4 Combining SSH and cDNA microarrays for rapid identification of ...

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Advances in Agricultural and Food Biotechnology, 2006: 55-69 ISBN: 81-7736-269-0 Editors: Ramón Gerardo Guevara-González and Irineo Torres-Pacheco

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Combining SSH and cDNA microarrays for rapid identification of ESTs associated with garlic white rot Lorenzo Guevara-Olvera1, María Isabel Hernández-Alvarez1 Humberto Ramírez-Medina1, José Jesús Magaña-Vázquez1,2 Felipe Delgadillo-Sánchez2 and Ramón Gerardo Guevara-González1 1 Departamento de Ingeniería Bioquímica, Instituto Tecnológico de Celaya Celaya, Guanajuato, México; 2Unidad de Biotecnología del Bajío, Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias Campo Experimental Bajío, Celaya, Guanajuato, México

Abstract Comparing patterns of expressed sequence tag (EST) in plant-pathogen interaction has important application in a variety of biological systems. There exist a variety of approaches that could be used to identify groups of genes that change in expression in response to a particular stimulus or environment. We here describe the application of suppression subtractive Correspondence/Reprint request: Dr. Lorenzo Guevara-Olvera, Departamento de Ingeniería Bioquímica Instituto Tecnológico de Celaya, Celaya, Guanajuato, México. E-mail: [email protected]

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hybridization (SSH) coupled with cDNA microarray analysis for isolation and identification of Sclerotium cepivorum Berk transcripts that change in expression on infection of garlic (Allium sativum L) and the genes that are differentially expressed by A. sativum cv blanco perla, which has shown resistance to white rot caused by S. cepivorum. SSH was used for isolation of differentially expressed transcripts, a validation was accomplished by microarrays analysis. Replicates of SSH library were hybridized individually by Southern with either driver or tester cDNA probes to confirm differential gene expression. The detailed methods described herein could be useful and adaptable to any biological system for studying change in gene expression

Introduction White rot caused by Sclerotium cepivorum Berk, is the predominant disease of garlic (A. sativum) crops worldwide. Once introduced into the field, the sclerotia can survive up to 20 years without the presence of an A. sativum host. The sclerotia are specifically induced to germinate by Allium root exudates, in particular alkyl cysteine sulfoxides (1). Several strategies for white rot control are now being used as part of an integrated control programme, including cultural practices such as soil solarisation and biological control (2). Unfortunately, fungicide application is still required for effective management with these systems, thus, it will be necessary to identify genes involved in S. cepivorum pathogenesis as molecular targets. On the other hand, successful, stable, widespread resistance to white rot in elite cultivar is in underway through conventional breeding and biotechnological methods. In concordance, A. sativum cv “blanco perla” has shown resistance to white rot caused by S. cepivorum (3), emerging as a good model to search for natural resistance. Studies of gene expression profiles during fungal-garlic interaction can provide clues about pathogenesis regulation resistance and may lead to the discovery of molecular targets for novel antifungal drugs, simultaneously the identification of genes involved in natural resistance could provide new information to design strategies to control of white rot disease.

Background Identification of differentially expressed genes The global investigation of changes in gene expression in a biological system can be carried out with a variety of available tools that promise the identification of differentially expressed transcripts between two populations of mRNA. These include differential display (DD) (4), representational difference analysis (RDA) (5), and serial analysis of gene expression (SAGE) (6). Despite that fact that these methods have proven successful in isolation of differentially expressed genes, they all possess some intrinsic drawbacks. In

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addition to their specific limitations, a common feature is the inability to isolate rare transcripts, i.e., the disproportion of concentrations of differentially expressed genes is maintained in the subtraction.

Suppression subtractive hybridization A novel technique named suppression subtractive hybridization (SSH) generates an equalized representation of differentially expressed genes without consideration of their relative abundance (7). SSH enables the construction of subtracted cDNA libraries and is based on hybridization and suppression PCR including normalization and subtraction in a single procedure (7). It provides a 100-1000 fold enrichment of differentially expressed mRNAs and has been successfully used to compare differences in gene expression between two transcriptomes (8-12). Study of global gene expression has been further revolutionized by the advent of microarray technology (13-19). Hundreds to thousands of cDNAs are microspotted on nylon membranes in an ordered array, hybridized with tester and driver fluorescently labeled probes and all cDNAs examined simultaneously for changes in expression level. SSH and microarray have been successfully used together for studying gene expression profiles in several systems (20, 21). There are several advantages of using SSH in combination with microarray analysis that make them appealing for identifying differentially expressed sequences. SSH is a comprehensive, largescale gene expression based approach that allows unbiased discovery of de genes upregulated (forward) or downregulated (reverse) by a specific treatment (7). In addition, since SSH allows the isolation of differentially expressed cDNAs without a prior knowledge of their sequence, it is highly desirable for studying differential gene expression in systems where the information on the genomic sequence is absent. Once isolated by SSH, the validity of SSH sequences can be confirmed by utilizing the method of microarray hybridization. The main advantage of using microarray analysis is that the expression status of hundreds or thousands of SSH clones can be validated simultaneously when spotted by duplicate on arrays and hybridized individually either control (driver) or test (tester) samples, thus generating significant amount of information that is difficult to obtain using any other currently available method.

Fungal-garlic clove interaction To characterize the pathogenicity and resistance transcriptomes of S. cepivorum and A. sativum cv perla, respectively, more thoroughly, we sought to identify genes whose expression levels change in response to garlic white rot caused by the fungus and during resistance showed by garlic “blanco perla”, respectively. Thus, 1 cm2 of S. cepivorum young mycelium grown in potato dextrose agar (PDA) was used to inoculate either a garlic clove Texcoco susceptible or blanco perla resistant during 72 h in a 50 mL glass flask

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containing 20 mL of doubled distilled water. As controls, the fungus was inoculated in absence of the susceptible garlic, whereas the garlic blanco perla was inoculated in absence of the pathogenic fungus.

RNA isolation and cDNA synthesis for SSH To detect genes involved in S. cepivorum pathogenesis and in garlic resistance, respectively, fungal mycelium and garlic clove blanco perla were harvested 72 h past inoculation and before any adhesion to the garlic surface for RNA isolation using RNeasy kit (Qiagen, Hilden, Germany). By formaldehyde agarose gel electrophoresis, the integrity and size were analyzed and clear bands of ribosomal RNA (RNAr) 18s and 28s were seen. The first strand of cDNA was obtained using the Superscript II Reverse Transcriptase (Life Technologies, Rockville, MD, USA) and double-stranded cDNA for SSH was synthesized by SMARTTM PCR cDNA synthesis kit (Switch Mechanism At the 5´ end of RNA Transcript)(Clontech, Palo Alto, CA, USA) method. For cDNA subtraction, it is necessary to optimize the number of PCR cycles to ensure that cDNA will remain in exponential phase of amplification. Overcycled cDNA is a very poor template, on the other hand, undercycling results in a lower yield of PCR product (7). The products obtained with 15, 18, 21, and 24 cycles were separated on 1.2 % agarose gel electrophoresis. For both tester (Fig. 1) and driver (not shown), the optimal cycles number were 18, while for placental RNA, the 21 cycle sample was selected (Fig. 1).

Figure 1. Analysis for optimizing PCR cycles. RNA samples. Optimal PCR cycles. Lane M, 1 kbp DNA marker; lanes 1, 2, 3, and 4, cDNA amplified 15, 18, 21, and 24 cycles respectively, from RNA tester; lanes 5, 6, and 7, cDNA amplified 15, 18, and 21 cycles respectively, from human placental mRNA (22).

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PCR-Selected cDNA subtraction Suppression subtractive hybridization was conducted using the CLONTECH PCR-SelectTM cDNA subtraction kit (Clontech, Palo Alto, CA, USA). The tester and driver cDNAs synthesized from each fungal-garlic clove interaction, were digested with Rsa I, a four base-cutting restriction enzyme that yields blunt ends. cDNA before digestion with Rsa I, appeared as a smear of 0.5-10 kbp on 1 % agarose gel electrophoresis, and after digestion the cDNA size was smaller (0.1-2 kbp)(not shown). After SSH a primary PCR was conducted to amplify those cDNAs that represented differentially expressed genes. A secondary PCR amplification was performed using nested primers 1 and 2R to reduce background, several bands could be seen clearly among these smears. PCR products (Fig. 2, Lane 1) were isolated and cloned into pCR2.1TOPO TA vector. White colonies were selected for plasmid DNA isolation and analysed for inserts presence using Eco RI restriction enzyme. Recombinant plasmids containing fragments with estimated size around 500 bp were selected for microarray hybridization.

Figure 2. Secondary PCR for subtracted samples. PCR using nested 1 and 2R primers. Lane M, 1 kbp DNA marker; lane 1, SSH from tester and driver; lane 2, SSH from tester and driver human placental mRNA (22).

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Differential expression of genes identified by SSH Differential expression was assayed by Southern blot analysis (23). Each recombinant plasmid (5 µg) was spotted by duplicate into 7X10 cm BrightStarTM-Plus positively charged nylon membrane (Ambion Inc, Austin, TX, USA) to construct a 6X4 clones array using Slot manifold (Amersham Biosciences, Buckinhamshire, UK HP7 9NA). As negative control 5 µg of pCR2.1TOPO TA vector was spotted and 5 µg of a plasmid containing housekeeping gene fragment of GpdhSc of S. cepivorum was used. As positive control 0.5 µg of each unlabeled cDNA was spotted. The microarrays were individually hybridized with tester and driver (Fig. 3) probes generated by incorporating fluorescein-11-dUTP using Gene Images CDP-Star random prime labeling module according to the manufacturer´s instructions (Amersham Pharmacia Biotech Inc, Piscataway, NJ, USA). Detection of fluoresceinlabelled probes in Southern dot blots was performed employing anti-fluorescein alkaline phosphatase conjugate and CDP-Star detection reagent (Amersham Pharmacia Biotech Inc, Piscataway, NJ, USA). The clones that hybridized exclusively with tester probe, confirmed the differential gene expression during pathogenesis of S. cepivorum and they were selected for DNA sequencing.

Figure 3. Differential screening of clones from subtracted library generated using SSH by Southern blot analysis using tester cDNA as probe. Each number indicates HR (Humberto Ramírez-Medina) clones: C-, pCR2.1TOPO TA vector; GdphSc, 5 µg of S. cepivorum Gdph gene fragment; C+, 0.5 µg of each unlabeled cDNA (22).

Sequence and homology analyses of SSH clones The nucleotide sequences of differentially expressed fragments were determined using the ABI PRISM 310 Genetic Analyzer (Perkin Elmer, Norwalk, CT, USA). On-line database comparisons were performed using Blastx algorithm from National Center for Biotechnology Information (NCBI).

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Genes upregulated during fungus-garlic clove Texcoco (susceptible) interaction Fourteen among the forty six clones differentially expressed were sequenced and analyzed for DNA homology and they were found more than once when compared to the GenBank non-redundant TRANSLATED queryPROTEIN database (blastx). The identity of these fourteen sequences are listed in Table 1 and were arbitrarily classified into five groups of proteins: I, Cell wall; II, Cell membrane; III, Host response avoidance; IV, Pathogenicity factors and V, Others. Two from fourteen gene fragments expressed during S. cepivorum pathogenesis on garlic encodes for cell wall proteins and they could be involved in host recognition: Fig2p (24) and Bap (25,26). Four sequences Table 1. Functional classification of gene products induced during Sclerotium cepivorum pathogenesis toward garlic (Allium sativum) (22). Clone (Accession Number) I.- Cell wall HR48-11 (DR774659) HR47-16 (DQ054537) II.- Cell membrane HR23-4 (DR774654) HR12-6 (DR774656) HR65-10 (DR774658) HR5-3 (DR774661) III.- Host response avoidance HR51-2 (DR774652) HR9-15 (DR774663) IV.- Pathogenicity factors HR62-1 (DR774651) HR14-12 (DR774660) HR66-14 (DR774662) V.- Others HR50-5 (DR774655) HR15-8 (DR774657) HR60-9 (DQ054537)

* % of I, Identities; P, Positives

Gene with highest homology Fig2P, Cell wall adhesin (Saccharomyces cerevisiae) Bap, Biofilm-associated surface protein (Staphylococcus aureus)

I/P *

Reference

35/50

(24)

26/43

(25,26)

Rds1p, Regulator of drug sensitivity (Saccharomyces cerevisiae) Omp1, Outer menbrane protein (Rickettsia prowazekii str. Madrid E) Mp, Potential transmembrane protein (Candida albicans SC5314) Pcm4, Calcium/calmodulin-binding membrane protein (Paramecium tetraurelia)

45/60

(27)

42/51

(28)

35/51

(29)

28/50

(30)

Nsf 1p, Cysteine desulfurase (Magnaporthe grisea) Glnd, PII Uridylyl transferase protein (Escherichia coli)

86/94

(31)

27/44

(32,33)

Oah, Oxaloacetate acetylhydrolase (Botryotinia fuckeliana) Adhy, Acyl dehydratase (Ralstonia metallidurans CH34) Geh-1, Lipase (Staphylococcus epidermidis RP62A)

90/97

(34)

30/56

(35)

28/45

(36,37)

Ycr106w, Probable membrane protein (Saccharomyces cerevisiae) Unknown protein (Oryza sativa cv japonica) Prp B, Carboxyphosphonoenolpyruvate phosphonomutase (Pyrobaculum aerophilum)

45/60

(38)

38/44 35/54

(39) (40)

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Lorenzo Guevara-Olvera et al.

encode for membrane proteins, three of them could be involved in host recognition: Rds1p (27), Omp1 (28) and Mp (29), and one involved in signal transduction Pcm4 (30). Two sequences are related to putative proteins involved in host response avoidance: Nsf1p (31) and Glnd (32,33). Three sequences exhibited homology to putative pathogenicity factors: (Oah (34), Adhy (35) and Geh-1 (36;37). Others gene fragments had homology to: transcriptional factor Ycr106w (38), unknown protein (39) and general metabolism PrpB (40). Furthermore, the clone HR62-1 (Table 1), whose nucleotides 99-584 reversely matches to the nucleotide sequence 960-475 of a putative pathogenicity factor (Oxalic acid)-associated protein (Oxaloacetate acetylhydrolase) of Botryotinia fuckeliana Whetz (the teleomorph of Botrytis cinerea), a haploid, filamentous, heterothallic ascomycete.

Genes downregulated during fungus-garlic clove Texcoco (susceptible) interaction Ten among the seventy six clones differentially expressed (not shown) sequenced and analyzed for DNA homology and they were found more than once when compared to the GenBank non-redundant TRANSLATED queryPROTEIN database (blastx). The identity of these ten sequences are listed in Table 2 and were arbitrarily classified into two groups of proteins: I, Apical Table 2. Functional classification of gene products repressed during Sclerotium cepivorum pathogenesis toward garlic (Allium sativum) (41). Clone (Accession Number) Gene with highest homology I.- Apical growth Sc 92 (DW520894) Neb, Nebulin (Homo sapiens) Sc 50 (DW520904) Murf2, Muscle specific RING finger 2 (Homo sapiens) Sc 88 (DW520896) Cbk1p, Protein kinase (Saccharomyces cerevisiae) Sc 71 (DW520899) Glo1, glyoxal oxidase (Sclerotinia sclerotiorum) II.- Others Sc 10 (DW520895) lysis protein (Coliphage øX174) Mod E, molecular chaperone HSP90 Sc 72 (DW520897) (Podospora anserina) Sc 11A (DW520898) IS10-right transposase (Shigella flexneri) Sc 115 (DW520900) Sc 18 (DW520901)

Sc 46 (DW520903) * % of I, Identities; P, Positives.

hypothetical protein (Plasmodium falciparum 3D7) Nramp 1, natural resistance associated macrophage protein-alpha (Oncorhynchus mykiss) protein-O-fucosyltransferase (Sus scrofa)

I/P *

Reference

100/100

(42)

94/100

(43)

87/92

(44)

53/61

(45)

100/100

(46) (47,48)

86/95 76/76

(49)

46/68

(50)

42/57

(51,52)

34/59

(53)

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growth, II, Others. Four from ten gene fragments repressed during S. cepivorum pathogenesis on garlic encode for apical filamentous growth proteins and they could be involved in a morphological change observed in the fungus when it is growing in garlic absence in order to avoid host resistance: Neb (42), Murf 2 (43), Cbk1p (44) and Glo1(45). Other sequences had homology to proteins with different function such as: lysis (46), Mod E molecular chaperone (47,48), transposase (49); Hypothetical protein could represent a novel gene involved in fungal pathogenesis (50). Nramp 1 (51, 52) could be associated to a transport system with high affinity and fucosyltransferase related to cellular differentiation and apoptosis (53).

Genes upregulated during garlic clove blanco perla (resistant)fungus interaction Ten among the one hundred and fifty four clones differentially expressed (not shown) were sequenced and analyzed for DNA homology and they were found more than once when compared to the GenBank nonredundant TRANSLATED query-PROTEIN database (blastx). The identity of these ten sequences are listed in Table 3 and were arbitrarily classified into four groups of proteins: I, Transcriptional regulators; II, Cell membrane III; Resistance; IV, Mitochondria. Three from ten gene fragments expressed during garlic blanco perla resistance toward S. cepivorum pathogenesis exhibited high homology to transcriptional factors and they could be regulating other genes involved in resistance: NAM and NAC proteins could be involved in embryos and flowers development in plants (55,56) and PPR-repeat protein which is involved in RNA stabilization (57). Three clones encode membrane proteins and they could be involved in pathogen avoidance: Hyperpolarization-activate (Ih) channel, widely distributed in biologically active cells, Ih could be play an important role in regulating cell excitability, rhythmic activity and synaptic function (58); Putative Sodium Channel, these ion channels are involved in excitation, contraction, secretion and synaptic transmission (59) and cardiolipin synthetase could be involved in conduct to apoptosis in order to restrict fungal invasion (60). Three sequences exhibited homology to proteins involved in resistance: β-Galactosidase, which could be involved in cell wall hydrolysis in order to avoid fungal penetration (61); Polyprotein (62), and Transposases, which contains Zinc finger domain and could regulate the expression of genes involved in fungal pathogenesis avoidance (63). One gene fragment had homology to a mitochondrial protein: NADH dehydrogenase which could be involved in cell detoxification (57).

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Table 3. Functional classification of gene products induced during garlic clove blanco perla (resistant)-fungus interaction (54). Clone (Accession Number) I.- Transcriptional regulators AspbB-1 (DW985624) Aspb83-2 (EB739781) AspbI-1 (DW985628) II.- Cell membrane Aspb1-1 (DW985627) Aspb102-1 (DW985629) Aspb74-2 (EB739780)

III .- Resistance Aspb111-1 (DW985625) Aspb10-2 (EB739774) Aspb22-2 (EB739777) IV.- Mitochondria Aspb10-1 (DW985626)

Gene with highest homology

I/P *

Reference

Putative no apical meristem (NAM) protein (Oryza sativa) Putative NAC transcription factor (Oryza sativa cv japonica) PPR-repeat protein-like (Oryza sativa)

76/80

(55)

65/69

(56)

31/50

(57)

33/49

(58)

26/48

(59)

35/52

(60)

44/68 30/46 25/55

(61) (62) (63)

Hyperpolarization-activated (Ih) channel (Strongylocentrotus purpuratus) Putative sodium channel (Schizosaccharomyces pombe) Cardiolipin synthetase (Desulfovibrio vulgaris subsp. vulgaris str. Hildenborough) β-galactosidase (Thermotoga maritima) polyprotein (Porcine enterovirus 8) is231-related, transposase, (pxo1-36) (Bacillus anthracis) NADH dehydrogenase (Ceratitis capitata)

(64)

* % of I, Identities; P, Positives.

Genes downregulated during garlic clove blanco perla (resistant)-fungus interaction Eight among the eighty six clones differentially expressed (not shown) were sequenced and analyzed for DNA homology and they were found more than once when compared to the GenBank non-redundant TRANSLATED query-PROTEIN database (blastx). The identity of these eight sequences are listed in Table 4 and were arbitrarily classified into two groups of proteins: I, Cell membrane and II, Others. Three from eight gene fragment repressed membrane proteins: ABC (ATP binding cassette) constitute one of the more abundant protein families in prokaryotes and eukaryotes (65) involved in membranal transport; Penicillin-binding protein these proteins are involved in elongation and cellular division (66); Sodium bicarbonate cotransporter (NBC) could be related in regulating intracellular pH (67). Others protein include: NATCH domain which could be involved in modulating the immune response to pathogen avoidance (68); Hialuronan synthase which is related to cell adhesion (69); Histone deacetylase is required to maintain the gene silencing and determines the nuclear organization of the ADNr (70); Similar to alpha isoform regulatory subunit A, protein phosphatase 2 which is a protein kinase that could play an important role in protein phosphorylation (71); Catalase regulates synthesis of reactive species of I oxygenate (ROS) and apoptosis.

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Table 4. Functional classification of gene products repressed during garlic clove blanco perla (resistant)-fungus interaction (54).

Clone (Accession Number) I.- Cell membrane Aspb18-3 (EB739750)

Aspb23-3 (EB739751)

Aspb29-3(EB739753) II.- Others Aspb40-3 (EB739758) Aspb4-3 (EB739759) Aspb43-3 (EB739760) Aspb48-3 (EB739763)

Gene with highest homology

I/P *

Reference

Putative iron inhibited ABC transporter 2 (Oryza sativa japónica, cultivar-group) Penicillin-binding protein 2 (Clostridium acetobutylicum ATCC 824) Sodium bicarbonate cotransporter (Tribolodon hakonensis)

55/78

(65)

30/47

(66)

47/66

(67)

36/58

(68)

29/59

(69)

31/48

(70)

41/46

(71)

80/82

(72)

NACHT domain protein, putative (Aspergillus fumigatus Af293) Hyaluronan synthase related sequence protein (Xenopus laevis) Histone deacetylase family protein (HDA18) (Arabidopsis thaliana) Similar to alpha isoform of regulatory subunit A, protein phosphatase 2 (Mus musculus) Catalase (Campylobacter jejuni)

Aspb68-3 (EB739768) * % of I, Identities; P, Positives.

Differential expression of OahSc transcript during pathogenesis of Sclerotium cepivorum Berk To confirm differential expression of HM62-1 clone (OahSc, Table 1) a putative pathogenicity factor, RT-PCR analysis were performed. Thus, total RNA isolation from S. cepivorum mycelium in absence (driver) and presence (tester) of garlic followed of reverse transcription were conducted as described above. PCR amplification of the OahSc cDNA (177 bp) was performed using specific sense and antisense primers whose sequence were as follows: 5´-CTCTTGAATAGCCAACATAGCCG-3´ and 5´AAAGGAGATGGCTGCGAAGACT-3´, respectively. As internal control, housekeeping GdphSc gene of 350 bp was amplified (22) was obtained using specific sense and antisense primers whose sequence were as follows: 5´-GGTGTCAACAACGAGACCTACA-3´ and 5´GCGGACAGTCAAGTCAACAAC-3´, respectively. 100 ng each driver and tester cDNA was used as template. PCR products were separated by agarose gel electrophoresis (1.2 %) and the optical density of the EtBr-stained bands was recorded using a Vilber Lourmat gel documentation system (Marne-LaValée Cedex, France) equipped with an ultraviolet light transiluminator. The

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Lorenzo Guevara-Olvera et al.

results of RT-PCR analysis of OahSc expression during pathogenesis of Sclerotium cepivorum Berk are shown in Fig. 4. The amount of OahSc transcript amplified from cDNA tester was highly enriched (Fig. 4, lane 2), relative to the detected amount of OahSc synthesized from cDNA driver (Fig. 4, lane 1). Although nonquantitative, this technique did provide evidence for differential expression of OahSc transcript during pathogenic stage of S. cepivorum Berk. From the results of the present work, we also speculate that the protein OAH encoded by OahSc gene may have an important role in white rot caused by S. cepivorum Berk toward garlic. M

1

2

250 pb

OahSc 500 pb

GdphSc 250 pb

Figure 4. RT-PCR analysis of OahSc expression. RT-PCR detection of OahSc (177 bp) transcript by amplification with specific primers. Lane M, 1 kbp DNA marker; lane 1, cDNA driver as template; lane 2, cDNA tester as template. As internal control, PCR amplification of the GdphSc cDNA (22).

Conclusion Our results demonstrate a novel application of SSH and cDNA microarrays for identifying differentially expressed genes (upregulated and downregulated) during garlic-fungal interaction which could be involved in pathogenesis or resistance and the strategy described herein could be useful and adaptable to any biological system for studying change in gene expression.

References 1. 2. 3.

4. 5. 6. 7.

Coley-Smith, J.R., Mitchell, C.M., and Sansford, C.E. 1990, Plant. Path., 39, 58. Delgadillo, S.F. 1998. Tesis Doctoral, Colegio de postgraduados, Montecillo, México. Delgadillo, S.F., Arévalo, A., and Torres, P.I. 2000. En desplegable para productores No. 3, Guanajuato, México. Instituto Nacional de Investigaciones Forestales Agrícolas y Pecuarias. Liang, P., and Pardee, A.B. 1992, Science, 257, 967. Lisitsyn, N., Lisitsyn, N., and Wigler, M. 1993, Science, 259, 946. Velculescu, V.E., Zhang, L., Vogelstein, B., and Kinzler, K.W. 1995, Science, 270, 484. Diatchenko, L., Lau, Y.F., Campbell, A.P., Chenchik, A., Moqadam, F., Huang, B., Lukyanov, S., Lukyanov, K., Gurskaya, N., Sverdlov, E.D., and Siebert, P.D. 1996, Proc. Natl. Acad. Sci., 93, 6025.

Agricultural biotechnology

8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22.

23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35.

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Shackel, N.A., McGuinness, P.H., Abbott, C.A., Gorrell, M.D., and McCaughan, G.W. 2003, Hepatology, 38, 577. Kiss, C., Nishikawa, J., Dieckmann, A., Takada, K., Klein, G., and Szekely, L. 2003, J. Virol. Methods, 107, 195. Patzwahl, R., Meier, V., Ramadori, G., and Mihm, S. 2001, J, Virol., 75, 1332. Kuang, W.W., Thompson, D.A., Hoch, R.V., and Weigel, R.J. 1998, Nucleic. Acids Res., 26, 1116. Carmeci, C., Thompson, D.A., Kuang, W.W., Lightdale, N., Furthmayr, H., and Weigel, R.J. 1998, Surgery, 124, 211. Nam, J.H., Hwang, K.A., Yu, C.H., Kang, T.H., Shing, J.Y., Choi, W.Y., Kim, I.B., Joo, Y.R., and Park, K.Y. 2003, Virus Genes, 26, 31. Su, Z.Z., Chen, Y., Kang, D.C., Chao, W., Simm, M., Volsky, D.J., and Fisher, P.B. 2003, Gene, 306, 67. Nam, J.H., Yu, C.H., Hwang, K.A., Kim, S., Ahn, S.H., Shin, J.Y., Choi, W.Y., Joo, Y.R., and Park, K.Y. 2002, Ada. Virol., 46, 141. Aizaki, H., Harada, T., Otsuka, M., Seki, N., Matsuda, M., Li, Y.W., Kawakami, H., Matsuura, Y., Miyamura, T., and Suzuki, T. 2002, Hepatology, 36, 1431. Jones, J.O., Arvin, A.M. 2003, J. Virol., 77, 1268. Carter, K.L., Cahir-MacFarland, E., and Kieff, E. 2002, J. Virol., 76, 10427. Zhu, H., Zhao, H., Collins, C.D., Eckenrode, S.E, Run, Q., McIndoe, R.A., Crawford, J.M., Nelson, D.R., She, JX, and Liu, C. 2003, Hepatology, 37, 1180. Yang, Y.P., Ross, D.T., Kuang, W.W., Brown, P.O., and Weigel, R.J. 1999, Nucleic Acids Res., 27, 1517. Villaret, D.B., Wang, T., Dillon, D., Xu, J., Sivam, D., Cheever, M.A., and Reed, S.G. 2000, Laryngoscope, 110, 374. Ramírez-Medina, H., Hernández-Alvarez, M.I., Muñoz-Sánchez, C. I., GuevaraGonzález, R. G., Delgadillo-Sánchez, F., Torres-Pacheco, I., González-Chavira, M. M., and Guevara-Olvera, L. 2006, Can. J. Plant. Pathol., Submmited. Sambrook, J., Fritch, E.E., and Maniatis, T. 1989, Cold Spring Harbor Laboratory Press, Cold Spring Harbor New York, USA. Zhang, M., Bennett, D., and Erdman, S.E. 2002, Eukaryotic Cell, 1, 811. Arrizubieta, M.J., Toledo-Arana, A., Amorena, B., Penades, J.R., and Lasa, I. 2004, J. Bacteriol., 186, 7490. Cucarella, C., Solano, C., Valle, J., Amorena, B., Lasa, I., and Penades, J.R. 2001, J. Bacteriol., 183, 2888. Wolfe, D., Reiner, T., Keeley, J.L., Pizzini, M., and Keil, R.L. 1999, Mol. Cell Biol., 19, 8254. Emelyanov, V.V., and Demyanova, N.G. 1999, Biochem (Moscow), 64, 494. Monteagudo, C., Viudes, A., Lazzell, A., Martinez, J.P., and Lopez-Ribot, J.L. 2004, J. Clin. Pathol., 57, 598. Lu, G., Jantasuriyarat, C., Zhou, B., and Wang, G.L. 2004, Theor. Appl. Genet., 108, 525. Chan, C.W., Saimi, Y., and Kung, C. 1999, Gene, 231, 21. Garcia, E., and Rhee, S.G. 1983, J. Biol. Chem., 258, 2246. Jiang, P., Peliska, J.A., and Ninfa, A.J. 1998, Biochem., 37, 12782. Joosten, H.J. and Schaap, P.J. 2004. Unpublished (Accession number, AY590264). Larimer, F.W. 1997, http://genome.ornl.gov/microbial/rpal/embl/rpalI_cogs.html.

68

Lorenzo Guevara-Olvera et al.

36. Sayari, A., Agrebi, N., Jaoua, S., and Gargouri, Y. 2001, Biochimie., 83, 863. 37. Simons, J.W., van Kampen, M.D., Riel, S., Gotz, F., Egmond, M.R., and Verheij, H.M. 1998, Eur. J. Biochem., 253, 675. 38. Harrison, P., Kumar, A., Lan, N., Echols, N., Snyder, M., and Gerstein, M.B. 2001, J. Mol. Biology, In press. 39. Sakata, K. 2002. http://alnilam.mi.mss.co.jp/rgadb/chro10/OSJNAa0019 40. Horswill, A.R., and Escalante-Semerena, J.C. 1997. J. Bacteriol., 179, 928. 41. Hernández-Alvarez, M. I. 2006. Tesis de Maestría, Instituto Potosino de Investigación Científica y Tecnológica (IPICYT), San Luis Potosí, San Luis Potosí. México. 42. Labeit, S. and Kolmerer, B. 1995, J Mol Biol, 248, 308. 43. Centner, T. Yano, J. Kimura, E. McElhinny, A.S. Pelin, K. Witt, C.C. Bang ML, Trombitas K, Granzier H, Gregorio CC, Sorimachi H and Labeit S. 2001, J Mol Biol., 306, 717. 44. Weiss, E.L., Kurischko, C., Zhang, C., Shokat, K., Drubin, D.G., and Luca, F.C. 2002, J Cell Biol., 158, 885. 45. Leuthner, B., Aichinger, C., Oehmen, E., Koopmann, E., Muller, O., Muller, P., Kahmann, R., Bolker, M., and Schreier, P.H. 2005, Mol. Genet. Genomics, 272, 639. 46. Henrich, B. and Schmidtberger, B. 1995. Gene, 154, 51. 47. Scholz, G. M., Hartson, S.D., Cartledge K., Volk, L., Matts, R.L., and Dunn, A.R. 2001, Cell Growth & Differentiation, 12, 409. 48. Loubradou, G., Begueret, J., and Turcq, B. 1997. Genetics, 147, 581. 49. Chalmers, R., Sewitz, S., Lipkow, K., and Crellin, P. 2000, J. Bacteriol., 182, 2970. 50. Seeger, K., Murphy, L., Harris, D., Berriman, M., Pain, A., Hall, N., Quail, M. and Barrell, B. 2002, Unpublished. 51. Dorschner, M.O. and Phillips, R.B. 1999, DNA Cell Biol., 18, 573. 52. Boechat, N. Lagier-Roger B, Petit S, Bordat Y, Rauzier J, Hance AJ, Gicquel B, and Reyrat JM. 2002, Infect Immun., 70, 4124. 53. Martinez-Dunker, I.; Mollicone, R.; Candelier, J.J.; Breton, C. and Oriol, R. 2003, Glycobiology, 13, 1. 54. Robson, G. 1999, Hyphal cell biology, Cambridge University Press, England, 164. 55. Magaña-Vázquez, J.J. 2006, Tesis para obtener el grado de Maestría en Ciencias en Ingeniería Bioquímica, Instituto Tecnológico de Celaya, Guanajuato, México. 56. Zhang, Y., Oliva, R., Gisselmann, G., Hatt, H., Guckenheimer, J., y HarrisWarrick, R.M. 2003, J. Neurosci., 23, 9059. 57. Taylor, W.A., Xu, F.Y., Ma, B.J., Mutter, T.C., Dolinsky, V.W., y Hatch, G.M. 2002, Biochemistry, 3, 1. 58. Corpas, F.J, Barroso, J.B., Sandalio, L.M., Distefano, Palma, J.M., Lupiañez, J.A., and del Rio, L.A. 1998, Biochem. J., 330, 777. 59. Small, I.D. y Peeters, I. 2000, Trends Biochem. Sci., 25, 45. 60. Mack, A.M. y Crawford, N.M. 2001, Plant Cell, 13, 2319. 61. Ren, T., Qu, F., and Morris, T.J. 2000, Plant Cell, 12, 1917. 62. Ren, D., Navarro, B., Xu, H., Yue, L., Shi, Q., y Clapham, D.E. 2001, Science, 294, 2372. 63. Dougherty, W.G., Cary, S.M. y Parks, T.D. 1989, Virology, 171, 356.

Agricultural biotechnology

69

64. O’Donnell, P.J., Schmelz, E.A., Moussatche, P., Lund, S.T., Jones, J.B., and Klee, H.J. 2003, Plant J., 33, 245 65. Rossignoli, E., Malacarne, G., Mica, E., Zago, E., Polesani, M., y Polverari, A. 2005, Genetics Annual Congress Potenza, Italy. 66. Higgins, C.F. 1992, Ann. Review of Cell Biology, 8, 67. 67. Spratt, B.G. 1975, PNAS., 72, 2999. 68. Lipovich, L., Lynch, E.D., Lee, M.K. y King, M.C. 2001, Genome Biology, 2, 4. 69. Damiano, J.S., Oliveira, V., Welsh, K. y Reed, J.C. 2004, Biochem. J., 381, 213. 70. DeAngelis, P. L., Jing, W., Graves, M. V., Burbank, D. E., and Van Etten, J. L. 1997, Science 278, 1800. 71. Probst, A.V., Fagard, M., Proux, F., Mourrain, P., Boutet, S., Earley, K., Lawrence, R.J., Pikaard, C.S., Murfett, J., Furner, I., Vaucheret, H., y Scheida, O.M. 2004, Plant Cell, 16, 1021. 72. Janssens, V. y Goris, J. 2001, Biochem. J., 353, 417. 73. Borges, A.A., Cools, H.J. y Lucas, J.A. 2003, Plant Pathology, 52, 429.