1 201F Plant Science Building, Department of Plant Pathology, University of Kentucky, Lexington, KY 40546, USA
2 Department of Statistics, University of Kentucky, Lexington, KY 40506, USA
3 Advanced Genetics Technologies Center (AGTC), University of Kentucky, Lexington, KY 40546, USA
Correspondence
M. M. Goodin
mgoodin{at}uky.edu
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ABSTRACT |
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Raw microarray data and more comprehensive lists of the Gene Ontology results are available as supplementary material in JGV Online.
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INTRODUCTION |
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SYNV, an aphid- and mechanically transmissible virus, replicates and undergoes morphogenesis in the nuclei of infected plant cells (Jackson et al., 1987; Martins et al., 1998
). The SYNV genome is encoded by a single segment of negative-stranded RNA of 13 720 nt in length (Heaton et al., 1989
). In contrast to SYNV, INSV is a thrips- and mechanically transmissible plant bunyavirus that replicates and undergoes morphogenesis in the cytoplasm of infected cells. The spherical particles of INSV contain the viral genome, which is divided into three segments of negative- or ambisense single-stranded RNA, designated S (2922 nt), M (4972 nt) and L (8776 nt) (Law et al., 1992
; van Poelwijk et al., 1996
). Given the contrasting genetics of SYNV and INSV, their use in microarray-based experiments may provide a stringent test of the hypothesis that genetically distinct RNA viruses may induce the expression of common sets of genes in susceptible plants (Golem & Culver, 2003
; Whitham et al., 2003
). Furthermore, such genetic diversity should result in markedly different changes in plant gene expression compared with that observed for plus-strand RNA viruses (Golem & Culver, 2003
; Whitham et al., 2003
).
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METHODS |
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Experimental design.
To average out differences in gene expression due to plant-to-plant variation, RNA was isolated from leaves collected from a group of five plants and pooled. Tissue from two or three replicate sets was harvested for each time point for experiments conducted with INSV or SYNV. In turn, for each RNA sample, two array hybridizations were conducted on independent arrays, with one of the arrays being hybridized with reciprocally labelled cDNA samples as described below. Therefore, a total of six hybridizations were performed for each time point using RNA isolated from SYNV-infected plants. Four hybridizations per time point were conducted using INSV samples. In addition to evaluating variation among sets of plants, this experimental design permitted determination of the effect of each fluorescent dye on hybridization efficiency, as well as the reproducibility of the hybridizations. Independent sets of plants grown at different times were used for microarray and Northern hybridizations to validate the differential expression.
Potato cDNA microarray.
Potato (S. tuberosum) cDNA microarrays were obtained from The Institute of Genomic Research (TIGR). These microarrays consist of 15 264 ESTs derived from potato cDNA libraries (Ronning et al., 2003; www.tigr.org/tdb/potato) spotted in duplicate on Corning UltraGaps Slides (Corning Incorporated). The sequences of these ESTs can be accessed through the TIGR website and GenBank.
RNA extraction, fluorescent labelling and microarray hybridization.
Total RNA was extracted from the leaf tissue by using an RNeasy Plant kit (Qiagen) according to the manufacturer's instructions. cDNA synthesis, labelling of cDNA with Cy3 and Cy5 fluorescent dyes and microarray hybridizations were performed by using a 3DNA Submicro EX Expression Detection kit (Genisphere) following the manufacturer's protocol. Total RNA (5 µg) from virus-infected and healthy leaves was reverse-transcribed to cDNA for each array. For each time point, reciprocal labelling was performed to ensure that our results were not biased by dye effects.
Microarray processing, data analysis and hierarchical clustering.
Following post-hybridization washes, microarrays were scanned by using a ScanArray Express 4000 confocal laser scanner (Perkin-Elmer). Data acquisition and quantification of spot intensities were performed by using the ScanArray Express Microarray analysis system, version 2.0 (Perkin-Elmer). The foreground and background fluorescence intensities for each spot were calculated by using the adaptive-circle segmentation protocol included in the ScanArray software. The median signal intensity of each spot was obtained by subtracting the local median background intensity from the median intensity of each spot. To eliminate the spatial and intensity variations within a slide, the LOWESS normalization method was applied to the median spot intensities of images generated from either channel 1 (Cy5) or channel 2 (Cy3). Prior to statistical analysis, the datasets were filtered to exclude data points if they did not meet the following criteria across all replicates: (i) if the normalized median spot intensities were zero or <200 (pixel intensity), (ii) if the spot was determined to be unusable as defined by criteria in the ScanArray Express software or (iii) if the median foreground intensity was <20 % of the median background intensity. As each EST sequence was duplicated on the slide, a mean intensity of the two spots was used for statistical analysis. Preliminary analysis of dye-swap experiments did not suggest a significant dye effect and, hence, they were considered as replicates in subsequent statistical analyses. The filtered data were used to identify the differentially regulated genes by calculating the log2 ratios, where the normalized median intensity values of virus-treated samples were divided by similar values from control samples (Cy5-infected/Cy3-control or Cy3-infected/Cy5-control in a dye-swap experiment). The fold changes of differentially regulated genes in virus-infected samples compared with the control samples were calculated based on these ratios. The log2 ratios were analysed by a one-sample t-test to detect significant differences in gene expression at each time point. The EST sequences that showed differential expression with P values of 0·01 were considered statistically significant. The expression profiles resulting from different treatments were grouped based on similarity in pattern of their expression by using hierarchical cluster analysis based on the Pearson correlation by GeneSpring version 6.1 software (Silicon Genetics). Reliability of the microarray data was estimated by calculating correlation coefficients based on the Pearson correlation.
Northern hybridization analysis.
Northern hybridization analysis was performed by using 15 µg total RNA derived from sets of plants independent of those used for microarray experiments. Following separation on 1·2 % denaturing agarose gels containing 2·2 M formaldehyde, RNA was transferred to a Hybond-N+ nylon membrane (Amersham Biosciences) by capillary blotting (Maniatis et al., 1982). Probes for hybridization were generated by PCR amplification of N. benthamiana cDNA using primers designed based on the potato EST sequence. DNA sequencing confirmed the authenticity of the amplified DNA fragments. The PCR fragments were labelled with [
-32P]dCTP by using a RediPrime random primer-labelling kit (Amersham Biosciences) following the manufacturer's instructions. Membranes were hybridized overnight in Ultrahyb solution (Ambion) at 42 °C. Membranes were washed twice with a solution containing 2x SSC and 0·1 % SDS for 5 min at room temperature, then twice with a solution of 0·1x SSC and 0·1 % SDS for 15 min at 68 °C. The Northern blots were exposed to a phosphorimager screen and the images were visualized with ImageQuant software (Molecular Dynamics). Each probe cDNA was tested at least twice, using independent samples of RNA.
Functional categories.
Functional categorization was conducted according to Gene Ontology (GO) guidelines (Martin et al., 2004; Lewis, 2005
). Following statistical analysis of the array hybridization data, ESTs of interest were grouped into lists that were (i) commonly expressed in response to INSV and SYNV or (ii) specifically up- or downregulated in response to these viruses. The sequences of these ESTs were obtained from the TIGR website (www.tigr.org). GO was used for functional classification of the differentially expressed ESTs into three categories with respect to gene function: (i) molecular function, (ii) biological process and (iii) cellular component. Prior to compilation of the ontologies, the available GO and sequence information for all solanaceous species (S. tuberosum, N. benthamiana, Nicotiana tabacum and Lycopersicon esculentum) available on the TIGR website was pooled to form a custom database. Potato EST sequences in each list were then used to find homologous matches in the custom database by using BLAST. Only ESTs with high-scoring (score value >100) BLAST comparisons (<e4) were matched with gene names in the pooled GO database.
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RESULTS |
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Reliability of the microarray data
To assess the reliability of the microarray data, the normalized median signal intensities resulting from control samples (mock-inoculated plants) were compared across all the replicates for each treatment. A high correlation (0·900·95) among the healthy control samples for each time point was observed, indicating low technical and biological variation (Table 1). Variation due to differences between fluorescent dyes was calculated based on correlation coefficient between dye-swap experiments, using datasets from mock-inoculated control plants. The high correlation (0·9) observed among the dye-swap replicates indicated that dye effects were insignificant.
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Although we have focused primarily on identification of genes upregulated in response to virus infection, we have also confirmed the validity of microarray results for downregulated genes (Fig. 4b). As seen in Table 2(b)
, histone genes were downregulated in response to virus infection. The results of our Northern blots supported our array results in that only a slight downregulation of histone 2b (H2b) was observed in response to SYNV infection at 11 (1·3-fold, P=0·02439) and 14 (1·9-fold, P=0·00090) d.p.i. In dramatic contrast, the H2b transcript was virtually undetectable in RNA samples isolated from leaves infected with INSV at 4 (2·5-fold, P=0·02879) or 5 (10·5-fold, P=0·00002; Fig. 4b
) d.p.i.
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DISCUSSION |
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In addition to reporting the changes in host gene expression, we provide insight into relationship between these changes and the accumulation of viral RNAs. In the case of INSV, the accumulation of higher amounts of viral RNAs was correlated with a corresponding increase in the number of plant genes that were expressed differentially. This can be explained either by an increase in the amount of viral RNA per infected cell or by the expansion of the number of infected cells, particularly between 4 and 5 d.p.i. Neither of these two mechanisms can be ruled out at this time, particularly as no change in the ratio of the amounts of S-RNA to INSV-N mRNA was observed. In contrast to INSV, Northern blots suggested that SYNV-N mRNA was in higher abundance at 11 d.p.i. than at 14 d.p.i. (Fig. 1c). Light microscopy and immunolocalization experiments failed to detect any differences in the number of cells in systemically infected leaves at 11 and 14 d.p.i. (data not shown). Therefore, at this time, we cannot accept the hypothesis that a change in the number of infected cells was responsible for the observed results. Thus, the implications of our results are twofold. Firstly, the detection of viral mRNA in higher abundance at 11 d.p.i. suggests the possibility that most of the infecting virus particles were in the transcription stage of their replication cycle, which is an early event. It follows that genes that are upregulated at early time points of infection would be detected preferentially at 11 d.p.i. This is clearly demonstrated for probe BQ512878, an EST with homology to a WRKY4 transcription factor (Fig. 3a
). These proteins comprise a major family of transcription factors that are essential in pathogen and salicylic acid responses of higher plants, as well as a variety of plant-specific reactions, and are expressed at early stages of infection (Eulgem et al., 2000
). Consistent with this is the observation that genes expressed at late stages of pathogen invasion, such as chitinase, PR-1 and calmodulin (Fig. 3a
), are also primarily upregulated at 14 d.p.i. On a larger scale, our Venn analyses show that only 45 % (300/665) of the ESTs that were expressed differentially at 11 d.p.i. were represented in the 14 d.p.i. dataset (Fig. 2b
). Further studies are required to establish the relationship between host gene expression and the replicative status (transcription vs replication) of SYNV. Taken together, these results suggest that our present datasets accurately described the temporal changes in host gene expression in relation to the changes in SYNV gene expression.
Whilst our data agree with predictions for induced expression of plant defence genes, examination of the expression patterns for heat-shock genes revealed marked contrast between the effects of SYNV and INSV on host gene expression. As with previous reports involving potyviruses and tobamoviruses (Aranda et al., 1996; Aranda & Maule, 1998
; Whitham et al., 2003
), infection by INSV caused rapid induction of heat-shock genes, whereas SYNV did not (Fig. 4a
). Similar to reports for tobamoviruses (Whitham et al., 2003
), the induction of the small HSP genes by INSV was transient, with maximal expression at 4 d.p.i. (Fig. 4a
). Whilst HSPs have been shown to play a direct role in viral transcription complexes (Qanungo et al., 2004
) or defence signalling (Liu et al., 2004
), such a requirement has not been established for INSV replication. To the contrary, the induction of HSP expression may reflect a generalized stress response of the plant, due to the nuclease activity of the INSV polymerase during cap snatching of plant mRNAs to produce ribonucleotide primers for transcription of viral mRNAs. This generalized stress response may also account for the downregulation of histone gene expression.
Examination of the 25 genes associated with the greatest fold changes in response to INSV or SYNV revealed an insightful trend, whereby the fold change in host gene expression in response to infection by SYNV was always lower than that for INSV (Table 2a, b). This trend was observed over the entire array for all ESTs that passed our statistical analysis (data not shown). As a difference in the number of cells that became infected by either of these two viruses was not observed, we hypothesize that infection by SYNV may result in modulation of the transcriptional response in plant cells, like their animal-infecting counterparts (Weck & Wagner, 1978
; Ahmed & Lyles, 1997
).
In spite of this highly modulated effect on host transcriptional profiles, we were able to identify genes that were upregulated specifically in response to infection by SYNV (Table 2d). Of particular interest is the upregulation of a subtilisin-like protease (GenBank accession no. BQ519430; P=0·00102, fold change 3·2). Further investigations will determine whether this protease is responsible for cleavage of the SYNV-N protein that is observed during late stages of infection (Jones & Jackson, 1990
). Processing of the N protein has significant consequences for replication and morphogenesis of SYNV, as this protein is required in high amounts for encapsidation of full-length genomic and anti-genomic RNA molecules. Furthermore, systemic activation of such a protease may, in part, account for the recovery phenotype characterized by reduced titre of SYNV and symptom severity in leaves produced after 14 d.p.i. We note that precedent for such proteolytic processing is established in the literature, including cleavage of the nucleocapsid proteins of human influenza viruses A and B at late stages of infection (Zhirnov et al., 1999
). Additionally, we are presently characterizing antibodies raised against peptides corresponding to the termini of the SYNV N protein that detect a 21 kDa derivative in virus-infected plants (data not shown).
In addition to providing insight into the interaction of plants and enveloped viruses, we have demonstrated unequivocally that heterologous microarrays are a powerful tool for transcriptional profiling of N. benthamiana genes. Given the close genetic relatedness between species in the family Solanaceae (D'Arcy, 1979; Borisjuk et al., 1994
), we hypothesized that S. tuberosum cDNA microarrays could be employed to identify changes in N. benthamiana gene expression in response to infection by lipid-enveloped plant viruses. The hybridization data shown in Figs 2, 3 and 4
support this hypothesis. Of the 15 264 unique ESTs printed on the arrays, we found that 11 383 (75 %) could hybridize to cDNA made from RNA isolated from N. benthamiana leaves. Thus, we are confident that our microarray results presented a true picture of the effects of INSV and SYNV on host gene expression.
In conclusion, we have used heterologous microarrays to identify specific and common changes in N. benthamiana gene expression in response to infection by the enveloped viruses SYNV and INSV. Whilst these experiments provide significant insight into the biology of these viruses, future studies are expected to establish the spatial, in addition to the temporal, relationship between host gene expression and sites of virus accumulation. Moreover, when coupled with facile methods for gene silencing (Lu et al., 2003) and protein localization (Goodin et al., 2002
), our results may provide the foundation for studies aimed at identifying host genes that are required for the replication and/or movement of enveloped viruses in plants. Identification of such genes may provide targets from which novel control strategies can be developed for controlling these, or related, viruses that threaten agriculture.
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ACKNOWLEDGEMENTS |
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Received 17 March 2005;
accepted 26 May 2005.
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