Time-series transcriptomics reveals a BBX32-directed control of acclimation to high light in mature Arabidopsis leaves.

The photosynthetic capacity of mature leaves increases after several days' exposure to constant or intermittent episodes of high light (HL) and is manifested primarily as changes in chloroplast physiology. How this chloroplast-level acclimation to HL is initiated and controlled is unknown. From expanded Arabidopsis leaves, we determined HL-dependent changes in transcript abundance of 3844 genes in a 0-6 h time-series transcriptomics experiment. It was hypothesized that among such genes were those that contribute to the initiation of HL acclimation. By focusing on differentially expressed transcription (co-)factor genes and applying dynamic statistical modelling to the temporal transcriptomics data, a regulatory network of 47 predominantly photoreceptor-regulated transcription (co-)factor genes was inferred. The most connected gene in this network was B-BOX DOMAIN CONTAINING PROTEIN32 (BBX32). Plants overexpressing BBX32 were strongly impaired in acclimation to HL and displayed perturbed expression of photosynthesis-associated genes under LL and after exposure to HL. These observations led to demonstrating that as well as regulation of chloroplast-level acclimation by BBX32, CRYPTOCHROME1, LONG HYPOCOTYL5, CONSTITUTIVELY PHOTOMORPHOGENIC1 and SUPPRESSOR OF PHYA-105 are important. In addition, the BBX32-centric gene regulatory network provides a view of the transcriptional control of acclimation in mature leaves distinct from other photoreceptor-regulated processes, such as seedling photomorphogenesis.

Analysis of the impact of indole-3-acetic acid (IAA) on gene expression during leaf senescence in Arabidopsis thaliana.

Leaf senescence is an important developmental process for the plant life cycle. It is controlled by endogenous and environmental factors and can be positively or negatively affected by plant growth regulators. It is characterised by major and significant changes in the patterns of gene expression. Auxin, especially indole-3-acetic acid (IAA), is a plant growth hormone that affects plant growth and development. The effect of IAA on leaf senescence is still unclear. In this study, we performed microarray analysis to investigate the role of IAA on gene expression during senescence in Arabidopsis thaliana. We sprayed IAA on plants at 3 different time points (27, 31 or 35 days after sowing). Following spraying, PSII activity of the eighth leaf was evaluated daily by measurement of chlorophyll fluorescence parameters. Our results show that PSII activity decreased following IAA application and the IAA treatment triggered different gene expression responses in leaves of different ages.

Time-Series Transcriptomics Reveals That AGAMOUS-LIKE22 Affects Primary Metabolism and Developmental Processes in Drought-Stressed Arabidopsis.

In Arabidopsis thaliana, changes in metabolism and gene expression drive increased drought tolerance and initiate diverse drought avoidance and escape responses. To address regulatory processes that link these responses, we set out to identify genes that govern early responses to drought. To do this, a high-resolution time series transcriptomics data set was produced, coupled with detailed physiological and metabolic analyses of plants subjected to a slow transition from well-watered to drought conditions. A total of 1815 drought-responsive differentially expressed genes were identified. The early changes in gene expression coincided with a drop in carbon assimilation, and only in the late stages with an increase in foliar abscisic acid content. To identify gene regulatory networks (GRNs) mediating the transition between the early and late stages of drought, we used Bayesian network modeling of differentially expressed transcription factor (TF) genes. This approach identified AGAMOUS-LIKE22 (AGL22), as key hub gene in a TF GRN. It has previously been shown that AGL22 is involved in the transition from vegetative state to flowering but here we show that AGL22 expression influences steady state photosynthetic rates and lifetime water use. This suggests that AGL22 uniquely regulates a transcriptional network during drought stress, linking changes in primary metabolism and the initiation of stress responses.

Comparative transcriptome analysis in Arabidopsis ein2/ore3 and ahk3/ore12 mutants during dark-induced leaf senescence.

Leaf senescence involves degenerative but active biological processes that require balanced regulation of pro- and anti-senescing activities. Ethylene and cytokinin are major antagonistic regulatory hormones that control the timing and progression rate of leaf senescence. To identify the roles of these hormones in the regulation of leaf senescence in Arabidopsis, global gene expression profiles in detached leaves of the wild type, an ethylene-insensitive mutant (ein2/ore3), and a constitutive cytokinin response mutant (ahk3/ore12) were investigated during dark-induced leaf senescence. Comparative transcriptome analyses revealed that genes involved in oxidative or salt stress response were preferentially altered in the ein2/ore3 mutant, whereas genes involved in ribosome biogenesis were affected in the ahk3/ore12 mutant during dark-induced leaf senescence. Similar results were also obtained for developmental senescence. Through extensive molecular and physiological analyses in ein2/ore3 and ahk3/ore12 during dark-induced leaf senescence, together with responses when treated with cytokinin and ethylene inhibitor, we conclude that ethylene acts as a senescence-promoting factor via the transcriptional regulation of stress-related responses, whereas cytokinin acts as an anti-senescing agent by maintaining cellular activities and preserving the translational machinery. These findings provide new insights into how plants utilize two antagonistic hormones, ethylene and cytokinin, to regulate the molecular programming of leaf senescence.

Transcriptional Dynamics Driving MAMP-Triggered Immunity and Pathogen Effector-Mediated Immunosuppression in Arabidopsis Leaves Following Infection with Pseudomonas syringae pv tomato DC3000.

Transcriptional reprogramming is integral to effective plant defense. Pathogen effectors act transcriptionally and posttranscriptionally to suppress defense responses. A major challenge to understanding disease and defense responses is discriminating between transcriptional reprogramming associated with microbial-associated molecular pattern (MAMP)-triggered immunity (MTI) and that orchestrated by effectors. A high-resolution time course of genome-wide expression changes following challenge with Pseudomonas syringae pv tomato DC3000 and the nonpathogenic mutant strain DC3000hrpA- allowed us to establish causal links between the activities of pathogen effectors and suppression of MTI and infer with high confidence a range of processes specifically targeted by effectors. Analysis of this information-rich data set with a range of computational tools provided insights into the earliest transcriptional events triggered by effector delivery, regulatory mechanisms recruited, and biological processes targeted. We show that the majority of genes contributing to disease or defense are induced within 6 h postinfection, significantly before pathogen multiplication. Suppression of chloroplast-associated genes is a rapid MAMP-triggered defense response, and suppression of genes involved in chromatin assembly and induction of ubiquitin-related genes coincide with pathogen-induced abscisic acid accumulation. Specific combinations of promoter motifs are engaged in fine-tuning the MTI response and active transcriptional suppression at specific promoter configurations by P. syringae.

Wigwams: identifying gene modules co-regulated across multiple biological conditions.

MOTIVATION: Identification of modules of co-regulated genes is a crucial first step towards dissecting the regulatory circuitry underlying biological processes. Co-regulated genes are likely to reveal themselves by showing tight co-expression, e.g. high correlation of expression profiles across multiple time series datasets. However, numbers of up- or downregulated genes are often large, making it difficult to discriminate between dependent co-expression resulting from co-regulation and independent co-expression. Furthermore, modules of co-regulated genes may only show tight co-expression across a subset of the time series, i.e. show condition-dependent regulation. RESULTS: Wigwams is a simple and efficient method to identify gene modules showing evidence for co-regulation in multiple time series of gene expression data. Wigwams analyzes similarities of gene expression patterns within each time series (condition) and directly tests the dependence or independence of these across different conditions. The expression pattern of each gene in each subset of conditions is tested statistically as a potential signature of a condition-dependent regulatory mechanism regulating multiple genes. Wigwams does not require particular time points and can process datasets that are on different time scales. Differential expression relative to control conditions can be taken into account. The output is succinct and non-redundant, enabling gene network reconstruction to be focused on those gene modules and combinations of conditions that show evidence for shared regulatory mechanisms. Wigwams was run using six Arabidopsis time series expression datasets, producing a set of biologically significant modules spanning different combinations of conditions. AVAILABILITY AND IMPLEMENTATION: A Matlab implementation of Wigwams, complete with graphical user interfaces and documentation, is available at: warwick.ac.uk/wigwams. .

Conserved noncoding sequences highlight shared components of regulatory networks in dicotyledonous plants.

Conserved noncoding sequences (CNSs) in DNA are reliable pointers to regulatory elements controlling gene expression. Using a comparative genomics approach with four dicotyledonous plant species (Arabidopsis thaliana, papaya [Carica papaya], poplar [Populus trichocarpa], and grape [Vitis vinifera]), we detected hundreds of CNSs upstream of Arabidopsis genes. Distinct positioning, length, and enrichment for transcription factor binding sites suggest these CNSs play a functional role in transcriptional regulation. The enrichment of transcription factors within the set of genes associated with CNS is consistent with the hypothesis that together they form part of a conserved transcriptional network whose function is to regulate other transcription factors and control development. We identified a set of promoters where regulatory mechanisms are likely to be shared between the model organism Arabidopsis and other dicots, providing areas of focus for further research.

Arabidopsis defense against Botrytis cinerea: chronology and regulation deciphered by high-resolution temporal transcriptomic analysis.

Transcriptional reprogramming forms a major part of a plant's response to pathogen infection. Many individual components and pathways operating during plant defense have been identified, but our knowledge of how these different components interact is still rudimentary. We generated a high-resolution time series of gene expression profiles from a single Arabidopsis thaliana leaf during infection by the necrotrophic fungal pathogen Botrytis cinerea. Approximately one-third of the Arabidopsis genome is differentially expressed during the first 48 h after infection, with the majority of changes in gene expression occurring before significant lesion development. We used computational tools to obtain a detailed chronology of the defense response against B. cinerea, highlighting the times at which signaling and metabolic processes change, and identify transcription factor families operating at different times after infection. Motif enrichment and network inference predicted regulatory interactions, and testing of one such prediction identified a role for TGA3 in defense against necrotrophic pathogens. These data provide an unprecedented level of detail about transcriptional changes during a defense response and are suited to systems biology analyses to generate predictive models of the gene regulatory networks mediating the Arabidopsis response to B. cinerea.

A local regulatory network around three NAC transcription factors in stress responses and senescence in Arabidopsis leaves.

A model is presented describing the gene regulatory network surrounding three similar NAC transcription factors that have roles in Arabidopsis leaf senescence and stress responses. ANAC019, ANAC055 and ANAC072 belong to the same clade of NAC domain genes and have overlapping expression patterns. A combination of promoter DNA/protein interactions identified using yeast 1-hybrid analysis and modelling using gene expression time course data has been applied to predict the regulatory network upstream of these genes. Similarities and divergence in regulation during a variety of stress responses are predicted by different combinations of upstream transcription factors binding and also by the modelling. Mutant analysis with potential upstream genes was used to test and confirm some of the predicted interactions. Gene expression analysis in mutants of ANAC019 and ANAC055 at different times during leaf senescence has revealed a distinctly different role for each of these genes. Yeast 1-hybrid analysis is shown to be a valuable tool that can distinguish clades of binding proteins and be used to test and quantify protein binding to predicted promoter motifs.

Modelling transcriptional networks in leaf senescence.

The process of leaf senescence is induced by an extensive range of developmental and environmental signals and controlled by multiple, cross-linking pathways, many of which overlap with plant stress-response signals. Elucidation of this complex regulation requires a step beyond a traditional one-gene-at-a-time analysis. Application of a more global analysis using statistical and mathematical tools of systems biology is an approach that is being applied to address this problem. A variety of modelling methods applicable to the analysis of current and future senescence data are reviewed and discussed using some senescence-specific examples. Network modelling with a senescence transcriptome time course followed by testing predictions with gene-expression data illustrates the application of systems biology tools.

High-resolution temporal profiling of transcripts during Arabidopsis leaf senescence reveals a distinct chronology of processes and regulation.

Leaf senescence is an essential developmental process that impacts dramatically on crop yields and involves altered regulation of thousands of genes and many metabolic and signaling pathways, resulting in major changes in the leaf. The regulation of senescence is complex, and although senescence regulatory genes have been characterized, there is little information on how these function in the global control of the process. We used microarray analysis to obtain a high-resolution time-course profile of gene expression during development of a single leaf over a 3-week period to senescence. A complex experimental design approach and a combination of methods were used to extract high-quality replicated data and to identify differentially expressed genes. The multiple time points enable the use of highly informative clustering to reveal distinct time points at which signaling and metabolic pathways change. Analysis of motif enrichment, as well as comparison of transcription factor (TF) families showing altered expression over the time course, identify clear groups of TFs active at different stages of leaf development and senescence. These data enable connection of metabolic processes, signaling pathways, and specific TF activity, which will underpin the development of network models to elucidate the process of senescence.

Expression of the Arabidopsis redox-related LEA protein, SAG21 is regulated by ERF, NAC and WRKY transcription factors.

SAG21/LEA5 is an unusual late embryogenesis abundant protein in Arabidopsis thaliana, that is primarily mitochondrially located and may be important in regulating translation in both chloroplasts and mitochondria. SAG21 expression is regulated by a plethora of abiotic and biotic stresses and plant growth regulators indicating a complex regulatory network. To identify key transcription factors regulating SAG21 expression, yeast-1-hybrid screens were used to identify transcription factors that bind the 1685 bp upstream of the SAG21 translational start site. Thirty-three transcription factors from nine different families bound to the SAG21 promoter, including members of the ERF, WRKY and NAC families. Key binding sites for both NAC and WRKY transcription factors were tested through site directed mutagenesis indicating the presence of cryptic binding sites for both these transcription factor families. Co-expression in protoplasts confirmed the activation of SAG21 by WRKY63/ABO3, and SAG21 upregulation elicited by oligogalacturonide elicitors was partially dependent on WRKY63, indicating its role in SAG21 pathogen responses. SAG21 upregulation by ethylene was abolished in the erf1 mutant, while wound-induced SAG21 expression was abolished in anac71 mutants, indicating SAG21 expression can be regulated by several distinct transcription factors depending on the stress condition.

Nonparametric Bayesian inference for perturbed and orthologous gene regulatory networks.

MOTIVATION: The generation of time series transcriptomic datasets collected under multiple experimental conditions has proven to be a powerful approach for disentangling complex biological processes, allowing for the reverse engineering of gene regulatory networks (GRNs). Most methods for reverse engineering GRNs from multiple datasets assume that each of the time series were generated from networks with identical topology. In this study, we outline a hierarchical, non-parametric Bayesian approach for reverse engineering GRNs using multiple time series that can be applied in a number of novel situations including: (i) where different, but overlapping sets of transcription factors are expected to bind in the different experimental conditions; that is, where switching events could potentially arise under the different treatments and (ii) for inference in evolutionary related species in which orthologous GRNs exist. More generally, the method can be used to identify context-specific regulation by leveraging time series gene expression data alongside methods that can identify putative lists of transcription factors or transcription factor targets. RESULTS: The hierarchical inference outperforms related (but non-hierarchical) approaches when the networks used to generate the data were identical, and performs comparably even when the networks used to generate data were independent. The method was subsequently used alongside yeast one hybrid and microarray time series data to infer potential transcriptional switches in Arabidopsis thaliana response to stress. The results confirm previous biological studies and allow for additional insights into gene regulation under various abiotic stresses. AVAILABILITY: The methods outlined in this article have been implemented in Matlab and are available on request.

Arabidopsis HEAT SHOCK TRANSCRIPTION FACTORA1b overexpression enhances water productivity, resistance to drought, and infection.

Heat-stressed crops suffer dehydration, depressed growth, and a consequent decline in water productivity, which is the yield of harvestable product as a function of lifetime water consumption and is a trait associated with plant growth and development. Heat shock transcription factor (HSF) genes have been implicated not only in thermotolerance but also in plant growth and development, and therefore could influence water productivity. Here it is demonstrated that Arabidopsis thaliana plants with increased HSFA1b expression showed increased water productivity and harvest index under water-replete and water-limiting conditions. In non-stressed HSFA1b-overexpressing (HSFA1bOx) plants, 509 genes showed altered expression, and these genes were not over-represented for development-associated genes but were for response to biotic stress. This confirmed an additional role for HSFA1b in maintaining basal disease resistance, which was stress hormone independent but involved H2O2 signalling. Fifty-five of the 509 genes harbour a variant of the heat shock element (HSE) in their promoters, here named HSE1b. Chromatin immunoprecipitation-PCR confirmed binding of HSFA1b to HSE1b in vivo, including in seven transcription factor genes. One of these is MULTIPROTEIN BRIDGING FACTOR1c (MBF1c). Plants overexpressing MBF1c showed enhanced basal resistance but not water productivity, thus partially phenocopying HSFA1bOx plants. A comparison of genes responsive to HSFA1b and MBF1c overexpression revealed a common group, none of which harbours a HSE1b motif. From this example, it is suggested that HSFA1b directly regulates 55 HSE1b-containing genes, which control the remaining 454 genes, collectively accounting for the stress defence and developmental phenotypes of HSFA1bOx.

Perturbation of cytokinin and ethylene-signalling pathways explain the strong rooting phenotype exhibited by Arabidopsis expressing the Schizosaccharomyces pombe mitotic inducer, cdc25.

BACKGROUND: Entry into mitosis is regulated by cyclin dependent kinases that in turn are phosphoregulated. In most eukaryotes, phosphoregulation is through WEE1 kinase and CDC25 phosphatase. In higher plants a homologous CDC25 gene is unconfirmed and hence the mitotic inducer Schizosaccharomyces pombe (Sp) cdc25 has been used as a tool in transgenic plants to probe cell cycle function. Expression of Spcdc25 in tobacco BY-2 cells accelerates entry into mitosis and depletes cytokinins; in whole plants it stimulates lateral root production. Here we show, for the first time, that alterations to cytokinin and ethylene signaling explain the rooting phenotype elicited by Spcdc25 expression in Arabidopsis. RESULTS: Expressing Spcdc25 in Arabidopsis results in increased formation of lateral and adventitious roots, a reduction of primary root width and more isodiametric cells in the root apical meristem (RAM) compared with wild type. Furthermore it stimulates root morphogenesis from hypocotyls when cultured on two way grids of increasing auxin and cytokinin concentrations. Microarray analysis of seedling roots expressing Spcdc25 reveals that expression of 167 genes is changed by > 2-fold. As well as genes related to stress responses and defence, these include 19 genes related to transcriptional regulation and signaling. Amongst these was the up-regulation of genes associated with ethylene synthesis and signaling. Seedlings expressing Spcdc25 produced 2-fold more ethylene than WT and exhibited a significant reduction in hypocotyl length both in darkness or when exposed to 10 ppm ethylene. Furthermore in Spcdc25 expressing plants, the cytokinin receptor AHK3 was down-regulated, and endogenous levels of iPA were reduced whereas endogeous IAA concentrations in the roots increased. CONCLUSIONS: We suggest that the reduction in root width and change to a more isodiametric cell phenotype in the RAM in Spcdc25 expressing plants is a response to ethylene over-production. The increased rooting phenotype in Spcdc25 expressing plants is due to an increase in the ratio of endogenous auxin to cytokinin that is known to stimulate an increased rate of lateral root production. Overall, our data reveal important cross talk between cell division and plant growth regulators leading to developmental changes.

A new broccoli × broccoli immortal mapping population and framework genetic map: tools for breeders and complex trait analysis.

A unique broccoli × broccoli doubled haploid (DH) population has been created from the F(1) of a cross between two DH broccoli lines derived from cultivars Green Duke and Marathon. We genotyped 154 individuals from this population with simple sequence repeat and amplified fragment length polymorphism markers to create a B. oleracea L. var. italica 'intra-crop' specific framework linkage map. The map is composed of nine linkage groups with a total length of 946.7 cM. Previous published B. oleracea maps have been constructed using diverse crosses between morphotypes of B. oleracea; this map therefore represents a useful breeding resource for the dissection of broccoli specific traits. Phenotype data have been collected from the population over five growing seasons; the framework linkage map has been used to locate quantitative trait loci for agronomically important broccoli traits including head weight (saleable yield), head diameter, stalk diameter, weight loss and relative weight loss during storage, as well as traits for broccoli leaf architecture. This population and associated linkage map will aid breeders to directly map agronomically important traits for the improvement of elite broccoli cultivars.

Temporal clustering by affinity propagation reveals transcriptional modules in Arabidopsis thaliana.

MOTIVATION: Identifying regulatory modules is an important task in the exploratory analysis of gene expression time series data. Clustering algorithms are often used for this purpose. However, gene regulatory events may induce complex temporal features in a gene expression profile, including time delays, inversions and transient correlations, which are not well accounted for by current clustering methods. As the cost of microarray experiments continues to fall, the temporal resolution of time course studies is increasing. This has led to a need to take account of detailed temporal features of this kind. Thus, while standard clustering methods are both widely used and much studied, their shared shortcomings with respect to such temporal features motivates the work presented here. RESULTS: Here, we introduce a temporal clustering approach for high-dimensional gene expression data which takes account of time delays, inversions and transient correlations. We do so by exploiting a recently introduced, message-passing-based algorithm called Affinity Propagation (AP). We take account of temporal features of interest following an approximate but efficient dynamic programming approach due to Qian et al. The resulting approach is demonstrably effective in its ability to discern non-obvious temporal features, yet efficient and robust enough for routine use as an exploratory tool. We show results on validated transcription factor-target pairs in yeast and on gene expression data from a study of Arabidopsis thaliana under pathogen infection. The latter reveals a number of biologically striking findings. AVAILABILITY: Matlab code for our method is available at http://www.wsbc.warwick.ac.uk/stevenkiddle/tcap.html.

Probing the reproducibility of leaf growth and molecular phenotypes: a comparison of three Arabidopsis accessions cultivated in ten laboratories.

A major goal of the life sciences is to understand how molecular processes control phenotypes. Because understanding biological systems relies on the work of multiple laboratories, biologists implicitly assume that organisms with the same genotype will display similar phenotypes when grown in comparable conditions. We investigated to what extent this holds true for leaf growth variables and metabolite and transcriptome profiles of three Arabidopsis (Arabidopsis thaliana) genotypes grown in 10 laboratories using a standardized and detailed protocol. A core group of four laboratories generated similar leaf growth phenotypes, demonstrating that standardization is possible. But some laboratories presented significant differences in some leaf growth variables, sometimes changing the genotype ranking. Metabolite profiles derived from the same leaf displayed a strong genotype x environment (laboratory) component. Genotypes could be separated on the basis of their metabolic signature, but only when the analysis was limited to samples derived from one laboratory. Transcriptome data revealed considerable plant-to-plant variation, but the standardization ensured that interlaboratory variation was not considerably larger than intralaboratory variation. The different impacts of the standardization on phenotypes and molecular profiles could result from differences of temporal scale between processes involved at these organizational levels. Our findings underscore the challenge of describing, monitoring, and precisely controlling environmental conditions but also demonstrate that dedicated efforts can result in reproducible data across multiple laboratories. Finally, our comparative analysis revealed that small variations in growing conditions (light quality principally) and handling of plants can account for significant differences in phenotypes and molecular profiles obtained in independent laboratories.

A temporal precedence based clustering method for gene expression microarray data.

BACKGROUND: Time-course microarray experiments can produce useful data which can help in understanding the underlying dynamics of the system. Clustering is an important stage in microarray data analysis where the data is grouped together according to certain characteristics. The majority of clustering techniques are based on distance or visual similarity measures which may not be suitable for clustering of temporal microarray data where the sequential nature of time is important. We present a Granger causality based technique to cluster temporal microarray gene expression data, which measures the interdependence between two time-series by statistically testing if one time-series can be used for forecasting the other time-series or not. RESULTS: A gene-association matrix is constructed by testing temporal relationships between pairs of genes using the Granger causality test. The association matrix is further analyzed using a graph-theoretic technique to detect highly connected components representing interesting biological modules. We test our approach on synthesized datasets and real biological datasets obtained for Arabidopsis thaliana. We show the effectiveness of our approach by analyzing the results using the existing biological literature. We also report interesting structural properties of the association network commonly desired in any biological system. CONCLUSIONS: Our experiments on synthesized and real microarray datasets show that our approach produces encouraging results. The method is simple in implementation and is statistically traceable at each step. The method can produce sets of functionally related genes which can be further used for reverse-engineering of gene circuits.

A molecular and structural characterization of senescing Arabidopsis siliques and comparison of transcriptional profiles with senescing petals and leaves.

Senescence of plant organs is a genetically controlled process that regulates cell death to facilitate nutrient recovery and recycling, and frequently precedes, or is concomitant with, ripening of reproductive structures. In Arabidopsis thaliana, the seeds are contained within a silique, which is itself a photosynthetic organ in the early stages of development and undergoes a programme of senescence prior to dehiscence. A transcriptional analysis of the silique wall was undertaken to identify changes in gene expression during senescence and to correlate these events with ultrastructural changes. The study revealed that the most highly up-regulated genes in senescing silique wall tissues encoded seed storage proteins, and the significance of this finding is discussed. Global transcription profiles of senescing siliques were compared with those from senescing Arabidopsis leaf or petal tissues using microarray datasets and metabolic pathway analysis software (MapMan). In all three tissues, members of NAC and WRKY transcription factor families were up-regulated, but components of the shikimate and cell-wall biosynthetic pathways were down-regulated during senescence. Expression of genes encoding ethylene biosynthesis and action showed more similarity between senescing siliques and petals than between senescing siliques and leaves. Genes involved in autophagy were highly expressed in the late stages of death of all plant tissues studied, but not always during the preceding remobilization phase of senescence. Analyses showed that, during senescence, silique wall tissues exhibited more transcriptional features in common with petals than with leaves. The shared and distinct regulatory events associated with senescence in the three organs are evaluated and discussed.