Resistance to Botrytis cinerea in Solanum lycopersicoides involves widespread transcriptional reprogramming
© Smith et al.; licensee BioMed Central Ltd. 2014
Received: 23 August 2013
Accepted: 25 April 2014
Published: 3 May 2014
Tomato (Solanum lycopersicum), one of the world’s most important vegetable crops, is highly susceptible to necrotrophic fungal pathogens such as Botrytis cinerea and Alternaria solani. Improving resistance through conventional breeding has been hampered by a shortage of resistant germplasm and difficulties in introgressing resistance into elite germplasm without linkage drag. The goal of this study was to explore natural variation among wild Solanum species to identify new sources of resistance to necrotrophic fungi and dissect mechanisms underlying resistance against B. cinerea.
Among eight wild species evaluated for resistance against B. cinerea and A. solani, S. lycopersicoides expressed the highest levels of resistance against both pathogens. Resistance against B. cinerea manifested as containment of pathogen growth. Through next-generation RNA sequencing and de novo assembly of the S. lycopersicoides transcriptome, changes in gene expression were analyzed during pathogen infection. In response to B. cinerea, differentially expressed transcripts grouped into four categories: genes whose expression rapidly increased then rapidly decreased, genes whose expression rapidly increased and plateaued, genes whose expression continually increased, and genes with decreased expression. Homology-based searches also identified a limited number of highly expressed B. cinerea genes. Almost immediately after infection by B. cinerea, S. lycopersicoides suppressed photosynthesis and metabolic processes involved in growth, energy generation, and response to stimuli, and simultaneously induced various defense-related genes, including pathogenesis-related protein 1 (PR1), a beta-1,3-glucanase (glucanase), and a subtilisin-like protease, indicating a shift in priority towards defense. Moreover, cluster analysis revealed novel, uncharacterized genes that may play roles in defense against necrotrophic fungal pathogens in S. lycopersicoides. The expression of orthologous defense-related genes in S. lycopersicum after infection with B. cinerea revealed differences in the onset and intensity of induction, thus illuminating a potential mechanism explaining the increased susceptibility. Additionally, metabolic pathway analyses identified putative defense-related categories of secondary metabolites.
In sum, this study provided insight into resistance against necrotrophic fungal pathogens in the Solanaceae, as well as novel sequence resources for S. lycopersicoides.
KeywordsNecrotrophic pathogenesis Botrydial Phytoalexins
Plant pathogens are classified as necrotrophs, biotrophs, or hemibiotrophs based on their modes of nutrition [1–3]. Biotrophs feed on living tissue and subtly manipulate host physiology to obtain nutrients [1, 2]. Necrotrophs kill host cells to obtain nutrients, often inducing expanding, necrotic lesions [1, 4]. Hemibiotrophs undergo a biotrophic stage of nutrition before shifting to a necrotrophic strategy for nutrient uptake [1, 3]. Due to their fundamentally distinct mechanism of pathogenesis, biotrophs have evolved mechanisms to suppress cell death while necrotrophs promote it as a virulence strategy [5–8]. When hosts fail to constrain necrosis caused by necrotrophs and hemibiotrophs, diseases can culminate in the death and decay of the entire plant. Toxins and hydrolytic enzymes are central to virulence in necrotrophs but have minimal contributions to biotrophic pathogenesis [2, 4, 8]. Consequently, host responses to pathogen infection vary depending on the nature of the pathogen. Whereas the molecular basis of resistance against biotrophic infection strategies is becoming increasingly well understood [9, 10], the current understanding of plant resistance against necrotrophic fungi is fragmentary.
Necrotrophs are classified as either broad host-range or host-specific pathogens . While broad-host-range necrotrophs produce a variety of cell wall-degrading enzymes, phytotoxic metabolites, and cell death elicitors that kill host cells and induce necrosis, the ability of host-specific necrotrophs to cause disease is generally attributed to the production of toxins that have activity on a limited number of related plant species [11, 12]. The broad host-range necrotroph, Botrytis cinerea, is a ubiquitous and cosmopolitan pathogen that causes gray mold disease on more than 200 host plants  with worldwide losses in affected crops estimated at 20% . B. cinerea induces necrosis by producing toxins and reactive oxygen species [15, 16], and also manipulates hosts into producing oxidative bursts that facilitate colonization [17, 18]. Two classes of toxins have been identified in B. cinerea that exhibit non-specific phytotoxicity: the sesquiterpene toxin, botrydial, and related metabolites, and the polyketide toxin, botcinic acid, and its derivatives [15, 19–21]. In contrast to B. cinerea, Alternaria solani primarily infects members of the Solanaceae such as tomato, potato, peppers, and eggplant . Like B. cinerea, A. solani uses toxins to induce necrosis in its hosts . While as many as eleven toxins have been identified in cultures of A. solani, alternaric acid and solanopyrones A, B, and C, have been implicated as the primary necrosis-inducing toxins [22, 24, 25]. Although necrosis of host tissues is known to be induced by toxins, additional, unknown factors may be involved in the host specificity of A. solani.
The Solanaceae is one of the world’s most economically important plant families and includes vegetables, ornamentals, and medicinal plants . Among the solanaceous crops, tomato (Solanum lycopersicum) is particularly susceptible to B. cinerea and A. solani[27, 28]. Due to a lack of genetic resistance against necrotrophic fungal pathogens in commercial tomato cultivars, B. cinerea and A. solani inflict heavy losses, and thus frequent applications of fungicides are required for disease management. In the absence of chemical protection, over 50% of the annual tomato crop can be lost to necrotrophic pathogens . Although tomato lacks resistance to B. cinerea and A. solani, robust resistance against some necrotrophic fungal pathogens has been identified in closely related species within the Solanaceae [30, 31]. However, the underlying mechanisms of resistance have not been characterized at the molecular level, in part due to a lack of molecular resources for many members of the Solanaceae, particularly non-crop species.
Identification and characterization of genetic resistance against necrotrophic fungi would provide a crucial biological foundation for crop improvement within the Solanaceae. The overarching goal of this study was to identify and characterize resistance to necrotrophic fungal pathogens among members of the Solanaceae. To this end, we screened a panel of Solanum species for resistance to B. cinerea and A. solani and found that S. lycopersicoides (LA2951) showed a high level of resistance to both pathogens. This resistance manifested as constrained lesion expansion as well as reduced pathogen growth. Then, we generated gene expression profiles from S. lycopersicoides 24 and 48 hours after inoculation with B. cinerea, as well as a pre-infection baseline, via high-throughput RNA-sequencing (Roche-454). Analyses of the transcriptomes revealed that numerous genes were differentially expressed in S. lycopersicoides in response to B. cinerea, including pathogenesis-related proteins, proteases, a glucanase, and genes involved in biosynthesis of secondary metabolites. Additionally, a set of highly expressed B. cinerea genes was identified, which could facilitate the elucidation of fungal genes involved in necrotrophic pathogenesis.
Evaluation of resistance against necrotrophic fungi among wild Solanum species
Of the eleven lines tested, Solanum lycopersicoides (LA2951) was the most resistant to both B. cinerea and A. solani (Figure 1A, B), suggesting the presence of broad-spectrum resistance to necrotrophs. B. cinerea caused indistinguishably high levels of necrosis in all three S. lycopersicum varieties tested. In contrast, the wild Solanum species showed varying levels of resistance, which manifested as a reduction in lesion diameter compared to the S. lycopersicum varieties. The reduction in lesion diameter ranged from 13% for S. arcanum (LA1708) to 51% for S. lycopersicoides (LA2951). A high level of resistance to B. cinerea was also observed in S. pennellii (LA0716), which showed a 47% reduction in lesion diameter as compared to S. lycopersicum. Interestingly, resistance responses to A. solani followed a different pattern than observed for B. cinerea. Among the eleven lines tested, VF-36 (S. lycopersicum, LA0490) was the most susceptible. The S. lycopersicum varieties were not equally susceptible to A. solani; M-82 and Castlemart II exhibited a 26% and 25% reduction in lesion diameter respectively as compared to VF-36. Among the wild species tested, S. lycopersicoides (LA2951) was the most resistant to A. solani, and appeared to exhibit even higher levels of resistance to A. solani than B. cinerea. In contrast, S. pennellii (LA0716) was only moderately resistant to A. solani but was highly resistant to B. cinerea. Therefore, given the high level of resistance of S. lycopersicoides to both necrotrophic pathogens, this accession was selected to investigate molecular mechanisms of resistance to necrotrophs (Figure 1C, D). B. cinerea was chosen to serve a model necrotroph in this study because it has a sequenced genome , readily sporulates in culture, and causes disease on all tomato varieties tested.
Characterization of resistance against B. cinerea in S. lycopersicoides
To determine whether the smaller lesions on S. lycopersicoides were due primarily to reduced pathogen growth, ergosterol was quantified from S. lycopersicum and S. lycopersicoides leaves inoculated with B. cinerea. Interestingly, fungal growth was not significantly different between S. lycopersicum and S. lycopersicoides 48 h after inoculation (Figure 2C). However, by 72 h after inoculation, the ergosterol content of S. lycopersicum was over twice that of inoculated S. lycopersicoides leaves (Figure 2C). The increased detection of B. cinerea in S. lycopersicum as compared to S. lycopersicoides 72 h after inoculation correlated closely with observed levels of necrosis and indicates that suppression of fungal growth may be a primary component of resistance to B. cinerea in S. lycopersicoides.
De novo assembly of the S. lycopersicoides transcriptome
Summary of Roche 454 GS-FLX assembly of S. lycopersicoides transcriptome sequences
Average read length
Average trimmed read length
Average contig length
Average large contig length
N50 large contig length
Average isotig length
N50 isotig length
The BLASTx algorithm was used to distinguish unigenes of S. lycopercicoides from those of B. cinerea and to remove sequences from contaminating species (e.g. bacteria and viruses). Of the 10,385 unigenes, 382 did not match any sequence in the non-redundant protein sequences database (nr, NCBI) or matched contaminating organisms and were thus excluded from further analyses. Of the remaining 10,003 unigenes, 9,414 (94.1%) had significant matches with sequences from plant species and were thus determined to be S. lyocpersicoides sequences, whereas 589 (5.9%) were determined to be of fungal origin. Among the 9,414 unigenes determined to be of plant origin, nearly 91% (8,566) were highly similar to genes from S. lycopersicum, which has a sequenced reference genome , and an additional 5% (466) were highly similar to genes from other species of Solanaceae, including S. tuberosum, Nicotiana tobacum, and Capsicum annuum. The remaining 4% (382) of S. lycopersicoides unigenes were most similar to sequences found in comparatively distant plant species, including A. thaliana, Medicago truncatula, and Populus trichocarpa. The high percentage of S. lycopersicoides unigenes matching sequences from other members of the Solanaceae validates the de novo assembly of the S. lycopersicoides transcriptome and indicates high levels of sequence conservation between S. lycopersicoides and related species.
Cluster analyses reveal distinct patterns of gene expression in response to B. cinerea
GO slim analyses revealed many similarities between clusters 1 and 2. The major GO slim terms for biological processes associated with cluster 1 were “transport”, “generation of precursor metabolites and energy”, and “response to stress” (Figure 3B), and the major GO slim terms for molecular function were “nucleotide binding” and “hydrolase activity” (Figure 3C). The major GO slim terms for cellular component were “chloroplast”, “mitochondrion”, and “plasma membrane” (Figure 3D). Similar to cluster 1, the major GO slim terms for biological processes associated with cluster 2 were “transport”, “response to stress”, and “generation of precursor metabolites and energy” (Figure 4B), and the major GO slim terms for molecular function were “protein binding”, “hydrolase activity”, and “nucleotide binding” (Figure 4C). The major GO slim terms for cellular component were “mitochondrion”, “chloroplast”, and “plasma membrane” (Figure 4D). The similarities between biological processes, molecular functions, and cellular components for clusters 1 and 2 suggest that these two groups of genes are involved in similar responses to B. cinerea.
For cluster 3, GO slim terms were substantially different than clusters 1, 2, or 4. Specifically, the major GO slim terms for biological processes associated with cluster 3 were “response to stress”, “protein metabolic process”, “signal transduction”, and “electron transport” (Figure 5B), and the major GO slim terms for molecular function were “hydrolase activity”, “protein binding”, and “nucleotide binding” (Figure 5C). The major GO slim terms for cellular component were “nucleus”, “extracellular region”, and “mitochondrion” (Figure 5D). The induction of cluster 3 genes after pathogen attack is consistent with induced defense responses, however, the substantial differences in major GO slim terms in cluster 3 as compared to clusters 1 and 2 may reflect distinctly separate mechanisms of defense.
Cluster 4 contained the most pronounced differences in GO slim terms among the four clusters. The major GO slim terms for biological processes associated with this cluster were “protein metabolic process”, “generation of precursor metabolites and energy”, “transport”, and “response to stress” (Figure 6B), and the major GO slim terms for molecular function were “hydrolase activity” and “nucleotide binding” (Figure 6C). The major GO slim term for cellular component was “chloroplast” (Figure 6D). Overall, these results strongly suggest a rapid and intense suppression of primary metabolism upon challenge with B. cinerea, presumably due to resource reallocation to defense responses.
Comparative expression analysis of selected genes in S. lycopersicoides and S. lycopersicum
Metabolic pathway analysis
For metabolic pathway mapping, KEGG (Kyoto Encyclopedia of Genes and Genomes) orthology (KO) identifiers were assigned throughout the four differentially expressed clusters of S. lycopersicoides genes which were then mapped individually to pathway maps in the KEGG database. This process identified potential shunts in metabolism resulting from B. cinerea infection, the most striking example of which was in the pathway for terpenoid backbone biosynthesis (Additional file 2). Specifically, several genes in the 2-C-methyl-D-erythritol 4-phosphate (MEP) pathway were suppressed in response to B. cinerea, while genes in the mevalonate pathway were induced. The mevalonate pathway is used by plants for the biosynthesis of sesquiterpene phytoalexins [48–50], while the MEP pathway is localized in plastids and is the pathway for the production of structurally distinct terpenoids including carotenoids and the phytol chain of chlorophyll . Recently, the MEP pathway was also implicated in stress response [51, 52]. The MEP pathway acts as stress sensor and, through the biosynthesis of retrograde signaling molecules, an inducer of stress response genes. However, accumulation of methylerythritol cyclodiphosphate (MEcPP), a stress-induced, retrograde signaling molecule produced via the MEP pathway, is associated with abiotic stress and results in increased resistance to biotrophs and enhanced susceptibility to B. cinerea. Thus, the coordinated change in gene expression from the MEP pathway to the mevalonate pathway, in S. lycopersicoides during defense against B. cinerea, is consistent with a shift away from abiotic stress response and biotrophic pathogen resistance and with the increased phytoalexin biosynthesis observed in other solanaceous plants [48, 53].
Identification of B. cinerea genes highly expressed during infection
For each B. cinerea gene identified, expression profiles were analyzed throughout the infection time course. Very few sequences from B. cinerea were detected at the 0 h time point (immediately after inoculation with fungal conidia), and thus expression of all fungal unigenes were significantly higher at 24 and 48 h after inoculation. Interestingly, genes implicated in pathogenesis and necrosis were abundantly expressed 24 and 48 h after inoculation, such as genes encoding an endopolygalacturonase (Bcpg1) demonstrated to play a role in virulence on tomato [4, 54], a superoxide dismutase (bcsod1) required for lesion expansion on Phaseolus vulgaris, and two cytochrome p450 monooxygenases (BcBOT1 and BcBOT2) required for biosynthesis of the phytotoxin, botrydial [56, 57] (Additional file 3). The observed induction patterns of toxin biosynthetic genes, genes encoding cell wall degrading enzymes, and genes involved in scavenging reactive oxygen species indicate that B. cinerea actively induces necrosis in its host as early as 24 h after contact. In addition to genes involved in disease development, genes related to growth and energy production were among the most highly expressed in B. cinerea during pathogenesis, such as elongation factor 1 alpha and glyceraldehyde 3-phosphate dehydrogenase (Additional file 3). Although the primary objective of this study was to generate a sequence-based resource to identify genes in S. lycopersicoides involved in resistance to B. cinerea, the dataset created could assist efforts to identify novel genes in B. cinerea involved in early stages of infection.
Previous research has demonstrated that S. lycopersicoides is tolerant to abiotic stresses such as cold injury and nutrient deficiency, and is simultaneously resistant to diverse pathogens that are problematic on tomato, including viruses (tomato mosaic virus and cucumber mosaic virus), oomycetes (Phytophthora parasitica), and fungi (Cladosporium fulvum and Botrytis cinerea) [30, 31, 58]. In this study, S. lycopersicoides was confirmed to express resistance against B. cinerea, and newly found to be resistant to A. solani. S. lycopersicoides is a wild solanaceous species native to the Andean region of Chile and Peru, which is the center of diversity for many Solanum species [31, 58], and thus has likely evolved robust resistance responses to broad-range and host-specific necrotrophic fungal pathogens. Because S. lycopersicoides is closely related to and can be crossed with tomato , introgression lines have been created in which chromosomal segments from S. lycopersicoides have been incorporated into the genome of cultivated tomato . Introgression lines provide a powerful resource for future determination of genes conferring resistance to B. cinerea and/or A. solani. Thus, genetic compatibility with cultivated tomato, a high level of resistance to necrotrophs, and availability of genetic resources make S. lycopersicoides an ideal source of novel genes to be harnessed through transgenic or conventional breeding techniques to improve the resistance of tomato to necrotrophic pathogens. By sequencing the transcriptome of S. lycopersicoides during early infection by B. cinerea, this work provides a novel and important resource for future work.
The molecular basis of resistance against B. cinerea and A. solani is not known. In general, plant resistance mechanisms to necrotrophic pathogens are believed to be distinct from or antagonistic to plant responses to biotrophs, which is consistent with their contrasting pathogenesis strategies [7, 8, 11]. Multiple examples signify differences in host resistance to these groups of pathogens [7, 59]. R-gene mediated resistance (e.g., effector triggered immunity, ETI) is normally activated upon recognition of race specific effector proteins by R-proteins and confers resistance to biotrophic pathogens . ETI is a widespread and strong form of resistance but is not known to be effective against necrotrophs. Indeed, R-gene mediated susceptibility to necrotrophs has been documented [60–62]. The major manifestation of ETI is often the hypersensitive response (HR), a form of cell death, is central to plant resistance to biotrophs but promotes susceptibility to necrotrophs . Production of reactive oxygen species (ROS) orchestrates HR and modulates resistance to biotrophs but may act as a virulence factor in some necrotrophs such as B. cinerea. The signaling molecule salicylic acid (SA) promotes resistance to biotrophs but actually suppresses defense against necrotrophs [64, 65]. Systemic acquired resistance (SAR) is an SA-dependent resistance response that protects plants against many biotrophic pathogens [66–70] whereas its efficacy in conferring resistance to necrotrophs is unclear. Arabidopsis mutants impaired in SAR show normal resistance to necrotrophic fungi , whereas mutants that constitutively express SAR are more susceptible [71, 72]. Systemic and local defenses mediated by ethylene (ET) and jasmonate (JA) are required for resistance to necrotrophic pathogens [67, 73], whereas SA is generally associated with resistance to biotrophic infection [66, 69, 74, 75]. Although the scientific literature is replete with examples of antagonistic interactions between pathways mediated by SA and JA/ET in Arabidopsis, such interactions are not studied in other plant systems including tomato [7, 76–78]. These and many other examples suggest defense strategies that have evolved to guard plants against necrotrophs that operate distinctly or by antagonizing other responses.
The regulatory mechanism involved in host responses to broad-host necrotrophs such as B. cinerea is slowly emerging, predominantly from studies in Arabidopsis, but also to a limited extent in tomato. Diverse and unique processes that specifically mediate basal resistance to necrotrophs without any effect on biotrophic pathogens have been described. The tomato TPK1b and AIM1 function in defense against necrotrophic fungi with no role in resistance to other obligate or biotrophic pathogens [79, 80]. TPK1b function in defense is through modulation of ET signaling while AIM1 functions in ABA dependent immune responses. Many transcription-factors (TFs) that mediate defense response to necrotrophic infection have been identified through microarray and genetic analysis . Among these, WRKY33, ZFAR1, ERF1 and ERF104, MYB, AS1, and HD-Zip homeodomain proteins are required for resistance to necrotrophic fungi, underlining the importance of transcriptional regulation in defense to these pathogens [46, 81–86]. The role of transcriptional regulation is further reinforced by the recent discovery of the immune response functions of subunits of the transcriptional coactivator Mediator complex as specific regulators of plant immune responses to necrotrophs [87, 88]. Genetic evidence linking chromatin modifications such as histone ubiquitination, methylation, and deacetylation and chromatin remodeling to defense responses to necrotrophs due to their effects on expression of genes encoding various plant defense responses have been established [88–91]. Components of the plant cell wall and cuticle, predominantly considered physical barriers to infection, have found new and unexpected defense roles with mutants harboring defects in cuticle and cell wall components becoming more resistant to necrotrophs, thus revealing the dependence of virulence in necrotrophic fungi on critical host components [78, 92–96].
While the mechanisms of resistance to necrotrophic fungal pathogens are not fully understood, the ability of S. lycopersicoides to rapidly shift metabolism from photosynthesis to the production of resistance associated proteins and secondary metabolites appears to be a key factor for resistance to B. cinerea. Several classes of genes including pathogenesis related protein genes (PR1), protease genes (subtilisin) and glucanase genes (beta-1,3-glucanase) are rapidly and strongly induced in S. lycopersicoides in response to B. cinerea infection. However, this increased expression of defense related genes coincides with a reduced expression of genes involved in photorespiration such as ribulose-1,5-bisphosphate carboxylase and glycolate oxidase. This metabolic shunt occurs in S. lycopersicum as well as S. lycopersicoides, but at a slower rate and to less dramatic levels. Furthermore, metabolic pathway analysis in S. lycopersicoides demonstrates a shift within terpenoid biosynthesis away from the plastidic MEP pathway involved in pigment biosynthesis  to the mevalonate pathway involved in the synthesis of phytoalexins . Taken together, these results point to a global change in metabolism that allows S. lycopersicoides to more effectively react to infection by necrotrophs.
In addition to identifying genes and metabolic changes associated with resistance to necrotrophs, this research has uncovered a number of fungal genes that are highly expressed during the early stages of infection of S. lycopersicoides. Several highly expressed genes, such as elongation factor 1 alpha and glyceraldehyde 3-phosphate dehydrogenase, are not surprising due to their fundamental roles in fungal growth. However, several genes coding hydrolytic enzymes, including an endo-polygalacturonase and an aspartic protease, as well as other genes, such as a cytochrome p450 monooxygenase required for the biosynthesis of phytotoxic secondary metabolites, were also induced. These findings demonstrate the potential value of the transcriptomic data generated in this research for identifying novel genes required for necrotrophy.
Another distinct value of this RNA-seq dataset is that it represents the first large-scale public sequence resource for S. lycopersicoides. Analogous to an EST sequencing experiment before the advent of next-generation sequencing, this study provides a dataset of species-specific sequence data for future validation of genome sequencing and identification of genes (based on homology as well as expression pattern) for functional characterization. Prior to this study, little information was available regarding molecular mechanisms of resistance in S. lycopersicoides. Based on the analyses of fungal growth and changes in host gene expression during the resistance response, a key mechanism of resistance appears to be constraining the growth of the pathogen through rapid and extensive reprogramming of the S. lycopersicoides transcriptome. In this study, numerous candidate defense-related genes were identified through clustering analyses; extensive functional characterization will be required to determine the genetic regulatory network underlying resistance.
It is important to note that RNA samples were pooled prior to sequencing in our approach, and thus the expression values obtained from sequencing the S. lycopersicoides transcriptome are indicative of qualitative trends in expression rather than exact quantitative measures of gene expression. Replicates were pooled to maximize the number of biological conditions evaluated within the experiment, and clustering analyses were performed to assess changes in expression. Sequencing separate replicates would have provided certain advantages, particularly with respect to calculating more precise digital expression values with greater rigor. However, pooled RNA samples are inherently normalized; expression is averaged among individuals, and thus this approach reduces the impact of isolated variability among individuals within a treatment. Similarly, pooled samples have proven useful to analyze differential expression in various other systems, including plants , animals [100, 101], and fungi [102, 103].
Research into mechanisms of plant resistance to necrotrophic fungal pathogens has been generally limited. A majority of studies, to date, have focused on Arabidopsis. Tomato, as a model for studying necrotrophic interactions, has been problematic due to the universal susceptibility of all tested varieties to important necrotrophs including B. cinerea. However, the availability of a resistant species that can be crossed with tomato provides a unique opportunity to study plant/necrotroph interactions in a commercially important crop species. Furthermore, the availability of this transcriptome data could be effectively used in conjunction with existing tomato lines containing defined introgressions of S. lycopersicoides chromosomal segments to identify features of the S. lycopersicoides genome that are crucial for resistance to necrotrophs.
Tomato (Solanum lycopersicum), one of the world’s most important vegetable crops, is highly susceptible to necrotrophic fungal pathogens such as Botrytis cinerea and Alternaria solani. Improving resistance through conventional breeding has been hampered by a shortage of resistant germplasm and difficulties in introgressing resistance into elite germplasm without linkage drag. Screening of wild Solanum species uncovered a relative of tomato, S. lycopersicoides, that is resistant to both B. cinerea and A. solani. Transcriptome analysis of S. lycopersicoides at 0, 24, and 48 hours after inoculation with B. cinerea revealed possible mechanisms for resistance to necrotrophs and identified genes from B. cinerea that are induced during pathogenesis. Taken together, this research provides new insight into resistance to necrotrophs while providing a novel sequence resource for S. lycopersicoides.
Plant materials and fungal isolates
Accessions: LA0490 (S. lycopersicum, VF-36), LA2951 (S. lycopersicoides), LA3475 (S. lycopersicum, M-82), LA1932 (S. chilense), LA1708 (S. arcanum), LA1589 (S. pimpinellifolium), LA0716 (S. pennellii), LA0317 (S. galapagense), LA1777 (S. habrochaites), and LA1223 (S. habrochaites f. glabratum, Chimbalo) were developed by and/or obtained from the UC Davis/C.M. Rick Tomato Genetics Resource Center and maintained by the Department of Plant Sciences, University of California, Davis, CA 95616. S. lycopersicum cv. Bradley was obtained from the New England Seed Company (http://www.neseed.com/); Hartford, CT 06120). S. lycopersicum cv. Castlemart II was kindly provided by Greg Howe (Michigan State University). B. cinerea (B05.10) was maintained on 2xV8 agar in the dark at 25°C and A. solani (AR18, isolated from tomato in Arkansas) was maintained on V8 agar.
Wild relatives of tomato and tomato cultivars were evaluated for their resistance to B. cinerea and A. solani by inoculating detached leaves. Inoculum of B. cinerea was prepared by cutting blocks of agar from 10-day-old cultures and agitating in 1% Sabouraud maltose broth (SMB). Conidia were separated from agar and mycelium by filtration through sterile cheesecloth. The spore concentration was checked with a hemacytometer and adjusted to 5×105/ml with SMB. Detached leaves of S. lycopersicum and S. lycopersicoides (4 each per time point) were inoculated with 8 drops (5 μl each) of the B. cinerea spore suspension and placed on sterile filter paper moistened with sterile H2O in a covered petri dish. Inoculated leaves were incubated in a growth chamber with a 12/12 light/dark cycle at 21°C day and 18°C night temperatures. Lesion diameters were measured daily and a subset of leaves was collected each day for RNA extraction and ergosterol analysis. Due to low sporulation of the pathogen, mycelial fragments of A. solani at a concentration of 400 mg/mL was used for drop inoculation; otherwise conditions were similar to those described for B. cinerea.
Quantification of ergosterol by HPLC
Inoculated leaves were frozen in liquid nitrogen and ground to a fine powder with a mortar and pestle. Ergosterol was then extracted from ground leaf tissue (150–550 mg) and analyzed by high pressure liquid chromatography as described by de Sio et al.  with minor adjustments. Briefly, ground leaves were added to 2.0 ml of 2:1 chloroform:methanol and extracted overnight. The extract was filtered through a 0.2 μm filter and 20 μl was injected onto a 25 mm C18 column (phenomenex, Torrance, CA). The mobile phase consisted of 80% methanol in H2O (solvent A) and 100% dichloromethane (solvent B). The gradient program consisted of a linear increase from 0% to 50% solvent B over 20 minutes followed by 15 minutes at 50% solvent B. Ergosterol was measured based on absorbance at 282 nm and was quantified based on comparison of peak area to pure standards (Alfa Aesar, Ward Hill, MA). Ergosterol concentration was then normalized to the mass of the extracted tissue and leaf mass.
RNA extraction and cDNA synthesis
Inoculated leaves were frozen in liquid nitrogen and ground with a mortar and pestle. Total RNA was extracted from the ground tissue with TRIzol Reagent (Life Technologies, Grand Island, NY) according to the manufacturer’s instructions. RNA quantity and quality was determined with a NanoDrop spectrophotometer (Thermo Scientific, Wilmington, DE) and by visual inspection after electrophoresis. A total of 1 μg of RNA from each sample was treated with RQ1 DNase (Promega, Madison, WI) according to the manufacturer’s instructions. The DNase treated RNA (1 μg) was used as template to generate cDNA with M-MLV Reverse Transcriptase (Promega, Madison, WI) according to the manufacturer’s instructions.
454 sequencing and data processing
For transcriptome sequencing, S. lycopersicoides plants were spray inoculated with spores of B. cinerea at a concentration of 3×105/ml. Total RNA was collected from inoculated leaves from 2 plants per time point at 0 hours, 24 hours, and 48 hours after inoculation. RNA from replicate leaf samples was pooled prior to sequencing. Conceptually, RNA pooling was performed as described by TJ Huth and SP Place , PA Olsvik, V Vikeså, KK Lie and EM Hevrøy  Library construction, sequencing, and de novo assembly were performed by the Purdue Genomics Core Facility (West Lafayette, IN). Read counts at each time point from individual isotigs within an isogroup were summed to reduce overrepresentation of genes with multiple splice variants. To identify unigenes from S. lycopersicoides and B. cinerea, as well as to remove contaminating sequences, Blast2GO (version 2.6.6)  was used to query the assembled unigenes against the nr database. The Audic and Claverie method  was used to identify plant unigenes that were differentially expressed between 0, 24, and 48 hours after inoculation with a false discovery rate of <0.0033. K-means clustering was performed on the differentially expressed plant genes with the genesis software (version 1.7.6) . For K-means clustering, unigenes were assigned to one of four clusters. The basis for choosing four clusters was the closeness of fit of unigenes within each cluster, as well as the biological relevance of the expression patterns observed for each cluster. Blast2GO was used to functionally characterize unigenes within each plant cluster, as well as all fungal unigenes. InterProScan  was used to annotate unigenes with conserved protein domains. To identify GO terms that were enriched within each plant cluster, the Audic and Claverie method  was applied to all GO terms identified in all plant clusters. To make the number of GO terms associated with each cluster more manageable, GO slim analysis was performed with The Arabidopsis Information Resource (TAIR) GO slim for plants, while the Generic GO slim was applied to fungal unigenes.
Analysis of gene expression with qPCR
cDNA from S. lycopersicum and S. lycopersicoides obtained immediately after (0 hours after inoculation), 24 hours after, or 48 hours after inoculation with B. cinerea was used as template for qPCR. qPCR was performed by combining SYBR green master mix (Life Technologies, Grand Island, NY) with primers (Additional file 4) and template according to the manufacturers instructions and monitoring fluorescence during template amplification in a stratagene M×300 P real-time PCR system (Agilent Technologies, Inc., Santa Clara, CA). The mean gene expression of three technical replications was normalized to expression of beta tubulin and calculated, relative to expression at 0 hours after inoculation, with the 2-ΔΔCT method .
Metabolic pathway analysis
Plant unigenes in each cluster were analyzed with the KEGG Automatic Annotation Server (KAAS)  to detect KEGG Orthologs (KO). KOs from clusters 1, 2, and 3 were combined into a single cluster representing up-regulated genes, while cluster 4 was kept separate to represent down-regulated genes. The KEGG Mapper – Reconstruct Pathway tool was then used to highlight genes within KEGG pathways that were up- or down-regulated in response to B.cinerea.
Availability of supporting data
The 454 reads for S. lycopersicoides inoculated with B. cinerea have been submitted to NCBI sequence read archive (SRA, http://www.ncbi.nlm.nih.gov/sra) under the accession number SRR1054293.
The authors would like to thank Jason Tipton for assistance with data analysis, and John Ridenour and Sandeep M.T. Sharma for careful review of the manuscript. This work was supported by the University of Arkansas Division of Agriculture funding to BHB and by Binational Agricultural Development Fund (BARD) funding to TM.
- Divon HH, Fluhr R: Nutrition acquisition strategies during fungal infection of plants. FEMS Microbiol Lett. 2007, 266 (1): 65-74. 10.1111/j.1574-6968.2006.00504.x.PubMedGoogle Scholar
- Mendgen K, Hahn M: Plant infection and the establishment of fungal biotrophy. Trends Plant Sci. 2002, 7 (8): 352-356. 10.1016/S1360-1385(02)02297-5.PubMedGoogle Scholar
- Perfect SE, Green JR: Infection structures of biotrophic and hemibiotrophic fungal plant pathogens. Mol Plant Pathol. 2001, 2 (2): 101-108. 10.1046/j.1364-3703.2001.00055.x.PubMedGoogle Scholar
- van Kan JAL: Licensed to kill: the lifestyle of a necrotrophic plant pathogen. Trends Plant Sci. 2006, 11 (5): 247-253. 10.1016/j.tplants.2006.03.005.PubMedGoogle Scholar
- Greenberg JT: Programmed cell death in plant-pathogen interactions. Annu Rev Plant Physiol Plant Mol Biol. 1997, 48: 525-545. 10.1146/annurev.arplant.48.1.525.PubMedGoogle Scholar
- Govrin EM, Levine A: The hypersensitive response facilitates plant infection by the necrotrophic pathogen Botrytis cinerea. Curr Biol. 2000, 10 (13): 751-757. 10.1016/S0960-9822(00)00560-1.PubMedGoogle Scholar
- Glazebrook J: Contrasting mechanisms of defense against biotrophic and necrotrophic pathogens. Annu Rev Phytopathol. 2005, 43: 205-227. 10.1146/annurev.phyto.43.040204.135923.PubMedGoogle Scholar
- Mengiste T: Plant Immunity to Necrotrophs. Annu Rev Phytopathol. 2012, 50: 267-294. 10.1146/annurev-phyto-081211-172955.PubMedGoogle Scholar
- Schulze-Lefert P, Panstruga R: Establishment of biotrophy by parasitic fungi and reprogramming of host cells for disease resistance. Annu Rev Phytopathol. 2003, 41: 641-667. 10.1146/annurev.phyto.41.061002.083300.PubMedGoogle Scholar
- Dodds PN, Rafiqi M, Gan PHP, Hardham AR, Jones DA, Ellis JG: Effectors of biotrophic fungi and oomycetes: pathogenicity factors and triggers of host resistance. New Phytol. 2009, 183 (4): 993-999. 10.1111/j.1469-8137.2009.02922.x.PubMedGoogle Scholar
- Laluk K, Mengiste T: Necrotroph attacks on plants: wanton destruction or covert extortion?. Arabidopsis Book. 2010, 8: e0136-PubMed CentralPubMedGoogle Scholar
- Friesen TL, Faris JD, Solomon PS, Oliver RP: Host-specific toxins: effectors of necrotrophic pathogenicity. Cell Microbiol. 2008, 10 (7): 1421-1428. 10.1111/j.1462-5822.2008.01153.x.PubMedGoogle Scholar
- Jarvis WR: Botryotinia and Botrytis species: taxonomy, physiology, and pathogenicity. Monograph, Research Branch Canada Department of Agriculture. 1977Google Scholar
- Genescope. http://www.cns.fr/spip/Botrytis-cinerea-estimated-losses.html,
- Colmenares AJ, Aleu J, Duran-Patron R, Collado IG, Hernandez-Galan R: The putative role of botrydial and related metabolites in the infection mechanism of Botrytis cinerea. J Chem Ecol. 2002, 28 (5): 997-1005. 10.1023/A:1015209817830.PubMedGoogle Scholar
- Cutler HG, Parker SR, Ross SA, Crumley FG, Schreiner PR: Homobotcinolide: a biologically active natural homolog of botcinolide from Botrytis cinerea. Biosci Biotechnol Biochem. 1996, 60 (4): 656-658. 10.1271/bbb.60.656.PubMedGoogle Scholar
- Choquer M, Fournier E, Kunz C, Levis C, Pradier J-M, Simon A, Viaud M: Botrytis cinerea virulence factors: new insights into a necrotrophic and polyphageous pathogen. FEMS Microbiol Lett. 2007, 277 (1): 1-10. 10.1111/j.1574-6968.2007.00930.x.PubMedGoogle Scholar
- Williamson B, Tudzynski B, Tudzynski P, Van Kan JAL: Botrytis cinerea: the cause of grey mould disease. Mol Plant Pathol. 2007, 8 (5): 561-580. 10.1111/j.1364-3703.2007.00417.x.PubMedGoogle Scholar
- Tani H, Koshino H, Sakuno E, Nakajima H: Botcinins A, B, C, and D, metabolites produced by Botrytis cinerea, and their antifungal activity against Magnaporthe grisea, a pathogen of rice blast disease. J Nat Prod. 2005, 68 (12): 1768-1772. 10.1021/np0503855.PubMedGoogle Scholar
- Tani H, Koshino H, Sakuno E, Cutler HG, Nakajima H: Botcinins E and F and botcinolide from Botrytis cinerea and structural revision of botcinolides. J Nat Prod. 2006, 69 (4): 722-725. 10.1021/np060071x.PubMedGoogle Scholar
- Dalmais B, Schumacher J, Moraga J, Le Pecheur P, Tudzynski B, Gonzalez Collado I, Viaud M: The Botrytis cinerea phytotoxin botcinic acid requires two polyketide synthases for production and has a redundant role in virulence with botrydial. Mol Plant Pathol. 2011, 12 (6): 564-579. 10.1111/j.1364-3703.2010.00692.x.PubMedGoogle Scholar
- Shahbazi H, Aminian H, Sahebani N, Halterman D: Effect of Alternaria solani exudates on resistant and susceptible potato cultivars from two different pathogen isolates. Plant Pathol J. 2011, 27 (1): 14-19. 10.5423/PPJ.2011.27.1.014.Google Scholar
- Pound GS, Stahmann MA: The production of a toxic material by Alternaria solani and its relation to the early blight disease of tomato. Phytopathology. 1951, 41: 1104-1114.Google Scholar
- Langsdorf G, Furuichi N, Doke N, Nishimura S: Investigations on Alternaria solani infections: detection of alternaric acid and a susceptibility-inducing factor in the spore-germination fluid of A. solani. J Phytopathol. 1990, 128 (4): 271-282. 10.1111/j.1439-0434.1990.tb04274.x.Google Scholar
- Ichihara A, Sakamura S, Tazaki H: Solanapyrones A, B and C, phytotoxic metabolites from the fungus Alternaria solani. Tetrahedron Lett. 1983, 24 (48): 5373-5376. 10.1016/S0040-4039(00)87872-7.Google Scholar
- Rigano MM, De Guzman G, Walmsley AM, Frusciante L, Barone A: Production of pharmaceutical proteins in solanaceae food crops. Int J Mol Sci. 2013, 14 (2): 2753-2773. 10.3390/ijms14022753.PubMed CentralPubMedGoogle Scholar
- ten Have A, van Berloo R, Lindhout P, van Kan JAL: Partial stem and leaf resistance against the fungal pathogen Botrytis cinerea in wild relatives of tomato. Eur J Plant Pathol. 2007, 117 (2): 153-166. 10.1007/s10658-006-9081-9.Google Scholar
- Chaerani R, Groenwold R, Stam P, Voorrips RE: Assessment of early blight (Alternaria solani) resistance in tomato using a droplet inoculation method. J Gen Plant Pathol. 2007, 73 (2): 96-103. 10.1007/s10327-006-0337-1.Google Scholar
- Gianessi L, Reigner N: The importance of fungicides in U.S. crop production. Outlooks on Pest Management. 2006, 17 (5): 209-213. 10.1564/17oct06.Google Scholar
- Guimaraes RL, Chetelat RT, Stotz HU: Resistance to Botrytis cinerea in Solanum lycopersicoides is dominant in hybrids with tomato, and involves induced hyphal death. Eur J Plant Pathol. 2004, 110 (1): 13-23.Google Scholar
- Chetelat RT, Cisneros P, Stamova L, Rick CM: A male-fertile Lycopersicon esculentum x Solanum lycopersicoides hybrid enables direct backcrossing to tomato at the diploid level. Euphytica. 1997, 95 (1): 99-108. 10.1023/A:1002958030799.Google Scholar
- Finkers R, Bai Y, Berg P, Berloo R, Meijer-Dekens F, Have A, Kan J, Lindhout P, Heusden A: Quantitative resistance to Botrytis cinerea from Solanum neorickii. Euphytica. 2008, 159 (1/2): 83-92.Google Scholar
- Egashira H, Kuwashima A, Ishiguro H, Fukushima K, Kaya T, Imanishi S: Screening of wild accessions resistant to grey mold (Botrytis cinerea Pers.) in Lycopersicon. Acta Physiol Plant. 2000, 22 (3): 324-326. 10.1007/s11738-000-0046-x.Google Scholar
- Canady MA, Meglic V, Chetelat RT: A library of Solanum lycopersicoides introgression lines in cultivated tomato. Genome. 2005, 48 (4): 685-697. 10.1139/g05-032.PubMedGoogle Scholar
- Eshed Y, Zamir D: An introgression line population of Lycopersicon pennellii in the cultivated tomato enables the identification and fine mapping of yield-associated QTL. Genetics. 1995, 141 (3): 1147-1162.PubMed CentralPubMedGoogle Scholar
- Blanca J, Cañzares J, Cordero L, Pascual L, Diez MJ, Nuez F: Variation revealed by SNP genotyping and morphology provides insight into the origin of the tomato. PLoS One. 2012, 7 (10): 1-17.Google Scholar
- Amselem J, Cuomo CA, van Kan JAL, Viaud M, Benito EP, Couloux A, Coutinho PM, de Vries RP, Dyer PS, Fillinger S, Fournier E, Gout L, Hahn M, Kohn L, Lapalu N, Plummer KM, Pradier J-M, Quévillon E, Sharon A, Simon A, ten Have A, Tudzynski B, Tudzynski P, Wincker P, Andrew M, Anthouard V, Beever RE, Beffa R, Benoit I, Bouzid O: Genomic analysis of the necrotrophic fungal pathogens Sclerotinia sclerotiorum and Botrytis cinerea. PLoS Genet. 2011, 7 (8): e1002230-e1002230. 10.1371/journal.pgen.1002230.PubMed CentralPubMedGoogle Scholar
- Sato S, Tabata S, Hirakawa H, Asamizu E, Shirasawa K, Isobe S, Kaneko T, Nakamura Y, Shibata D, Aoki K, Egholm M, Knight J, Bogden R, Li C, Shuang Y, Xu X, Pan S, Cheng S, Liu X, Ren Y, Wang J, Albiero A, Dal Pero F, Todesco S, Van Eck J, Buels RM, Bombarely A, Gosselin JR, Huang M, Leto JA: The tomato genome sequence provides insights into fleshy fruit evolution. Nature. 2012, 485 (7400): 635-641. 10.1038/nature11119.Google Scholar
- Camon E, Magrane M, Barrell D, Lee V, Dimmer E, Maslen J, Binns D, Harte N, Lopez R, Apweiler R: The Gene Ontology Annotation (GOA) database: sharing knowledge in uniprot with gene ontology. Nucleic Acids Res. 2004, 32 (Database issue): D262-D266.PubMed CentralPubMedGoogle Scholar
- Windram O, Madhou P, McHattie S, Hill C, Hickman R, Cooke E, Jenkins DJ, Penfold CA, Baxter L, Breeze E, Kiddle SJ, Rhodes J, Atwell S, Kliebenstein DJ, Kim Y-S, Stegle O, Borgwardt K, Zhang C, Tabrett A, Legaie R, Moore J, Finkenstadt B, Wild DL, Mead A, Rand D, Beynon J, Ott S, Buchanan-Wollaston V, Denby KJ: Arabidopsis defense against Botrytis cinerea: chronology and regulation deciphered by high-resolution temporal transcriptomic analysis. Plant Cell. 2012, 24 (9): 3530-3557. 10.1105/tpc.112.102046.PubMed CentralPubMedGoogle Scholar
- De Cremer K, Mathys J, Vos C, Froenicke L, Michelmore RW, Cammue BPA, De Coninck B: RNAseq-based transcriptome analysis of Lactuca sativa infected by the fungal necrotroph Botrytis cinerea. Plant Cell Environ. 2013, 36 (11): 1992-2007.PubMedGoogle Scholar
- Berger S, Papadopoulos M, Schreiber U, Kaiser W, Roitsch T: Complex regulation of gene expression, photosynthesis and sugar levels by pathogen infection in tomato. Physiol Plant. 2004, 122 (4): 419-428. 10.1111/j.1399-3054.2004.00433.x.Google Scholar
- Sánchez-Vallet A, López G, Ramos B, Delgado-Cerezo M, Riviere M-P, Llorente F, Fernández PV, Miedes E, Estevez JM, Grant M, Molina A: Disruption of abscisic acid signaling constitutively activates Arabidopsis resistance to the necrotrophic fungus Plectosphaerella cucumerina. Plant Physiol. 2012, 160 (4): 2109-2124. 10.1104/pp.112.200154.PubMed CentralPubMedGoogle Scholar
- Loon LC, Rep M, Pieterse CMJ: Significance of inducible defense-related proteins in infected plants. Annu Rev Phytopathol. 2006, 44: 135-162. 10.1146/annurev.phyto.44.070505.143425.PubMedGoogle Scholar
- Kamoun S: A catalogue of the effector secretome of plant pathogenic oomycetes. Annu Rev Phytopathol. 2006, 44: 41-60. 10.1146/annurev.phyto.44.070505.143436.PubMedGoogle Scholar
- AbuQamar S, Chen X, Dhawan R, Bluhm B, Salmeron J, Lam S, Dietrich RA, Mengiste T: Expression profiling and mutant analysis reveals complex regulatory networks involved in Arabidopsis response to Botrytis infection. Plant J. 2006, 48 (1): 28-44. 10.1111/j.1365-313X.2006.02849.x.PubMedGoogle Scholar
- Marrs KA: The functions and regulation of glutathione S-transferases in plants. Annu Rev Plant Physiol Plant Mol Biol. 1996, 47: 127-158. 10.1146/annurev.arplant.47.1.127.PubMedGoogle Scholar
- Bianchini GM, Paiva NL, Stermer BA: Induction of early mevalonate pathway enzymes and biosynthesis of end products in potato (Solanum tuberosum) tubers by wounding and elicitation. Phytochemistry. 1996, 42 (6): 1563-1571. 10.1016/0031-9422(96)00139-2.Google Scholar
- Ha SH, Kim JB, Hwang YS, Lee SW: Molecular characterization of three 3-hydroxy-3-methylglutaryl-CoA reductase genes including pathogen-induced Hmg2 from pepper (Capsicum annuum). Biochim Biophys Acta. 2003, 1625 (3): 253-260. 10.1016/S0167-4781(02)00624-3.PubMedGoogle Scholar
- Dubey VS, Bhalla R, Luthra R: An overview of the non-mevalonate pathway for terpenoid biosynthesis in plants. J Biosci. 2003, 28 (5): 637-646. 10.1007/BF02703339.PubMedGoogle Scholar
- Xiao Y, Savchenko T, Baidoo EEK, Chehab WE, Hayden DM, Tolstikov V, Corwin JA, Kliebenstein DJ, Keasling JD, Dehesh K: Retrograde signaling by the plastidial metabolite MEcPP regulates expression of nuclear stress-response genes. Cell. 2012, 149 (7): 1525-1535. 10.1016/j.cell.2012.04.038.PubMedGoogle Scholar
- Gil MJ, Coego A, Mauch-Mani B, Jordá L, Vera P: The Arabidopsis csb3 mutant reveals a regulatory link between salicylic acid-mediated disease resistance and the methyl-erythritol 4-phosphate pathway. Plant J. 2005, 44 (1): 155-166. 10.1111/j.1365-313X.2005.02517.x.PubMedGoogle Scholar
- Guest D, Brown J: Plant defences against pathogens. Plant pathogens and plant diseases. Edited by: Brown J, Ogle H. 1997, Armidale: Rockvale Publications, 263-286.Google Scholar
- ten Have A, Mulder W, Visser J, van Kan JA: The endopolygalacturonase gene Bcpg1 is required for full virulence of Botrytis cinerea. Mol Plant Microbe Interact. 1998, 11 (10): 1009-1016. 10.1094/MPMI.19184.108.40.2069.PubMedGoogle Scholar
- Rolke Y, Liu S, Quidde T, Williamson B, Schouten A, Weltring K-M, Siewers V, Tenberge KB, Tudzynski B, Tudzynski P: Functional analysis of H (2) O (2)-generating systems in Botrytis cinerea: the major Cu-Zn-superoxide dismutase (BCSOD1) contributes to virulence on French bean, whereas a glucose oxidase (BCGOD1) is dispensable. Mol Plant Pathol. 2004, 5 (1): 17-27. 10.1111/j.1364-3703.2004.00201.x.PubMedGoogle Scholar
- Pinedo C, Wang C-M, Pradier J-M, Dalmais B, Choquer M, Le Pêcheur P, Morgant G, Collado IG, Cane DE, Viaud M: Sesquiterpene synthase from the botrydial biosynthetic gene cluster of the phytopathogen Botrytis cinerea. ACS Chem Biol. 2008, 3 (12): 791-801. 10.1021/cb800225v.PubMed CentralPubMedGoogle Scholar
- Wang C-M, Hopson R, Lin X, Cane DE: Biosynthesis of the sesquiterpene botrydial in Botrytis cinerea. Mechanism and stereochemistry of the enzymatic formation of presilphiperfolan-8beta-ol. J Am Chem Soc. 2009, 131 (24): 8360-8361. 10.1021/ja9021649.PubMed CentralPubMedGoogle Scholar
- Zhao L, Qiu C, Li J, Chai Y, Kai G, Li Z, Sun X, Tang KX: Investigation of disease resistance and cold tolerance of Solanum lycopersicoides for tomato improvement. HortSci. 2005, 40 (1): 43-46.Google Scholar
- Jones JDG, Dangl JL: The plant immune system. Nature. 2006, 444 (7117): 323-329. 10.1038/nature05286.PubMedGoogle Scholar
- Lorang JM, Sweat TA, Wolpert TJ: Plant disease susceptibility conferred by a “resistance” gene. Proc Natl Acad Sci U S A. 2007, 104 (37): 14861-14866. 10.1073/pnas.0702572104.PubMed CentralPubMedGoogle Scholar
- Faris JD, Zhang Z, Lu H, Lu S, Reddy L, Cloutier S, Fellers JP, Meinhardt SW, Rasmussen JB, Xu SS, Oliver RP, Simons KJ, Friesen TL: A unique wheat disease resistance-like gene governs effector-triggered susceptibility to necrotrophic pathogens. Proc Natl Acad Sci U S A. 2010, 107 (30): 13544-13549. 10.1073/pnas.1004090107.PubMed CentralPubMedGoogle Scholar
- Nagy ED, Lee T-C, Ramakrishna W, Xu Z, Klein PE, SanMiguel P, Cheng C-P, Li J, Devos KM, Schertz K, Dunkle L, Bennetzen JL: Fine mapping of the Pc locus of Sorghum bicolor, a gene controlling the reaction to a fungal pathogen and its host-selective toxin. Theor Appl Genet. 2007, 114 (6): 961-970. 10.1007/s00122-006-0481-1.PubMedGoogle Scholar
- Edlich W, Lorenz G, Lyr H, Nega E, Pommer EH: New aspects on the infection mechanism of Botrytis cinerea Pers. Neth J Plant Pathol. 1989, 95: 53-62. 10.1007/BF01974284.Google Scholar
- Spoel SH, Johnson JS, Dong X: Regulation of tradeoffs between plant defenses against pathogens with different lifestyles. Proc Natl Acad Sci U S A. 2007, 104 (47): 18842-18847. 10.1073/pnas.0708139104.PubMed CentralPubMedGoogle Scholar
- Veronese P, Nakagami H, Bluhm B, AbuQamar S, Chen X, Salmeron J, Dietrich RA, Hirt H, Mengiste T: The membrane-anchored BOTRYTIS-INDUCED KINASE1 plays distinct roles in Arabidopsis resistance to necrotrophic and biotrophic pathogens. Plant Cell. 2006, 18 (1): 257-273. 10.1105/tpc.105.035576.PubMed CentralPubMedGoogle Scholar
- Delaney TP, Uknes S: A central role of salicylic acid in plant disease resistance. Science. 1994, 266 (5188): 1247-10.1126/science.266.5188.1247.PubMedGoogle Scholar
- Thomma BP, Eggermont K, Penninckx IA, Mauch-Mani B, Vogelsang R, Cammue BP, Broekaert WF: Separate jasmonate-dependent and salicylate-dependent defense-response pathways in Arabidopsis are essential for resistance to distinct microbial pathogens. Proc Natl Acad Sci U S A. 1998, 95 (25): 15107-15111. 10.1073/pnas.95.25.15107.PubMed CentralPubMedGoogle Scholar
- Cao H, Glazebrook J, Clarke JD, Volko S, Dong X: The Arabidopsis NPR1 gene that controls systemic acquired resistance encodes a novel protein containing ankyrin repeats. Cell. 1997, 88 (1): 57-63. 10.1016/S0092-8674(00)81858-9.PubMedGoogle Scholar
- Reuber TL, Plotnikova JM, Dewdney J, Rogers EE, Wood W, Ausubel FM: Correlation of defense gene induction defects with powdery mildew susceptibility in Arabidopsis enhanced disease susceptibility mutants. Plant J. 1998, 16 (4): 473-485. 10.1046/j.1365-313x.1998.00319.x.PubMedGoogle Scholar
- Dempsey DA, Klessig DF, Shah J: Salicylic acid and disease resistance in plants. Crit Rev Plant Sci. 1999, 18 (4): 547-575. 10.1080/07352689991309397.Google Scholar
- Kachroo P, Shanklin J, Shah J, Whittle EJ, Klessig DF: A fatty acid desaturase modulates the activation of defense signaling pathways in plants. Proc Natl Acad Sci U S A. 2001, 98 (16): 9448-9453. 10.1073/pnas.151258398.PubMed CentralPubMedGoogle Scholar
- Govrin EM, Levine A: Infection of Arabidopsis with a necrotrophic pathogen, Botrytis cinerea, elicits various defense responses but does not induce systemic acquired resistance (SAR). Plant Mol Biol. 2002, 48 (3): 267-276. 10.1023/A:1013323222095.PubMedGoogle Scholar
- Thomma BP, Eggermont K, Tierens KF, Broekaert WF: Requirement of functional ethylene-insensitive 2 gene for efficient resistance of Arabidopsis to infection by Botrytis cinerea. Plant Physiol. 1999, 121 (4): 1093-1102. 10.1104/pp.121.4.1093.PubMed CentralPubMedGoogle Scholar
- Métraux JP, Signer H, Ryals J, Ward E, Wyss-Benz M, Gaudin J, Raschdorf K, Schmid E, Blum W, Inverardi B: Increase in salicylic Acid at the onset of systemic acquired resistance in cucumber. Science. 1990, 250 (4983): 1004-1006. 10.1126/science.250.4983.1004.PubMedGoogle Scholar
- Gaffney T, Friedrich L, Vernooij B, Negrotto D, Nye G, Uknes S, Ward E, Kessmann H, Ryals J: Requirement of salicylic Acid for the induction of systemic acquired resistance. Science. 1993, 261 (5122): 754-756. 10.1126/science.261.5122.754.PubMedGoogle Scholar
- Kunkel BN, Brooks DM: Cross talk between signaling pathways in pathogen defense. Curr Opin Plant Biol. 2002, 5 (4): 325-331. 10.1016/S1369-5266(02)00275-3.PubMedGoogle Scholar
- Anderson JP, Badruzsaufari E, Schenk PM, Manners JM, Desmond OJ, Ehlert C, Maclean DJ, Ebert PR, Kazan K: Antagonistic interaction between abscisic acid and jasmonate-ethylene signaling pathways modulates defense gene expression and disease resistance in Arabidopsis. Plant Cell. 2004, 16 (12): 3460-3479. 10.1105/tpc.104.025833.PubMed CentralPubMedGoogle Scholar
- Mang HG, Laluk KA, Parsons EP, Kosma DK, Cooper BR, Park HC, AbuQamar S, Boccongelli C, Miyazaki S, Consiglio F, Chilosi G, Bohnert HJ, Bressan RA, Mengiste T, Jenks MA: The Arabidopsis RESURRECTION1 gene regulates a novel antagonistic interaction in plant defense to biotrophs and necrotrophs. Plant Physiol. 2009, 151 (1): 290-305. 10.1104/pp.109.142158.PubMed CentralPubMedGoogle Scholar
- Abuqamar S, Chai M-F, Luo H, Song F, Mengiste T: Tomato protein kinase 1b mediates signaling of plant responses to necrotrophic fungi and insect herbivory. Plant Cell. 2008, 20 (7): 1964-1983. 10.1105/tpc.108.059477.PubMed CentralPubMedGoogle Scholar
- Abuqamar S, Luo H, Laluk K, Mickelbart MV, Mengiste T: Crosstalk between biotic and abiotic stress responses in tomato is mediated by the AIM1 transcription factor. Plant J. 2009, 58 (2): 347-360. 10.1111/j.1365-313X.2008.03783.x.PubMedGoogle Scholar
- Zheng Z, Qamar SA, Chen Z, Mengiste T: Arabidopsis WRKY33 transcription factor is required for resistance to necrotrophic fungal pathogens. Plant J. 2006, 48 (4): 592-605. 10.1111/j.1365-313X.2006.02901.x.PubMedGoogle Scholar
- Mengiste T, Chen X, Salmeron J, Dietrich R: The BOTRYTIS SUSCEPTIBLE1 gene encodes an R2R3MYB transcription factor protein that is required for biotic and abiotic stress responses in Arabidopsis. Plant Cell. 2003, 15 (11): 2551-2565. 10.1105/tpc.014167.PubMed CentralPubMedGoogle Scholar
- Lorenzo O, Chico JM, Sánchez-Serrano JJ, Solano R: JASMONATE-INSENSITIVE1 encodes a MYC transcription factor essential to discriminate between different jasmonate-regulated defense responses in Arabidopsis. Plant Cell. 2004, 16 (7): 1938-1950. 10.1105/tpc.022319.PubMed CentralPubMedGoogle Scholar
- Bethke G, Unthan T, Uhrig JF, Pöschl Y, Gust AA, Scheel D, Lee J: Flg22 regulates the release of an ethylene response factor substrate from MAP kinase 6 in Arabidopsis thaliana via ethylene signaling. Proc Natl Acad Sci U S A. 2009, 106 (19): 8067-8072. 10.1073/pnas.0810206106.PubMed CentralPubMedGoogle Scholar
- Nurmberg PL, Knox KA, Yun B-W, Morris PC, Shafiei R, Hudson A, Loake GJ: The developmental selector AS1 is an evolutionarily conserved regulator of the plant immune response. Proc Natl Acad Sci U S A. 2007, 104 (47): 18795-18800. 10.1073/pnas.0705586104.PubMed CentralPubMedGoogle Scholar
- Coego A, Ramirez V, Gil MJ, Flors V, Mauch-Mani B, Vera P: An Arabidopsis homeodomain transcription factor, OVEREXPRESSOR OF CATIONIC PEROXIDASE 3, mediates resistance to infection by necrotrophic pathogens. Plant Cell. 2005, 17 (7): 2123-2137. 10.1105/tpc.105.032375.PubMed CentralPubMedGoogle Scholar
- Kidd BN, Edgar CI, Kumar KK, Aitken EA, Schenk PM, Manners JM, Kazan K: The mediator complex subunit PFT1 is a key regulator of jasmonate-dependent defense in Arabidopsis. Plant Cell. 2009, 21 (8): 2237-2252. 10.1105/tpc.109.066910.PubMed CentralPubMedGoogle Scholar
- Dhawan R, Luo H, Foerster AM, Abuqamar S, Du H-N, Briggs SD, Mittelsten Scheid O, Mengiste T: HISTONE MONOUBIQUITINATION1 interacts with a subunit of the mediator complex and regulates defense against necrotrophic fungal pathogens in Arabidopsis. Plant Cell. 2009, 21 (3): 1000-1019. 10.1105/tpc.108.062364.PubMed CentralPubMedGoogle Scholar
- Walley JW, Rowe HC, Xiao Y, Chehab EW, Kliebenstein DJ, Wagner D, Dehesh K: The chromatin remodeler SPLAYED regulates specific stress signaling pathways. PLoS Pathog. 2008, 4 (12): e1000237-e1000237. 10.1371/journal.ppat.1000237.PubMed CentralPubMedGoogle Scholar
- Zhou C, Zhang L, Duan J, Miki B, Wu K: HISTONE DEACETYLASE19 is involved in jasmonic acid and ethylene signaling of pathogen response in Arabidopsis. Plant Cell. 2005, 17 (4): 1196-1204. 10.1105/tpc.104.028514.PubMed CentralPubMedGoogle Scholar
- Berr A, McCallum EJ, Alioua A, Heintz D, Heitz T, Shen W-H: Arabidopsis histone methyltransferase SET DOMAIN GROUP8 mediates induction of the jasmonate/ethylene pathway genes in plant defense response to necrotrophic fungi. Plant Physiol. 2010, 154 (3): 1403-1414. 10.1104/pp.110.161497.PubMed CentralPubMedGoogle Scholar
- Cantu D, Vicente AR, Greve LC, Dewey FM, Bennett AB, Labavitch JM, Powell ALT: The intersection between cell wall disassembly, ripening, and fruit susceptibility to Botrytis cinerea. Proc Natl Acad Sci U S A. 2008, 105 (3): 859-864. 10.1073/pnas.0709813105.PubMed CentralPubMedGoogle Scholar
- Bessire M, Chassot C, Jacquat A-C, Humphry M, Borel S, Petétot JM-C, Métraux J-P, Nawrath C: A permeable cuticle in Arabidopsis leads to a strong resistance to Botrytis cinerea. EMBO J. 2007, 26 (8): 2158-2168. 10.1038/sj.emboj.7601658.PubMed CentralPubMedGoogle Scholar
- Chassot C, Nawrath C, Métraux J-P: Cuticular defects lead to full immunity to a major plant pathogen. Plant J. 2007, 49 (6): 972-980. 10.1111/j.1365-313X.2006.03017.x.PubMedGoogle Scholar
- Tang D, Simonich MT, Innes RW: Mutations in LACS2, a long-chain acyl-coenzyme A synthetase, enhance susceptibility to avirulent Pseudomonas syringae but confer resistance to Botrytis cinerea in Arabidopsis. Plant Physiol. 2007, 144 (2): 1093-1103. 10.1104/pp.106.094318.PubMed CentralPubMedGoogle Scholar
- Hernández-Blanco C, Feng DX, Hu J, Sánchez-Vallet A, Deslandes L, Llorente F, Berrocal-Lobo M, Keller H, Barlet X, Sánchez-Rodríguez C, Anderson LK, Somerville S, Marco Y, Molina A: Impairment of cellulose synthases required for Arabidopsis secondary cell wall formation enhances disease resistance. Plant Cell. 2007, 19 (3): 890-903. 10.1105/tpc.106.048058.PubMed CentralPubMedGoogle Scholar
- Rohmer M: The mevalonate-independent methylerythritol 4-phosphate (MEP) pathway for isoprenoid biosynthesis, including carotenoids. Pure Appl Chem. 1999, 71 (12): 2279-2284.Google Scholar
- Stermer BA, Bianchini GM, Korth KL: Regulation of HMG-CoA reductase activity in plants. J Lipid Res. 1994, 35 (7): 1133-1140.PubMedGoogle Scholar
- Santos CS, Pinheiro M, Silva AI, Egas C, Vasconcelos MW: Searching for resistance genes to Bursaphelenchus xylophilus using high throughput screening. BMC Genomics. 2012, 13: 599-599. 10.1186/1471-2164-13-599.PubMed CentralPubMedGoogle Scholar
- Huth TJ, Place SP: De novo assembly and characterization of tissue specific transcriptomes in the emerald notothen, Trematomus bernacchii. BMC Genomics. 2013, 14: 805-805. 10.1186/1471-2164-14-805.PubMed CentralPubMedGoogle Scholar
- Olsvik PA, Vikeså V, Lie KK, Hevrøy EM: Transcriptional responses to temperature and low oxygen stress in Atlantic salmon studied with next-generation sequencing technology. BMC Genomics. 2013, 14: 817-817. 10.1186/1471-2164-14-817.PubMed CentralPubMedGoogle Scholar
- Ries L, Pullan ST, Delmas S, Malla S, Blythe MJ, Archer DB: Genome-wide transcriptional response of Trichoderma reesei to lignocellulose using RNA sequencing and comparison with Aspergillus niger. BMC Genomics. 2013, 14 (1): 1-12. 10.1186/1471-2164-14-1.Google Scholar
- Tremblay A, Hosseini P, Li S, Alkharouf NW, Matthews BF: Analysis of Phakopsora pachyrhizi transcript abundance in critical pathways at four time-points during infection of a susceptible soybean cultivar using deep sequencing. BMC Genomics. 2013, 14: 614-614. 10.1186/1471-2164-14-614.PubMed CentralPubMedGoogle Scholar
- de Sio F, Laratta B, Giovane A, Quagliuolo L, Castaldo D, Servillo L: Analysis of free and esterified ergosterol in tomato products. J Agric Food Chem. 2000, 48 (3): 780-784. 10.1021/jf990475d.PubMedGoogle Scholar
- Conesa A, Götz S, García-Gómez JM, Terol J, Talón M, Robles M: Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics. 2005, 21 (18): 3674-3676. 10.1093/bioinformatics/bti610.PubMedGoogle Scholar
- Audic S, Claverie JM: The significance of digital gene expression profiles. Genome Res. 1997, 7 (10): 986-995.PubMedGoogle Scholar
- Sturn A, Quackenbush J, Trajanoski Z: Genesis: cluster analysis of microarray data. Bioinformatics. 2002, 18 (1): 207-208. 10.1093/bioinformatics/18.1.207.PubMedGoogle Scholar
- Zdobnov EM, Apweiler R: InterProScan--an integration platform for the signature-recognition methods in InterPro. Bioinformatics. 2001, 17 (9): 847-848. 10.1093/bioinformatics/17.9.847.PubMedGoogle Scholar
- Livak KJ, Schmittgen TD: Analysis of relative gene expression data using real-time quantitative PCR and the 2(−Delta Delta C (T)) Method. Methods. 2001, 25 (4): 402-408. 10.1006/meth.2001.1262.PubMedGoogle Scholar
- Moriya Y, Itoh M, Okuda S, Yoshizawa AC, Kanehisa M: KAAS: an automatic genome annotation and pathway reconstruction server. Nucleic Acids Res. 2007, 35 (Web Server issue): W182-W185.PubMed CentralPubMedGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.