Regulatory network rewiring for secondary metabolism in Arabidopsis thaliana under various conditions

Exploration of the B3 transcription factor superfamily in Aquilaria sinensis reveal their involvement in seed recalcitrance and agarwood formation

The endangered tree species of the Aquilaria genus produce agarwood, a high value material produced only after wounding; however, conservation of Aquilaria seeds is difficult. The B3 transcription factor family has diverse important functions in plant development, especially in seed development, although their functions in other areas, such as stress responses, remain to be revealed. Here germination tests proved that the seeds of A. sinensis were recalcitrant seeds. To provide insights into the B3 superfamily, the members were identified and characterized by bioinformatic approaches and classified by phylogenetic analysis and domain structure. In total, 71 members were identified and classified into four subfamilies. Each subfamily not only had similar domains, but also had conserved motifs in their B3 domains. For the seed-related LAV subfamily, the B3 domain of AsLAV3 was identical to that of AsVALs but lacked a typical zf-CW domain such as VALs. AsLAV5 lacks a typical PHD-L domain present in Arabidopsis VALs. qRT-PCR expression analysis showed that the LEC2 ortholog AsLAV4 was not expressed in seeds. RAVs and REMs induced after wound treatment were also identified. These findings provide insights into the functions of B3 genes and seed recalcitrance of A. sinensis and indicate the role of B3 genes in wound response and agarwood formation.This is the first work to investigate the B3 family in A. sinensis and to provide insights of the molecular mechanism of seed recalcitrance.This will be a valuable guidance for studies of B3 genes in stress responses, secondary metabolite biosynthesis, and seed development.

Plant-microbe interactions in the rhizosphere via a circular metabolic economy

Chemical exchange often serves as the first step in plant-microbe interactions and exchanges of various signals, nutrients, and metabolites continue throughout the interaction. Here, we highlight the role of metabolite exchanges and metabolic crosstalk in the microbiome-root-shoot-environment nexus. Roots secret a diverse set of metabolites; this assortment of root exudates, including secondary metabolites such as benzoxazinoids, coumarins, flavonoids, indolic compounds, and terpenes, shapes the rhizosphere microbiome. In turn, the rhizosphere microbiome affects plant growth and defense. These inter-kingdom chemical interactions are based on a metabolic circular economy, a seemingly wasteless system in which rhizosphere members exchange (i.e. consume, reuse, and redesign) metabolites. This review also describes the recently discovered phenomenon "Systemically Induced Root Exudation of Metabolites" in which the rhizosphere microbiome governs plant metabolism by inducing systemic responses that shift the metabolic profiles of root exudates. Metabolic exchange in the rhizosphere is based on chemical gradients that form specific microhabitats for microbial colonization and we describe recently developed high-resolution methods to study chemical interactions in the rhizosphere. Finally, we propose an action plan to advance the metabolic circular economy in the rhizosphere for sustainable solutions to the cumulative degradation of soil health in agricultural lands.

Both Binding Strength and Evolutionary Accessibility Affect the Population Frequency of Transcription Factor Binding Sequences in Arabidopsis thaliana

Mutations in DNA sequences that bind transcription factors and thus modulate gene expression are a source of adaptive variation in gene expression. To understand how transcription factor binding sequences evolve in natural populations of the thale cress Arabidopsis thaliana, we integrated genomic polymorphism data for loci bound by transcription factors with in vitro data on binding affinity for these transcription factors. Specifically, we studied 19 different transcription factors, and the allele frequencies of 8,333 genomic loci bound in vivo by these transcription factors in 1,135 A. thaliana accessions. We find that transcription factor binding sequences show very low genetic diversity, suggesting that they are subject to purifying selection. High frequency alleles of such binding sequences tend to bind transcription factors strongly. Conversely, alleles that are absent from the population tend to bind them weakly. In addition, alleles with high frequencies also tend to be the endpoints of many accessible evolutionary paths leading to these alleles. We show that both high affinity and high evolutionary accessibility contribute to high allele frequency for at least some transcription factors. Although binding sequences with stronger affinity are more frequent, we did not find them to be associated with higher gene expression levels. Epistatic interactions among individual mutations that alter binding affinity are pervasive and can help explain variation in accessibility among binding sequences. In summary, combining in vitro binding affinity data with in vivo binding sequence data can help understand the forces that affect the evolution of transcription factor binding sequences in natural populations.

Identification of biological pathway and process regulators using sparse partial least squares and triple-gene mutual interaction

Identification of biological process- and pathway-specific regulators is essential for advancing our understanding of regulation and formation of various phenotypic and complex traits. In this study, we applied two methods, triple-gene mutual interaction (TGMI) and Sparse Partial Least Squares (SPLS), to identify the regulators of multiple metabolic pathways in Arabidopsis thaliana and Populus trichocarpa using high-throughput gene expression data. We analyzed four pathways: (1) lignin biosynthesis pathway in A. thaliana and P. trichocarpa; (2) flavanones, flavonol and anthocyannin biosynthesis in A. thaliana; (3) light reaction pathway and Calvin cycle in A. thaliana. (4) light reaction pathway alone in A. thaliana. The efficiencies of two methods were evaluated by examining the positive known regulators captured, the receiver operating characteristic (ROC) curves and the area under ROC curves (AUROC). Our results showed that TGMI is in general more efficient than SPLS in identifying true pathway regulators and ranks them to the top of candidate regulatory gene lists, but the two methods are to some degree complementary because they could identify some different pathway regulators. This study identified many regulators that potentially regulate the above pathways in plants and are valuable for genetic engineering of these pathways.

The PalWRKY77 transcription factor negatively regulates salt tolerance and abscisic acid signaling in Populus

High salinity, one of the most widespread abiotic stresses, inhibits photosynthesis, reduces vegetation growth, blocks respiration and disrupts metabolism in plants. In order to survive their long-term lifecycle, trees, such as Populus species, recruit the abscisic acid (ABA) signaling pathway to adapt to a saline environment. However, the molecular mechanism behind the ABA-mediated salt stress response in woody plants remains elusive. We have isolated a WRKY transcription factor gene, PalWRKY77, from Populus alba var. pyramidalis (poplar), the expression of which is repressed by salt stress. PalWRKY77 decreases salt tolerance in poplar. Furthermore, PalWRKY77 negatively regulated ABA-responsive genes and relieved ABA-mediated growth inhibition, indicating that PalWRKY77 is a repressor of the ABA response. In vivo and in vitro assays revealed that PalWRKY77 targets the ABA- and salt-induced PalNAC002 and PalRD26 genes by binding to the W-boxes in their promoters. In addition, overexpression of both PalNAC002 and PalRD26 could elevate salt tolerance in transgenic poplars. These findings reveal a novel negative regulation mechanism for the ABA signaling pathway mediated by PalWRKY77 that results in more sensitivity to salt stress in poplar. This deepens our understanding of the complex responses of woody species to salt stress.

Gene Coexpression Network Reveals Insights into the Origin and Evolution of a Theanine-Associated Regulatory Module in Non-Camellia and Camellia Species

Theanine (thea) is one of the most important plant-derived characteristic secondary metabolites and a major healthcare product because of its beneficial biological activities, such as being an antianxiety agent, promoting memory, and lowering blood pressure. Thea mostly accumulates in Camellia plants and is especially rich in Camellia sinensis (tea plant). Although some functional genes (e.g., TS, GOGAT, and GS) attributed to thea accumulation have been separately well explored in tea plants, the evolution of a regulatory module (highly interacting gene group) related to thea metabolism remains to be elaborated. Herein, a thea-associated regulatory module (TARM) was mined by using a comprehensive analysis of a weighted gene coexpression network in Camellia and non-Camellia species. Comparative genomic analysis of 84 green plant species revealed that TARM originated from the ancestor of green plants (algae) and that TARM genes were recruited from different evolutionary nodes with the most gene duplication events at the early stage. Among the TARM genes, two core transcription factors of NAC080 and LBD38 were deduced, which may play a crucial role in regulating the biosynthesis of thea. Our findings provide the first insights into the origin and evolution of TARM and indicate a promising paradigm for identifying vital regulatory genes involved in thea metabolism.

Characterizing the Role of the miR156-SPL Network in Plant Development and Stress Response

MicroRNA (miRNA) is a short, single-stranded, non-coding RNA found in eukaryotic cells that can regulate the expression of many genes at the post-transcriptional level. Among various plant miRNAs with diverse functions, miR156 plays a key role in biological processes, including developmental regulation, immune response, metabolic regulation, and abiotic stress. MiRNAs have become the regulatory center for plant growth and development. MicroRNA156 (miR156) is a highly conserved and emerging tool for the improvement of plant traits, including crop productivity and stress tolerance. Fine-tuning of squamosa promoter biding-like (SPL) gene expression might be a useful strategy for crop improvement. Here, we studied the regulation of the miR156 module and its interaction with SPL factors to understand the developmental transition of various plant species. Furthermore, this review provides a strong background for plant biotechnology and is an important source of information for further molecular breeding to optimize farming productivity.

Specialized phenolic compounds in seeds: structures, functions, and regulations

Plants produce a huge diversity of specialized metabolites (SM) throughout their life cycle that play important physiological and ecological functions. SM can protect plants and seeds against diseases, predators, and abiotic stresses, or support their interactions with beneficial or symbiotic organisms. They also have strong impacts on human nutrition and health. Despite this importance, the biosynthesis and biological functions of most of the SM remain elusive and their diversity and/or quantity have been reduced in most crops during domestication. Seeds present a large number of SM that are important for their physiological, agronomic, nutritional or industrial qualities and hence, provide interesting models for both studying biosynthesis and producing large amounts of specialized metabolites. For instance, phenolics are abundant and widely distributed in seeds. More specifically, flavonoid pathway has been instrumental for understanding environmental or developmental regulations of specialized metabolic pathways, at the molecular and cellular levels. Here, we summarize current knowledge on seed phenolics as model, and discuss how recent progresses in omics approaches could help to further characterize their diversity, regulations, and the underlying molecular mechanisms involved.

Gene Regulatory Network Inference: Connecting Plant Biology and Mathematical Modeling

Plant responses to environmental and intrinsic signals are tightly controlled by multiple transcription factors (TFs). These TFs and their regulatory connections form gene regulatory networks (GRNs), which provide a blueprint of the transcriptional regulations underlying plant development and environmental responses. This review provides examples of experimental methodologies commonly used to identify regulatory interactions and generate GRNs. Additionally, this review describes network inference techniques that leverage gene expression data to predict regulatory interactions. These computational and experimental methodologies yield complex networks that can identify new regulatory interactions, driving novel hypotheses. Biological properties that contribute to the complexity of GRNs are also described in this review. These include network topology, network size, transient binding of TFs to DNA, and competition between multiple upstream regulators. Finally, this review highlights the potential of machine learning approaches to leverage gene expression data to predict phenotypic outputs.

A pathway for every product? Tools to discover and design plant metabolism

The vast diversity of plant natural products is a powerful indication of the biosynthetic capacity of plant metabolism. Synthetic biology seeks to capitalize on this ability by understanding and reconfiguring the biosynthetic pathways that generate this diversity to produce novel products with improved efficiency. Here we review the algorithms and databases that presently support the design and manipulation of metabolic pathways in plants, starting from metabolic models of native biosynthetic pathways, progressing to novel combinations of known reactions, and finally proposing new reactions that may be carried out by existing enzymes. We show how these tools are useful for proposing new pathways as well as identifying side reactions that may affect engineering goals.

TGMI: an efficient algorithm for identifying pathway regulators through evaluation of triple-gene mutual interaction

Despite their important roles, the regulators for most metabolic pathways and biological processes remain elusive. Presently, the methods for identifying metabolic pathway and biological process regulators are intensively sought after. We developed a novel algorithm called triple-gene mutual interaction (TGMI) for identifying these regulators using high-throughput gene expression data. It first calculated the regulatory interactions among triple gene blocks (two pathway genes and one transcription factor (TF)), using conditional mutual information, and then identifies significantly interacted triple genes using a newly identified novel mutual interaction measure (MIM), which was substantiated to reflect strengths of regulatory interactions within each triple gene block. The TGMI calculated the MIM for each triple gene block and then examined its statistical significance using bootstrap. Finally, the frequencies of all TFs present in all significantly interacted triple gene blocks were calculated and ranked. We showed that the TFs with higher frequencies were usually genuine pathway regulators upon evaluating multiple pathways in plants, animals and yeast. Comparison of TGMI with several other algorithms demonstrated its higher accuracy. Therefore, TGMI will be a valuable tool that can help biologists to identify regulators of metabolic pathways and biological processes from the exploded high-throughput gene expression data in public repositories.

Targeted and Untargeted Metabolic Profiling of Wild Grassland Plants identifies Antibiotic and Anthelmintic Compounds Targeting Pathogen Physiology, Metabolism and Reproduction

Plants traditionally used by farmers to manage livestock ailments could reduce reliance on synthetic antibiotics and anthelmintics but in many cases their chemical composition is unknown. As a case study, we analyzed the metabolite profiles of 17 plant species and 45 biomass samples from agricultural grasslands in England using targeted and untargeted metabolite profiling by liquid-chromatography mass spectrometry. We identified a range of plant secondary metabolites, including 32 compounds with known antimicrobial/anthelmintic properties which varied considerably across the different plant samples. These compounds have been shown previously to target multiple aspects of pathogen physiology and metabolism in vitro and in vivo, including inhibition of quorum sensing in bacteria and egg viability in nematodes. The most abundant bioactive compounds were benzoic acid, myricetin, p-coumaric acid, rhamnetin, and rosmarinic acid. Four wild plants (Filipendula ulmaria (L.) Maxim., Prunella vulgaris L., Centuarea nigra L., and Rhinanthus minor L.) and two forage legumes (Medicago sativa L., Trifolium hybridium L.) contained high levels of these compounds. Forage samples from native high-diversity grasslands had a greater abundance of medicinal compounds than samples from agriculturally improved grasslands. Incorporating plants with antibiotic/anthelmintic compounds into livestock feeds may reduce global drug-resistance and preserve the efficacy of last-resort drugs.

Metabolite profiling and associated gene expression reveal two metabolic shifts during the seed-to-seedling transition in Arabidopsis thaliana

Metabolic and transcriptomic correlation analysis identified two distinctive profiles involved in the metabolic preparation for seed germination and seedling establishment, respectively. Transcripts were identified that may control metabolic fluxes. The transition from a quiescent metabolic state (dry seed) to the active state of a vigorous seedling is crucial in the plant's life cycle. We analysed this complex physiological trait by measuring the changes in primary metabolism that occur during the transition in order to determine which metabolic networks are operational. The transition involves several developmental stages from seed germination to seedling establishment, i.e. between imbibition of the mature dry seed and opening of the cotyledons, the final stage of seedling establishment. We hypothesized that the advancement of growth is associated with certain signature metabolite profiles. Metabolite-metabolite correlation analysis underlined two specific profiles which appear to be involved in the metabolic preparation for seed germination and efficient seedling establishment, respectively. Metabolite profiles were also compared to transcript profiles and although transcriptional changes did not always equate to a proportional metabolic response, in depth correlation analysis identified several transcripts that may directly influence the flux through metabolic pathways during the seed-to-seedling transition. This correlation analysis also pinpointed metabolic pathways which are significant for the seed-to-seedling transition, and metabolite contents that appeared to be controlled directly by transcript abundance. This global view of the transcriptional and metabolic changes during the seed-to-seedling transition in Arabidopsis opens up new perspectives for understanding the complex regulatory mechanism underlying this transition.

Large-scale transcriptome analysis reveals arabidopsis metabolic pathways are frequently influenced by different pathogens

Through large-scale transcriptional data analyses, we highlighted the importance of plant metabolism in plant immunity and identified 26 metabolic pathways that were frequently influenced by the infection of 14 different pathogens. Reprogramming of plant metabolism is a common phenomenon in plant defense responses. Currently, a large number of transcriptional profiles of infected tissues in Arabidopsis (Arabidopsis thaliana) have been deposited in public databases, which provides a great opportunity to understand the expression patterns of metabolic pathways during plant defense responses at the systems level. Here, we performed a large-scale transcriptome analysis based on 135 previously published expression samples, including 14 different pathogens, to explore the expression pattern of Arabidopsis metabolic pathways. Overall, metabolic genes are significantly changed in expression during plant defense responses. Upregulated metabolic genes are enriched on defense responses, and downregulated genes are enriched on photosynthesis, fatty acid and lipid metabolic processes. Gene set enrichment analysis (GSEA) identifies 26 frequently differentially expressed metabolic pathways (FreDE_Paths) that are differentially expressed in more than 60% of infected samples. These pathways are involved in the generation of energy, fatty acid and lipid metabolism as well as secondary metabolite biosynthesis. Clustering analysis based on the expression levels of these 26 metabolic pathways clearly distinguishes infected and control samples, further suggesting the importance of these metabolic pathways in plant defense responses. By comparing with FreDE_Paths from abiotic stresses, we find that the expression patterns of 26 FreDE_Paths from biotic stresses are more consistent across different infected samples. By investigating the expression correlation between transcriptional factors (TFs) and FreDE_Paths, we identify several notable relationships. Collectively, the current study will deepen our understanding of plant metabolism in plant immunity and provide new insights into disease-resistant crop improvement.

Gene expression analysis of rocket salad under pre-harvest and postharvest stresses: A transcriptomic resource for Diplotaxis tenuifolia

Diplotaxis tenuifolia L. is of important economic value in the fresh-cut industry for its nutraceutical and sensorial properties. However, information on the molecular mechanisms conferring tolerance of harvested leaves to pre- and postharvest stresses during processing and shelf-life have never been investigated. Here, we provide the first transcriptomic resource of rocket by de novo RNA sequencing assembly, functional annotation and stress-induced expression analysis of 33874 transcripts. Transcriptomic changes in leaves subjected to commercially-relevant pre-harvest (salinity, heat and nitrogen starvation) and postharvest stresses (cold, dehydration, dark, wounding) known to affect quality and shelf-life were analysed 24h after stress treatment, a timing relevant to subsequent processing of salad leaves. Transcription factors and genes involved in plant growth regulator signaling, autophagy, senescence and glucosinolate metabolism were the most affected by the stresses. Hundreds of genes with unknown function but uniquely expressed under stress were identified, providing candidates to investigate stress responses in rocket. Dehydration and wounding had the greatest effect on the transcriptome and different stresses elicited changes in the expression of genes related to overlapping groups of hormones. These data will allow development of approaches targeted at improving stress tolerance, quality and shelf-life of rocket with direct applications in the fresh-cut industries.

De novo transcriptome analysis of rose-scented geranium provides insights into the metabolic specificity of terpene and tartaric acid biosynthesis

Background

Rose-scented geranium (Pelargonium sp.) is a perennial herb that produces a high value essential oil of fragrant significance due to the characteristic compositional blend of rose-oxide and acyclic monoterpenoids in foliage. Recently, the plant has also been shown to produce tartaric acid in leaf tissues. Rose-scented geranium represents top-tier cash crop in terms of economic returns and significance of the plant and plant products. However, there has hardly been any study on its metabolism and functional genomics, nor any genomic expression dataset resource is available in public domain. Therefore, to begin the gains in molecular understanding of specialized metabolic pathways of the plant, de novo sequencing of rose-scented geranium leaf transcriptome, transcript assembly, annotation, expression profiling as well as their validation were carried out.

Results

De novo transcriptome analysis resulted a total of 78,943 unique contigs (average length: 623 bp, and N50 length: 752 bp) from 15.44 million high quality raw reads. In silico functional annotation led to the identification of several putative genes representing terpene, ascorbic acid and tartaric acid biosynthetic pathways, hormone metabolism, and transcription factors. Additionally, a total of 6,040 simple sequence repeat (SSR) motifs were identified in 6.8% of the expressed transcripts. The highest frequency of SSR was of tri-nucleotides (50%). Further, transcriptome assembly was validated for randomly selected putative genes by standard PCR-based approach. In silico expression profile of assembled contigs were validated by real-time PCR analysis of selected transcripts.

Conclusion

Being the first report on transcriptome analysis of rose-scented geranium the data sets and the leads and directions reflected in this investigation will serve as a foundation for pursuing and understanding molecular aspects of its biology, and specialized metabolic pathways, metabolic engineering, genetic diversity as well as molecular breeding.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3437-0) contains supplementary material, which is available to authorized users.

Molecular and physiological responses to titanium dioxide and cerium oxide nanoparticles in Arabidopsis

Changes in tissue transcriptomes and productivity of Arabidopsis thaliana were investigated during exposure of plants to 2 widely used engineered metal oxide nanoparticles, titanium dioxide (nano-titania) and cerium dioxide (nano-ceria). Microarray analyses confirmed that exposure to either nanoparticle altered the transcriptomes of rosette leaves and roots, with comparatively larger numbers of differentially expressed genes found under nano-titania exposure. Nano-titania induced more differentially expressed genes in rosette leaves, whereas roots had more differentially expressed genes under nano-ceria exposure. MapMan analyses indicated that although nano-titania up-regulated overall metabolism in both tissues, metabolic processes under nano-ceria remained mostly unchanged. Gene enrichment analysis indicated that both nanoparticles mainly enriched ontology groups such as responses to stress (abiotic and biotic), and defense responses (pathogens), and responses to endogenous stimuli (hormones). Nano-titania specifically induced genes associated with photosynthesis, whereas nano-ceria induced expression of genes related to activating transcription factors, most notably those belonging to the ethylene responsive element binding protein family. Interestingly, there were also increased numbers of rosette leaves and plant biomass under nano-ceria exposure, but not under nano-titania. Other transcriptomic responses did not clearly relate to responses observed at the organism level, possibly because of functional and genomic redundancy in Arabidopsis, which may mask expression of morphological changes, despite discernable responses at the transcriptome level. In addition, transcriptomic changes often relate to transgenerational phenotypic development, and hence it may be productive to direct further experimental work to integrate high-throughput genomic results with longer term changes in subsequent generations. Environ Toxicol Chem 2017;36:71-82. Published 2016 Wiley Periodicals Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America.

The N-Terminal UND Motif of the Arabidopsis U-Box E3 Ligase PUB18 Is Critical for the Negative Regulation of ABA-Mediated Stomatal Movement and Determines Its Ubiquitination Specificity for Exocyst Subunit Exo70B1

The Arabidopsis thaliana U-box E3 ligases PUB18/PUB19 and PUB22/PUB23 are negative regulators of drought stress responses. PUB18/PUB19 regulate the drought stress response in an abscisic acid (ABA)-dependent manner, whereas PUB22/PUB23 regulate this response in an ABA-independent manner. A major structural difference between PUB18/PUB19 and PUB22/PUB23 is the presence of the UND (U-box N-terminal domain). Here, we focused on elucidating the molecular mechanism that mediates the functional difference between PUB18 and PUB22 and found that the UND^PUB18 was critically involved in the negative regulation of ABA-mediated stomatal movements. Exo70B1, a subunit of the exocyst complex, was identified as a target of PUB18, whereas Exo70B2 was a substrate of PUB22. However, the ∆UND-PUB18 derivative failed to ubiquitinate Exo70B1, but ubiquitinated Exo70B2. By contrast, the UND^PUB18-PUB22 chimeric protein ubiquitinated Exo70B1 instead of Exo70B2, suggesting that the ubiquitination specificities of PUB18 and PUB22 to Exo70B1 and Exo70B2, respectively, are dependent on the presence or absence of the UND^PUB18 motif. The ABA-insensitive phenotypes of the pub18 pub19 exo70b1 triple mutant were reminiscent of those of exo70b1 rather than pub18 pub19, indicating that Exo70B1 functions downstream of PUB18. Overall, our results suggest that the UND^PUB18 motif is crucial for the negative regulation of ABA-dependent stomatal movement and for determination of its ubiquitination specificity to Exo70B1.

Differential Coexpression Analysis Reveals Extensive Rewiring of Arabidopsis Gene Coexpression in Response to Pseudomonas syringae Infection

Plant defense responses to pathogens involve massive transcriptional reprogramming. Recently, differential coexpression analysis has been developed to study the rewiring of gene networks through microarray data, which is becoming an important complement to traditional differential expression analysis. Using time-series microarray data of Arabidopsis thaliana infected with Pseudomonas syringae, we analyzed Arabidopsis defense responses to P. syringae through differential coexpression analysis. Overall, we found that differential coexpression was a common phenomenon of plant immunity. Genes that were frequently involved in differential coexpression tend to be related to plant immune responses. Importantly, many of those genes have similar average expression levels between normal plant growth and pathogen infection but have different coexpression partners. By integrating the Arabidopsis regulatory network into our analysis, we identified several transcription factors that may be regulators of differential coexpression during plant immune responses. We also observed extensive differential coexpression between genes within the same metabolic pathways. Several metabolic pathways, such as photosynthesis light reactions, exhibited significant changes in expression correlation between normal growth and pathogen infection. Taken together, differential coexpression analysis provides a new strategy for analyzing transcriptional data related to plant defense responses and new insights into the understanding of plant-pathogen interactions.