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.