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Transcriptomic and proteomic analysis of a compatible tomato-aphid interaction reveals a predominant salicylic acid-dependent plant response.

Coppola V, Coppola M, Rocco M, Digilio MC, D'Ambrosio C, Renzone G, Martinelli R, Scaloni A, Pennacchio F, Rao R, Corrado G - BMC Genomics (2013)

Bottom Line: Among them, the SA-signaling pathway and stress-responsive SA-dependent genes play a dominant role.Furthermore, tomato response is characterized by a reduced accumulation of photosynthetic proteins and a modification of the expression of various cell wall related genes.Considering the rapid advancement of tomato genomics, this information will be important for the development of new protection strategies.

View Article: PubMed Central - HTML - PubMed

Affiliation: Dipartimento di Agraria, Università degli Studi di Napoli Federico II, 80055 Portici, NA, Italy.

ABSTRACT

Background: Aphids are among the most destructive pests in temperate climates, causing significant damage on several crops including tomato. We carried out a transcriptomic and proteomic study to get insights into the molecular mechanisms and dynamics of the tomato response to the Macrosyphum euphorbiae aphid.

Results: The time course analysis of aphid infestation indicated a complex, dynamic pattern of gene expression. Several biological functions were affected and genes related to the stress and defence response were the most represented. The Gene Ontology categories of the differentially expressed genes (899) and identified proteins (57) indicated that the tomato response is characterized by an increased oxidative stress accompanied by the production of proteins involved in the detoxification of oxygen radicals. Aphids elicit a defense reaction based on the cross-communication of different hormone-related signaling pathways such as those related to the salicylic acid (SA), jasmonic acid (JA), ethylene and brassinosteroids. Among them, the SA-signaling pathway and stress-responsive SA-dependent genes play a dominant role. Furthermore, tomato response is characterized by a reduced accumulation of photosynthetic proteins and a modification of the expression of various cell wall related genes.

Conclusions: Our work allowed a more comprehensive understanding of the signaling events and the defense dynamics of the tomato response to aphids in a compatible interaction and, based on experimental data, a model of the tomato-aphid molecular interaction was proposed. Considering the rapid advancement of tomato genomics, this information will be important for the development of new protection strategies.

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Hierarchical cluster of all differentially expressed probes. Distances were calculated using the Pearson similarity and agglomeration was performed according to the Ward's minimum variance algorithm. The heat-map diagram shows the relative expression level at the three time points (24, 48 and 96 hours post infection). Gradation from red to green represents strong up-regulation to strong down-regulation on a log scale. In each time point, each colored column represents a single biological replicate.
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Figure 1: Hierarchical cluster of all differentially expressed probes. Distances were calculated using the Pearson similarity and agglomeration was performed according to the Ward's minimum variance algorithm. The heat-map diagram shows the relative expression level at the three time points (24, 48 and 96 hours post infection). Gradation from red to green represents strong up-regulation to strong down-regulation on a log scale. In each time point, each colored column represents a single biological replicate.

Mentions: To profile the variation in gene expression in tomato following the establishment of a compatible interaction with the M. euphorbiae, we analysed plants 24, 48 and 96 hours after infestation. In our data analysis, three filtering criteria were used to identify differentially expressed genes: a two-fold change in transcript levels between unifested and infested plants, a p <0.05 and a significant match between the oligonucleotide probe and a tomato gene. Taking into account the three time points, 999 annotated probes were significantly differentially expressed (Table 1). All differentially expressed probes were grouped according to the similarity of their expression profiles at the three data-points by cluster analysis. The dendrogram indicated that, as expected, the three biological replicates for each time point assort together, showing a good congruence (Figure 1). Moreover, the heat-map illustrates a weak linkage among the three conditions, with the most intense transcriptional response at 48 h. Cluster analysis identified groups of similarly behaving transcripts that have different expression trends, highlighting a relevant dynamism of gene expression in tomato. The recent release of the tomato genome sequence allowed us to map the microarray probes on the genome sequence, thus providing the opportunity of a more accurate functional annotation of the array. A similarity analysis, performed against SGN Tomato Unigene database for the differentially expressed 999 probes, identified 819 genes. Specifically, the data indicated that at 24 h after infestation, 148 genes (72 up and 76 down) were significantly affected by aphid infestation. The number of responsive genes at 48 h was 637 (320 genes up and 317 down), while at 96 h, 34 genes (17 up and 17 down) were differential expressed. The complete list of differentially expressed genes, including their expression levels in all three time points, is accessible as supplementary material (Additional file1: Table S2, S3, S4). The Venn diagram (Figure 2) shows the intersections between the differentially expressed genes at the three time points. For all combinations, the overlap was limited, and only three genes were significantly affected throughout the whole time course (Table 2), indicating that the induction of most response genes is transient[20]. It is therefore noteworthy that two genes encode transcription factors belonging to the WRKY family, important regulators of SA-dependent defense responses. Specifically, the WRKY6 gene codes for a protein that in Arabidopsis thaliana has the highest similarity to the AtWRKY70 (identity: 41%; similarity: 58%; e-value: 1e-36), considered its orthologue[21]. This is strengthened by the presence in the WRKY6 promoter region of the core binding consensus sequence for the AtMYB44, which was recently described as a transcriptional activator in Arabidopsis[22]. The tomato WRKY46 protein is most similar to AtWRKY40 (identity: 43%; similarity: 54%; e-value: 2e-54). The AtWRKY40 gene is associated with pathogen response and it was also induced by the aphid B. brassicae[14]. The third gene codes for a GDSL esterase/lipase. GDSL-lipase belongs to a subfamily of lipolytic enzymes which appear to be primarily involved in the regulation of plant development and morphogenesis[23]. Some GDSL-lipase genes have been involved in plant defense because of their induction by SA and pathogens[24-26].


Transcriptomic and proteomic analysis of a compatible tomato-aphid interaction reveals a predominant salicylic acid-dependent plant response.

Coppola V, Coppola M, Rocco M, Digilio MC, D'Ambrosio C, Renzone G, Martinelli R, Scaloni A, Pennacchio F, Rao R, Corrado G - BMC Genomics (2013)

Hierarchical cluster of all differentially expressed probes. Distances were calculated using the Pearson similarity and agglomeration was performed according to the Ward's minimum variance algorithm. The heat-map diagram shows the relative expression level at the three time points (24, 48 and 96 hours post infection). Gradation from red to green represents strong up-regulation to strong down-regulation on a log scale. In each time point, each colored column represents a single biological replicate.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3733717&req=5

Figure 1: Hierarchical cluster of all differentially expressed probes. Distances were calculated using the Pearson similarity and agglomeration was performed according to the Ward's minimum variance algorithm. The heat-map diagram shows the relative expression level at the three time points (24, 48 and 96 hours post infection). Gradation from red to green represents strong up-regulation to strong down-regulation on a log scale. In each time point, each colored column represents a single biological replicate.
Mentions: To profile the variation in gene expression in tomato following the establishment of a compatible interaction with the M. euphorbiae, we analysed plants 24, 48 and 96 hours after infestation. In our data analysis, three filtering criteria were used to identify differentially expressed genes: a two-fold change in transcript levels between unifested and infested plants, a p <0.05 and a significant match between the oligonucleotide probe and a tomato gene. Taking into account the three time points, 999 annotated probes were significantly differentially expressed (Table 1). All differentially expressed probes were grouped according to the similarity of their expression profiles at the three data-points by cluster analysis. The dendrogram indicated that, as expected, the three biological replicates for each time point assort together, showing a good congruence (Figure 1). Moreover, the heat-map illustrates a weak linkage among the three conditions, with the most intense transcriptional response at 48 h. Cluster analysis identified groups of similarly behaving transcripts that have different expression trends, highlighting a relevant dynamism of gene expression in tomato. The recent release of the tomato genome sequence allowed us to map the microarray probes on the genome sequence, thus providing the opportunity of a more accurate functional annotation of the array. A similarity analysis, performed against SGN Tomato Unigene database for the differentially expressed 999 probes, identified 819 genes. Specifically, the data indicated that at 24 h after infestation, 148 genes (72 up and 76 down) were significantly affected by aphid infestation. The number of responsive genes at 48 h was 637 (320 genes up and 317 down), while at 96 h, 34 genes (17 up and 17 down) were differential expressed. The complete list of differentially expressed genes, including their expression levels in all three time points, is accessible as supplementary material (Additional file1: Table S2, S3, S4). The Venn diagram (Figure 2) shows the intersections between the differentially expressed genes at the three time points. For all combinations, the overlap was limited, and only three genes were significantly affected throughout the whole time course (Table 2), indicating that the induction of most response genes is transient[20]. It is therefore noteworthy that two genes encode transcription factors belonging to the WRKY family, important regulators of SA-dependent defense responses. Specifically, the WRKY6 gene codes for a protein that in Arabidopsis thaliana has the highest similarity to the AtWRKY70 (identity: 41%; similarity: 58%; e-value: 1e-36), considered its orthologue[21]. This is strengthened by the presence in the WRKY6 promoter region of the core binding consensus sequence for the AtMYB44, which was recently described as a transcriptional activator in Arabidopsis[22]. The tomato WRKY46 protein is most similar to AtWRKY40 (identity: 43%; similarity: 54%; e-value: 2e-54). The AtWRKY40 gene is associated with pathogen response and it was also induced by the aphid B. brassicae[14]. The third gene codes for a GDSL esterase/lipase. GDSL-lipase belongs to a subfamily of lipolytic enzymes which appear to be primarily involved in the regulation of plant development and morphogenesis[23]. Some GDSL-lipase genes have been involved in plant defense because of their induction by SA and pathogens[24-26].

Bottom Line: Among them, the SA-signaling pathway and stress-responsive SA-dependent genes play a dominant role.Furthermore, tomato response is characterized by a reduced accumulation of photosynthetic proteins and a modification of the expression of various cell wall related genes.Considering the rapid advancement of tomato genomics, this information will be important for the development of new protection strategies.

View Article: PubMed Central - HTML - PubMed

Affiliation: Dipartimento di Agraria, Università degli Studi di Napoli Federico II, 80055 Portici, NA, Italy.

ABSTRACT

Background: Aphids are among the most destructive pests in temperate climates, causing significant damage on several crops including tomato. We carried out a transcriptomic and proteomic study to get insights into the molecular mechanisms and dynamics of the tomato response to the Macrosyphum euphorbiae aphid.

Results: The time course analysis of aphid infestation indicated a complex, dynamic pattern of gene expression. Several biological functions were affected and genes related to the stress and defence response were the most represented. The Gene Ontology categories of the differentially expressed genes (899) and identified proteins (57) indicated that the tomato response is characterized by an increased oxidative stress accompanied by the production of proteins involved in the detoxification of oxygen radicals. Aphids elicit a defense reaction based on the cross-communication of different hormone-related signaling pathways such as those related to the salicylic acid (SA), jasmonic acid (JA), ethylene and brassinosteroids. Among them, the SA-signaling pathway and stress-responsive SA-dependent genes play a dominant role. Furthermore, tomato response is characterized by a reduced accumulation of photosynthetic proteins and a modification of the expression of various cell wall related genes.

Conclusions: Our work allowed a more comprehensive understanding of the signaling events and the defense dynamics of the tomato response to aphids in a compatible interaction and, based on experimental data, a model of the tomato-aphid molecular interaction was proposed. Considering the rapid advancement of tomato genomics, this information will be important for the development of new protection strategies.

Show MeSH
Related in: MedlinePlus