought-induced genes, seven were exclusively ABA-induced, while 70 were only induced by drought.

Many of the genes up-regulated by stress and ABA share significant homology with higher plant genes whose expression is ABA- and stress-regulated. The polypeptides encoded by these genes were used in blast searches of the plant protein database, and the gene products assigned functional categories following gene ontology analysis. The results of this analysis are summarized in Fig. 4, and the sequences of the polypeptides encoded by both up- and down-regulated genes are provided in Tables S1 and S2. A significant subset of the strongly up-regulated genes (n = 16) were found to contain amino acid sequence motifs characteristic of LEA proteins (Table 1). The majority of these have the characteristic signatures of group 3 LEA proteins, while two contain motifs typical of the group 2 (‘dehydrin’) gene family. Several other sequences have homology with higher plant proteins whose GenBank annotations directly associate their expression with ABA and abiotic stress treatments, including drought, cold and salt stresses (Table 2). Additionally, a number (n = 14) encode proteins with membrane association, involved in either signalling or transmembrane transport of solutes: an important feature of osmoregulation in response to water deficit stress in plants (Table 3). Ten genes encoded polypeptides with no significant homologues, and thus correspond to novel moss-specific genes. This category included the most strongly up-regulated gene (feature 5076) and a related transcript (feature 18538) up-regulated 16.8-fold and threefold by drought stress, respectively. The majority of genes down-regulated by drought stress encode chloroplast components, most being photosynthesis-associated (Fig. 4; n = 53).

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Figure 4. Functional categorization of up- and down-regulated genes. Conceptual translation of the up- and down-regulated genes was used to determine the polypeptide sequences of their products. blastp analysis of the plant protein database was used to identify their nearest homologues and their likely functions were further characterized by GO function searches. ABA, abscisic acid; LEA, late embryogenesis abundant; HSP, heat shock protein.

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Table 1. Physcomitrella late embryogenesis abundant (LEA) genes up-regulated by abscisic acid (ABA)- and stress treatment
FeatureProtein IDAMSDAnnotation
  • The up-regulation for each gene is indicated: A, ABA; M, 10% (w/v) mannitol; S, 0.3 m NaCl; D, dehydration to 84% fresh weight loss.

  • a

    Three identical tandemly arrayed genes recognize chip feature 11860: see Table 5.

  • b

    This chip feature was designed from an incompletely spliced transcript and thus has reduced identity with the mature mRNA.

155571665666.425.613.09 7.61Group 3 LEA
180081665667.654.103.2015.95Duplicate of above
19261b1665662.51   3.04Duplicate of above
11860228647a6.993.17  4.49Group 3
102522119986.462.51  9.37Group 3
152871733313.593.082.44 3.97Group 2 LEA
81282286683.53   4.77Group 3
28042286692.84   7.22Group 3
208692286733.50   3.31Group 3
138582286753.25   5.88Group 3
167832286812.692.11  3.20Group 3
15827166565    4.51Group 3
5581166565    2.26Duplicate of above
128642236702.91   3.65Group 3
164612236702.44   2.87Duplicate of above
53502286683.13   3.08Group 3
155952286972.62   3.26Group 3
162242287102.12   2.8Group 3
17721228735    2.51Group 2-like
19583228736    2.45Group 3
Table 2.  Other Physcomitrella genes homologous with flowering plant abscisic acid (ABA)- and stress-induced genes
FeatureProtein IDAMSDFlowering plant annotation
  • The up-regulation for each gene is indicated: A, ABA; M, 10% (w/v) mannitol; S, 0.3 m NaCl; D, dehydration to 84% fresh weight loss.

  • a

    Chip feature 6933 identifies two near-identical genes encoding Protein ID205434, and Protein ID 70357.

4902286453.57  4.23Unknown dehydration-associated (Xerophyta humilis)
60272286543.723.36 3.78At5g01300 cold-regulated phosphatidylethanolamine binding protein
92772286742.60  3.86AT3g05500 stress-related rubber elongation factor
137622286782.412.402.265.56WCOR413 cold-stress related
2398228689  2.17 Glutathione-S-transferase ‘ERD’
71951101352.33  3.07At3g50830.1 cold-acclimation protein
189141811422.05  4.51At3g50830.1 cold-acclimation protein
16491177939   2.76ERD-1 ATP-binding chaperone (chloroplast?)
6933205434a   2.22Small heat-shock protein.
70357 a     
4257171674   2.13Ethylene-responsive rice protein: contains ‘universal stress protein’ domain
13165228750   2.09HSP40 type heat-shock protein (DNAJ domain)
7842215149   3.03ALDH21 family aldehyde dehydrogenase
Table 3.  Membrane-associated abscisic acid (ABA)- and stress up-regulated genes
FeatureProtein IDAMSDAnnotation
  1. The up-regulation for each gene is indicated: A, 10−5 m ABA; M, 10% Mannitol; S, 0.3 m NaCl; D, dehydration to 84% fresh weight loss.

176841660824.85  4.29AWPM-19 membrane channel protein
202132286632.78  2.34At2g47770 benzodiazepene receptor like
162342286762.98  4.73AWPM-19 membrane channel protein
137622286782.412.402.265.56WCOR413 cold-acclimation protein
155312286952.21  2.13At1g22710 sucrose transporter
71951101352.33  3.07WCOR413 cold-acclimation protein
189141811422.05  4.51WCOR413 cold-acclimation protein
69672286982.26   AWPM-19 membrane channel protein
145091643912.35  2.43Chloroplast envelope protein
5415109889   2.64Voltage-dependent ion channel
177381911072.29  2.96Tonoplast intrinsic protein (aquaporin)
3290228745   2.19Predicted integral membrane protein
4457228747   2.16Calcium exchange protein
5484189127   2.00Sugar transporter

Among the drought up-regulated genes, two encode proteins with possible functions in the ABA and/or drought-stress response. A gene encoding a Snf-related protein kinase similar to the Arabidopsis gene ‘OPEN STOMATA1’ (OST1) was induced 3.4-fold (chip features 19662 and 7931; protein ID 228733), and a gene encoding a member of the Apetala-2 ‘DREB’ transcription factor family (chip feature 3326; protein ID 228738) showed 2.4-fold induction. OST1 is both ABA-induced and required for ABA-mediated stomatal closure in Arabidopsis (Mustilli et al., 2002), while DREB transcription factors activate drought-inducible gene expression (Shinozaki et al., 2003).

Microarray analysis provides a powerful and rapid means of identifying genes that are differentially regulated in response to abiotic stresses, but it is a technique that is subject to many sources of experimental variability, and it is prudent to verify the results obtained using an alternative means of estimating steady-state transcript abundance. A number of genes were therefore selected whose sequence analysis indicated that they encoded LEA proteins, and their transcript abundance was independently determined by northern blot hybridization. The results obtained (Fig. 5) generally confirmed the accuracy of the microarray analysis for these sequences. For each of the LEA genes analysed, the highest transcript abundances were observed following ABA and drought treatment, with significantly lower increases in transcript abundance occurring in response to treatments with 10% mannitol and 0.3 m NaCl. Notably, although these two treatments were much less effective in inducing transcript accumulation than ABA and drought treatment, an increase in steady-state transcript abundance was detectable by blot hybridization in relation to the control samples for these treatments. This is in agreement with several studies that have noted that microarray analysis, whilst an excellent tool for large-scale identification of up-regulated sequences, can significantly underestimate the true extent of transcript accumulation (Yuen et al., 2002; Barczak et al., 2003). Some genes are represented by duplicate chip features. Generally, the amounts of transcript induction detected by these features correspond well, although it is well attested that different oligonucleotide designs can result in markedly different signal intensities corresponding to the same transcript (Barczak et al., 2003). In one case (the gene encoding group 3 LEA protein 166533), one chip feature (19261) was designed from an incompletely spliced EST contig, and so has only partial homology with the mature transcript (Table 1).

image

Figure 5. RNA gel blot hybridization with selected cDNA probes. RNA used for the various chip hybridizations was analysed by RNA gel blot hybridization with selected cDNA probes. C, control treatment; A, 10−5 m abscisic acid (ABA); M, 10% (w/v) mannitol; S, 0.3 m NaCl; D8, dehydration to 84% water loss; D9, dehydration to 95% water loss. Probes used were as follows: panel 1, feature 15557/18008 (group 3 LEA: EST clone BQ827691); 2, feature 17684 (AWPM-19 membrane channel protein: EST clone BQ041987); 3, feature 6027 (cold-regulated phosphatidylethanolamine-binding protein: EST clone BQ826761); 6, feature 17209 (protein of unknown function: EST clone AW476845); 7, feature 15287 (PpLEA-2: EST clone AW497323); 8, feature 8128 (group 3 LEA protein: EST clone BQ826612); 9, feature 13858 (group 3 LEA protein: EST clone BQ827490); 10, feature 15827/5581 (group 3 LEA protein: EST clone BQ827063). Equivalence of sample loading is shown in panels 4 and 5; methylene blue-stained RNA transferred to the nylon membrane on each of two filters that were successively probed, stripped and re-probed. Panel 4 corresponds to hybridizations 1–3 and panel 5 to hybridizations 6–10. The region of the stained filters shown contains 26S rRNA (topmost band) and 18S rRNA, and fragments derived from the chloroplast 23S and 16S rRNA (these fragments derive from denaturation of the rRNA molecules which contain ‘hidden breaks’).

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The transcriptional response to ABA is very rapid. The significant transcript accumulation that occurred in response to ABA treatment did so within 2 h of the application of the growth regulator. To elucidate the rate of the response in more detail, the accumulation of selected transcripts was monitored at very much shorter intervals during this two-hour period. Northern blot analysis demonstrates that, for representative LEA transcripts, accumulation of transcript can be observed during the first 15 min of application, with transcript abundance showing a steady increase throughout the 2 h period (Fig. 6).

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Figure 6. Time-course of late embryogenesis abundant (LEA) mRNA accumulation. RNA was harvested at intervals following the application of 10−5 m abscisic acid (ABA) and analysed by RNA gel blot hybridization with a selection of cDNA probes encoding group 3 LEA proteins. Track 1, control (zero time); 2, 15 min; 3, 30 min; 4, 45 min; 5, 60min; 6, 90min; 7, 2 h. Probes used were as follows: panel a, AW497323 (PpLea-2: chip feature 15287; protein ID 173331); b, BU052152 (group 3 LEA: chip features 15557/18008; protein ID 166566); c, AJ225549 (group 3 LEA: chip feature 12864; protein ID 223670); d, BQ827572 (group 3 LEA: chip feature 11860; protein IDs 228647, 228650, 228651); e, AW509984 (plastocyanin: chip feature 17161; protein ID 170637) to monitor RNA loading.

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Promoter analysis of ABA- and stress-regulated genes

The coordinate regulation of gene expression is most frequently mediated by transcriptional induction. Bioinformatic analysis represents a powerful tool with which stress-responsive genes may be recognized through their common promoter elements (Zhang et al., 2005). The sequences 5′-proximal to the mRNA coding sequences (the putative promoters) were therefore examined to identify the presence of conserved sequence motifs that might correspond to binding sites for trans-acting transcription factors, and represent targets for future experimental investigation. Two approaches were taken: a scan for sequences known to be implicated in ABA- and abiotic stress-mediated transcription in higher plants, and an approach not based on a priori expectations, in which all possible hexameric sequences were evaluated for whether they were overrepresented in the promoter regions, relative to the entire sequence of each up-regulated gene. Highly conserved stress-related transcription factors that have been identified in flowering plants include members of the basic domain-leucine zipper (bZip) family that associate with ‘G-box’ elements (motifs containing an ACGT core sequence) in ABA-response elements (ABREs). Such a motif has been previously identified as instrumental in the ABA-induction of the gene PpLea-1, encoding a Physcomitrella group 1 LEA protein (Kamisugi & Cuming, 2005). Additionally, ‘DREB’ transcription factors of the ethylene response element binding factor/APETALA-2 (EREB/Ap2) class interact with dehydration response elements (DREs) (also known as C-repeat (CRTs), or ‘coupling elements’ when found in tandem with ABREs; Shen & Ho, 1995) to mediate expression of genes in response to drought and low-temperature stress. In flowering plants, the DRE/CRT motif contains a conserved A/GCCGAC sequence that is the binding site for these factors. Other transcription factors implicated in similar abiotic stress responses include the basic helix-loop-helix-zipper domain (bHLHZip) MYC factors (binding site CANNTG) and helix-turn-helix MYB factors (binding site YAACTG) (Abe et al., 1997, 2003). Hexanucleotides corresponding to these consensus sequences were found with relatively high frequency in the presumptive promoters, being especially concentrated within the 400 bp region immediately adjacent to the TATA box. The relative distribution of these and other motifs in the promoters of the 25 most strongly up-regulated genes is summarized in Table 4 and Fig. 7.

Table 4.  The 25 genes most strongly up-regulated by abscisic acid (ABA)
GeneFeatureProtein IDAIdentity
  • The up-regulation by ABA is indicated in A.

  • a

    This chip feature identifies three identical tandemly repeated genes.

1180081665667.65Group 3 LEA
2 50762286427.41No significant homologue
 228647a Group 3 LEA: three tandemly arrayed genes recognize the same chip feature
311860228650a6.99 
 228651a  
4102522119986.46Group 3 LEA
5176841660826.42AWPM-19 membrane channel
6185381667064.85Similar to gene 2
7 81652286584.84Protein of unknown function (At5g01750)
8109562286554.22Protein kinase C
9 60272286544.00Cold-regulated PE-binding protein
10146362286433.72Protein of unknown function (At4g31830)
11132002286723.68‘Little protein 1’ (O. sativa)
12152871733313.67Group 2 LEA
13  4902286453.59Unknown dehydration- associated
14 37952286703.57Phosphoglycerate kinase
15 81282286683.55Group 3 LEA
16208692286733.53Group 3 LEA
17138582286753.50Group 3 LEA
18 83162286623.25Alpha-amylase type B isozyme
19 53502286683.16Group 3 LEA
20220552286803.13Possible LEA protein
21 78602286833.08Translation elongation factor 1a
22118172286923.02Unknown – possible protein kinase
23162342286762.98AWPM-19 membrane channel
24128642236702.98Group 3 LEA
25 28042286692.91Group 3 LEA
image

Figure 7. Distribution of putative cis-acting sequences. The first 1000 bp immediately 5′- to the presumptive TATA box in the 25 genes most strongly up-regulated by abscisic acid (ABA; Table 5) were scanned for sequences corresponding to known higher plant cis-acting sequences using the PlantCARE search tool. G-box, ACGT-core motifs; CE3, ‘coupling element’ associated with VP1/ABI3 mediated gene expression; DRE, drought responsive element; LTR, low-temperature responsive element; MBS, MYB-binding site; HSE, heat-shock element; ARE, anaerobic response element; GC-anoxia, GC-rich anoxia response element; HD-Zip, homeodomain-basic leucine zipper binding site; TA-enhancer, TA-rich sequence required for high expression; RHE, rehydration responsive element. Candidate MYC-binding elements are not shown; owing to their degenerate nature, these were too numerous for clear reproduction.

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The search for hexameric sequences identified a number of GC-rich motifs as being significantly over-represented in the promoters of the Physcomitrella ABA- and stress-induced gene set (Table 5). Significantly, the promoters of the Physcomitrella genes are generally less GC-rich overall (41% GC) than the coding sequences (46% GC), implicating these sequences as candidates for cis-acting regulatory elements. Notably, this approach also identified the canonical ACGT-containing elements as being significantly over-represented among the promoters of the induced gene set.

Table 5.  Hexameric sequences significantly over-represented in the promoters of abscisic acid (ABA)- and stress-induced genes
PromoterEntire gene
MotifOccurrencesOccurrences% in promoter
  1. All possible hexameric sequences were identified in the induced gene set, and scored for their occurrence in the promoter and protein-coding sequences. The number of occurrences in each region and the percentage of these in the promoter region are shown. The promoter regions of the entire sequence set represented 45% of the total quantity of sequence analysed, and only those hexamers that occur in promoters with a frequency > 45% are shown. Hexamers that correspond to all or part of an ACTG-containing ‘G-box’ element are in bold type.

CCCCCC18826371.48
GGGGGG18826371.48
GGGCCC 6810465.38
GCGCGC 44 6864.71
CGCGCG 50 8260.98
CACGTG12622456.25
ACGTGG15628055.71
CCACGT15628055.71
GGCCCC 6111951.26
GGGGCC 6111951.26
GGGGGA10020249.50
TCCCCC10020249.50
CCCCCA10221747.00
TGGGGG10221747.00
CCCCCG 5211146.85
CGGGGG 5211146.85
CGCGCC 37 8046.25
GGCGCG 37 8046.25
CGTGGC12727745.85
GCCACG12727745.85
CCCGCG 33 7345.21
CGCGGG 33 7345.21

Discussion

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods and Materials
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

During dehydration, substantial accumulation of novel transcripts was observed, many of which are also induced by the growth regulator ABA, and which encode conserved members of gene families associated with the acquisition of desiccation tolerance. A significant number of these encode LEA proteins: a class of protein originally identified in seeds during the later stages of embryogenesis, and since found to be highly conserved in other anhydrobiotic taxa, including green algae (Honjoh et al., 1995), nematodes (Browne et al., 2001) and rotifers (Tunnacliffe et al., 2005). LEA proteins are believed to relieve the consequences of desiccation through sequestration of water or ions (Cuming, 1999; Hoekstra et al., 2001), acting as chaperone-like ‘molecular shields’ (Goyal et al., 2005) or through structurally reinforcing the cell following desiccation-induced structural changes (Goyal et al., 2003; Wise & Tunnacliffe, 2004). Thus, there appears to be a close correspondence between the responses of ABA- and dehydration-stressed Physcomitrella protonemal tissue and the preparations made by the seeds of higher plants for the desiccation that is both an inherent part of their development and a requirement for the longevity that ensures their dispersal in time as well as in space.

Another significant group of Physcomitrella genes induced both by ABA and by dehydration encode proteins with a probable function in osmoregulation. These include membrane transport functions such as aquaporins and sugar transporters (Table 3), but also metabolic enzymes such as a stress-associated aldehyde dehydrogenase of the moss-specific ALDH21 subfamily (Chen et al., 2002; Kirch et al., 2004) (Table 2).

There are more genes whose transcripts accumulate in response to dehydration, than in response to other treatments, and also a significant number of genes that are down-regulated by dehydration but not by the other treatments. This may simply reflect the longer period over which dehydration stress was applied, relative to other treatments (24 vs 2 h). Alternatively, it may indicate the existence of ABA-dependent and ABA-independent response pathways. In flowering plants, ABA-specific induction of stress-related gene expression typically operates via the binding of bZip transcription factors to ABREs, a mechanism that also occurs in Physcomitrella (Knight et al., 1995; Kamisugi & Cuming, 2005). The angiosperm ABA-independent dehydration-specific response is mediated by the ‘DREB’ class of Apetala2-type transcription factors binding to a GC-rich DRE (Shinozaki & Yamaguchi-Shinozaki, 1997; Dubouzet et al., 2003; Shinozaki et al., 2003). The existence of a comparable pathway in mosses has yet to be experimentally demonstrated. However, our observation that a DREB-like transcription factor is up-regulated during dehydration stress, together with the identification of DRE-like elements within the 5′-flanking sequences of some dehydration-induced genes, suggests that this mechanism may also be conserved between bryophytes and angiosperms.

Transcripts exhibiting a substantial reduction in abundance included a preponderance of chloroplast-specific gene products. This was also observed in Arabidopsis (Seki et al., 2002) and likely accounts for the generally inhibitory effect of drought stress on photosynthetic activity. However, mosses typically exhibit morphogenetic changes following prolonged exposure to dehydration stress, or to ABA, resulting in the formation of brachycytes, or ‘brood cells’ (Bopp & Werner, 1993): these are typically thick-walled, lipid-rich vegetative spores (Schnepf & Reinhard, 1997), with substantially altered chloroplast morphology. Thus, widespread changes in chloroplast gene products may reflect the early stages of brachycyte differentiation. Similarly, proteomic studies of Physcomitrella brachycyte formation have identified specific changes in the extracellular protein spectrum in response to ABA (S. Tintelnot, pers. comm.), including changes in several gene products identified in this study (pectin methylesterase, proline-rich wall proteins, LRR-containing proteins, a plant-specific fasciclin and germin-like proteins) with probable wall-modifying functions.

Desiccation tolerance is widespread among bryophytes, yet the underlying mechanism of tolerance and its relationship to the mechanisms operating in the desiccation-tolerant stages of angiosperm development remain unclear. In the desiccation-tolerant moss Tortula ruralis, desiccation-associated changes in gene expression occur principally during the rehydration phase, rather than in the period during which water loss is occurring, leading to the suggestion that such species are constitutively prepared for desiccation, and that novel gene expression is required for the rapid repair of desiccation-induced cellular damage (Oliver, 1991; Oliver et al., 2004, 2005). It is clear that Physcomitrella differs in this respect, and interesting that many of the genes induced before dehydration encode proteins similar to those identified in the rehydration transcriptome of Tortula (Oliver et al., 2004, 2005).

It is noteworthy that the genes up-regulated by ABA and stress treatment of Physcomitrella are generally fewer in number than those identified in similar experiments undertaken with Arabidopsis thaliana. Physcomitrella is intermediate in its degree of dehydration stress tolerance in comparison with Tortula and Arabidopsis; although protonemal tissue does not survive desiccation, it is nevertheless highly tolerant of dehydration (Frank et al., 2005). Moreover, plants comprising both protonemata and gametophores will tolerate complete desiccation following slow drying, if first pretreated with ABA, a process that is associated with a substantial increase in intracellular concentrations of sucrose (Oldenhof et al., 2006), as is cold-acclimation leading to freezing tolerance (Nagao et al., 2005). This is similar to the ABA-mediated induction of desiccation tolerance in cultured tissue of the resurrection plant, Craterostigma plantagineum, and to the ABA-mediated acquisition of desiccation tolerance during angiosperm embryogenesis (Bartels et al., 1988, 1990; Bianchi et al., 1991; Ooms et al., 1993; Bartels, 2005; Smith-Espinoza et al., 2005). It may be that Physcomitrella retains a residual population of constitutively expressed genes with a stress-protective function, whereas the corresponding genes in angiosperms have undergone ‘evolutionary capture’ by an inducible mechanism.

It is clear that genes that confer desiccation tolerance have not been lost during the evolution of the land plants. Instead, their expression has become developmentally sequestered within the reproductive stages of the life cycle (typically during seed development). Moreover, the frequency with which vegetative desiccation tolerance has independently re-evolved throughout the land plant phylogeny (Oliver et al., 2005) implies that mutations in a relatively small number of regulatory genes may account for the this developmental sequestration.

Within the angiosperms, a subset of the genes expressed during late embryogenesis is restricted to this stage of development owing to a requirement for seed-specific transcription factors. Principal among these is the ABI3 class of transcriptional activator that mediates ABA-induced gene expression specifically in developing seeds through an interaction with the ABI5-type bZip factors (Ezcurra et al., 2000; Nakamura et al., 2001). In Physcomitrella protonemata, a similar mechanism activates the ABA-mediated expression of the group 1 LEA genes that in angiosperms are seed-specific (Knight et al., 1995; Kamisugi & Cuming, 2005; Marella et al., 2006). Interestingly, whereas all fully characterized angiosperm genomes contain only a single ABI3 gene, the Physcomitrella genome contains at least three such genes (Marella et al., 2006). If this multiplicity of the ABI3 family within the Physcomitrella genome reflects the situation more widely among the bryophytes, then it could be hypothesized that the evolutionary loss of the additional copies during the tracheophyte divergences, coupled with the developmental ‘capture’ of this transcription factor by the embryogenic developmental programme, would have resulted in the wholesale capture of its subordinate genes to this stage of the life cycle.

Acknowledgements

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods and Materials
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

ACC thanks the UK Biotechnology and Biological Sciences Research Council for their support of the Physcomitrella EST programme (PEP). SHC was the recipient of a fellowship from the Korea Research Foundation (MOEHRD, Basic Research Promotion Fund, M01-2004-000-10317-0). The support of the Physcomitrella Genome Consortium by the US Department of Energy's Community Sequencing Program at the Joint Genome Institute is gratefully acknowledged.

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  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information
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Supporting Information

  1. Top of page
  2. Summary
  3. Introduction
  4. Methods and Materials
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Text S1 Supplementary information

Tables S1 and S2 Relative fold-induction or down-regulation

Figs S1 and S2 Products of up- and down-regulated genes

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