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Isolation and analysis of candidate ascochyta blight defence genes in chickpea. Part I. Generation and analysis of an expressed sequence tag (EST) library
Physiological and Molecular Plant Pathology 66 (2005) 192–200 www.elsevier.com/locate/pmpp
Isolation and analysis of candidate ascochyta blight defence genes in chickpea. Part I. Generation and analysis of an expressed sequence tag (EST) library Tristan E. Coram*, Edwin C.K. Pang School of Applied Sciences, Biotechnology and Environmental Biology, RMIT University, Building 223, Level 1, Plenty Road, Bundoora, Vic. 3083, Australia Accepted 2 August 2005
Abstract Chickpea (Cicer arietinum L.) is the world’s third-most important pulse crop, but a major limiting factor to production is a severe and destructive fungal disease known as ascochyta blight (Ascochyta rabiei (Pass.) Labrousse). A chickpea accession (ICC3996) resistant to ascochyta blight, but uncultivated due to poor agronomic characters, was used to generate an enriched library of EST sequences. The library, consisting of 1021 ESTs, was characterised by homology searches in public databases, where 571 (56%) showed significant homology to existing database entries. The ESTs were clustered and assembled into 516 unigenes, of which 4% were defence-related, encoding lignin and phytoalexin biosynthesis enzymes, pathogenesis-related proteins, signalling proteins, and putative defensive proteins. These unigenes may be involved in chickpea defence against ascochyta blight, and are discussed in detail. The generation of an EST library represents the first step in a functional genomics approach aimed at elucidating the function of genes involved in ascochyta blight resistance and the pathway of their action. Applications of the EST library to microarray expression studies and molecular mapping are discussed, with emphasis on the development of agronomically viable chickpea cultivars with durable and broad-spectrum resistance to ascochyta blight. q 2005 Elsevier Ltd. All rights reserved. Keywords: Chickpea; Ascochyta blight; Genomics; EST
1. Introduction The world collection of chickpea (Cicer arietinum L.) germplasm contains accessions resistant to ascochyta blight (Ascochyta rabiei (Pass.) Lab) that remain uncultivated due to poor agronomic characteristics. Studies of one such accession, ICC3996, have revealed a strong capacity for A. rabiei resistance [1], indicating that ICC3996 may be a valuable source of resistance (R) and defence-related genes for use in the development of chickpea cultivars that are resistant to ascochyta blight. Previous studies have been undertaken to elucidate the genetic basis of ascochyta blight resistance [2,3], identify quantitative trait loci (QTL) associated with resistance
* Corresponding author. Tel.: C61 3 99257140; fax: C61 3 99257110. E-mail address: [email protected] (T.E. Coram).
0885-5765/$ - see front matter q 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.pmpp.2005.08.003
[4–6], map resistance gene analogs to existing chickpea linkage maps [7], and identify differentially expressed cDNA clones [8]. However, the disadvantage of previous studies is that the overall coordinated defence response remains largely uncharacterised. A genomics approach may assist in illuminating the chickpea resistance mechanism, as it enables the simultaneous discovery and study of many genes. The potential gene sequence data may provide information concerning the specific resistance pathway employed by the plant, as well as the function and number of genes involved. A common first step in functional genomics, referred to as Expressed Sequence Tag (EST) analysis, involves largescale partial sequencing of randomly selected clones from cDNA libraries constructed from mRNA isolated at a particular developmental stage. Functional identification of sequenced clones is being made easier by the availability of rapidly growing sequence databases that allow for the detection of regions showing sequence similarity in functionally related gene products, thus leading to
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the assignment of putative functions for many anonymous cDNA clones. EST analysis has become a popular method for gene discovery and mapping in many organisms. For plants such as rice, maize and Arabidopsis thaliana, comprehensive sets of EST sequences are available and have been used for the generation of molecular markers [9], identification of gene families [10], single nucleotide polymorphism (SNP) development [11], and the study of gene expression with microarrays [12,13]. To date, the study of the chickpea defence response to ascochyta blight through EST analysis and microarray expression experiments has not been performed. Whilst the National Center for Biotechnology Information EST database (GenBank dbEST) contains 23 970 155 ESTs (October 1, 2004; http://www.ncbi.nlm.nih.gov/dbEST/ dbEST_summary.html), of which wheat (561 786), maize (416 090), barley (367 798), and soybean (342 359) are the largest collections for plant species, chickpea is represented by just 641 ESTs. Such a low number of available chickpea ESTs exposes the need for a larger collection of sequence information before highly effective functional genomics strategies can be employed in chickpea research. The initial part of the present study was aimed at uncovering and characterising genes from the resistant chickpea accession, ICC3996, which may potentially be involved in the defence response against A. rabiei. This paper reports the analysis of 1198 ESTs from an enriched cDNA library composed of mRNA isolated from stem and leaf tissue of ICC3996 after inoculation with A. rabiei. Focusing on putative defence-related ESTs, the paper also reports clustering and assembling of the ESTs into unigenes. The subsequent availability of this EST resource enabled the development of methods for gene expression analysis using microarray technology [14].
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before adjusting the concentration to 1!105 spores/mL using a haemocytometer. 2.2. Cultivation and inoculation The ICC3996 seeds were surface-sterilised according to Collard et al. [1] and sown in 15 cm diameter pots (3 seeds/ pot) with five replicates, in a completely randomised design. All plants were grown in a glasshouse (20G4 8C) for 14 days (six- to eight-leaf stage) before inoculation with A. rabiei. Inoculations were performed by spraying approximately 5 mL of the spore suspension per plant with a plastic sprayer until run-off. One replicate served as an uninoculated control for comparison of infection development, and these plants were sprayed with sterile distilled water (5 mL/plant). All plants were then placed in plastic boxes covered with plastic to maintain high humidity for 48 h (20G4 8C), before being returned to the glasshouse. 500 mg of stem/leaf tissue was extracted from all inoculated plants at both 24 and 48 h post-inoculation. 2.3. Generation of cDNA library In order to enrich the library for defence-related transcripts, ICC3996 was challenged with A. rabiei before extracting RNA. Using the RNeasyw Plant Mini Kit (QIAGENe), total RNA was extracted from pooled 24 and 48 h stem and leaf samples of all inoculated ICC3996 plants before using the SMARTe PCR cDNA Synthesis Kit (Clontechw) to generate double-stranded cDNA. The resulting cDNA was ligated into pGEMw-T Easy Vector (Promegaw) and transformed into E. coli JM109 cells (Promegaw) according to manufacturer’s instructions. 2.4. Sequencing of clones
2. Materials and methods 2.1. Plant material and fungal isolate Seeds of C. arietinum (ICC3996) were obtained from the Australian Temperate Field Crops Collection (ATFCC) in Horsham, Victoria, Australia. Seven isolates of A. rabiei were collected from seven different chickpea cultivars in Horsham, Victoria in 2003. To ensure the isolation of lowly and highly virulent A. rabiei pathotypes, the cultivars selected for spore isolation included those known to be susceptible to A. rabiei, as well as several that are known to be highly resistant. For each isolate, single-spore isolates were prepared and maintained on V8 agar according to the method of Collard et al. [1]. Spore suspensions were prepared from 14-day-old fungal cultures by adding sterile distilled water to the culture surface and disrupting the fungal colonies with a glass spreader. The suspensions were mixed and filtered through four layers of muslin cloth,
Plasmid DNA was isolated from single colonies using the QIAquickw Spin Miniprep Kit (QIAGENe). Over 1000 clones were randomly selected and the size of each insert was assessed by specific PCR amplification with T7 and SP6 sequencing primers. All clones were subjected to singlepass sequencing from the 5 0 end of the vector using BigDyee Terminator chemistry (PE Biosystems) and an ABI Prism 377 DNA Sequencer (School of Biomolecular and Biomedical Sciences, Griffith University, Queensland, Australia). Sequences identified as defence-related were subjected to further sequencing, using an additional 5 0 read as well as two 3 0 reads. 2.5. Sequence analysis Low quality sequence reads were manually removed, and vector sequences were removed using CodonCode Matchere (BioManagere 2.0, Australian National Genomic Information Service, University of Sydney, NSW). Each independent EST was characterised using BLASTN
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and BLASTX to determine sequence homology with existing entries in the GenBankw Main, GenBankw ESTs (dbEST), SwissProtw and SpTrEMBLw databases. Database hits were ranked by Expectation (e) value, and were regarded as significantly similar to the input sequence if P!1.0!10K10. Each EST was assigned a putative cellular function based on the significant database hit with the lowest e value, and the functional categories used were based on the Munich Information Center for Protein Sequences (MIPS) classification system applied to the A. thaliana genome [15]. ESTs that matched to hypothetical proteins were classified as ‘unclear’ whilst ESTs with no significant match were classified as ‘unknown’. The putative defence-related ESTs were deposited into GenBank (dbEST) with accession numbers from CV793585 to CV793610. 2.6. EST clustering To identify the number of non-redundant ESTs, all sequenced and classified ESTs were clustered and assembled into unigenes of contigs and singlets using CodonCode Assemblere (BioManagere 2.0, Australian National Genomic Information Service, University of Sydney, NSW). ESTs producing an alignment of O50 overlapping bases and O95% identity with another EST were assembled. After clustering, unigenes were functionally characterised and classified according to the method outlined for the independent ESTs.
3. Results 3.1. cDNA library and sequencing Of the randomly selected clones, PCR amplification revealed insert sizes ranging from 100 to 2500 bp, but only those with an insert O200 bp were sequenced. The clones were sequenced from the 5 0 end to generate 1198 cDNA transcripts ranging from 200 to 2000 bp, but this number was reduced to 1021 after removing poor-quality sequence reads. The overall sequence success rate was 85%. 3.2. Functional classification & EST clustering For the 1021 independent ESTs, sequence searches revealed that 450 (44%) possessed no significant database hit that would allow functional classification, and therefore may represent novel gene sequences or 5 0 untranslated regions. This category may be further divided into ESTs that significantly matched putative or hypothetical proteins (9% Unclear), and ESTs that did not match any nucleotide or protein sequence (35% Unknown). The remaining 571 ESTs (56%) showed significant homology to existing sequences from the databases. The putative defence-related sequences, targeted by this study, accounted for 26 (3%) of the 1021
ESTs, coding for potential antimicrobial, receptor, and defence-activating proteins. Clustering and assembling of the 1021 independent ESTs produced 516 unigenes. The unigenes ranged from 200 to 1800 bp, with an average length of 755 bp. The majority of the unigenes were from singletons (78%), whilst 17% were generated from two to three homologous ESTs, 4% were generated from four to 10 homologous ESTs, and only 1% of the unigenes were generated from more than 10 homologues sequences. Analysis and characterisation of the 516 unigenes (Fig. 1) revealed that 50% possessed no significant functional database hit; of which 12% were classified as ‘unclear’ and the remaining 38% were ‘unknown’. Of the 50% that were functionally annotated, the largest category was ‘cellular metabolism’ (11%), made up of various putative enzymes and metabolic proteins. Cytochrome-like proteins were the most common, especially one resembling cytochrome P450, and several metabolic pathways were represented, including fatty acid metabolism, nitrogen fixation, amino acid biosynthesis, sterol biosynthesis and fruit development. The next largest category was ‘protein synthesis/fate’ (10%), of which the majority encoded putative nuclear, mitochondrial, and chloroplast ribosomal proteins. The ‘energy’ (9%) category included unigenes of the photosynthesis/ATP synthesis/ electron transport pathways, such as the chlorophyll a/b binding protein, ATP synthase, Rubisco, and ferredoxin. Proteins implicated in stress responses formed the majority of the ‘cell rescue/death/ageing’ (5%) category, the most common examples resembling auxin-repressed proteins, heat-shock proteins, and wound-induced proteins. Another 4% represented ‘cellular communication/signal transduction’, including protein kinases, and other putative membrane-bound signal proteins. Few proteins were involved in ‘transport facilitation’ (3%), some examples being aquaporin, sugar transport proteins, and ion-channel proteins. The ‘transcription’ (2%) category included messenger RNAs and transcription factors, whilst ‘cell cycle & DNA processing’ (2%) included putative DNA methylation proteins. Clustering of the 26 putative defencerelated ESTs resulted in 20 unigenes (Table 1), representing 4% of the unigene set. A comparison can be made between the functional distributions of the independent ESTs and clustered unigenes to show those categories represented by highly expressed genes, as these categories will have a lesser value in the clustered distribution compared to the independent EST distribution (Fig. 2). This was clearly apparent for ‘protein synthesis/fate’, ‘energy’, and ‘transcription’ where the numbers of independent ESTs are more than double the number of unigenes. The members of these categories, which include various ribosomal/messenger RNA molecules as well as transcripts involved in photosynthesis and respiration, are sampled more frequently in random sequencing, supporting their high level of expression and potential involvement in general housekeeping.
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Fig. 1. Functional distribution of the 516 Cicer arietinum (ICC3996) unigenes.
Table 1 Cicer arietinum (ICC3996) defence-related unigenes after BLASTN and BLASTX sequence homology searches performed on the 23/02/2004 EST number
Database match
Matching database accession
e value
Copy number
CA0070 CA0082 CA0117 CA0188
A. thaliana extensin-like disease resistance protein G. max gamma-thionin defensin/protease inhibitor N. tabacum Avr9/Cf-9 rapidly elicited protein 65 B. oleracea pathogen-induced translation initiation factor nps45 V. unguiculata S1-3 pathogen-induced protein A. thaliana putative disease resistance protein C. arietinum transcription factor EREBP-1 M. sativa caffeoyl-CoA-methyltransferase (EC 2.1.1.104) P. sativum pathogenesis-related protein 4A C. arietinum beta-1-3-glucanase O. sativa protein with leucine zipper S. tuberosum pathogen-induced transcription factor E. esula leucine-zipper containing protein M. domestica cinnamyl alcohol dehydrogenase (CAD1) C. arietinum nematode resistance protein Hs1pro-1 O. sativa multi-resistance transporter protein A. thaliana putative flavonol glucosyl transferase S. tuberosum SNAKIN2 antimicrobial peptide precursor A. thaliana elicitor-induced receptor protein M. sativa pathogenesis-related protein class 10
O82202b Q39807b Q9FQZ0b SUI1_BRAOLa
6!10K28 2!10K11 2!10K12 4!10K34
1 1 2 1
Q9MB24b DR29_ARATHa Q8GTE5b CAMT_MEDSAa Q9M7D9b Q9XFW9b Q8RZJ0b Q9LL86b Q945B7b O65152b Q94BW7b Q943U4b HQGT_ARATHa Q93X17b Q9FH56b PR1_MEDSAa
4!10K20 6!10K13 2!10K95 5!10K98 5!10K61 2!10K26 3!10K48 2!10K11 2!10K13 2!10K34 7!10K16 7!10K12 4!10K25 5!10K23 1!10K11 1!10K30
1 1 3 2 1 1 1 1 1 1 1 1 1 2 1 2
CA0191 CA0228 CA0257 CA0260 CA0303 CA0329 CA0442 CA0452 CA0557 CA0632 CA0641 CA0758 CA0984 CA1012 CA1079 CA1159 a b
Matching to SwissProt database accession. Matching to SpTrEMBL database accession.
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Fig. 2. Comparison of functional distributions amongst independent ESTs and clustered unigenes.
Interestingly, the ‘unknown’ category also fits this scenario, suggesting that many of its members may become highly expressed after A. rabiei challenge. Detailed examination of the eight unigenes that contain more than 10 independent ESTs (Table 2) shows that the most highly expressed EST is a chloroplast mRNA of the ‘transcription’ category. Other highly expressed ESTs include ribosomal RNAs (‘protein synthesis/fate’), putative enzymes of the ‘cellular metabolism’ category, and a chlorophyll protein and Rubisco enzyme (‘energy’). 3.3. Comparison with other plant species The availability of the annotated set of the entire Arabidopsis thaliana genome, as well as large EST sets for other leguminous plant species, enabled the determination of the level of gene conservation and similarity between C. arietinum and other related plant species. The C. arietinum (ICC3996) unigenes were compared with
the TIGR Gene Indices of A. thaliana (http://www.tigr.org/ tdb/tgi/atgi), Medicago truncatula (http://www.tigr.org/tdb/ tgi/mtgi), Lotus japonicus (http://www.tigr.org/tdb/tgi/ljgi) and Glycine max (http://www.tigr.org/tdb/tgi/gmgi) using TBLASTX. The similarities of each species to the C. arietinum (ICC3996) unigenes are shown in Fig. 3. An important observation was the high level of weak/no similarity detected for the model legumes M. truncatula (47.48%) and L. japonicus (58.14%), indicating that C. arietinum may possess many genes with little or no homology to genes within these model legumes. Integration of the search results revealed that 33.91% of the unigenes were conserved in all five species, whilst 4.46% were conserved only in the legume species, and included defencerelated, cell signalling/communication and cellular metabolism unigenes, as well as several hypothetical proteins. Interestingly, 57.56% of the C. arietinum (ICC3996) unigenes were not significantly similar to the A. thaliana genome, and may represent genes for morphological
Table 2 Description of the eight unigene clusters containing more than 10 independent ESTs Number of ESTs in cluster
Cluster identification from BLASTN or BLASTX
e value
Functional category
173 34 31 24 17 16 15
C. arietinum chloroplast 4.5S/5S/16S/23S messenger RNA C. arietinum 26S ribosomal RNA C. arietinum putative deoxycytidylate deaminase L. esculentumlt;/AsSETItalicO chlorophyll a/b binding protein O. sativa ribosomal RNA intron-encoded homing endonuclease P. sativum UDP-glucose 4-epimerase (EC 5.1.3.2) C. arietinum ribulose 1,5-bisphosphate carboxylase small subunit precursor (EC 4.1.1.39) A. thaliana mitochondrial 26S ribosomal RNA
4!10K11 1!10K101 2!10K48 2!10K83 4!10K26 1!10K26 1!10K95
Transcription Protein synthesis/fate Cellular metabolism Energy Protein synthesis/fate Cellular metabolism Energy
4!10K12
Protein synthesis/fate
15
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Fig. 3. Distribution of conservation between C. arietinum (ICC3996) unigenes and the Gene Indices of Arabidopsis thaliana, Medicago truncatula, Lotus japonicus and Glycine max according to similarity levels determined by TBLASTX e values.
features or metabolic processes specific to leguminous species. Although A. thaliana represents a model for flowering plants, it may not possess all the desired characteristics of other plant species, and subsequently may be unsuitable for use in the study of those characteristics. Alternatively, the sequencing of untranslated regions, or the presence of non-annotated A. thaliana genes could cause absences in sequence similarities.
The unigenes conserved between C. arietinum (ICC3996) and A. thaliana were classified into their functional categories, and the levels of similarities for each category are shown in Fig. 4. The most highly conserved categories included ‘transcription’, ‘protein synthesis/fate’, ‘energy’ and ‘cellular metabolism’, whilst the least conserved categories included ‘defence’, ‘cell rescue/death/ageing’ and ‘cellular communication/signal transduction’.
Fig. 4. Levels of similarity for the unigenes conserved between C. arietinum (ICC3996) and A. thaliana according to functional categories. Similarity levels were determined by TBLASTX e values.
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4. Discussion A collection of 1021 independent ESTs was clustered and assembled to generate 516 unigenes. Clustering allowed the detection of highly expressed transcripts, and the comparison between functional distributions of the independent ESTs and unigenes provided evidence for this (Fig. 2). It was expected that functional categories mainly involved with general housekeeping activities would show the highest level of expression, and this was apparent by the ‘transcription’, ‘energy’, ‘cellular metabolism’ and ‘protein synthesis/fate’ category comparisons. The specific ESTs with the highest expression (Table 2) were also as expected. These ESTs all belonged to general housekeeping categories and possess well-characterised functions in common plant activities. An unexpected observation was the independent ESTs to clustered unigenes comparison of the ‘unknown’ category in Fig. 2, where the majority of ESTs were expected to possess a non-housekeeping role to justify their anonymity amongst databases. A possible explanation for this may be that the A. rabiei inoculation of the plant caused a substantial increase in the expression of numerous unknown defence-related transcripts, resulting in the skewing of the data toward high levels of expression in the ‘unknown’ category. The large amount of nucleotide sequence data in public databases enabled the comparison of the C. arietinum (ICC3996) unigenes to the entire genome content of A. thaliana, as well as the current EST collections of M. truncatula, L. japonicus and G. max (Fig. 3). The highest level of similarity was observed in M. truncatula, followed by G. max, whilst L. japonicus and A. thaliana possessed the least similarity. It was expected that the three leguminous species would show the highest levels of similarity, as was observed for M. truncatula and G. max. The lower similarity level observed for L. japonicus may be attributed to a smaller EST collection, and it is important to recognise that the similarity levels observed do not reflect phylogenetic relationships, but rather the coverage of EST sequencing for each species. Further, the high levels of weak/no similarity observed for the two model legumes, M. truncatula and L. japonicus may indicate a significant divergence in C. arietinum gene content, or the presence of many untranslated sequences within the chickpea unigene collection. However, the levels of similarity observed for the model legumes were only marginally superior than observed for A. thaliana, indicating a possible insufficiency of homology for their use in the study of economically important legumes. Subsequently, the use of these models for the study of chickpea may be limited. The expanding collections of ESTs for the model legumes may eventually provide adequate homology to the chickpea transcriptome, but the results of this study suggest a significant proportion of chickpea genes will remain non-homologous to those collections. The comparisons also revealed several gene
candidates that were absent in A. thaliana but present in all legume species, including defence-related and cellular communication/signal transduction unigenes that may be functionally specific for the protection of leguminous plants only. Further, several cellular metabolism unigenes were identified only in the legumes, indicating a possible role in a legume-specific metabolic pathway such as nodulation. Numerous legume-specific hypothetical proteins may also represent genes involved in these pathways. The level of similarity between the functionally annotated C. arietinum (ICC3996) unigenes and the A. thaliana genome (Fig. 4) may reflect the speed of gene evolution, based on the assumption that slow evolving genes show a high level of conservation, and fast evolving genes show a low conservation level. The most highly conserved categories contained unigenes encoding structural, ribosomal, photosynthetic, translational and metabolic proteins, whilst the least conserved categories contained unigenes encoding defence and stress-related proteins, as well as signalling proteins such as protein kinases. These observations are similar to those witnessed in soybean [16] and L. japonicus [17], and lend support to the theory that genes related to basic processes have not significantly evolved, whereas regulatory genes have. Most pertinent to the aims of this study were the potential defence-related ESTs. To enrich for these sequences, postinoculation tissue samples of a resistant chickpea (ICC3996) were used as starting material to generate cDNA. Stem and leaf tissue samples were taken at two time points (24 and 48 h) and pooled in an attempt to capture a broad range of gene sequences that may be involved in different branches of potential defence-related pathways. The putative defence-related ESTs identified in this study (Table 1) accounted for 4% of the unigene set and represented a variety of plant defence mechanisms and pathways, and will be the basis for the investigations detailed in a subsequent paper [14]. Briefly, the Extensinlike protein (CA0070), Caffeoyl-CoA-methyltransferase (CCoAOMT) (CA0260), and Cinnamyl alcohol dehydrogenase (CAD1) (CA0632) are all putatively involved in the synthesis of lignin or cell walls. CCoAOMT has previously been identified as part of an elicitor-induced plant defence response [18], whilst an extensin has been shown to proliferate rapidly after the oxidative burst in chickpea [19]. Pathogenesis-related protein 4A (CA0303), Beta-1,3glucanase (CA0329), and pathogenesis-related protein class 10 (CA1159) may all be grouped as pathogenesisrelated (PR) proteins, which can have a beta-glucanase, chitinase, or lysozyme activity. Of these, only a Beta-1,3glucanase has previously been isolated from chickpea. One other defence-related unigene may be classed as a PR protein—the gamma-thionin defensin/protease inhibitor (CA0082), which may be involved in pathogen defence by preventing the hydrolysis of plant cell proteins by fungal toxins [20].
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Five of the defence-related unigenes may be grouped into a putative signalling or defence-activating category; Translation initiation factor nps45 (CA0188), Transcription factor EREBP-1 (CA0257), Avr9/Cf-9 rapidly elicited protein 65 (CA0277), Pathogen-induced transcriptional activator (CA0452), and Elicitor-induced receptor protein (CA1079). The most characterised protein from this group is the transcription factor EREBP-1 (Ethylene Responsive Element Binding Protein), which is involved in the regulation of disease resistance pathways, and has been previously isolated from chickpea. The largest sub-group of the defence-related unigenes were those of putative defensive functions that had not been fully characterised, including; S1-3 pathogen-induced protein (CA0191), Putative disease resistance protein (CA0228), Protein with leucine zipper (CA0442), Leucine-zipper containing protein (CA0557), Multi-resistance transporter protein (CA0758), and SNAKIN2 antimicrobial peptide precursor (CA1012). The leucine-zipper proteins were identified as defencerelated as they may represent basic region/leucine-zipper motif (bZIP) transcription factors that are involved in several plant processes including pathogen defence [21]. One of the defence-related unigenes was implicated in phytoalexin production; the salicylic acid-induced UDP flavonol glucosyl transferase (CA0984), whilst the final defence-related unigene that cannot be grouped with any others is the Nematode resistance protein (CA0641) that, although only implicated in chickpea nematode resistance, could possibly represent a broad-spectrum defence protein. The defence-related transcripts aside, the present study also isolated numerous signalling and abiotic-stress-induced transcripts that may be important in the overall A. rabiei defence mechanism of chickpea. Although such transcripts may not be differentially expressed, they may represent integral parts of defence-activating and regulatory pathways. This study was the first step in a genomics approach to enable the discovery and study of many genes simultaneously. The overall gene sequence data generated in this study is important as it may, through the use of microarray expression studies, provide information concerning the specific defence pathway employed by chickpea, as well as the function of genes involved. In summary, a collection of chickpea ESTs was generated from which potential A. rabiei defence-related unigenes were uncovered. Similarity comparisons to the chickpea unigenes revealed that a high proportion of the chickpea transcriptome may be insufficiently homologous to model legumes, limiting use of their EST collections for the study of chickpea. In addition to the putative defencerelated unigenes, perhaps the most important group of unigenes was those of ‘unknown’ and ‘unclear’ identity. The unigenes making up these categories may include novel defence-related genes acting against A. rabiei, and similarly, the ‘cellular communication/signal transduction’ and ‘cell rescue/death/ageing’ categories may contain unigenes that are essential to the coordination of defence
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responses. The next step will involve the use of cDNA microarrays to study expression patterns of all unigenes identified in this study. By studying up- or down-regulation in resistant and susceptible chickpea accessions over a range of post-inoculation time points, it may be possible to identify the genes involved and the pathway of A. rabiei defence, which would prove a valuable resource to understand ascochyta blight resistance. In addition to microarray analysis, the defence-related unigenes isolated in this study may also be applied to genetic mapping experiments where, if polymorphic between parents, they may act as ‘perfect’ markers to identify QTLs associated with A. rabiei defence. The unigenes may also be used in SNP discovery, which involves the amplification and analysis of genomic DNA sequences homologous to each unigene from various chickpea accessions, restriction fragment length polymorphism (RFLP) mapping, and cleaved amplified polymorphic sequences (CAPS) mapping. These alternative applications are all directed toward producing molecular markers linked to A. rabiei defence, and the defence-related unigenes generated in this study provide a valuable resource for such purposes. Potential markers derived from the unigene sequences may be used in breeding and selection programs aimed at developing agronomically viable chickpea cultivars with resistance to ascochyta blight.
Acknowledgements The authors would like to acknowledge the Grains Research and Development Corporation (GRDC) for their generous granting of a research scholarship. The authors thank Kevin Meredith, Dr Chris Pittock, Dr Trevor Bretag, and Kristy Hobson (Department of Primary Industry, Horsham) for the supply of seeds, fungal cultures, and valuable advice.
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[6] Cho S, Chen W, Muehlbauer F. Pathotype-specific genetic factors in chickpea (Cicer arietinum L.) for quantitative resistance to ascochyta blight. Theor Appl Genet 2004;109:733–9. [7] Rajesh P, Tekeoglu M, Gupta V, Ranjekar P, Muehlbauer F. Molecular mapping and characterisation of an RGA locus RGAPtokin1-2 171 in chickpea. Euphytica 2002;128(427):433. [8] Ichinose Y, Tiemann K, Schwenger-Erger C, Toyoda K, Hein F, Hanselle T, et al. Genes expressed in Ascochyta rabiei-inoculated chickpea plants and elicited cell cultures as detected by differential cDNA-hybridization. Z Naturforsch 2000;55:44–54. [9] Yu J, La Rota M, Kantety R, Sorrells M. EST derived SSR markers for comparativemapping in wheat and rice. Mol Genet Genomics 2004; 271:742–51. [10] Epple P, Apel K, Bohlmann H. ESTs reveal a multigene family for plant defensins in Arabidopsis thaliana. FEBS Lett 1997;400:168–72. [11] Cho R, Mindrinos M, Richards D, Sapolsky R, Anderson M, Drenkhard E, et al. Genome-wide mapping with biallelic markers in Arabidopsis thaliana. Nat Genet 1999;23:203–7. [12] Schenk P, Kazan K, Wilson I, Anderson J, Richmond T, Somerville S, et al. Coordinated plant defense responses in Arabidopsis revealed by microarray analysis. Proc Natl Acad Sci USA 2000;97:11655–60. [13] Lan L, Chen W, Lai Y, Suo J, Kong Z, Li C, et al. Monitoring of gene expression profiles and isolation of candidate genes involved in pollination and fertilization in rice (Oryza sativa L.) with a 10K cDNA microarray. Plant Mol Biol 2004;54:471–87.
[14] Coram T, Pang E. Isolation and analysis of candidate ascochyta blight resistance genes in chickpea. II. Microarray expression analysis of putative defence-related ESTs. Physiol Mol Plant Pathol (doi: 10.1016/j.pmpp.2005.08.002). [15] Mewes H, Frishman D, Guldener U, Mannhaupt G, Mayer K, Mokrejs M, et al. MIPS: a database for genomes and protein sequences. Nucleic Acids Res 2002;30:31–4. [16] Tian A-G, Wang J, Cui P, Han Y-J, Xu H, Cong L-J, et al. Characterization of soybean genomic features by analysis of its expressed sequence tags. Theor Appl Genet 2004;108:903–13. [17] Asamizu E, Nakamura Y, Sato S, Tabata S. Characteristics of the Lotus japonicus gene repertoire deduced from large-scale expressed sequence tag (EST) analysis. Plant Mol Biol 2004;54: 405–14. [18] Pakusch A, Kneusel R, Matern U. S-adenosyl-L-methionine:transcaffeoyl-coenzyme A 3-O-methyltransferase from elicitor-treated parsley cell suspension cultures. Arch Biochem Biophys 1991;258: 488–94. [19] Otte O, Barz W. Characterization and oxidative in vitro cross-linking of an extensin-like proteon and a proline-rich protein purified from chickpea cell walls. Phytochemistry 2000;53:1–5. [20] Koiwa H, Bressan R, Hasegawa P. Regulation of protease inhibitors and plant defense. Trends Plant Sci 1997;2:379–84. [21] Jakoby M, Weisshaar B, Droge-Laser W, Vicente-Carbajosa J, Tiedemann J, Kroj T, et al. bZIP transcription factors in Arabidopsis. Trends Plant Sci 2002;7:106–11.
Isolation and analysis of candidate ascochyta blight defence genes in chickpea. Part I. Generation and analysis of an expressed sequence tag (EST) library Tristan E. Coram*, Edwin C.K. Pang School of Applied Sciences, Biotechnology and Environmental Biology, RMIT University, Building 223, Level 1, Plenty Road, Bundoora, Vic. 3083, Australia Accepted 2 August 2005
Abstract Chickpea (Cicer arietinum L.) is the world’s third-most important pulse crop, but a major limiting factor to production is a severe and destructive fungal disease known as ascochyta blight (Ascochyta rabiei (Pass.) Labrousse). A chickpea accession (ICC3996) resistant to ascochyta blight, but uncultivated due to poor agronomic characters, was used to generate an enriched library of EST sequences. The library, consisting of 1021 ESTs, was characterised by homology searches in public databases, where 571 (56%) showed significant homology to existing database entries. The ESTs were clustered and assembled into 516 unigenes, of which 4% were defence-related, encoding lignin and phytoalexin biosynthesis enzymes, pathogenesis-related proteins, signalling proteins, and putative defensive proteins. These unigenes may be involved in chickpea defence against ascochyta blight, and are discussed in detail. The generation of an EST library represents the first step in a functional genomics approach aimed at elucidating the function of genes involved in ascochyta blight resistance and the pathway of their action. Applications of the EST library to microarray expression studies and molecular mapping are discussed, with emphasis on the development of agronomically viable chickpea cultivars with durable and broad-spectrum resistance to ascochyta blight. q 2005 Elsevier Ltd. All rights reserved. Keywords: Chickpea; Ascochyta blight; Genomics; EST
1. Introduction The world collection of chickpea (Cicer arietinum L.) germplasm contains accessions resistant to ascochyta blight (Ascochyta rabiei (Pass.) Lab) that remain uncultivated due to poor agronomic characteristics. Studies of one such accession, ICC3996, have revealed a strong capacity for A. rabiei resistance [1], indicating that ICC3996 may be a valuable source of resistance (R) and defence-related genes for use in the development of chickpea cultivars that are resistant to ascochyta blight. Previous studies have been undertaken to elucidate the genetic basis of ascochyta blight resistance [2,3], identify quantitative trait loci (QTL) associated with resistance
* Corresponding author. Tel.: C61 3 99257140; fax: C61 3 99257110. E-mail address: [email protected] (T.E. Coram).
0885-5765/$ - see front matter q 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.pmpp.2005.08.003
[4–6], map resistance gene analogs to existing chickpea linkage maps [7], and identify differentially expressed cDNA clones [8]. However, the disadvantage of previous studies is that the overall coordinated defence response remains largely uncharacterised. A genomics approach may assist in illuminating the chickpea resistance mechanism, as it enables the simultaneous discovery and study of many genes. The potential gene sequence data may provide information concerning the specific resistance pathway employed by the plant, as well as the function and number of genes involved. A common first step in functional genomics, referred to as Expressed Sequence Tag (EST) analysis, involves largescale partial sequencing of randomly selected clones from cDNA libraries constructed from mRNA isolated at a particular developmental stage. Functional identification of sequenced clones is being made easier by the availability of rapidly growing sequence databases that allow for the detection of regions showing sequence similarity in functionally related gene products, thus leading to
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the assignment of putative functions for many anonymous cDNA clones. EST analysis has become a popular method for gene discovery and mapping in many organisms. For plants such as rice, maize and Arabidopsis thaliana, comprehensive sets of EST sequences are available and have been used for the generation of molecular markers [9], identification of gene families [10], single nucleotide polymorphism (SNP) development [11], and the study of gene expression with microarrays [12,13]. To date, the study of the chickpea defence response to ascochyta blight through EST analysis and microarray expression experiments has not been performed. Whilst the National Center for Biotechnology Information EST database (GenBank dbEST) contains 23 970 155 ESTs (October 1, 2004; http://www.ncbi.nlm.nih.gov/dbEST/ dbEST_summary.html), of which wheat (561 786), maize (416 090), barley (367 798), and soybean (342 359) are the largest collections for plant species, chickpea is represented by just 641 ESTs. Such a low number of available chickpea ESTs exposes the need for a larger collection of sequence information before highly effective functional genomics strategies can be employed in chickpea research. The initial part of the present study was aimed at uncovering and characterising genes from the resistant chickpea accession, ICC3996, which may potentially be involved in the defence response against A. rabiei. This paper reports the analysis of 1198 ESTs from an enriched cDNA library composed of mRNA isolated from stem and leaf tissue of ICC3996 after inoculation with A. rabiei. Focusing on putative defence-related ESTs, the paper also reports clustering and assembling of the ESTs into unigenes. The subsequent availability of this EST resource enabled the development of methods for gene expression analysis using microarray technology [14].
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before adjusting the concentration to 1!105 spores/mL using a haemocytometer. 2.2. Cultivation and inoculation The ICC3996 seeds were surface-sterilised according to Collard et al. [1] and sown in 15 cm diameter pots (3 seeds/ pot) with five replicates, in a completely randomised design. All plants were grown in a glasshouse (20G4 8C) for 14 days (six- to eight-leaf stage) before inoculation with A. rabiei. Inoculations were performed by spraying approximately 5 mL of the spore suspension per plant with a plastic sprayer until run-off. One replicate served as an uninoculated control for comparison of infection development, and these plants were sprayed with sterile distilled water (5 mL/plant). All plants were then placed in plastic boxes covered with plastic to maintain high humidity for 48 h (20G4 8C), before being returned to the glasshouse. 500 mg of stem/leaf tissue was extracted from all inoculated plants at both 24 and 48 h post-inoculation. 2.3. Generation of cDNA library In order to enrich the library for defence-related transcripts, ICC3996 was challenged with A. rabiei before extracting RNA. Using the RNeasyw Plant Mini Kit (QIAGENe), total RNA was extracted from pooled 24 and 48 h stem and leaf samples of all inoculated ICC3996 plants before using the SMARTe PCR cDNA Synthesis Kit (Clontechw) to generate double-stranded cDNA. The resulting cDNA was ligated into pGEMw-T Easy Vector (Promegaw) and transformed into E. coli JM109 cells (Promegaw) according to manufacturer’s instructions. 2.4. Sequencing of clones
2. Materials and methods 2.1. Plant material and fungal isolate Seeds of C. arietinum (ICC3996) were obtained from the Australian Temperate Field Crops Collection (ATFCC) in Horsham, Victoria, Australia. Seven isolates of A. rabiei were collected from seven different chickpea cultivars in Horsham, Victoria in 2003. To ensure the isolation of lowly and highly virulent A. rabiei pathotypes, the cultivars selected for spore isolation included those known to be susceptible to A. rabiei, as well as several that are known to be highly resistant. For each isolate, single-spore isolates were prepared and maintained on V8 agar according to the method of Collard et al. [1]. Spore suspensions were prepared from 14-day-old fungal cultures by adding sterile distilled water to the culture surface and disrupting the fungal colonies with a glass spreader. The suspensions were mixed and filtered through four layers of muslin cloth,
Plasmid DNA was isolated from single colonies using the QIAquickw Spin Miniprep Kit (QIAGENe). Over 1000 clones were randomly selected and the size of each insert was assessed by specific PCR amplification with T7 and SP6 sequencing primers. All clones were subjected to singlepass sequencing from the 5 0 end of the vector using BigDyee Terminator chemistry (PE Biosystems) and an ABI Prism 377 DNA Sequencer (School of Biomolecular and Biomedical Sciences, Griffith University, Queensland, Australia). Sequences identified as defence-related were subjected to further sequencing, using an additional 5 0 read as well as two 3 0 reads. 2.5. Sequence analysis Low quality sequence reads were manually removed, and vector sequences were removed using CodonCode Matchere (BioManagere 2.0, Australian National Genomic Information Service, University of Sydney, NSW). Each independent EST was characterised using BLASTN
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and BLASTX to determine sequence homology with existing entries in the GenBankw Main, GenBankw ESTs (dbEST), SwissProtw and SpTrEMBLw databases. Database hits were ranked by Expectation (e) value, and were regarded as significantly similar to the input sequence if P!1.0!10K10. Each EST was assigned a putative cellular function based on the significant database hit with the lowest e value, and the functional categories used were based on the Munich Information Center for Protein Sequences (MIPS) classification system applied to the A. thaliana genome [15]. ESTs that matched to hypothetical proteins were classified as ‘unclear’ whilst ESTs with no significant match were classified as ‘unknown’. The putative defence-related ESTs were deposited into GenBank (dbEST) with accession numbers from CV793585 to CV793610. 2.6. EST clustering To identify the number of non-redundant ESTs, all sequenced and classified ESTs were clustered and assembled into unigenes of contigs and singlets using CodonCode Assemblere (BioManagere 2.0, Australian National Genomic Information Service, University of Sydney, NSW). ESTs producing an alignment of O50 overlapping bases and O95% identity with another EST were assembled. After clustering, unigenes were functionally characterised and classified according to the method outlined for the independent ESTs.
3. Results 3.1. cDNA library and sequencing Of the randomly selected clones, PCR amplification revealed insert sizes ranging from 100 to 2500 bp, but only those with an insert O200 bp were sequenced. The clones were sequenced from the 5 0 end to generate 1198 cDNA transcripts ranging from 200 to 2000 bp, but this number was reduced to 1021 after removing poor-quality sequence reads. The overall sequence success rate was 85%. 3.2. Functional classification & EST clustering For the 1021 independent ESTs, sequence searches revealed that 450 (44%) possessed no significant database hit that would allow functional classification, and therefore may represent novel gene sequences or 5 0 untranslated regions. This category may be further divided into ESTs that significantly matched putative or hypothetical proteins (9% Unclear), and ESTs that did not match any nucleotide or protein sequence (35% Unknown). The remaining 571 ESTs (56%) showed significant homology to existing sequences from the databases. The putative defence-related sequences, targeted by this study, accounted for 26 (3%) of the 1021
ESTs, coding for potential antimicrobial, receptor, and defence-activating proteins. Clustering and assembling of the 1021 independent ESTs produced 516 unigenes. The unigenes ranged from 200 to 1800 bp, with an average length of 755 bp. The majority of the unigenes were from singletons (78%), whilst 17% were generated from two to three homologous ESTs, 4% were generated from four to 10 homologous ESTs, and only 1% of the unigenes were generated from more than 10 homologues sequences. Analysis and characterisation of the 516 unigenes (Fig. 1) revealed that 50% possessed no significant functional database hit; of which 12% were classified as ‘unclear’ and the remaining 38% were ‘unknown’. Of the 50% that were functionally annotated, the largest category was ‘cellular metabolism’ (11%), made up of various putative enzymes and metabolic proteins. Cytochrome-like proteins were the most common, especially one resembling cytochrome P450, and several metabolic pathways were represented, including fatty acid metabolism, nitrogen fixation, amino acid biosynthesis, sterol biosynthesis and fruit development. The next largest category was ‘protein synthesis/fate’ (10%), of which the majority encoded putative nuclear, mitochondrial, and chloroplast ribosomal proteins. The ‘energy’ (9%) category included unigenes of the photosynthesis/ATP synthesis/ electron transport pathways, such as the chlorophyll a/b binding protein, ATP synthase, Rubisco, and ferredoxin. Proteins implicated in stress responses formed the majority of the ‘cell rescue/death/ageing’ (5%) category, the most common examples resembling auxin-repressed proteins, heat-shock proteins, and wound-induced proteins. Another 4% represented ‘cellular communication/signal transduction’, including protein kinases, and other putative membrane-bound signal proteins. Few proteins were involved in ‘transport facilitation’ (3%), some examples being aquaporin, sugar transport proteins, and ion-channel proteins. The ‘transcription’ (2%) category included messenger RNAs and transcription factors, whilst ‘cell cycle & DNA processing’ (2%) included putative DNA methylation proteins. Clustering of the 26 putative defencerelated ESTs resulted in 20 unigenes (Table 1), representing 4% of the unigene set. A comparison can be made between the functional distributions of the independent ESTs and clustered unigenes to show those categories represented by highly expressed genes, as these categories will have a lesser value in the clustered distribution compared to the independent EST distribution (Fig. 2). This was clearly apparent for ‘protein synthesis/fate’, ‘energy’, and ‘transcription’ where the numbers of independent ESTs are more than double the number of unigenes. The members of these categories, which include various ribosomal/messenger RNA molecules as well as transcripts involved in photosynthesis and respiration, are sampled more frequently in random sequencing, supporting their high level of expression and potential involvement in general housekeeping.
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Fig. 1. Functional distribution of the 516 Cicer arietinum (ICC3996) unigenes.
Table 1 Cicer arietinum (ICC3996) defence-related unigenes after BLASTN and BLASTX sequence homology searches performed on the 23/02/2004 EST number
Database match
Matching database accession
e value
Copy number
CA0070 CA0082 CA0117 CA0188
A. thaliana extensin-like disease resistance protein G. max gamma-thionin defensin/protease inhibitor N. tabacum Avr9/Cf-9 rapidly elicited protein 65 B. oleracea pathogen-induced translation initiation factor nps45 V. unguiculata S1-3 pathogen-induced protein A. thaliana putative disease resistance protein C. arietinum transcription factor EREBP-1 M. sativa caffeoyl-CoA-methyltransferase (EC 2.1.1.104) P. sativum pathogenesis-related protein 4A C. arietinum beta-1-3-glucanase O. sativa protein with leucine zipper S. tuberosum pathogen-induced transcription factor E. esula leucine-zipper containing protein M. domestica cinnamyl alcohol dehydrogenase (CAD1) C. arietinum nematode resistance protein Hs1pro-1 O. sativa multi-resistance transporter protein A. thaliana putative flavonol glucosyl transferase S. tuberosum SNAKIN2 antimicrobial peptide precursor A. thaliana elicitor-induced receptor protein M. sativa pathogenesis-related protein class 10
O82202b Q39807b Q9FQZ0b SUI1_BRAOLa
6!10K28 2!10K11 2!10K12 4!10K34
1 1 2 1
Q9MB24b DR29_ARATHa Q8GTE5b CAMT_MEDSAa Q9M7D9b Q9XFW9b Q8RZJ0b Q9LL86b Q945B7b O65152b Q94BW7b Q943U4b HQGT_ARATHa Q93X17b Q9FH56b PR1_MEDSAa
4!10K20 6!10K13 2!10K95 5!10K98 5!10K61 2!10K26 3!10K48 2!10K11 2!10K13 2!10K34 7!10K16 7!10K12 4!10K25 5!10K23 1!10K11 1!10K30
1 1 3 2 1 1 1 1 1 1 1 1 1 2 1 2
CA0191 CA0228 CA0257 CA0260 CA0303 CA0329 CA0442 CA0452 CA0557 CA0632 CA0641 CA0758 CA0984 CA1012 CA1079 CA1159 a b
Matching to SwissProt database accession. Matching to SpTrEMBL database accession.
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Fig. 2. Comparison of functional distributions amongst independent ESTs and clustered unigenes.
Interestingly, the ‘unknown’ category also fits this scenario, suggesting that many of its members may become highly expressed after A. rabiei challenge. Detailed examination of the eight unigenes that contain more than 10 independent ESTs (Table 2) shows that the most highly expressed EST is a chloroplast mRNA of the ‘transcription’ category. Other highly expressed ESTs include ribosomal RNAs (‘protein synthesis/fate’), putative enzymes of the ‘cellular metabolism’ category, and a chlorophyll protein and Rubisco enzyme (‘energy’). 3.3. Comparison with other plant species The availability of the annotated set of the entire Arabidopsis thaliana genome, as well as large EST sets for other leguminous plant species, enabled the determination of the level of gene conservation and similarity between C. arietinum and other related plant species. The C. arietinum (ICC3996) unigenes were compared with
the TIGR Gene Indices of A. thaliana (http://www.tigr.org/ tdb/tgi/atgi), Medicago truncatula (http://www.tigr.org/tdb/ tgi/mtgi), Lotus japonicus (http://www.tigr.org/tdb/tgi/ljgi) and Glycine max (http://www.tigr.org/tdb/tgi/gmgi) using TBLASTX. The similarities of each species to the C. arietinum (ICC3996) unigenes are shown in Fig. 3. An important observation was the high level of weak/no similarity detected for the model legumes M. truncatula (47.48%) and L. japonicus (58.14%), indicating that C. arietinum may possess many genes with little or no homology to genes within these model legumes. Integration of the search results revealed that 33.91% of the unigenes were conserved in all five species, whilst 4.46% were conserved only in the legume species, and included defencerelated, cell signalling/communication and cellular metabolism unigenes, as well as several hypothetical proteins. Interestingly, 57.56% of the C. arietinum (ICC3996) unigenes were not significantly similar to the A. thaliana genome, and may represent genes for morphological
Table 2 Description of the eight unigene clusters containing more than 10 independent ESTs Number of ESTs in cluster
Cluster identification from BLASTN or BLASTX
e value
Functional category
173 34 31 24 17 16 15
C. arietinum chloroplast 4.5S/5S/16S/23S messenger RNA C. arietinum 26S ribosomal RNA C. arietinum putative deoxycytidylate deaminase L. esculentumlt;/AsSETItalicO chlorophyll a/b binding protein O. sativa ribosomal RNA intron-encoded homing endonuclease P. sativum UDP-glucose 4-epimerase (EC 5.1.3.2) C. arietinum ribulose 1,5-bisphosphate carboxylase small subunit precursor (EC 4.1.1.39) A. thaliana mitochondrial 26S ribosomal RNA
4!10K11 1!10K101 2!10K48 2!10K83 4!10K26 1!10K26 1!10K95
Transcription Protein synthesis/fate Cellular metabolism Energy Protein synthesis/fate Cellular metabolism Energy
4!10K12
Protein synthesis/fate
15
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Fig. 3. Distribution of conservation between C. arietinum (ICC3996) unigenes and the Gene Indices of Arabidopsis thaliana, Medicago truncatula, Lotus japonicus and Glycine max according to similarity levels determined by TBLASTX e values.
features or metabolic processes specific to leguminous species. Although A. thaliana represents a model for flowering plants, it may not possess all the desired characteristics of other plant species, and subsequently may be unsuitable for use in the study of those characteristics. Alternatively, the sequencing of untranslated regions, or the presence of non-annotated A. thaliana genes could cause absences in sequence similarities.
The unigenes conserved between C. arietinum (ICC3996) and A. thaliana were classified into their functional categories, and the levels of similarities for each category are shown in Fig. 4. The most highly conserved categories included ‘transcription’, ‘protein synthesis/fate’, ‘energy’ and ‘cellular metabolism’, whilst the least conserved categories included ‘defence’, ‘cell rescue/death/ageing’ and ‘cellular communication/signal transduction’.
Fig. 4. Levels of similarity for the unigenes conserved between C. arietinum (ICC3996) and A. thaliana according to functional categories. Similarity levels were determined by TBLASTX e values.
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4. Discussion A collection of 1021 independent ESTs was clustered and assembled to generate 516 unigenes. Clustering allowed the detection of highly expressed transcripts, and the comparison between functional distributions of the independent ESTs and unigenes provided evidence for this (Fig. 2). It was expected that functional categories mainly involved with general housekeeping activities would show the highest level of expression, and this was apparent by the ‘transcription’, ‘energy’, ‘cellular metabolism’ and ‘protein synthesis/fate’ category comparisons. The specific ESTs with the highest expression (Table 2) were also as expected. These ESTs all belonged to general housekeeping categories and possess well-characterised functions in common plant activities. An unexpected observation was the independent ESTs to clustered unigenes comparison of the ‘unknown’ category in Fig. 2, where the majority of ESTs were expected to possess a non-housekeeping role to justify their anonymity amongst databases. A possible explanation for this may be that the A. rabiei inoculation of the plant caused a substantial increase in the expression of numerous unknown defence-related transcripts, resulting in the skewing of the data toward high levels of expression in the ‘unknown’ category. The large amount of nucleotide sequence data in public databases enabled the comparison of the C. arietinum (ICC3996) unigenes to the entire genome content of A. thaliana, as well as the current EST collections of M. truncatula, L. japonicus and G. max (Fig. 3). The highest level of similarity was observed in M. truncatula, followed by G. max, whilst L. japonicus and A. thaliana possessed the least similarity. It was expected that the three leguminous species would show the highest levels of similarity, as was observed for M. truncatula and G. max. The lower similarity level observed for L. japonicus may be attributed to a smaller EST collection, and it is important to recognise that the similarity levels observed do not reflect phylogenetic relationships, but rather the coverage of EST sequencing for each species. Further, the high levels of weak/no similarity observed for the two model legumes, M. truncatula and L. japonicus may indicate a significant divergence in C. arietinum gene content, or the presence of many untranslated sequences within the chickpea unigene collection. However, the levels of similarity observed for the model legumes were only marginally superior than observed for A. thaliana, indicating a possible insufficiency of homology for their use in the study of economically important legumes. Subsequently, the use of these models for the study of chickpea may be limited. The expanding collections of ESTs for the model legumes may eventually provide adequate homology to the chickpea transcriptome, but the results of this study suggest a significant proportion of chickpea genes will remain non-homologous to those collections. The comparisons also revealed several gene
candidates that were absent in A. thaliana but present in all legume species, including defence-related and cellular communication/signal transduction unigenes that may be functionally specific for the protection of leguminous plants only. Further, several cellular metabolism unigenes were identified only in the legumes, indicating a possible role in a legume-specific metabolic pathway such as nodulation. Numerous legume-specific hypothetical proteins may also represent genes involved in these pathways. The level of similarity between the functionally annotated C. arietinum (ICC3996) unigenes and the A. thaliana genome (Fig. 4) may reflect the speed of gene evolution, based on the assumption that slow evolving genes show a high level of conservation, and fast evolving genes show a low conservation level. The most highly conserved categories contained unigenes encoding structural, ribosomal, photosynthetic, translational and metabolic proteins, whilst the least conserved categories contained unigenes encoding defence and stress-related proteins, as well as signalling proteins such as protein kinases. These observations are similar to those witnessed in soybean [16] and L. japonicus [17], and lend support to the theory that genes related to basic processes have not significantly evolved, whereas regulatory genes have. Most pertinent to the aims of this study were the potential defence-related ESTs. To enrich for these sequences, postinoculation tissue samples of a resistant chickpea (ICC3996) were used as starting material to generate cDNA. Stem and leaf tissue samples were taken at two time points (24 and 48 h) and pooled in an attempt to capture a broad range of gene sequences that may be involved in different branches of potential defence-related pathways. The putative defence-related ESTs identified in this study (Table 1) accounted for 4% of the unigene set and represented a variety of plant defence mechanisms and pathways, and will be the basis for the investigations detailed in a subsequent paper [14]. Briefly, the Extensinlike protein (CA0070), Caffeoyl-CoA-methyltransferase (CCoAOMT) (CA0260), and Cinnamyl alcohol dehydrogenase (CAD1) (CA0632) are all putatively involved in the synthesis of lignin or cell walls. CCoAOMT has previously been identified as part of an elicitor-induced plant defence response [18], whilst an extensin has been shown to proliferate rapidly after the oxidative burst in chickpea [19]. Pathogenesis-related protein 4A (CA0303), Beta-1,3glucanase (CA0329), and pathogenesis-related protein class 10 (CA1159) may all be grouped as pathogenesisrelated (PR) proteins, which can have a beta-glucanase, chitinase, or lysozyme activity. Of these, only a Beta-1,3glucanase has previously been isolated from chickpea. One other defence-related unigene may be classed as a PR protein—the gamma-thionin defensin/protease inhibitor (CA0082), which may be involved in pathogen defence by preventing the hydrolysis of plant cell proteins by fungal toxins [20].
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Five of the defence-related unigenes may be grouped into a putative signalling or defence-activating category; Translation initiation factor nps45 (CA0188), Transcription factor EREBP-1 (CA0257), Avr9/Cf-9 rapidly elicited protein 65 (CA0277), Pathogen-induced transcriptional activator (CA0452), and Elicitor-induced receptor protein (CA1079). The most characterised protein from this group is the transcription factor EREBP-1 (Ethylene Responsive Element Binding Protein), which is involved in the regulation of disease resistance pathways, and has been previously isolated from chickpea. The largest sub-group of the defence-related unigenes were those of putative defensive functions that had not been fully characterised, including; S1-3 pathogen-induced protein (CA0191), Putative disease resistance protein (CA0228), Protein with leucine zipper (CA0442), Leucine-zipper containing protein (CA0557), Multi-resistance transporter protein (CA0758), and SNAKIN2 antimicrobial peptide precursor (CA1012). The leucine-zipper proteins were identified as defencerelated as they may represent basic region/leucine-zipper motif (bZIP) transcription factors that are involved in several plant processes including pathogen defence [21]. One of the defence-related unigenes was implicated in phytoalexin production; the salicylic acid-induced UDP flavonol glucosyl transferase (CA0984), whilst the final defence-related unigene that cannot be grouped with any others is the Nematode resistance protein (CA0641) that, although only implicated in chickpea nematode resistance, could possibly represent a broad-spectrum defence protein. The defence-related transcripts aside, the present study also isolated numerous signalling and abiotic-stress-induced transcripts that may be important in the overall A. rabiei defence mechanism of chickpea. Although such transcripts may not be differentially expressed, they may represent integral parts of defence-activating and regulatory pathways. This study was the first step in a genomics approach to enable the discovery and study of many genes simultaneously. The overall gene sequence data generated in this study is important as it may, through the use of microarray expression studies, provide information concerning the specific defence pathway employed by chickpea, as well as the function of genes involved. In summary, a collection of chickpea ESTs was generated from which potential A. rabiei defence-related unigenes were uncovered. Similarity comparisons to the chickpea unigenes revealed that a high proportion of the chickpea transcriptome may be insufficiently homologous to model legumes, limiting use of their EST collections for the study of chickpea. In addition to the putative defencerelated unigenes, perhaps the most important group of unigenes was those of ‘unknown’ and ‘unclear’ identity. The unigenes making up these categories may include novel defence-related genes acting against A. rabiei, and similarly, the ‘cellular communication/signal transduction’ and ‘cell rescue/death/ageing’ categories may contain unigenes that are essential to the coordination of defence
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responses. The next step will involve the use of cDNA microarrays to study expression patterns of all unigenes identified in this study. By studying up- or down-regulation in resistant and susceptible chickpea accessions over a range of post-inoculation time points, it may be possible to identify the genes involved and the pathway of A. rabiei defence, which would prove a valuable resource to understand ascochyta blight resistance. In addition to microarray analysis, the defence-related unigenes isolated in this study may also be applied to genetic mapping experiments where, if polymorphic between parents, they may act as ‘perfect’ markers to identify QTLs associated with A. rabiei defence. The unigenes may also be used in SNP discovery, which involves the amplification and analysis of genomic DNA sequences homologous to each unigene from various chickpea accessions, restriction fragment length polymorphism (RFLP) mapping, and cleaved amplified polymorphic sequences (CAPS) mapping. These alternative applications are all directed toward producing molecular markers linked to A. rabiei defence, and the defence-related unigenes generated in this study provide a valuable resource for such purposes. Potential markers derived from the unigene sequences may be used in breeding and selection programs aimed at developing agronomically viable chickpea cultivars with resistance to ascochyta blight.
Acknowledgements The authors would like to acknowledge the Grains Research and Development Corporation (GRDC) for their generous granting of a research scholarship. The authors thank Kevin Meredith, Dr Chris Pittock, Dr Trevor Bretag, and Kristy Hobson (Department of Primary Industry, Horsham) for the supply of seeds, fungal cultures, and valuable advice.
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