SuperSAGE revealed different classes of early resistance response genes in Capsicum chinense plants harboring L3-resistance gene infected with Pepper mild mottle virus

  • Hiroyuki Hamada
  • Hideo Matsumura
  • Reiko Tomita
  • Ryohei Terauchi
  • Kazumi Suzuki
  • Kappei Kobayashi
Viral and Viroid Diseases


We used SuperSAGE, an improved version of serial analysis of gene expression, to explore transcriptome changes early in the L3-mediated resistance response of pepper plants against a tobamovirus. Capsicum chinense plants homozygous for the L3 resistance gene were infected with virulent and avirulent strains of Pepper mild mottle virus (PMMoV). Plants were maintained at a temperature nonpermissive for the resistance gene to allow the viruses to spread, then transferred to a permissive temperature for 3 h and subsequently analyzed. In the incompatible reaction, we selected 152 SuperSAGE tags (each 26 nucleotides long) possibly corresponding to upregulated genes, and 84 tags for downregulated genes. Approximately 70% of tags had matching ESTs in the genus Capsicum, other genera within the Solanaceae and/or other families of plants. More than 90% of tags with EST matches could be annotated with either functionally characterized or uncharacterized proteins. We compared genes annotated by SuperSAGE tags and those annotated by partial cDNA that was obtained using the SuperSAGE tag sequences as rapid amplification of the cDNA ends-PCR primers. Of genes annotated by SuperSAGE tags, c. 90% were consistent with those annotated by longer cDNA sequences. We cloned 17 full-length cDNAs from different SuperSAGE tags and confirmed that these genes were upregulated during normal infection in the incompatible interaction. We identified several early resistance response genes including a Ran/TC4 protein and a β-oxidation multifunctional protein, indicating that SuperSAGE is a powerful tool for investigating plant–pathogen interactions.


Early response L3 PMMoV Resistance SuperSAGE Transcriptome 


Plants resist pathogen attacks by activating a variety of defense mechanisms such as the hypersensitive response (HR), in which rapid cell death occurs locally at the infection site (Baker et al. 1997). The HR is frequently associated with increased expression of many defense-related genes, i.e., PR-protein genes such as PR1 and PR4b (Bol et al. 1990) and HR-related genes such as HSR203J and HIN1 (Pontier et al. 1999). These proteins are known to be regulated by particular signal molecules involved in defense responses including salicylic acid, jasmonic acid, and ethylene, and therefore have been used as biomarkers to analyze signaling pathways activated in a given plant–pathogen interaction (e.g., Kiba et al. 2006). In addition to the aforementioned defense-related genes, a number of pathogen-induced host genes have been isolated in the plant disease resistance response (e.g., Nakane et al. 2003). However, it is still important to identify more host genes that are specifically upregulated during the resistance response to elucidate the molecular mechanisms of plant disease resistance.

One of the best analyzed experimental systems in plant–virus interaction research is the pathosystem of Tobacco mosaic virus (TMV) and tobacco (Nicotiana tabacum) carrying the TMV-resistance gene, N. Studies have identified several important defense-related genes (e.g., Seo et al. 1995, 2000) in a synchronous defense response system, in which the temperature-sensitive N gene function is activated by shifting to a permissive temperature after TMV has propagated and spread in the inoculated leaves under a nonpermissive temperature (Weststeijn 1981). Although this system is quite powerful to analyze gene expression and biochemical changes during the resistance response, there are few suitable virulent virus isolates that propagate in the host but do not activate the resistance response. Therefore, it is difficult with this system to detect differences between the expression patterns of defense-related genes in compatible and incompatible interactions. A desirable system is one in which we can analyze closely related virulent and avirulent pathogens. A system meeting these requirements is comprised of Pepper mild mottle virus (PMMoV) isolates and Capsicum plants harboring the tobamovirus resistance gene, L3 (Berzal-Herranz et al. 1995; García-Luque et al. 1993; Hamada et al. 2002; Tsuda et al. 1998).

The L3 gene confers resistance against tobamoviruses in Capsicum plants and is accompanied by the induction of necrotic local lesions by an HR (Boukema 1984). L3-gene-mediated resistance is elicited by the coat protein (CP) of tobamoviruses (Berzal-Herranz et al. 1995; Gilardi et al. 2004). Analyses of chimeric and point-mutated viruses have indicated that various single or double amino acid changes in the PMMoV CP can overcome L3-gene-mediated resistance (Berzal-Herranz et al. 1995; Hamada et al. 2002; Tsuda et al. 1998). In our previous study, both the spatial and temporal patterns of defense-related gene induction were critical factors in restricting virus spread by L3-gene-mediated resistance (Hamada et al. 2005), suggesting that the extent of the early response to the viral elicitor is important in determining the overall host response.

To explore the molecular basis of L3-mediated resistance with special emphasis on the early responses, we attempted to identify host genes induced only by avirulent PMMoV isolates at early stages after the onset of the resistance response. We used a temperature shift procedure similar to that of the TMV-N gene system mentioned to obtain plant material that has synchronous resistance responses.

A number of methods have been used to isolate differentially expressed plant genes. We selected SuperSAGE, an improved version of serial analysis of gene expression (Matsumura et al. 2003, 2005), to profile mRNAs from infected Capsicum chinense plants. SuperSAGE is a powerful tag-based method that provides a quantitative profile of genes expressed in the biological material of interest. SuperSAGE gives 26-base tag sequences of expressed genes, which are almost twice as long as those obtained using the original SAGE technique. Because the longer tag sequences enable tag-to-gene annotation with higher specificity, it is especially useful for expression profiling in organisms in which little genome information is available (Coemans et al. 2005; Nasir et al. 2005). In this report, we describe the genes identified by SuperSAGE that are up- or downregulated during the early resistance response to PMMoV in C. chinense plants. These plant genes belong to different classes of genes; the involvement of some genes identified is not well known in the plant disease response. The importance of the genes identified here in the resistance response is discussed.

Materials and methods

Plants and viruses

C. chinense PI159236, a pepper that is homozygous for L3 (L3-Cc), was grown in pots containing commercial soil (Sakata Seed, Yokohama, Japan) in a plant growth room at 24°C with 16 h illumination per day. An infectious cDNA clone of PMMoV P1,2,3 pathotype, pPIW138N, was constructed by introducing an amino acid substitution, M138N, into the infectious cDNA clone of PMMoV-Iw (pathotype P1,2), as described previously (Hamada et al. 2007). The oligonucleotide primers used were as follows: 138NF (5′-CGTGGCACGGGAAATTACAATCAAGCTCTG-3′) and 138NR (5′-ATTGTAATTTCCCGTGCCACGAACTAACTC-3′). Purified PMMoV virions, namely, PIW and PIW-138N, were prepared from N. benthamiana plants inoculated with in vitro RNA transcripts from the cDNA clones pPIW and pPIW-138N, respectively, as previously described (Hamada et al. 2007).

Induction of synchronous resistance response

L3-Cc plants mechanically inoculated with purified PMMoV (0.2 μg/ml in 10 mM phosphate buffer, pH 7.2) were maintained in a growth chamber at 32°C for 7 days, then transferred to a growth chamber at 22°C. The inoculated leaves were harvested or observed at indicated times after transferring the plants to 22°C. Spread of the viruses was examined by hammer blot analysis as described previously (Kobayashi et al. 2002).

Generation of SuperSAGE libraries and data analysis

Total RNA was extracted from inoculated leaves 3 h after the temperature shift described. We isolated mRNA from total RNA using the PolyATract mRNA isolation system (Promega, Madison, WI, USA), according to the manufacturer’s protocol. SuperSAGE was carried out as described (Matsumura et al. 2003) using 5 μg mRNA starting material. Briefly, double-stranded cDNA synthesized from the mRNA with biotinylated oligo(dT) primer was digested with the restriction enzyme NlaIII. The biotin-labeled, digested cDNA fragments were collected using streptavidin-magnetic beads. Two linkers, each carrying an EcoP15I recognition site, were ligated to the end of cDNA fragments on the beads. Linker-ligated cDNA on the beads was digested with EcoP15I, and the released fragments (linker and 26–27 bp cDNA) were ligated after blunt-ending to form randomly paired ditags. These ditags were PCR amplified, and linker fragments were removed by NlaIII digestion and gel purification. Purified ditags (without linkers) were concatenated by ligation, and longer (>500 bp) concatemers were cloned into plasmids and sequenced. Extraction and counting of SuperSAGE tags and statistical analysis by a Monte–Carlo simulation method were performed using SAGE2000 software kindly provided by Dr. K. W. Kinzler, Johns Hopkins University.

Cloning of cDNA corresponding to SuperSAGE tags

To isolate longer cDNAs fragments adjacent to SuperSAGE tags, we performed 5′- and 3′-rapid amplification of the cDNA ends (RACE) with a GeneRacer kit (Invitrogen, Carlsbad, CA, USA) using total RNA from C. chinense leaves infected with PIW for 3 days. RACE PCR was performed using either GeneRacer 5′ or 3′ primers, together with the 22-nucleotide primers consisting of SuperSAGE tag sequences without common four-bases NlaIII sites. Full-length cDNA was amplified with gene-specific PCR primers that were designed based on the sequence data from 5′- and 3′-RACE analyses. The PCR products were cloned into a pSTBlue vector (Novagen, Madison, WI, USA) and sequenced.

RNA extraction, RT-PCR and real-time PCR analysis

RNA was extracted using the RNAqueous kit (Ambion, Austin, TX, USA) for RT-PCR and real-time PCR. RT-PCR was carried out using the PrimeScript 1st strand cDNA synthesis kit and ExTaq DNA polymerase (Takara, Otsu, Japan) with primer pairs shown in Table S1. Real-time PCR analysis was carried out using QuantiTect SYBR Green RT-PCR (Qiagen, ABI Prism 7000 sequence detection systems) and 100 ng of total RNA as template. The primers were designed based on sequence data from 3′- or 5′-RACE analysis of SuperSAGE-tagged genes (Table S1). For internal reference, 18S ribosomal RNA levels were measured in parallel.

Results and discussion

Synchronous HR-inducing system by temperature shift in pepper plants

Incubation of plants at temperatures over 28°C leads to loss of L3 function, resulting in systemic infection of tobamoviruses in pepper plants harboring L3 (Boukema 1982). Using this property of the L3 gene, we established a synchronous HR-inducing system, in which the L3 function is turned on by a temperature shift as in the TMV-N gene tobacco system (Seo et al. 1995, 2000; Weststeijn 1981). L3-Cc plants inoculated with PIW (P1,2 pathotype) or PIW138N (P1,2,3 pathotype) were incubated at 32°C for 7 days, then shifted to 22°C. L3-Cc plants restrict the spread of P1,2 pathotype PIW (Fig. 1a); P1,2,3 pathotype PIW138N breaks this resistance and causes systemic infection at 22°C (Fig. 1c and data not shown for systemic infection). Incubation of the plants at 32°C allowed both viruses to spread through the inoculated leaves with no visible symptoms (Fig. 1b, d and e) and to the uninoculated upper leaves (Fig. 1g). In PIW-infected plants, expanding necrosis was induced within 48 h of the temperature shift in both inoculated and uninoculated systemic leaves (Fig. 1f, h), but no symptoms were observed in PIW138 N-infected plants (data not shown). RT-PCR analysis of RNA from plants 3 and 6 h after the temperature shift revealed that PR1a and PR4b were marginally upregulated at 3 h and further upregulated at 6 h after the temperature shift (Fig. 1i). These results are evidence that L3-Cc plant cells were in the early phase of resistance response 3 h after the temperature shift as reported for the TMV–N gene tobacco system (Seo et al. 2000).
Fig. 1

System to induce synchronous resistance response in pepper. Capsicum chinense plants harboring the L3 resistance gene were inoculated with P1,2 (a, b, eh) or P1,2,3 (c, d) pathotypes of Pepper mild mottle virus (PMMoV) and grown for 7 days at 22°C (a, c) or 32°C (b, d, e, g). At 7 days postinfection, virus spread in the inoculated leaves was examined by hammer blotting and immunodetection using anti-PMMoV antibody (ad). Plants grown at 32°C did not develop visible symptoms in inoculated leaves (e), but mosaic formed on uninoculated systemic leaves (g). After the temperature shift to 22°C for 2 days, the leaves developed necrosis (f, h). i RT-PCR analysis of pathogenesis-related gene expression in normal infection and temperature shift experiments. RNAs from normal infection (0 and 48 h postinoculation) and from the temperature shift experiment (3 and 6 h posttemperature shift) were analyzed for the expression of PR1a and PR4b and for virus accumulation (PMMoV). EF1a was a control for the RNA input into the reaction

Generation of SuperSAGE libraries and annotation of SuperSAGE tags

To isolate early defense-response genes in pepper plants, we generated SuperSAGE libraries from both PIW-infected (R-library after resistance response in incompatible combination) and PIW138N-infected (S-library after susceptible response in compatible combination) L3-Cc plants at 3 h after the temperature shift. Table 1 summarizes the analysis of R- and S-libraries. Of more than 12,000 tags in each library we counted, 2,118 tags were common to both libraries, 2,711 tags were specific to the R-library, and 2,785 tags were specific to the S-library. Because frequent tags are known to give better tag-to-gene annotation (Coemans et al. 2005), of these 7,614 tags, we focused on 664 tags that were counted more than four times in either R- or S-libraries. We found 236 differentially expressed tags showing at least threefold difference between R- and S-libraries. As shown in Table 1, 152 tags were upregulated (R/S ≥ 3) and 84 tags were downregulated (S/R ≥ 3) during the resistance response. The threefold difference in tag counts was not always statistically significant in this experiment: e.g., the P-value was 20.3 for the tags that were found six times and twice in R- and S-libraries, respectively. Nevertheless, it is important to analyze more candidates further to discover biologically important genes by exhaustive gene expression analysis. Indeed, we found three tags with counts of 6 and 2 in R- and S-libraries, respectively, to be reproducibly induced during the resistance response (see below).
Table 1

Summary of SuperSAGE libraries





Total no. of different tagsb



Total tag countsc



Specific tags to each libraryd



Tags common to both librariese


R = Sf


R or S ≥ 4g




3 > R/S > 1/3h


R/S ≥ 3i


S/R ≥ 3j


aSuperSAGE libraries were generated from pepper plants with synchronous resistance responses of incompatible (R) and compatible (S) interaction (see text for detail)

bTotal number of different 26 bp SuperSAGE tags in each library

cTotal number of read 26 bp SuperSAGE tags

dNo. of SuperSAGE tags found only one of the two libraries

eNo. of tags found in both libraries

fNo. of tags with the same frequency in both libraries

gNo. of tags occurring more than four times in either R- or S-libraries (hereafter, referred to as O4 tags)

hNo. of O4 tags with less than threefold difference in frequency between the two libraries

iNo. of O4 tags with greater than threefold difference in frequency in R library than in S library

jNo. of O4 tags with greater than threefold difference in frequency in S library than in R library

To annotate these SuperSAGE tags, we first performed a BLASTN search of tag sequences against EST databases (Table 2). When matching ESTs were retrieved, the EST sequences were used for BLASTX against protein databases, which enabled us to make functional annotations of the SuperSAGE tags (Table 3). We evaluated this EST-guided annotation for its efficiency and accuracy. Although we expected that 26 bp tags should completely match EST sequences, we accepted up to six base mismatch in the sequence homology (20/26 match) for identifying the corresponding EST to tags not only from Capsicum species but also other solanaceous species. As shown in Table 2, 160 of 236 tags were found to match known EST sequences. ESTs corresponding to 150 tags enabled us to identify both functionally characterized proteins and uncharacterized proteins with an annotation success rate of 68%. As expected, Capsicum ESTs led to more frequent annotation than those from other genera, and solanaceous ESTs gave more frequent annotation than those from other families. Annotation was obtained in ~90% of SuperSAGE tags whose best-match ESTs were found in non-Capsicum species, suggesting that ESTs from plants that are distantly related to the material used for SuperSAGE library generation are also useful for the annotating SuperSAGE tags. To assess the accuracy of EST-guided annotation of SuperSAGE tags, we cloned partial cDNA by 3′- or 5′-RACE methods and compared the EST-guided annotations with those obtained using longer cDNA sequences. Both annotations matched in 33 of 38 SuperSAGE-tags, indicating that EST-guided annotation is substantially accurate. These results indicate that SuperSAGE is useful for profiling the transcriptome of organisms in which genome information is unavailable. Non-Capsicum Solanaceae ESTs gave annotations as accurate as those from Capsicum ESTs, suggesting that ESTs from the same family members are useful for the annotation of SuperSAGE tags.
Table 2

Summary for EST-guided annotation of SuperSAGE tags

Classification of SuperSAGE tags

R/S ≥ 3

S/R ≥ 3






With annotation/with EST (%)c

92/98 (94)

58/62 (94)

150/160 (94)

 Capsicum ESTd

54/57 (95)

36/36 (100)

90/93 (97)

 EST of other Solanaceaee

35/38 (92)

16/19 (84)

51/57 (89)

 EST of other familiesf

3/3 (100)

6/7 (86)

9/10 (90)

Tags with no EST matches (% of total)g

54 (36)

22 (26)

76 (32)

Long cDNA clonedh




 Matched annotation (%)i

29 (85)

4 (100)

33 (87)

  Capsicum ESTj




  Non-Capsicum Solanaceae ESTk




aSum of R/S ≥ 3 and S/R ≥ 3

bTotal no. of SuperSAGE tags of R/S ≥ 3, S/R ≥ 3 and their total

cNo. of SuperSAGE tags given EST-guided annotation/those which matching EST was found

dEST from Capsicum found among those in footnote c

eEST from Solanaceous plants excluding Capsicum found among those in footnote c

fEST from non-Solanaceous plants found among those in footnote c

gNo. of SuperSAGE tags where no ESTs were found

hNo. of SuperSAGE tags where longer cDNA fragments were cloned and sequenced

iNo. of SuperSAGE tags where EST-guided annotation matched annotation obtained with longer cDNA sequence

jEST from Capsicum found among those in footnote i

kEST from non-Capsicum plants found among those in footnote i

Table 3

Functional annotation of SuperSAGE-tagged genes

Functional category

R/S ≥ 3

S/R ≥ 3




Cellular structure









Protein modification









Stress and aging















aNo. of annotated SuperSAGE tags not included in the categories shown

bNo. of annotated SuperSAGE tags with uncertain identity e.g., protein containing a particular domain

cTotal of 87 SuperSAGE tags with EST-guided annotation and 15 SuperSAGE tags with annotation based on longer cDNA sequences from R/S ≥ 3 tags. Total of 58 SuperSAGE tags with EST-guided annotation, two of which were also confirmed by cDNA sequence. Tags from S/R ≥ 3 were analyzed

Functional categories of SuperSAGE tag annotations

Table 3 categorizes up- or downregulated genes in the resistance response corresponding to SuperSAGE tags as mentioned. It also includes an additional ten tags, which did not have homologous ESTs in the database but were annotated instead by partial cDNA cloning. Striking changes in the transcriptome after the onset of the resistance response presented here include (1) upregulation of genes involved in primary and secondary metabolism, (2) upregulation of signaling genes, stress- and aging-related genes and transporter genes, (3) up- and down-regulation of different photosynthetic genes, and (4) up- and downregulation of different ribosomal protein genes. Elicitation of primary and secondary metabolism was demonstrated in potatoes treated with a fungal elicitor and is a common feature of the resistance response (Nakane et al. 2003). Upregulation of signaling, stress/aging and transporter genes has been documented in several studies (for review, see Farmer 2000). Photosynthetic genes have been reported to be generally downregulated (Matsumura et al. 2003). However, we observed upregulation of a small set of photosynthetic genes, suggesting that functional and structural changes in photosynthetic machinery occur during the defense response. Similarly, translational machinery could also change its structure and function during the resistance response. Further analyses of each photosynthetic and ribosomal protein would determine the functional and structural alteration in these supermolecular machineries that are essential for plant cells.

Full-length cDNA cloning, expression analysis and annotation of SuperSAGE-tagged genes

SuperSAGE identified early resistance response genes with a reasonable success rate of annotation for each of the SuperSAGE tags, furthering our understanding of global changes in the plant transcriptome during the resistance response. However, a change in a gene’s expression level is not a direct indication of involvement of the gene in a biological process. Functional analysis of each gene included in the transcriptome changes is important to understand the mechanism underlying the biological process, e.g., the plant defense response, and also the biological significance of the global changes in gene expression. Cloning of the full-length gene is a prerequisite for functional analysis of the gene of interest, and this process is facilitated by SuperSAGE; SuperSAGE tag sequences can be used directly as primers in 3′- and 5′-RACE cloning, resulting in the cloning of so-called SuperSAGE-tagged genes. We have cloned partial cDNA for 38 SuperSAGE tags with EST-guided annotation and 15 tags without annotation. On the basis of the sequences of the cDNA clones, we successfully carried out real-time PCR for 43 SuperSAGE-tagged genes to quantify mRNAs. Comparison of expression profiles in temperature shift experiments and normal infections separated SuperSAGE-tagged genes into two groups: 21 genes had similar expression patterns during normal infection (48 h and/or 96 h postinoculation) and in temperature shift experiments, but the other genes were expressed differently in the two systems (Fig. 2 and S1). Among the similarly expressed genes, those upregulated at 48 h postinoculation in the incompatible interaction were selected for full-length cDNA cloning. Observation of the differently expressed group of genes suggests that some SuperSAGE-tagged genes were transiently up- or downregulated early after the onset of the resistance response, and therefore, changes in their expression levels could not be detected during a normal infection process. Because the RNA sample from the normal infection is a mixture of RNA from cells at different stages of the resistance response, the nature of the RNA sample could affect the magnitude of detection of gene expression, masking a potential transient upregulation of gene expression in the normal infection samples. Most likely for the same reason, the magnitude of induction of genes that were upregulated at 48 h postinoculation differed between the temperature shift experiments and normal infection (Fig. 2; Table 4). The expression patterns of these genes will be examined in detail.
Fig. 2

Real-time PCR analysis for mRNA levels of SuperSAGE-tagged genes in the plants during normal infection with PMMoV at 48 h postinoculation. Capsicumchinense plants harboring L3 resistance gene were inoculated with P1,2 (filled column) or P1,2,3 (gray column) pathotypes of Pepper mild mottle virus (PMMoV) or phosphate buffer (mock inoculation; open column). Total RNA was extracted from inoculated leaves, for real-time PCR using primers in Table S1 and normalized against 18S rRNA levels. The mRNA levels relative to untreated plants were determined in six independent RNA preparations, and mean values are shown. Error bars indicate standard deviation. Expression levels of pathogenesis- and HR-related proteins were also examined in parallel. Note that vertical axis values differ between left and right panels

Table 4

Partial list of SuperSAGE-tagged genes that were upregulated under normal avirulent Pepper mild mottle virus infection conditions

ID no.

Tag sequencea

Tag countsb










Cysteine proteinase





Cu/Zn superoxide dismutase





NADP-dependent malic enzyme










Aspartic protease





Multidrug resistance-associated protein 2





CONSTANS-interacting protein 2b





MATE family transporter





NADPH oxidoreductase





C2 domain-containing protein





4-Methyl-5(B-hydroxyethyl)-thiazol monophosphate biosynthesis enzyme





Glyoxysomal fatty acid beta-oxidation multifunctional protein










26S Proteasome subunit, RPN2a





Ran/TC4 protein





Erwinia carotovora subsp. atroseptica response gene 1, phosphate-induced protein 1 (phi-1)





Zinc finger (C3HC4-type RING finger) family protein

aNucleotide sequences of SuperSAGE tags, excluding common CATG NlaIII site proximal to 5′ end

bFrequency of tags in R and S libraries

For validating cDNA amplification by RACE using tag primers, we took a cautious approach for full-length cDNA cloning: (1) determination of both end sequences by 3′- and 5′-RACE, (2) amplification of almost the entire mRNA sequence using gene-specific primers designed from both end sequences, and (3) confirmation of the presence of SuperSAGE tag sequence within the amplified sequence. Thus, we isolated and confirmed the annotation of 17 SuperSAGE-tagged genes (Table 4). Supplementary table S2 lists the accession numbers of these genes and of their homologues referred to in their annotation.

Proteases, such as those encoded by SS12 and SS21, have roles in resistance signaling and HR (Gilroy et al. 2007; Hatsugai et al. 2004; Kruger et al. 2002; Xia et al. 2004). The NADP-dependent malic enzyme (SS14) was highly upregulated in both temperature-shift experiments and in a normal incompatible interaction. This gene and NADPH oxidoreductase (SS48) are reportedly upregulated by treatment of potato tubers with an oomycete elicitor (Nakane et al. 2003), indicating that they are commonly upregulated during the resistance response, at least in solanaceous plants. A recent study has shown that aconitase (SS84) has a role in the regulation of oxidative stress resistance via regulation of superoxide dismutase (SS13) gene expression (Moeder et al. 2007). Hsp90 (SS18) is a well-studied molecular chaperone and reportedly has roles in resistance signaling (Takahashi et al. 2003). Recent studies have shown that transporters have roles in resistance (for review, see Rea 2007). The EST-guided annotation of SuperSAGE tags suggested that five transporters including SS29 and SS45 were upregulated, supporting a crucial role for some transporters in plant defense. Studies have shown that various C2 domain-containing proteins (SS52) are induced by biotic and abiotic stresses (Kim et al. 2003; Ouelhadj et al. 2006). One of them, Arabidopsis BAP, was shown to negatively regulate defense responses (Yang et al. 2006, 2007), but others still need to be functionally characterized. Vitamin B was reported to activate plant defense mechanisms (Ahn et al. 2005, 2007), and the induction of an enzyme involved in its biosynthesis (SS62) during the resistance response is presented here for the first time. A subunit of the 26S proteasome (SS85) and a ring-finger protein (SS124) that are involved in the ubiquitin–proteasome pathway are known to be important for defense responses (Goritschnig et al. 2007). SS122 encodes a protein similar to one induced by bacterial infection in potato (Dellagi et al. 2000) and also to one induced by phosphate in tobacco (Sano et al. 1999).

Unlike those mentioned, the fatty acid β-oxidation multifunctional protein (SS77) and Ran/TC4 (SS86) have not been described in the context of disease resistance. Fatty acid β-oxidation is a process of energy production from storage lipids and is known to be activated during seed germination (Eastmond and Graham 2000; Rylott et al. 2006). The significance of the upregulation of a key enzyme in this process during the resistance response remains unclear. However, a possible role of this enzyme in the resistance response is the biosynthesis of lipid-derived signaling molecules, which reportedly have important roles in plant disease resistance (Shah 2005). Ran is a member of the Ras GTPase superfamily and is well conserved throughout the eukaryotes. Ran is known to have roles in nucleocytoplasmic macromolecular transport and spindle assembly during cell division (Joseph 2006). Overexpression of Ran in transgenic plants resulted in altered cell division and development (Wang et al. 2006), but it has not been analyzed in the context of disease resistance. Recent studies have identified a GTPase-activating protein of Ran, RanGAP, as an essential interaction partner of the virus resistance gene Rx (Sacco et al. 2007; Tameling and Baulcombe 2007). The Ran system, including Ran itself, RanGAP and a Ran guanine nucleotide exchange factor, might have a crucial role in resistance signaling or pathogen perception in plants.


We have identified in this study a number of SuperSAGE tags with reliable tag-to-gene annotations, which were up- or downregulated during the early resistance response to PMMoV in pepper plants harboring the L3 resistance gene. Because C. chinense, which we used in this study, is not a widely cultivated crop, genomic information for this species is not available. Nevertheless, SuperSAGE enabled us to identify a number of early resistance response genes with efficient EST-guided annotation procedures. Moreover, cloning of full-length cDNA can be carried out following SuperSAGE because the tag sequence is long enough to use as a PCR primer for 5′- and 3′-RACE cloning. We successfully isolated several full-length cDNA clones using SuperSAGE tag-derived primers and found some new resistance-associated genes. The functions of these genes in the resistance response are under investigation. Our results emphasize that SuperSAGE is a powerful tool to analyze plant–pathogen interactions in wide variety of crop plants, including those lacking genomic information.



We thank Dr. K. W. Kinzler for SAGE2000 software, Harumi Takahashi and Kazue Obara for technical assistance and all members of IBRC for fruitful discussion. This study was supported in part by the Iwate Prefecture Government and in part by a grant-in-aid for Scientific Research (C) (18580047) from the Japan Society for the Promotion of Science.

Supplementary material

10327_2008_106_MOESM1_ESM.doc (48 kb)
Tables S1 and S2 (DOC 47 kb)
10327_2008_106_MOESM2_ESM.tif (1.4 mb)
Fig. S1. Real-time PCR analysis for mRNA levels of SuperSAGE-tagged genes in normal infection process at 96 h postinoculation. C. chinense plants harboring the L3 resistance gene were inoculated with P1,2 (filled column) or P1,2,3 (gray column) pathotypes of PMMoV or phosphate buffer (mock inoculation; open column). Total RNA was extracted from inoculated leaves at 96 h postinoculation for real-time PCR using primers in Table S1 and normalized against 18S rRNA levels. The mRNA levels relative to untreated plants were determined in two independent RNA preparations, and mean values are shown. (TIFF 240 kb)


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Copyright information

© The Phytopathological Society of Japan and Springer 2008

Authors and Affiliations

  • Hiroyuki Hamada
    • 1
    • 2
  • Hideo Matsumura
    • 1
  • Reiko Tomita
    • 1
  • Ryohei Terauchi
    • 1
  • Kazumi Suzuki
    • 1
    • 3
  • Kappei Kobayashi
    • 1
  1. 1.Iwate Biotechnology Research CenterKitakamiJapan
  2. 2.National Agricultural Research CenterNational Agriculture and Food Research OrganizationTsukubaJapan
  3. 3.School of Environmental ScienceUniversity of Shiga PrefectureHikoneJapan

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