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 highresolution 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.

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.

SUMMARYIn nature, plants have to cope with a wide range of stress conditions that often occur simultaneously or in sequence. To investigate how plants cope with multi-stress conditions, we analyzed the dynamics of whole-transcriptome profiles of Arabidopsis thaliana exposed to six sequential double stresses inflicted by combinations of: (i) infection by the necrotrophic fungus Botrytis cinerea, (ii) herbivory by chewing larvae of Pieris rapae, and (iii) drought stress. Each of these stresses induced specific expression profiles over time, in which one-third of all differentially expressed genes was shared by at least two single stresses. Of these, 394 genes were differentially expressed during all three stress conditions, albeit often in opposite directions. When two stresses were applied in sequence, plants displayed transcriptome profiles that were very similar to the second stress, irrespective of the nature of the first stress. Nevertheless, significant first-stress signatures could be identified in the sequential stress profiles. Bioinformatic analysis of the dynamics of coexpressed gene clusters highlighted specific clusters and biological processes of which the timing of activation or repression was altered by a prior stress. The first-stress signatures in second stress transcriptional profiles were remarkably often related to responses to phytohormones, strengthening the notion that hormones are global modulators of interactions between different types of stress. Because prior stresses can affect the level of tolerance against a subsequent stress (e.g. prior herbivory strongly affected resistance to B. cinerea), the first-stress signatures can provide important leads for the identification of molecular players that are decisive in the interactions between stress response pathways.

Jasmonic acid (JA) is a critical hormonal regulator of plant growth and defense. To advance our understanding of the architecture and dynamic regulation of the JA gene regulatory network, we performed a high-resolution RNA-seq time series of methyl JA-treated Arabidopsis thaliana at 15 time points over a 16-h period. Computational analysis showed that methyl JA (MeJA) induces a burst of transcriptional activity, generating diverse expression patterns over time that partition into distinct sectors of the JA response targeting specific biological processes. The presence of transcription factor (TF) DNA binding motifs correlated with specific TF activity during temporal MeJA-induced transcriptional reprogramming. Insight into the underlying dynamic transcriptional regulation mechanisms was captured in a chronological model of the JA gene regulatory network. Several TFs, including MYB59 and bHLH27, were uncovered as early network components with a role in pathogen and insect resistance. Analysis of subnetworks surrounding the TFs ORA47, RAP2.6L, MYB59, and ANAC055, using transcriptome profiling of overexpressors and mutants, provided insights into their regulatory role in defined modules of the JA network. Collectively, our work illuminates the complexity of the JA gene regulatory network, pinpoints and validates previously unknown regulators, and provides a valuable resource for functional studies on JA signaling components in plant defense and development.

SummaryBelow ground, microbe‐associated molecular patterns (MAMPs) of root‐associated microbiota can trigger costly defenses at the expense of plant growth. However, beneficial rhizobacteria, such as Pseudomonas simiae WCS417, promote plant growth and induce systemic resistance without being warded off by local root immune responses. To investigate early root responses that facilitate WCS417 to exert its plant‐beneficial functions, we performed time series RNA‐Seq of Arabidopsis roots in response to live WCS417 and compared it with MAMPs flg22417 (from WCS417), flg22Pa (from pathogenic Pseudomonas aeruginosa) and fungal chitin. The MAMP transcriptional responses differed in timing, but displayed a large overlap in gene identity. MAMP‐upregulated genes are enriched for genes with functions in immunity, while downregulated genes are enriched for genes related to growth and development. Although 74% of the transcriptional changes inflicted by live WCS417 overlapped with the flg22417 profile, WCS417 actively suppressed more than half of the MAMP‐triggered transcriptional responses, possibly to allow the establishment of a mutually beneficial interaction with the host root. Interestingly, the sector of the flg22417‐repressed transcriptional network that is not affected by WCS417 has a strong auxin signature. Using auxin response mutant tir1afb2afb3, we demonstrate a dual role for auxin signaling in finely balancing growth‐promoting and defense‐eliciting activities of beneficial microbes in plant roots.

SummaryA 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.

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.

We present high‐speed, three‐colour photometry of the eclipsing cataclysmic variables CTCV J1300−3052, CTCV J2354−4700 and SDSS J115207.00+404947.8. These systems have orbital periods of 128.07, 94.39 and 97.52 min, respectively, placing all three systems below the observed ‘period gap’ for cataclysmic variables. For each system we determine the system parameters by fitting a parametrized model to the observed eclipse light curve by χ2 minimization. We also present an updated analysis of all other eclipsing systems previously analysed by our group. The updated analysis utilizes Markov chain Monte Carlo techniques which enable us to arrive confidently at the best fits for each system with more robust determinations of our errors. A new bright‐spot model is also adopted, that allows better modelling of bright‐spot dominated systems. In addition, we correct a bug in the old code which resulted in the white dwarf radius being underestimated, and consequently both the white dwarf and donor mass being overestimated. New donor masses are generally between 1σ and 2σ of those originally published, with the exception of SDSS 1502 (−2.9σ, ΔMr=−0.012 M⊙) and DV UMa (+6.1σ, ΔMr=+0.039 M⊙). We note that the donor mass of SDSS 1501 has been revised upwards by 0.024 M⊙ (+1.9σ). This system was previously identified as having evolved past the minimum orbital period for cataclysmic variables, but the new mass determination suggests otherwise. Our new analysis confirms that SDSS 1035 and SDSS 1433 have evolved past the period minimum for cataclysmic variables, corroborating our earlier studies. We find that the radii of donor stars are oversized when compared to theoretical models, by approximately 10 per cent. We show that this can be explained by invoking either enhanced angular momentum loss, or by taking into account the effects of star spots. We are unable to favour one cause over the other, as we lack enough precise mass determinations for systems with orbital periods between 100 and 130 min, where evolutionary tracks begin to diverge significantly. We also find a strong tendency towards high white dwarf masses within our sample, and no evidence for any He‐core white dwarfs. The dominance of high‐mass white dwarfs implies that erosion of the white dwarf during the nova outburst must be negligible, or that not all of the mass accreted is ejected during nova cycles, resulting in the white dwarf growing in mass.