Both authors have contributed equally to this paper.
Analysis of strawberry genes differentially expressed in response to Colletotrichum infection
Article first published online: 1 NOV 2006
Volume 128, Issue 4, pages 633–650, December 2006
How to Cite
Casado-Díaz, A., Encinas-Villarejo, S., Santos, B. d. l., Schilirò, E., Yubero-Serrano, E.-M., Amil-Ruíz, F., Pocovi, M. I., Pliego-Alfaro, F., Dorado, G., Rey, M., Romero, F., Muñoz-Blanco, J. and Caballero, J.-L. (2006), Analysis of strawberry genes differentially expressed in response to Colletotrichum infection. Physiologia Plantarum, 128: 633–650. doi: 10.1111/j.1399-3054.2006.00798.x
- Issue published online: 10 NOV 2006
- Article first published online: 1 NOV 2006
- Received 3 April 2006; revised 20 June 2006
- Top of page
- Materials and methods
Important losses in strawberry production are caused by species of the fungus Colletotrichum, the causal agent of anthracnose. However, very limited studies at molecular level exist of the mechanisms related to strawberry susceptibility against this pathogen. We have analysed a moderately resistant cultivar (cv. Andana) together with a very susceptible one (cv. Camarosa) during the process of infection with Colletotrichum acutatum at a molecular level. To gain insight into this interaction we have identified a large number of strawberry genes involved in signalling, transcriptional control, defence and many genes with unknown function with altered expression in response to C. acutatum infection. Spatial and temporal gene expression profiles after infection showed that the response was dependant on the tissue and cultivar analysed and also quicker and/or stronger in the moderately resistant cultivar (cv. Andana) than in the susceptible one (cv. Camarosa). Interestingly, we found that genes described as being induced during pathogen infection such as γ-thionins, peroxidases, chitinases and β-1-3-glucanases were downregulated in fruit and/or crown tissues of the very susceptible cultivar. Our results yielded a first insight on some of the genes responding to this plant–pathogen interaction at molecular level and suggest that pathogen progression can be dependent upon a reduction of the active defences of strawberry and this is genotype and tissue dependent.
disease severity index
expressed sequence tags
potato dextrose agar plus 2 g l−1 yeast extract
quantitative real time-polymerase chain reaction
suppression subtractive hybridization
- Top of page
- Materials and methods
Anthracnose is a severe strawberry (Fragaria x ananassa Duch.) disease caused by species of the fungus Colletotrichum, one of the most important genera of strawberry pathogens. In addition to strawberry, these fungi have an extremely wide host range including vegetables, field and forage crops, fruit trees and ornamentals (Dyko and Mordue 1979). Although little is known about the origin and relationship between the organisms that cause the disease, it is commonly accepted that Colletotrichum acutatum, Colletotrichum fragariae and Colletotrichum gloeosporioides (teleomorph Glomerella cingulata) are the three major species causing the fruit and crown rot diseases in strawberry (Maas 1984). The control of Colletotrichum diseases of strawberry requires a combination of chemical, cultural and genetic methods but regular pesticide applications are environmental contaminants and are not yet considered an appropriate cultivation practice. In Europe, C. acutatum is considered as a quarantine organism (Barrau et al. 2001, Bosshard 1997, Denoyes-Rothan and Baudry 1995, Freeman and Katan 1997).
In general, the use of disease-resistant cultivars is the most suitable method for disease control (Quirino and Bent 2003). Resistance has been defined as an incompatible interaction between host and pathogen. Incompatibility, involving processes in the plant that prevent or retard pathogen growth, can be dependent on a single gene pair, i.e. a host resistance gene and a pathogen avirulence gene (van der Biezen and Jones 1998). The establishment of infection is because of an inadequate defence response of the host to the invading pathogen in terms of timing and intensity. Such a response has generally been described as involving activation of signalling molecules and pathways, ultimately leading to changes in gene expression and defined cellular responses (Dangl and Jones 2001, Maleck and Dietrich 1999).
Most of the disease-resistant crop varieties have been generated by traditional breeding. This process is not only time consuming but, more importantly, brings about other undesirable traits with the disease-resistance trait, especially in the case of multigenically inherited resistance (Quirino and Bent 2003). On the other hand, disease resistance based on single race-specific resistance (R) genes has not been shown durable in many crop species (Quirino and Bent 2003). In addition, resistance against a given pathogen race or species cannot always be found in the available germplasm, and in many clonally propagated crops any plant breeding is minimally feasible (Quirino and Bent 2003).
Strawberry is a clonally propagated crop and substantial differences in susceptibility to C. acutatum has been reported among cultivars (Denoyes-Rothan and Baudry 1995, Howard et al. 1992, Smith and Black 1990). The development of a biotechnological strategy for improvement of resistance against C. acutatum may be important for effective control strategies as alternative to traditional breeding.
Only few molecular studies on strawberry–pathogen interactions exist in general and strawberry C. acutatum in particular. Despite the isolation of some genes in strawberry known to be involved in pathogen defence, no information is available about the response of strawberry to C. acutatum or any other pathogen (Khan and Shih 2004, Khan et al. 1999, 2003, Mehli et al. 2004, Wu et al. 2001).
To identify genes with altered expression during the interaction of strawberry and C. acutatum we have applied a suppression subtractive hybridization (SSH) approach (Diatchenko et al. 1996). The expression pattern of selected genes identified by SSH has been further characterized by quantitative real time-polymerase chain reaction (qRT-PCR) upon pathogen challenge. A comprehensive analysis of both induced and repressed genes in strawberry during pathogen infections will lead to a better understanding of the molecular processes involved in infection and resistance and will contribute to the development of future biotechnological strategies for resistance.
Materials and methods
- Top of page
- Materials and methods
For the evaluation of anthacnose crown rot caused by C. acutatum, plants from different strawberry cultivars (Table 1) were obtained by micropropagation following the procedure of López-Aranda et al. (1994). After an acclimatization period of 8 weeks, plantlets were placed in 20-cm diameter plastic pots containing sterilized peat (Klansmann-Deilmann, Geeste, Germany) and grown for a minimum of 6 additional weeks prior to inoculation. Plants were maintained in a greenhouse at 25°C day/15°C night ± 5°C. Older leaves were removed 15 days before inoculation and three to four young leaves remained on each plant at inoculation time as recommended by Smith and Black (1990). For experiments involving generation of subtracted libraries and identification of genes differentially expressed after inoculation with C. acutatum, two cultivars that showed extreme behaviour in terms of susceptibility to this pathogen and a good adaptability to the Spanish climatic conditions were selected and micropropagated under the same conditions.
|Advances lines and cultivars||DSI|
|Oso Grande||7.33 ab|
Fungal materials and Colletotrichum controlled inoculation of strawberry
The C. acutatum isolate CECT 20240 was obtained from strawberry crown and grown on Difco potato dextrose agar (Difco, Sparks, MD) plus 2 g l−1 yeast extract (PDAY) under continuous fluorescent light (Osram L 18 W/21-840 Hellweiss Lumilux Cool White, 75 mE m−2 s−1) for 7 days at 25°C. The resistance of different strawberry cultivars to anthracnose crown rot caused by C. acutatum was evaluated using the following procedure: a conidial suspension was prepared by flooding the surface of culture plates with sterile distilled water, scraping the surface with a scalpel and filtering the suspension through cheesecloth. The concentration was adjusted to 104 conidia/ml by dilution and counting with a haemocytometer. Ten micropropagated plants of each cultivar were dipped in the conidial suspension for 3 min. They were then transplanted into, and maintained in, plastic pots for 30 days at 25 ± 5°C (day)/15 ± 5°C (night) and 70–80% relative humidity before incubation at 100% R.H. for 72 h in a glasshouse at 15–25°C. Symptoms of disease were evaluated weekly. Disease severity indices (DSIs) were calculated using a 1–8 scale, based on crown tissues response (1 = healthy plant to 8 = dead plant, plus 0.5 when the pathogen was also isolated from root tissues). Analysis of variance was performed on the indices and least significant differences were calculated at P < 0.05. Data are presented as means for each cultivar. Cultivars were grouped into three categories based upon their disease response: the resistant group (disease responses 1 and 2, represented no visual symptoms); the moderately resistant group (disease responses from 3 to 4.5, represented crown necrosis without plant wilting) and the susceptible group (disease responses upper 5, represented a wilting reaction because of crown rot).
The same isolated of C. acutatum used in the experiment for selection of cultivars was used for the strawberry inoculations of micropropagated Camarosa and Andana plantlets for the generation of subtracted libraries and the experiments involving identification of strawberry genes showing differential expression to C. acutatum. The conidial suspension of C. acutatum was also prepared as indicated. Strawberry plants were artificially inoculated with a hand-pump sprayer and the conidial suspension was applied until runoff (Denoyes-Rothan and Baudry 1995). Inoculated plants were enclosed in light plastic bags until fixed in liquid nitrogen to maintain high relative humidity and were incubated in a growth chamber at 25°C, exposed to a 16-h photoperiod beneath fluorescent light (Sylvania Luxline Plus F58W/840 Cool White DE Luxe, Germany, 100.5 μE m−2 s−1). Control plants were sprayed with sterile distilled water and incubated as described above. Isolating the pathogen from the strawberry plants after the same time of incubation tested the efficacy of inoculation procedure: crown sections were surface sterilized and plated on PDAY for reisolation of the pathogen.
Generation of subtracted libraries
Total RNA was isolated from crowns of strawberry plants (cvs. Camarosa and Andana) inoculated under controlled conditions with C. acutatum or sprayed with water as control. To obtain a wide spectrum of differentially expressed genes, crown tissue was collected at 1, 3, 5 and 7 days after each treatment. Within each time point, a pool of crowns was obtained and messenger RNA (mRNA) was extracted from every pooled crown sample. A final ‘tester’ mRNA population, for both strawberry cultivars was generated by mixing equal quantities of mRNA from the inoculated time point samples. A final ‘driver’ mRNA population was also generated by mixing equal quantities of mRNA from the control time point samples. Messenger RNA was isolated by magnetic separation technology using Dynabeads mRNA Purification Kit (Dynal Biotech, Oslo, Norway).
SSH was performed as described by Diatchenko et al. (1996) using the PCR-Select complementary DNA (cDNA) Subtraction Kit (Clontech Laboratories, Palo Alto, CA) except that the SuperScript ‘One Step’ RT-PCR System (GibcoBRL) and 2 μg of poly(A)+ from each ‘tester’ and ‘driver’ populations were used to obtain double-stranded (ds)-cDNA. Subtracted cDNA fragments were directly cloned into a TA cloning vector (pGEM-T Easy, Promega, Madison, WI). Escherichia coli XL10-Gold Ultracompetent Cells from Stratagene (XGAL-IPTG, La Jolla, CA) was used as host cells. Transformants were grown on standard LB-Ampiciline-XGAL-IPTG plates (Duchefa Biochemie BV, Haarlem, The Netherlands) for positive selection in a blue-white screening. To also isolate downregulated genes, mRNA extracted from control crown samples was used as ‘tester’ mRNA population and the mRNA extracted from inoculated crown samples was used as ‘driver’ mRNA population for every strawberry cultivar. We generated four different cDNA libraries in all (one upregulated and one downregulated for every cultivar) with approximately 3 × 106 clones in each one, and insert sizes ranged from 400 to 1200 bp.
DNA sequencing and computer analysis
SSH clones were arranged in plates and used for SSH plasmid DNA template preparation, sequencing and analysis performed at NewBioTechnic, S.A. (NBT), Sevilla, Spain. Plasmid DNA templates were robotically isolated from the previously manually picked SSH clones using the Montage Plasmid Miniprep 96 Kit (Millipore, Billerica, MA) on a Biomek 2000 (Beckman, Fullerton, CA). Partial nucleotide sequences of the cDNA inserts were determined by single-pass sequencing using the Big Dye v.3 sequencing system (Applied Biosystems, Foster City, CA) with either the SP6 primer (5′ AGCTATTTAGGTGACACTATAG 3′) or the T7 primer (5′ TAATACGACTCACTATAGGG 3′). Samples were sequenced on an ABI 3100 sequencer (Applied Biosystems Foster City, CA).
DNA sequences were automatically surveyed for quality using the Phred software (Ewing et al. 1998). Sequences were screened for the presence of vector sequences, low quality sequences (Phred) and small insert (<100 bp) and were trimmed to remove vector sequences and linkers. Quality trimmed sequences were extracted and each library of expressed sequence tags (ESTs) was separately assembled into clusters consisting of overlapping and contiguous DNA sequences using the CAP3 assembler. Statistics of the assemblies were generated by perl scripts using BioPerl modules. We use the filtering criteria described by (Liang et al. 2000, Pertea et al. 2003) as follows: the minimum length of the overlap (default 40 bp), the minimum percent of identity for the overlap (default 95%) and the maximum mismatched overhang (dynamically adjusted for long sequences and overlaps; the default start at 30 nucleotides). The longest consensus sequence of each cluster was used to search against the public databases. Singleton ESTs that did not cluster but that exhibited similarity to the same identified database sequence as a given cluster were counted as part of that cluster, and thus counted as redundant. Unique sequences (singletons plus contig consensus) were translated and used as query sequences to search the GenBank non-redundant protein database by using the program blastx (Altschul et al. 1990). The top-scoring genes were used to group the transcripts by their putative function.
Genomic PCR analysis
To discriminate between both strawberry and C. acutatum sequences, the presence of each gene in the chromosome was detected by PCR. Thus, specific primers were designed from each EST sequence and PCR was performed using either strawberry or C. acutatum genomic DNA. PCR products were isolated and sequenced to confirm the specificity of the amplified sequence. All the selected clones studied here corresponded to strawberry plant genes.
Differential expression of strawberry EST clones
To determine what proportion of clones in the four strawberry subtractive libraries represent differentially expressed transcripts, and to identify ESTs for further study, we used a ‘reverse northern’ procedure previously described (Beyer et al. 2001, Medina-Escobar et al. 1997). Two identical DNA blots were made of the PCR amplified cDNA inserts from 400 clones (100 clones for each cultivar and ‘tester’) by loading equal quantities of each PCR product. Clontech nested PCR primer 1 and nested PCR primer 2R were used for the PCR reaction and for every clone. cDNA inserts from known constitutively expressed genes whose expression level did not significantly change after infection were also loaded to ensure equal labelling (internal controls). The blots were hybridized with a labelled cDNA as probe (108 cpm μg−1) derived from a pool of crown RNA samples from strawberry plants sprayed either with the conidia of the pathogen (inoculated sample) or with water (control sample), after 1, 3, 5 and 7 days of treatment.
Gene expression in response to infection with C. actatum
To analyse the expression pattern of genes in fruits naturally infected with C. acutatum, we used fruit collected from the field of the Camarosa (susceptible) strawberry cultivar. A pool made of red fruits with different degrees of infection (from 10 to 60% of the fruit surface visually affected) and another one consisting of non-infected red fruits were prepared. Total RNA was extracted from these pools to generate RNA infected and control samples, respectively.
To analyse the expression pattern of genes in crown tissue in response to infection with C. acutatum, we used crowns from both Camarosa (susceptible) and Andana (less susceptible) cultivars infected and non-infected (sprayed with water) with C. acutatum under controlled conditions as described above. For each cultivar, total RNA was extracted from a pool of crowns from several strawberry plants growth in pots under greenhouse conditions and after 1, 3, 5 and 7 days of treatment.
Each RNA sample was used for the relative quantification of gene expression as described above using specific internal primers. RT-reactions were carried out independently for every couple of genes: the internal control gene (Farib413) and the particular one under analysis.
Relative quantification of gene expression
Transcript quantification after C. acutatum inoculation was determined by real-time PCR methodology using the thermal iCycler system from Bio-Rad (Hercules, CA) and SYBR Green from Molecular Probes (Eugene, OR) as fluorophor. Each experiment was repeated twice and so, two independent RNA extractions were made for each time point sample.
Total RNA extraction was performed as previously described for other strawberry genes (Medina-Escobar et al. 1997). For every RNA sample, two independent RT reactions (20 μl each) were generated using iScript cDNA Synthesis kit (Bio-Rad), 1–3 μg of DNaseI-treated total RNA, following the manufacturer conditions. The product of both RT reactions was mixed to obtain a homogeneous RT reaction mix to avoid small changes in cDNA concentration because of differences in the efficiency of the RT reaction. Two microlitres of the RT reaction mix was used for the PCR reactions.
Quantitative PCR reactions
The primers were designed using the bioinformatics application (Oligo 6.78 for Mac OS X) (Rychlik 2002).
The amplification program was optimized for 40-step cycles including 20 s at 95°C followed by 40 s at 70°C. Detection of the fluorescent product was carried out after an additional step at 2°C below the Tm. A melting curve was obtained by heating to 95°C for 3 min, cooling at 60°C for 30 s and slowly heating at 0.5°C/10 s to 98°C. The correct size of the PCR products was also checked by agarose gel electrophoresis analysis.
PCR amplification reactions were carried out in 25 μl total volume of a mixture containing in 1× PCR buffer (Biotools, Madrid, Spain), 2 mM MgCl2, 0.25 mM dNTPs (deoxynucleotides-triphosphate), 0.5 μM of each sequence-specific primers, 2.5 μl SYBR Green I (1:15 000 diluted), 3 μl of transcribed cDNA and 0.4 U Taq polymerase (Biotools). Five hundred picograms of transfer RNA was added to the reaction mix to avoid/reduce the fluorescence from primer dimers (Stürzenbaum 1999).
For each time point and gene, six PCR reactions were performed (three for every independent RNA extraction) and the corresponding Ct values (threshold cycle value) were determined. A mean value of these Ct values was calculated for each sample and gene. The Ct is defined as the cycle at which fluorescence is first detectable above background and is inversely proportional to the logarithm of the initial copy number.
The Ct values of each gene were normalized using the Ct value of the strawberry Farib413 gene. The clone Farib413 corresponding to an internal strawberry RNA interspacer (16S–23S) region was chosen as control ‘housekeeping’ gene in all the experiments. No significant variation in gene expression was detected for this gene after infection (data not shown) as previously described (Simpson et al. 2000). The normalized Ct values were utilized to determine the fold changes of gene expression according to the following expressions:
In order for quantification to be accurate, the relative efficiencies of reverse transcription of the gene used as control and genes under study must be equal or nearly equal. A plot of the differences in Ct values of Farib413 and the experimental genes when these genes are amplified with serially diluted RNA samples was obtained as previously described (Khan and Shih 2004). In addition, and since the high copy number gene, different dilutions (1/100, 1/400, 1/1000, 1/2000, 1/4000) of the Farib413 cDNA obtained were also tested to avoid Ct values too low (i.e. lower than 10), which are considered not reliable for the gene expression quantification under our experimental conditions. All the slope values were found to be less than absolute value 0.1, indicating the relative reverse transcription efficiencies to be approximately equal for quantification purposes (Khan and Shih 2004). Farib413 cDNA dilution of 1/4000 was found sensitive enough to detect small changes (either two-fold increase or decrease) in Farib413 RNA concentration (data not shown) and was chosen for the gene quantification studies.
Northern blot analysis
Northern blot analyses were performed using specific gene probes as previously described (Medina-Escobar et al. 1997). A cDNA corresponding to 18S ribosomal RNA was used to control equal loading of RNA samples.
- Top of page
- Materials and methods
Selection of the strawberry cultivars
Prior to beginning the main study, the resistance of various cultivars of strawberry to anthracnose caused by C. acutatum was evaluated. A great variability was observed in the response of these cultivars following inoculation with the pathogen, with values in severity indices ranging from 2.40 to 8.50 (Table 1). For further studies, Camarosa (a popular Californian cultivar) and Andana (a new Spanish cultivar, currently being introduced into new markets; Baruzzi and Faedi 2005) were selected. The reasons for their choice were two-fold. Firstly, because they differed in their resistance to the pathogen, e.g. Camarosa showed a DSI of 6.55 and was included in the susceptible group (characteristic: the occurrence of a wilting reaction) while Andana showed a disease response of 3.70 and was assigned to the moderately resistant group (characteristic: occasional crown necrosis; no wilting). Secondly, because they also are very well adapted to the climatic crop conditions of SW Spain, the major strawberry growing area in Europe.
Identification of strawberry genes differentially expressed after C. acutatum infection
To determine genes putatively involved in the strawberry response to C. acutatum infection, we identified genes differentially expressed upon infection. For this purpose we generated strawberry normalized subtracted libraries of genes up- and downregulated after C. acutatum infection using the SSH methodology (Diatchenko et al. 1996). We anticipated that the use of the susceptible strawberry cultivar Camarosa and the moderately resistant cultivar Andana might allow the identification of cDNAs involved in strawberry plant defence and/or cDNAs differentially expressed in a specific cultivar after infection. From each cultivar, a ‘tester’ mRNA population was obtained by mixing equivalent quantities of mRNA extracted from strawberry crown samples at 1, 3, 5 and 7 days after Colletotrichum infection (see Materials and methods). The control ‘driver’ mRNA population was obtained following the same scheme and time points but from non-infected samples. The selected time points were chosen based on previous microscopic observations of C. acutatum progression (Arroyo et al. 2005).
We sequenced a total of 3191 ESTs of all four subtracted libraries generated (around 800 ESTs from each library). To determine the level of redundancy, those ESTs obtained from every individual library were initially analysed and individually assembled into clusters consisting of overlapping and contiguous DNA sequences. These sequences were then compared with other sequences present in public databases using blast. Each cluster was counted as a different individual species or unigene, and each individual species that did not exhibit similarity to a database sequence with similarity to a cluster was also counted as unigene (Nelson et al. 1999).
Most of the sequenced ESTs corresponded to non-ribosomal genes (Table 2). As expected and based on the normalisation process, most of these non-ribosomal genes were not assembled into contigs, thus representing unique sequences. Values of different species of ESTs or unigenes for up- and downregulated libraries were, respectively, 92.0 and 93.1%, for Andana, and 86.1 and 90.5%, for Camarosa.
|Non-ribosomal||778 (95.46%)||696 (96.94%)||747 (96.39%)||859 (97.28%)||3080 (96.52%)|
|Unique sequences||640 (82.26%)||587 (84.34%)||537 (71.89%)||690 (80.33%)||2183 (70.88%)|
|Unigenes||716 (92.03%)||648 (93.10%)||643 (86.08)||777 (90.45%)||2647 (85.94%)|
|Redundancy||62 (7.97%)||48 (6.90%)||104 (13.92%)||82 (9.55%)||433 (14.06%)|
When sequences were analysed altogether, the number of unigenes decreased as sequences from a particular library were found to be present in the other libraries. However, this number of total unigenes was still high (2647 sequences) with a low level of redundancy (Table 2). Therefore, based on the number of ESTs obtained in our study and the low level of redundancy, we conclude that we have identified a high proportion of genes from strawberry involved in the response to Colletotrichum.
Functional classification and analysis of genes differentially expressed
Comparison of unigene sequences to the nucleic acid and protein databases allowed function assignment based on homology. In Table 3, the overall of sequenced ESTs both from Andana and Camarosa has been grouped following the same functional classification used for Arabidopsis thaliana Munich Information Center for Protein Sequences, MIPS (http://www.mips.biochem.mpg.de). Genes potentially involved in defence, cell rescue, cell death and ageing were highly represented (11.9%). We also identified genes described to be involved in signal transduction pathways (4.5%), gene transcription processes (3.2%) and many genes of unknown function (38.3%). These categories represent 57.9% of the 3191 gene sequences already analysed by blast.
|Functional group classificationa||No. of sequences analysed||%|
|Cell growth, division and DNA synthesis||139||4.36|
|Cell rescue, defence, cell death, ageing||381||11.94|
|Cellular communication/signal transduction||144||4.51|
|Classification not yet clear-cut||506||15.86|
Based on the homologies identified by blast we selected 400 ESTs that were further analysed by reverse Northern (Fig. 1; see Materials and methods). A total of 171 genes increased their transcript abundance after infection, 102 genes showed reduced amount of transcripts and 127 (including the 20 clones used as controls) showed no significant changes. Based on these results we selected a number of candidate genes for further characterization (Table 4).
|Clone/cluster name||Size (bp)||Number of clones||Similar sequence from database||E value||Accession number|
|Cell rescue/defence/cell death/ageing|
|251CCI03||336||8||Disease-resistant-related protein, Orysa sativa—AF467728||1E−53||AJ871756|
|273ACI03||263||1||Phenylalanine ammonia-lyase, Rubus idaeus—AF237954||3E−42||AJ871757|
|319CCI04||630||3||Endo-1,4-β-d-glucanase, Populus tremuloides—AY535003||2E−67||AJ871758|
|362ACC04||431||14||Secretory peroxidase, Nicotiana tabacum—AF149251||7E−43||AJ871760|
|420CCI05||421||1||Cinnamyl alcohol dehydrogenase, Fragaria ananassa—FXU63534||4E−73||AJ871761|
|623ACI07||511||5||14-3-3-like protein D, Nicotiana tabacum—AB119472||4E−60||AJ871762|
|77ACI01*||392||1||Thaumatin-like protein PR-5b, Vitis riparia—AF178653||5E−22||AJ871763|
|284ACI03*||327||1||Pathogenesis-related protein 5-1, Helianthus annuus—AF364864||5E−15||AJ871764|
|122ACI02*||517||5||Class1 chitinase, Pisum sativum—AB087832||5E−99||AJ871765|
|367ACI04*||451||1||β-1,3-glucanase, acidic, Cottea arabica—AY389812||5E−83||AJ871767|
|368ACI04*||380||3||γ-Thionin, Castanea sativa—AF417297||4E−19||AJ871768|
|D111ACI01*||908||1||Hypersensitive-induced response protein (HIR3), Zea mays—AF236375||1E−135||AJ871769|
|A47ACC02*||464||1||Lupinus luteus pathogenesis-related-10.1B, Lupinus luteus—AF002278||2E−05||AJ871770|
|A68ACC01*||588||1||Plant peroxidase, Spinacea oleracea—Y10464||2E−59||AJ871771|
|J49CCI06*||637||1||WRKY-like transcription factor, Solanum tuberosum—AJ278507||4E−57||AJ871772|
|1045CCC11||381||4||Tomato leucine zipper-containing protein, Lycopersicon esculentum—Z12127||3E−53||AJ871773|
|1047ACC11||568||2||DNA binding protein EREBP-4, Nicotiana tabacum—D38125||2E−18||AJ871774|
|127CCI02||311||2||C2H2 zinc-finger protein SERRATE, Arabidopsis thaliana—NM_128268||2E−29||AJ871775|
|144CCI02||183||1||myb-like transcription factor 6, Gossypium hirsutum—AF034134||2E−31||AJ871776|
|523ACI06||616||1||βZIP transcription factor, Nicotiana tabacum—AY061648||9E−45||AJ871778|
|901CCI10||399||1||Putative βhelix-loop-helix transcription factor, Arabidopsis thaliana—NM_100009||5E−16||AJ871779|
|Signal transduction/cellular communication|
|346ACC04||318||1||Mitogen-activated protein kinase-I, Petroselinum crispum—Y12785||8E−61||AJ871781|
|484ACI06||295||1||Beta-Transducin-like tryptophan-aspartic acid (WD) 40 protein, Arabidopsis thaliana—NM_119407||1E−39||AJ871777|
|397CCC05||218||1||WD-repeat protein-like, Arabidopsis thaliana—AY064639||4E−32||AJ871780|
|1006CCC11||368||1||Serine/threonine protein kinase, Arabidopsis thaliana—L43125||6E−22||AJ871766|
|39ACI01*||468||2||Leucine-rich repeat (LRR) protein, tomato, Lycopersicon esculentum—T07079||6E−48||AJ871782|
|580ACI07*||225||1||LRR receptor-like protein kinase, Nicotiana tabacum—AF142596||7E−28||AJ871783|
|201ACC03*||417||1||LRR transmembrane protein kinase, Arabidopsis thaliana—NM_115033||4E−66||AJ871784|
|626ACC07||487||1||LRR protein family, Arabidopsis thaliana—NM_126131||4E−53||AJ871785|
|75ACI01||385||1||Phosphatidylinositol 4-kinase; PI4K, Arabidopsis thaliana—NM_103824||3E−67||AJ871786|
|946CCI01||268||1||rac GTPase activating protein 3, Arabidopsis thaliana—NM_180127||2E−41||AJ871787|
|424CCI05||631||1||Receptor protein kinase CLAVATA1 precursor, Arabidopsis thaliana—NM_106232||1E−36||AJ871788|
|665ACI07||604||2||Ser-Thr protein kinase-like protein, Arabidopsis thaliana—NM_106005||1E−33||AJ871789|
|916ACI10||610||1||Calcium-dependent protein kinase, isoform 2, Oryza sativa—X81394||1E−104||AJ871791|
|179CCI02||395||2||Pyruvate dehydrogenase E1 beta subunit isoform 2, Zea mays—AF069909||5E−62||AJ871792|
|191ACI02||312||2||UDP-glucose pyrophosphorylase, Solanum tuberosum—AY082620||2E−21||AJ871793|
|133ACI02||525||2||Putative acyl-CoA oxidase, Oryza sativa—XM_476282||3E−54||AJ871794|
|521ACI06||441||1||Sucrose synthase, Glycine max—AF030231||6E−86||AJ871795|
|420ACI05||359||1||Malonyl-CoA: Acyl carrier protein transacylase, Perilla frutescens—AF210698||3E−55||AJ871796|
|792ACC09||501||2||Glutamine synthetase GS1, Vitis vinifera—X94321||2E−62||AJ871797|
|325CCC04||201||1||Putative glutathione S-transferase OsGSTF3, Oryza sativa—AAN05495||4E−20||AJ871759|
|676CCI08||392||1||2-Oxoglutarate dehydrogenase E2 subunit, Arabidopsis thaliana—NM_124889||6E−41||AJ871798|
The origin of the sequences in Table 4, strawberry or C. acutatum, was primary assigned according to the level of similarity indicated by blast analyses. Therefore, a sequence with a very strong similarity to plant genes was assigned as a strawberry plant sequence. An additional genomic PCR analysis was also performed to confirm the origin, as described in Materials and methods. Thus, all of the reported genes in Table 4 putatively correspond to plant genes.
Table 4 also shows the number of strawberry clones contributing to each cluster. This is considered as indicative of the level of expression of the corresponding gene, the expression of gene copies or the presence of mRNA encoded by alleles. Clones for peroxidase were among the most abundant (14 ESTs) of the analysed strawberry genes. Peroxidases have been largely associated with defence mechanisms among other biological functions (Chittoor et al. 1999, Lamb and Dixon 1997). Other genes related to plant defence mechanisms and highly represented were those encoding a disease-resistant-related protein (251CCI03), a 14-3-3-like protein (623ACI07) and endo-1,4-β-d-glucanase (319CCI04).
Genes 144CCI02, 523ACI06 and 901CCI10 code for proteins like myb, basic-leucine zipper (βZIP) and basic-helix-loop-hetix (βHLH) transcription factors, respectively, that have been clearly related to plant defence (Chatel et al. 2003, Dröge-Laser et al. 1997, Weisshaar and Jenkins 1998) and genes 1045CCC11, 127CCI02 and 1047ACC11 encoding transcription factors like a leucine zipper-containing protein, a C2H2 zinc-finger protein and a EREBP-4 DNA binding protein, respectively, were also strongly represented. EREBP-4 DNA-binding proteins are known to bind GCC boxes present in the 5′ upstream region of ethylene-inducible pathogenesis-related genes (Ohme-Takagi and Shinshi 1995).
Other genes showed high similarity to genes encoding leucine-rich repeat (LRR) receptor-like proteins or phosphatidylinositol 3-and 4-kinase proteins also described as part of the mechanism leading to recognition of pathogen and activation of signal pathways related to plant defence and disease resistance (Belkhadir et al. 2004, Ellis et al. 2000).
Expression analysis of selected genes
We selected for further studies some of the genes that showed high similarity to genes already known to be pathogen or stress induced to test their expression pattern in strawberry tissues under Colletotrichum infection.
Those genes selected for further studies are indicated with an asterisk in Table 4. Selected genes showing increased transcript accumulation after infection were 39ACI01 (encoding a leucine-rich repeat), A68ACC01 (encoding a peroxidase), 368ACI04 (encoding a γ-thionin), 284ACI03 and 77ACI01 (encoding PR5), A47ACC02 (encoding a PR10) and J49CCI06 (encoding WRKY proteins) (see Fig. 1). Selected genes downregulated were 580ACI07 (encoding a leucine-rich repeat protein), 367ACI04 (encoding a glucan endo-1,3-beta-glucosidase), 201ACC03 (encoding leucine-rich repeat transmembrane protein kinases) and 122ACI02 (encoding a class-1 chitinase). Gene D111ACI01 (encoding a hypersensitive induced reaction HIR, protein) showing no significant changes was also selected.
Fruit gene expression in response to infection with C. acutatum
We analysed the expression pattern of these genes in fruits collected from the field that were naturally infected with C. acutatum or fruits that showed no symptoms of infection using qRT-PCR. For this set of experiments we used fruit of the Camarosa (susceptible) strawberry cultivar. The pathogen was isolated from fruit naturally infected as described in Materials and methods and identified to be the same as the one used in controlled infections.
As shown in Fig. 2, the genes analysed showed a wide range of responses after infection. The transcript level of genes J49CCI06 (Fawrky-1), 39ACI06 (Falrrp-1), 77ACI01 (Fapr5-1), 284ACI03 (Fapr5-2), D111ACIO1 (Fahir-1) and A47ACC02 (Falpr10-1) was higher in the infected fruit than in the control fruit, indicating a clear upregulation of these genes during C. acutatum infection (Fig. 2A). Interestingly, Fawrky-1 (encoding a protein with similarity to WRKY transcription factors; Eulgem et al. 2000) showed the highest induction after infection (13.4-fold).
A reduced level of transcripts after infection was found for genes 201ACC03 (Falrrk-1), 580ACI07 (Falrrk-2), 368ACI04 (Faγthio-1), A68ACC01 (Faprox-1), 367ACI04 (Faβgln-1) and 122ACI02 (Fachit-1), indicating a clear downregulation of these genes upon infection (Fig. 2B). γ-Thionins, peroxidases, β-1,3-glucanases and chitinases have been described to be involved in plant defence mechanisms against pathogens acting as key enzymes in the lysis of fungal cell walls during the infection process (Chittoor et al. 1999, da Silva-Conceição and Broekaert 1999, Leubner-Metzger and Meins 1999, Neuhaus 1999). Although some reports describe repression upon fungal infection for β-1,3-glucanase genes (Leubner-Metzger et al. 1995, Rezzonico et al. 1998, Vögeli-Lange et al. 1994), these genes have mainly been described as being induced and no reports exist describing repression of these genes upon pathogen infection in non-climacteric fruit like strawberry.
Crown gene expression in response to infection with C. acutatum
The expression of genes Fadhir-1, Faprox-1, Fathio-1, Fawrky-1, Fapr5-1, Falrrk-1, Falpr10-1, and Fachit-1 was analysed in crown tissue upon controlled C. acutatum infection in both Camarosa (susceptible) and Andana (moderately resistant) cultivars. The expression pattern was found to be different in cv. Andana and in cv. Camarosa for all the genes analysed and either a stronger and/or a quicker increase in gene expression was always found in cv. Andana than in cv. Camarosa for all of them (Fig. 3).
In Andana, Faprox-1 and Faγthio-1 were significantly upregulated after 3 days postinfection (dpi) (6.4-fold and 4.4-fold, respectively), and this increase gradually diminished from 3 to 7 dpi (Fig. 3-1, 3-3). In Camarosa, Faprox-1 gradually increased its expression during the 7 days of treatment (from 3.2- to 7.7-fold), whereas no significant upregulation was observed for Faγthio-1 (a 2.8-fold increase was only apparent after 5 days). A similar pattern of gene expression was also observed in Andana for genes Fahir-1 and Falpr10-1. These genes also showed significant upregulation (4.6-fold and 4.1-fold, respectively) at 1 dpi, although this increase gradually diminished in the course of the treatment (Fig. 3-2, 3-4). The expression of Falpr10-1 increased to similar level (4.1-fold) both in cv. Andana and cv. Camarosa, although this increase was quicker in cv. Andana (1 vs 3 dpi). No significant upregulation was observed for Fahir-1 in cv. Camarosa.
A quicker and very significant upregulation was also detected for gene Fapr5-1 (24.7-fold) at 1 dpi in cv. Andana, whereas it only increased 4.6-fold at 3 dpi in cv. Camarosa (Fig. 3-5). Although this increase slightly diminished during treatment in Andana, the expression level was always higher in this cultivar than in Camarosa.
In Andana, the expression pattern of Falrrk-1 and Fachit-1 was very similar and gene expression increased to a very significant value from 1 to 3 dpi (16.9-fold and 17.8-fold, respectively) followed by a drastic downregulation (Fig. 3-6, 3-7). Upregulation was also detected for these genes at 1 dpi (Fachit-1) and 3 dpi (Falrrk-1) in cv. Camarosa but to a much lower level (5.6-fold and 4.2-fold, respectively). In addition, a gradual but more significant downregulation was observed for these two genes in cv. Camarosa than in Andana from 5 to 7 dpi (−9.2-fold for Fachit-1 and −17.1-fold for Falrrk-1).
The most significant increase in gene expression was observed for Fawrky-1 in cv. Andana (Fig. 3-8). This gene started to be upregulated from 1 dpi (3.1-fold) to 7 dpi (87.5-fold). In cv. Camarosa, significant upregulation of this gene was detected only after 5 dpi and to lower level (18.8-fold) than in cv. Andana.
Interestingly, although differences in the expression pattern for all the genes analysed were detected in both cultivars, some of these genes also showed a very different pattern of expression depending upon the strawberry tissue analysed. In cv. Camarosa, Faprox-1 and Faγthio-1 were significantly downregulated in fruit tissue upon infection (Fig. 2B). However, these genes were upregulated in crown tissue upon infection (Fig. 3-1, 3-3, respectively). Furthermore, the relative values or fold level for most of these genes were also different. Fachit-1 showed a strong downregulation in infected fruit tissue (−59.7-fold, Fig. 2B) compared with infected crown tissue (−9.2-fold at 7 dpi, Fig. 3-7), whereas Falrrk-1 showed stronger downregulation in infected crown tissue (−17.1-fold at 7 dpi, Fig. 3-6) than in infected fruit tissue (−6.3-fold, Fig. 2B). Similarly, Fawrky-1 showed strong upregulation in infected crown tissue (18.8-fold, Fig. 3-8) than in infected fruit tissue (13.4-fold, Fig. 2A). No significant differences were detected for the other genes.
These results indicate that there seems to be a strawberry cultivar dependent expression pattern upon C. acutatum infection. However, it is too preliminary to talk about correlation with susceptibility to Colletotrichum. For such more cultivars differing in susceptibility should be tested.
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- Materials and methods
The approach described here has allowed the identification of a vast number of genes involved in the response of the strawberry plant to C. acutatum infection. A significant proportion of these genes resembled genes described as being involved directly in plant defence. Other high proportion of genes showed a similarity to genes encoding LRR receptor-like proteins, signal transduction protein kinases and transcription factors from different species described to be related with the signalling mechanism leading to plant defence against pathogen infections (Tables 3 and 4). Characterization of these genes in strawberry is of major commercial and scientific interest as strawberry cultivars showing different degrees of susceptibility to C. acutatum are known and no clear resistant phenotype in F. ananassa is yet available. Thus, this can provide useful insights to help developing biotechnological tools against this and other pathogens.
Based on genomic sequencing, it is estimated that some 14% of the 21 000 genes in Arabidopsis are directly related to defence (Bevans et al. 1998) and the products of many of these genes are involved in directly interacting with pathogen gene or protein products. According to these data and those obtained by the analysis of the strawberry subtractive libraries here described and shown in Tables 2–4, we conclude that we have generated a very representative strawberry library containing genes related with defence processes.
Differences in gene expression between strawberry tissues upon infection with C. acutatum
We have seen differences in gene expression between the strawberry tissues upon infection with C. acutatum. Increase in expression was detected both in infected fruit and crown tissues from cv. Camarosa for genes Fahir-1, Falpr10-1, Fapr5-1, and Fawrky-1. However, genes Faprox-1 and Faγthio-1 presented significant differences in the pattern of expression in these two strawberry tissues. Increased expression of both genes was detected in infected crown tissue (Fig. 3-1, 3-3) but gene repression was detected in fruit tissue for both genes (Fig. 2B). Also, genes Falrrk-1 and Fachit-1 showed significant gene repression in infected fruit tissue (Fig. 2B) and induction followed by repression in infected crown tissue (Fig. 3-6, 3-7).
Because different inoculation methods and environmental conditions (natural infection under the field condition vs artificial inoculation in a growth chamber) were used, it is difficult to draw any definitive conclusion comparing the gene expression pattern between these two tissues. However, these results might suggest that strawberry tissues can respond differently to infection by this particular pathogen. Consequently, different tissues can show variability in susceptibility to pathogen infection. In fact, strawberry fruit seems to be more susceptible to C. acutatum infection than crown tissue as pathogen can develop quicker on the former tissue under natural field conditions (Fernando Romero, personal communication).
Differences in gene expression pattern between tissues of the same plant can be considered as a result of both innate differences in plant tissue architecture and composition and the pathogen attack strategy. The pathogen primary strategy can be easily based on downregulation of those plant genes whose products are particularly dangerous (acting as a first line of defence) to the growth and development of conidia, appressorial and other pathogen structural components to establish a successful infection. In other words, pathogens must first be able to disable plant defences to enable them to grow. Because of differences in structural components, chemical and biological composition of plant tissues, this pathogen strategy can proceed quicker and be successful in some plant tissues rather than in others.
Differences in gene expression between strawberry cultivars upon infection with C. acutatum
All the tested genes showed differences in their expression pattern in the crown tissue of strawberry cv. Andana and cv. Camarosa. Upon pathogen infection, the gene expression level was always higher and/or quicker in cv. Andana than in cv. Camarosa for all the genes. This suggests that differences in the timing and intensity of gene response to pathogen infection are cultivar dependent. Interestingly, the results obtained with these two strawberry cultivars agree with the different degree of susceptibility to Colletotrichum infection exhibited by them: Camarosa, very susceptible; Andana, moderately resistant. Furthermore, these results suggest that a set of these gene expression profiles can be valuable as a biotechnological tool because they open the possibility of exploiting them as ‘molecular signatures’ to distinguish degrees of susceptibility to C. acutatum or other fungal pathogens among strawberry cultivars.
Analysis of the strawberry genes
Genes Fahir-1, Falpr10-1, Fapr5-1 and Fapr5-2 code for a hypersensitive response protein (HIR-protein), a PR10 protein and PR5 thaumatin-like proteins, respectively, and increase their expression both in fruit and crown strawberry tissues upon C. acutatum infection (Figs 2, 3). HIR-proteins, PR10 and PR5 proteins are considered part of the early mechanism of defence in plants and are known to be induced in response to microbial infection, abiotic stress and hormone treatments (Kombrink and Schmelzer 2001, Maleck and Dietrich 1999, Moiseyev et al. 1997). PR10 proteins represent an extensive family with structural homology to ribonucleases (Moiseyev et al. 1997). A few of them have been shown to possess RNase activity in vitro (Zhou et al. 2002). Thaumatin-like proteins are known to possess antifungal activity, and transgenic plants overexpressing PR5 proteins have enhanced disease resistance (Velazhahan et al. 1999). Recently, transgenic strawberry plants expressing a thaumatin II gene it has been shown to increase resistance to Botrytis cinerea (Schestibratov and Dolgov 2005). In addition, genes encoding these proteins are often useful as molecular marker for the expression of systemic acquired resistance (SAR), although the specific subset of pathogenesis-related (PR) genes that are appropriate SAR marker genes varies from species to species (Maleck and Dietrich 1999). Therefore, these strawberry genes could be valuable for biotechnological purposes and a further molecular characterization is currently in progress.
Our results show that the strawberry Fawrky-1 was remarkably induced in cv. Camarosa infected fruit tissue (13.4-fold, Fig. 2A) and crown tissue of both cultivars (18.8- and 87.5-fold, Fig. 3-8). The strawberry Fawrky-1 gene was very similar to genes encoding group II of WRKY proteins. These proteins belong to a large family of transcriptional regulators that has to date only been found in plants (Eulgem et al. 2000). Current data indicate that many WRKY proteins have a regulatory function in the plant defence response, and increased levels of WRKY mRNA are induced by infection with viruses, bacteria, oomycetes, by fungal elicitors, by signalling substances such as salicylic acid and by wounding (Chen and Chen 2002, Dong et al. 2003, Eulgem et al. 2000, Kalde et al. 2003). WRKY proteins have a binding preference for the known W box DNA sequence motif, and they have the potential to differentially regulate the expression of a wide range of target genes of the PR type including the WRKY genes themselves (Dong et al. 2003, Eulgem et al. 1999, Rushton and Somssich 1998, Yang et al. 1999). Therefore, the strawberry Fawrky-1 gene can be part of the concerted gene activation cascade occurring within the mechanisms of plant defence.
Interestingly, some of the strawberry genes identified here resemble genes whose products can be both part of the same cascade and putative target genes for the Fawrky-1 gene product. Indeed, genes encoding receptor-like kinases and the ankyrin-repeat protein NPR1 have been recently described to be putative target genes for WRKY factors (Asai et al. 2002, Du and Chen 2000, Robatzek and Somssich 2002, Yu et al. 2001), and some of the strawberry genes identified in Table 3 belong to this group.
Genes related with defence are down regulated upon C. acutatum infection
Gene Faprox-1 codes for a plant peroxidase. Plant peroxidases have been extensively associated to the oxidative burst. Among the multiple functions assigned to them, a role in the formation of toxic metabolic and structural barriers against invading pathogens (Bolwell and Wojtaszek 1997, Lamb and Dixon 1997, Wu et al. 1997) as well as in recognition phenomena (Lamb and Dixon 1997) has long been recognized but remains inconclusive and is still under investigation (Chittoor et al. 1999). This strawberry gene was one of the most represented (number of clones: 14) among the sequenced ESTs (Table 4). Interestingly, this strawberry gene showed strong gene repression in cv. Camarosa-infected fruit (Fig. 2B), although induction was detected in crown tissue both in cv. Camarosa and cv. Andana (Fig. 3-1).
Gene Faγthio-1 codes for a γ-thionin (PR12 protein). Induction of γ-thionin genes following pathogen attack has been well documented in several plant species and their antimicrobial and enzyme inhibitory activities have been widely described (da Silva-Conceição and Broekaert 1999, Garcia-Olmedo et al. 1998, Hammond-Kosack and Jones 2000). However, Faγthio-1 showed a significant repression in Camarosa infected fruit tissue (Fig. 2B) compared with infected crown tissue (Fig. 3-3). A moderate inhibition on γ-thionins gene expression has also been reported upon pathogen infection in pepper (Oh et al. 1999) and chestnut (Schafleitner and Wilhelm 2002).
Genes Falrrp-1, Falrrk-1 and Falrrk-2 code for LRR receptor-like proteins. Nucleotide binding-leucine-rich repeat (NB-LRR) proteins is to date the major class of proteins conditioning resistance to pathogens (Dangl and Jones 2001, Nimchuk et al. 2003). Their activation seems to be related to the recognition of specific avirulence factors triggering the mechanisms leading to resistance. However, direct or indirect interaction between NB-LRR proteins and avirulence factors is still obscure and remains under experimental research (Belkhadir et al. 2004). Both Falrrk-1 and Falrrk-2 showed significant repression in cv. Camarosa fruit tissue upon infection (Fig. 2B). Falrrk-1 was also strongly repressed in cv. Camarosa crown tissue 7 dpi upon infection (Fig. 3-6).
Strong inhibition has been detected in cv. Camarosa fruit tissue for genes Fachit1-1 and Faβgln-1 similar to plant genes encoding class I chitinases (PR3 proteins) and β-1,3-glucanases (PR2 proteins), respectively (Fig. 2B). The expression of Fachit1-1 was also significantly inhibited in cv. Camarosa crown tissue at 7 dpi to a lower level than the uninfected control. In contrast, plant chitinases and related β-glucanases are described to be rapidly induced by pathogen infection and treatment with elicitors (Leubner-Metzger and Meins 1999) and have been used as markers for SAR (Delaney 1997, Ryals et al. 1996). Fachit1-1 gene induction was indeed early observed in strawberry crown tissue at 1 and 3 dpi in both strawberry cultivars (Fig. 3-7) but severely repressed later. Downregulation of β-1,3-glucanase genes has only been reported for tobacco (class I) genes by treatment with abscisic acid (Leubner-Metzger et al. 1995, Rezzonico et al. 1998) and by combination of auxin and cytokinin (Vögeli-Lange et al. 1994).
In strawberry, one class III and two class II chitinase genes (Fachit2-1, and Fachit2-2 genes) have already been described but only the pattern of temporal expression of the later ones has been reported (Khan and Shih 2004, Khan et al. 1999). The temporal expression pattern of these two genes was considerably different but gene induction was detected for both genes under infection conditions. In addition, the expression of these two class II chitinases genes was higher after C. fragariae than C. acutatum inoculations clearly indicating that strawberry responds to infections by modulating the expression of these genes according to the pathogen. Differences in the expression pattern between Fachit1-1 and the other strawberry chitinases genes must be expected as different roles during pathogen infection can be accomplished for the different types of chitinases present in strawberry.
Recently, the cloning of two β-1,3-glucanase genes has been reported in strawberry (accessions AB106653 and AY170376). Although some molecular characterization analyses have been reported for one of these genes (a class II β-1,3-glucanase Fabg2-1 gene; accession AY170376) (Khan et al. 2003), no expression pattern or any published molecular data are yet available for these particular genes upon infection. Sequence comparisons showed that Faβgln-1 here described presented no significant similarity with these cloned strawberry genes at both nucleotide and amino acid levels, indicating that the three strawberry β-1,3-glucanase gene products so far identified are different.
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- Materials and methods
In the present study we have partially characterized the molecular basis of the interaction established between C. acutatum and strawberry plant (F. ananassa). Our results yielded a first insight on some of the genes responding to this plant–pathogen interaction at molecular level. The results described in this report indicate that important genes putatively involved in the mechanism of defence can be repressed in strawberry as a consequence of the C. acutatum infection.
Other interesting results have emerged from these studies. First, different patterns of gene expression have been detected for the studied strawberry genes upon infection of the susceptible (cv. Camarosa) and moderately resistant (cv. Andana) cultivars. In fact, the studied gene response to infection by this pathogen was always quicker and/or stronger in cv. Andana than in cv. Camarosa. This suggests that differences in the timing and intensity of gene response to pathogen infection are cultivar dependent. Secondly, the plant response might be tissue dependent as some of the tested genes responding to pathogen infection exhibited significant downregulation in fruit tissue but strong upregulation in crown tissue.
There is considerable interest in obtaining more productive crop plants that also exhibit increased resistance to fungal pathogens. A comprehensive analysis of genes described in this issue might lead to a quicker and better understanding of the mechanisms involved in strawberry plant defence and contribute to the design of molecular strategies to improve disease resistance of strawberry plants.
Edited by C. Guy
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Acknowledgements – This work was supported by grants PROFIT 010000-2001-100, 2002-81, 2003-32 and 2004-2 from Ministerio de Ciencia y Tecnología, MCYT, and Junta de Andalucía (Grupo CVI 278), Spain. The utilization of equipment of the Instituto Andaluz de Biotecnología, Andalucía, Spain, is also gratefully acknowledged. E. S. expresses his gratitude to Ministerio de Educación y Ciencia, MEC, (Spain) and to the University of Córdoba for a postdoctoral fellowship. F. A. R. thanks MEC for a predoctoral fellowship. We are grateful to Miguel A. Botella (University of Málaga, Spain) for his helpful comments on this paper.
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