Genes and co-expression modules common to drought and bacterial stress responses in Arabidopsis and rice

Involvement of Abscisic Acid in PSII Photodamage and D1 Protein Turnover for Light-Induced Premature Senescence of Rice Flag Leaves

D1 protein in the PSII reaction center is the major target of photodamage, and it exhibits the highest turnover rate among all the thylakoid proteins. In this paper, rice psf (premature senescence of flag leaves) mutant and its wild type were used to investigate the genotype-dependent alteration in PSII photo-damage and D1 protein turnover during leaf senescence and its relation to ABA accumulation in senescent leaves. The symptom and extent of leaf senescence of the psf mutant appeared to be sunlight-dependent under natural field condition. The psf also displayed significantly higher levels of ABA accumulation in senescent leaves than the wild type. However, the premature senescence lesion of psf leaves could be alleviated by shaded treatment, concomitantly with the strikingly suppressed ABA level in the shaded areas of flag leaves. The change in ABA concentration contributed to the regulation of shade-delayed leaf senescence. The participation of ABA in the timing of senescence initiation and in the subsequent rate of leaf senescence was closely associated with PSII photodamage and D1 protein turnover during leaf senescence, in which the transcriptional expression of several key genes (psbA, psbB, psbC and OsFtsH2) involved in D1 protein biosynthesis and PSII repair cycle was seriously suppressed by the significantly increased ABA level. This response resulted in the low rate of D1 protein synthesis and impaired repair recovery in the presence of ABA. The psf showed evidently decreased D1 protein amount in the senescent leaves. Both the inhibition of de novo synthesized D1 protein and the slow rate of proteolytic removal for the photodamaged D1 protein was among the most crucial steps for the linkage between light-dependent leaf senescence and the varying ABA concentration in psf mutant leaves. OsFtsH2 transcriptional expression possibly played an important role in the regulation of D1 protein turnover and PSII repair cycle in relation to ABA mediated leaf senescence.

Transcriptome Analysis of Sunflower Genotypes with Contrasting Oxidative Stress Tolerance Reveals Individual- and Combined- Biotic and Abiotic Stress Tolerance Mechanisms

In nature plants are often simultaneously challenged by different biotic and abiotic stresses. Although the mechanisms underlying plant responses against single stress have been studied considerably, plant tolerance mechanisms under combined stress is not understood. Also, the mechanism used to combat independently and sequentially occurring many number of biotic and abiotic stresses has also not systematically studied. From this context, in this study, we attempted to explore the shared response of sunflower plants to many independent stresses by using meta-analysis of publically available transcriptome data and transcript profiling by quantitative PCR. Further, we have also analyzed the possible role of the genes so identified in contributing to combined stress tolerance. Meta-analysis of transcriptomic data from many abiotic and biotic stresses indicated the common representation of oxidative stress responsive genes. Further, menadione-mediated oxidative stress in sunflower seedlings showed similar pattern of changes in the oxidative stress related genes. Based on this a large scale screening of 55 sunflower genotypes was performed under menadione stress and those contrasting in oxidative stress tolerance were identified. Further to confirm the role of genes identified in individual and combined stress tolerance the contrasting genotypes were individually and simultaneously challenged with few abiotic and biotic stresses. The tolerant hybrid showed reduced levels of stress damage both under combined stress and few independent stresses. Transcript profiling of the genes identified from meta-analysis in the tolerant hybrid also indicated that the selected genes were up-regulated under individual and combined stresses. Our results indicate that menadione-based screening can identify genotypes not only tolerant to multiple number of individual biotic and abiotic stresses, but also the combined stresses.

Meta-analysis and meta-regression of transcriptomic responses to water stress in Arabidopsis

The large amounts of transcriptome data available for Arabidopsis thaliana make a compelling case for the need to generalize results across studies and extract the most robust and meaningful information possible from them. The results of various studies seeking to identify water stress-responsive genes only partially overlap. The aim of this work was to combine transcriptomic studies in a systematic way that identifies commonalities in response, taking into account variation among studies due to batch effects as well as sampling variation, while also identifying the effect of study-specific variables, such as the method of applying water stress, and the part of the plant the mRNA was extracted from. We used meta-analysis, the quantitative synthesis of independent research results, to summarize expression responses to water stress across studies, and meta-regression to model the contribution of covariates that may affect gene expression. We found that some genes with small but consistent differential responses become evident only when results are synthesized across experiments, and are missed in individual studies. We also identified genes with expression responses that are attributable to use of different plant parts and alternative methods for inducing water stress. Our results indicate that meta-analysis and meta-regression provide a powerful approach for identifying a robust gene set that is less sensitive to idiosyncratic results and for quantifying study characteristics that result in contrasting gene expression responses across studies. Combining meta-analysis with individual analyses may contribute to a richer understanding of the biology of water stress responses, and may prove valuable in other gene expression studies.

Network-Based Comparative Analysis of Arabidopsis Immune Responses to Golovinomyces orontii and Botrytis cinerea Infections

A comprehensive exploration of common and specific plant responses to biotrophs and necrotrophs is necessary for a better understanding of plant immunity. Here, we compared the Arabidopsis defense responses evoked by the biotrophic fungus Golovinomyces orontii and the necrotrophic fungus Botrytis cinerea through integrative network analysis. Two time-course transcriptional datasets were integrated with an Arabidopsis protein-protein interaction (PPI) network to construct a G. orontii conditional PPI sub-network (gCPIN) and a B. cinerea conditional PPI sub-network (bCPIN). We found that hubs in gCPIN and bCPIN played important roles in disease resistance. Hubs in bCPIN evolved faster than hubs in gCPIN, indicating the different selection pressures imposed on plants by different pathogens. By analyzing the common network from gCPIN and bCPIN, we identified two network components in which the genes were heavily involved in defense and development, respectively. The co-expression relationships between interacting proteins connecting the two components were different under G. orontii and B. cinerea infection conditions. Closer inspection revealed that auxin-related genes were overrepresented in the interactions connecting these two components, suggesting a critical role of auxin signaling in regulating the different co-expression relationships. Our work may provide new insights into plant defense responses against pathogens with different lifestyles.

Differential Network Analysis Reveals Evolutionary Complexity in Secondary Metabolism of Rauvolfia serpentina over Catharanthus roseus

Comparative co-expression analysis of multiple species using high-throughput data is an integrative approach to determine the uniformity as well as diversification in biological processes. Rauvolfia serpentina and Catharanthus roseus, both members of Apocyanacae family, are reported to have remedial properties against multiple diseases. Despite of sharing upstream of terpenoid indole alkaloid pathway, there is significant diversity in tissue-specific synthesis and accumulation of specialized metabolites in these plants. This led us to implement comparative co-expression network analysis to investigate the modules and genes responsible for differential tissue-specific expression as well as species-specific synthesis of metabolites. Toward these goals differential network analysis was implemented to identify candidate genes responsible for diversification of metabolites profile. Three genes were identified with significant difference in connectivity leading to differential regulatory behavior between these plants. These genes may be responsible for diversification of secondary metabolism, and thereby for species-specific metabolite synthesis. The network robustness of R. serpentina, determined based on topological properties, was also complemented by comparison of gene-metabolite networks of both plants, and may have evolved to have complex metabolic mechanisms as compared to C. roseus under the influence of various stimuli. This study reveals evolution of complexity in secondary metabolism of R. serpentina, and key genes that contribute toward diversification of specific metabolites.

Comparisons of the Effects of Elevated Vapor Pressure Deficit on Gene Expression in Leaves among Two Fast-Wilting and a Slow-Wilting Soybean

Limiting the transpiration rate (TR) of a plant under high vapor pressure deficit (VPD) has the potential to improve crop yield under drought conditions. The effects of elevated VPD on the expression of genes in the leaves of three soybean accessions, Plant Introduction (PI) 416937, PI 471938 and Hutcheson (PI 518664) were investigated because these accessions have contrasting responses to VPD changes. Hutcheson, a fast-wilting soybean, and PI 471938, a slow-wilting soybean, respond to increased VPD with a linear increase in TR. TR of the slow-wilting PI 416937 is limited when VPD increases to greater than about 2 kPa. The objective of this study was to identify the response of the transcriptome of these accessions to elevated VPD under well-watered conditions and identify responses that are unique to the slow-wilting accessions. Gene expression analysis in leaves of genotypes PI 471938 and Hutcheson showed that 22 and 1 genes, respectively, were differentially expressed under high VPD. In contrast, there were 944 genes differentially expressed in PI 416937 with the same increase in VPD. The increased alteration of the transcriptome of PI 416937 in response to elevated VPD clearly distinguished it from the other slow-wilting PI 471938 and the fast-wilting Hutcheson. The inventory and analysis of differentially expressed genes in PI 416937 in response to VPD is a foundation for further investigation to extend the current understanding of plant hydraulic conductivity in drought environments.

Functional characterization of drought-responsive modules and genes in Oryza sativa: a network-based approach

Drought is one of the major environmental stress conditions affecting the yield of rice across the globe. Unraveling the functional roles of the drought-responsive genes and their underlying molecular mechanisms will provide important leads to improve the yield of rice. Co-expression relationships derived from condition-dependent gene expression data is an effective way to identify the functional associations between genes that are part of the same biological process and may be under similar transcriptional control. For this purpose, vast amount of freely available transcriptomic data may be used. In this study, we consider gene expression data for different tissues and developmental stages in response to drought stress. We analyze the network of co-expressed genes to identify drought-responsive genes modules in a tissue and stage-specific manner based on differential expression and gene enrichment analysis. Taking cues from the systems-level behavior of these modules, we propose two approaches to identify clusters of tightly co-expressed/co-regulated genes. Using graph-centrality measures and differential gene expression, we identify biologically informative genes that lack any functional annotation. We show that using orthologous information from other plant species, the conserved co-expression patterns of the uncharacterized genes can be identified. Presence of a conserved neighborhood enables us to extrapolate functional annotation. Alternatively, we show that single 'guide-gene' approach can help in understanding tissue-specific transcriptional regulation of uncharacterized genes. Finally, we confirm the predicted roles of uncharacterized genes by the analysis of conserved cis-elements and explain the possible roles of these genes toward drought tolerance.

Mining expressed sequence tags of rapeseed (Brassica napus L.) to predict the drought responsive regulatory network

It is of great significance to understand the regulatory mechanisms by which plants deal with drought stress. Two EST libraries derived from rapeseed (Brassica napus) leaves in non-stressed and drought stress conditions were analyzed in order to obtain the transcriptomic landscape of drought-exposed B. napus plants, and also to identify and characterize significant drought responsive regulatory genes and microRNAs. The functional ontology analysis revealed a substantial shift in the B. napus transcriptome to govern cellular drought responsiveness via different stress-activated mechanisms. The activity of transcription factor and protein kinase modules generally increased in response to drought stress. The 26 regulatory genes consisting of 17 transcription factor genes, eight protein kinase genes and one protein phosphatase gene were identified showing significant alterations in their expressions in response to drought stress. We also found the six microRNAs which were differentially expressed during drought stress supporting the involvement of a post-transcriptional level of regulation for B. napus drought response. The drought responsive regulatory network shed light on the significance of some regulatory components involved in biosynthesis and signaling of various plant hormones (abscisic acid, auxin and brassinosteroids), ubiquitin proteasome system, and signaling through Reactive Oxygen Species (ROS). Our findings suggested a complex and multi-level regulatory system modulating response to drought stress in B. napus.

Identification of conserved drought-adaptive genes using a cross-species meta-analysis approach

BACKGROUND

Drought is the major environmental stress threatening crop-plant productivity worldwide. Identification of new genes and metabolic pathways involved in plant adaptation to progressive drought stress at the reproductive stage is of great interest for agricultural research.

RESULTS

We developed a novel Cross-Species meta-Analysis of progressive Drought stress at the reproductive stage (CSA:Drought) to identify key drought adaptive genes and mechanisms and to test their evolutionary conservation. Empirically defined filtering criteria were used to facilitate a robust integration of 17 deposited microarray experiments (148 arrays) of Arabidopsis, rice, wheat and barley. By prioritizing consistency over intensity, our approach was able to identify 225 differentially expressed genes shared across studies and taxa. Gene ontology enrichment and pathway analyses classified the shared genes into functional categories involved predominantly in metabolic processes (e.g. amino acid and carbohydrate metabolism), regulatory function (e.g. protein degradation and transcription) and response to stimulus. We further investigated drought related cis-acting elements in the shared gene promoters, and the evolutionary conservation of shared genes. The universal nature of the identified drought-adaptive genes was further validated in a fifth species, Brachypodium distachyon that was not included in the meta-analysis. qPCR analysis of 27, randomly selected, shared orthologs showed similar expression pattern as was found by the CSA:Drought.In accordance, morpho-physiological characterization of progressive drought stress, in B. distachyon, highlighted the key role of osmotic adjustment as evolutionary conserved drought-adaptive mechanism.

CONCLUSIONS

Our CSA:Drought strategy highlights major drought-adaptive genes and metabolic pathways that were only partially, if at all, reported in the original studies included in the meta-analysis. These genes include a group of unclassified genes that could be involved in novel drought adaptation mechanisms. The identified shared genes can provide a useful resource for subsequent research to better understand the mechanisms involved in drought adaptation across-species and can serve as a potential set of molecular biomarkers for progressive drought experiments.

Differential regulation of genes by retrotransposons in rice promoters

Rice genome harbors genes and promoters with retrotransposon insertions. There is very little information about their function. The effect of retrotransposon insertions in four rice promoter regions on gene regulation, was investigated using promoter-reporter gene constructs with and without retrotransposons. Differences in expression levels of gus and egfp reporter genes in forward orientation and rfp in reverse orientation were evaluated in rice plants with transient expression employing quantitative RT-PCR analysis, histochemical GUS staining, and eGFP and RFP fluorescent microscopy. The presence of SINE in the promoter 1 (P1) resulted in higher expression levels of the reporter genes, whereas the presence of LINE in P2 or gypsy LTR retrotransposon in P3 reduced expression of the reporter genes. Furthermore, the SINE in P1 acts as an enhancer in contrast with the LINE in P2 and the gypsy LTR retrotransposon in P3 which act as silencers. CTAA and CGG motifs in these retrotransposons are the likely candidates for the downregulation compared to TCTT motif (SINE) which is a candidate for the upregulation of gene expression. The effect of retrotransposons on gene regulation correlated with the earlier investigation of conservation patterns of these four retrotransposon insertions in several rice accessions implying their evolutionary significance.

The interactive effects of simultaneous biotic and abiotic stresses on plants: mechanistic understanding from drought and pathogen combination

In nature, plants are simultaneously exposed to a combination of biotic and abiotic stresses that limit crop yields. Only recently, researchers have started understanding the molecular basis of combined biotic and abiotic stress interactions. Evidences suggest that under combined stress plants exhibit tailored physiological and molecular responses, in addition to several shared responses as part of their stress tolerance strategy. These tailored responses are suggested to occur only in plants exposed to simultaneous stresses and this information cannot be inferred from individual stress studies. In this review article, we provide update on the responses of plants to simultaneous biotic and abiotic stresses, in particular drought and pathogen. Simultaneous occurrence of drought and pathogen during plant growth provokes complex pathways controlled by different signaling events resulting in positive or negative impact of one stress over the other. Here, we summarize the effect of combined drought and pathogen infection on plants and highlight the tailored strategies adapted by plants. Besides, we enumerate the evidences from pathogen derived elicitors and ABA response studies for understanding simultaneous drought and pathogen tolerance.

Revealing shared and distinct gene network organization in Arabidopsis immune responses by integrative analysis

Pattern-triggered immunity (PTI) and effector-triggered immunity (ETI) are two main plant immune responses to counter pathogen invasion. Genome-wide gene network organizing principles leading to quantitative differences between PTI and ETI have remained elusive. We combined an advanced machine learning method and modular network analysis to systematically characterize the organizing principles of Arabidopsis (Arabidopsis thaliana) PTI and ETI at three network resolutions. At the single network node/edge level, we ranked genes and gene interactions based on their ability to distinguish immune response from normal growth and successfully identified many immune-related genes associated with PTI and ETI. Topological analysis revealed that the top-ranked gene interactions tend to link network modules. At the subnetwork level, we identified a subnetwork shared by PTI and ETI encompassing 1,159 genes and 1,289 interactions. This subnetwork is enriched in interactions linking network modules and is also a hotspot of attack by pathogen effectors. The subnetwork likely represents a core component in the coordination of multiple biological processes to favor defense over development. Finally, we constructed modular network models for PTI and ETI to explain the quantitative differences in the global network architecture. Our results indicate that the defense modules in ETI are organized into relatively independent structures, explaining the robustness of ETI to genetic mutations and effector attacks. Taken together, the multiscale comparisons of PTI and ETI provide a systems biology perspective on plant immunity and emphasize coordination among network modules to establish a robust immune response.

GEM2Net: from gene expression modeling to -omics networks, a new CATdb module to investigate Arabidopsis thaliana genes involved in stress response

CATdb (http://urgv.evry.inra.fr/CATdb) is a database providing a public access to a large collection of transcriptomic data, mainly for Arabidopsis but also for other plants. This resource has the rare advantage to contain several thousands of microarray experiments obtained with the same technical protocol and analyzed by the same statistical pipelines. In this paper, we present GEM2Net, a new module of CATdb that takes advantage of this homogeneous dataset to mine co-expression units and decipher Arabidopsis gene functions. GEM2Net explores 387 stress conditions organized into 18 biotic and abiotic stress categories. For each one, a model-based clustering is applied on expression differences to identify clusters of co-expressed genes. To characterize functions associated with these clusters, various resources are analyzed and integrated: Gene Ontology, subcellular localization of proteins, Hormone Families, Transcription Factor Families and a refined stress-related gene list associated to publications. Exploiting protein–protein interactions and transcription factors-targets interactions enables to display gene networks. GEM2Net presents the analysis of the 18 stress categories, in which 17 264 genes are involved and organized within 681 co-expression clusters. The meta-data analyses were stored and organized to compose a dynamic Web resource.

Enhancing crop resilience to combined abiotic and biotic stress through the dissection of physiological and molecular crosstalk

Plants growing in their natural habitats are often challenged simultaneously by multiple stress factors, both abiotic and biotic. Research has so far been limited to responses to individual stresses, and understanding of adaptation to combinatorial stress is limited, but indicative of non-additive interactions. Omics data analysis and functional characterization of individual genes has revealed a convergence of signaling pathways for abiotic and biotic stress adaptation. Taking into account that most data originate from imposition of individual stress factors, this review summarizes these findings in a physiological context, following the pathogenesis timeline and highlighting potential differential interactions occurring between abiotic and biotic stress signaling across the different cellular compartments and at the whole plant level. Potential effects of abiotic stress on resistance components such as extracellular receptor proteins, R-genes and systemic acquired resistance will be elaborated, as well as crosstalk at the levels of hormone, reactive oxygen species, and redox signaling. Breeding targets and strategies are proposed focusing on either manipulation and deployment of individual common regulators such as transcription factors or pyramiding of non- (negatively) interacting components such as R-genes with abiotic stress resistance genes. We propose that dissection of broad spectrum stress tolerance conferred by priming chemicals may provide an insight on stress cross regulation and additional candidate genes for improving crop performance under combined stress. Validation of the proposed strategies in lab and field experiments is a first step toward the goal of achieving tolerance to combinatorial stress in crops.

A multi-Poisson dynamic mixture model to cluster developmental patterns of gene expression by RNA-seq

Dynamic changes of gene expression reflect an intrinsic mechanism of how an organism responds to developmental and environmental signals. With the increasing availability of expression data across a time-space scale by RNA-seq, the classification of genes as per their biological function using RNA-seq data has become one of the most significant challenges in contemporary biology. Here we develop a clustering mixture model to discover distinct groups of genes expressed during a period of organ development. By integrating the density function of multivariate Poisson distribution, the model accommodates the discrete property of read counts characteristic of RNA-seq data. The temporal dependence of gene expression is modeled by the first-order autoregressive process. The model is implemented with the Expectation-Maximization algorithm and model selection to determine the optimal number of gene clusters and obtain the estimates of Poisson parameters that describe the pattern of time-dependent expression of genes from each cluster. The model has been demonstrated by analyzing a real data from an experiment aimed to link the pattern of gene expression to catkin development in white poplar. The usefulness of the model has been validated through computer simulation. The model provides a valuable tool for clustering RNA-seq data, facilitating our global view of expression dynamics and understanding of gene regulation mechanisms.

The role of ROS signaling in cross-tolerance: from model to crop

Reactive oxygen species (ROS) are key signaling molecules produced in response to biotic and abiotic stresses that trigger a variety of plant defense responses. Cross-tolerance, the enhanced ability of a plant to tolerate multiple stresses, has been suggested to result partly from overlap between ROS signaling mechanisms. Cross-tolerance can manifest itself both as a positive genetic correlation between tolerance to different stresses (inherent cross-tolerance), and as the priming of systemic plant tolerance through previous exposure to another type of stress (induced cross-tolerance). Research in model organisms suggests that cross-tolerance could be used to benefit the agronomy and breeding of crop plants. However, research under field conditions has been scarce and critical issues including the timing, duration, and intensity of a stressor, as well as its interactions with other biotic and abiotic factors, remain to be addressed. Potential applications include the use of chemical stressors to screen for stress-resistant genotypes in breeding programs and the agronomic use of chemical inducers of plant defense for plant protection. Success of these applications will rely on improving our understanding of how ROS signals travel systemically and persist over time, and of how genetic correlations between resistance to ROS, biotic, and abiotic stresses are shaped by cooperative and antagonistic interactions within the underlying signaling pathways.