Background: Nitrate and other nitrogen metabolites can act as signals that regulate global gene expression in plants. Adaptive changes in plant morphology and physiology triggered by changes in nitrate availability are partly explained by these changes in gene expression. Despite several genome-wide efforts to identify nitrate-regulated genes, no comprehensive study of the Arabidopsis root transcriptome under contrasting nitrate conditions has been carried out. Results: In this work, we employed the Illumina high throughput sequencing technology to perform an integrated analysis of the poly-A + enriched and the small RNA fractions of the Arabidopsis thaliana root transcriptome in response to nitrate treatments. Our sequencing strategy identified new nitrate-regulated genes including 40 genes not represented in the ATH1 Affymetrix GeneChip, a novel nitrate-responsive antisense transcript and a new nitrate responsive miRNA/TARGET module consisting of a novel microRNA, miR5640 and its target, AtPPC3. Conclusions: Sequencing of small RNAs and mRNAs uncovered new genes, and enabled us to develop new hypotheses for nitrate regulation and coordination of carbon and nitrogen metabolism.

In Arabidopsis (Arabidopsis thaliana), the High-Affinity Transport System (HATS) for root nitrate (⁠ $NO3−$⁠) uptake depends mainly on four NRT2 $NO3−$ transporters, namely NRT2.1, NRT2.2, NRT2.4, and NRT2.5. The HATS is the target of many regulations to coordinate nitrogen (N) acquisition with the N status of the plant and with carbon (C) assimilation through photosynthesis. At the molecular level, C and N signaling pathways control gene expression of the NRT2 transporters. Although several regulators of these transporters have been identified in response to either N or C signals, the response of NRT2 gene expression to the interaction of these signals has never been specifically investigated, and the underlying molecular mechanisms remain largely unknown. To address this question we used an original systems biology approach to model a regulatory gene network targeting NRT2.1, NRT2.2, NRT2.4, and NRT2.5 in response to N/C signals. Our systems analysis of the data identified three transcription factors, TGA3, MYC1, and bHLH093. Functional analysis of mutants combined with yeast one-hybrid experiments confirmed that all three transcription factors are regulators of NRT2.4 or NRT2.5 in response to N or C signals. These results reveal a role for TGA3, MYC1, and bHLH093 in controlling the expression of root NRT2 transporter genes.

The best ideotypes are under mounting pressure due to increased aridity. Understanding the conserved molecular mechanisms that evolve in wild plants adapted to harsh environments is crucial in developing new strategies for agriculture. Yet our knowledge of such mechanisms in wild species is scant. We performed metabolic pathway reconstruction using transcriptome information from 32 Atacama and phylogenetically related species that do not live in Atacama (sister species). We analyzed reaction enrichment to understand the commonalities and differences of Atacama plants. To gain insights into the mechanisms that ensure survival, we compared expressed gene isoform numbers and gene expression patterns between the annotated biochemical reactions from 32 Atacama and sister species. We found biochemical convergences characterized by reactions enriched in at least 50% of the Atacama species, pointing to potential advantages against drought and nitrogen starvation, for instance. These findings suggest that the adaptation in the Atacama Desert may result in part from shared genetic legacies governing the expression of key metabolic pathways to face harsh conditions. Enriched reactions corresponded to ubiquitous compounds common to extreme and agronomic species and were congruent with our previous metabolomic analyses. Convergent adaptive traits offer promising candidates for improving abiotic stress resilience in crop species.

Plants face the constant challenge of reconciling antagonistic environmental signals, such as nutrient-driven growth and water deficit–induced stress responses. However, the molecular mechanisms that integrate these conflicting pathways remain poorly understood. Through a comprehensive transcriptomic meta-analysis in Arabidopsis thaliana , we show that nitrogen (N) supply and water deficit signaling exhibit overlapping and often opposing gene expression responses. Regulatory network modeling identifies the NIN-LIKE PROTEIN 7 (NLP7) transcription factor (TF) as a central integrator of these convergent transcriptional responses. Through combinatorial water deficit and N supply treatments in wild-type and nlp7 mutant plants, we find that NLP7 accounts for 85% of the transcriptional interaction between these pathways. Chromatin immunoprecipitation and sequencing and a cell TF assay to detect TF regulation genome-wide reveal that NLP7 directly downregulate the expression of TFs such as HB6 , NAC6 , NAP , and WRKY18 , which are central regulators of water deficit–mediated stress signaling. Repression of these secondary TFs has distinct downstream effects on gene expression, influencing shared and water deficit–specific responses. Loss of NLP7 enhances water deficit tolerance, characterized by increased water retention, reduced abscisic acid-mediated stomatal aperture, and altered expression of stress-responsive genes. These findings establish NLP7 as a central hub balancing growth and stress responses, providing insight into how plants integrate competing environmental cues.

For comprehensive gene expression analyses of the phytopathogenic fungus Botrytis cinerea, which infects a number of plant taxa and is a cause of substantial agricultural losses worldwide, we developed BEB, a web-based B. cinerea gene Expression Browser. This computationally inexpensive web-based application and its associated database contain manually curated RNA-Seq data for B. cinerea. BEB enables expression analyses of genes of interest under different culture conditions by providing publication-ready heatmaps depicting transcript levels, without requiring advanced computational skills. BEB also provides details of each experiment and user-defined gene expression clustering and visualization options. If needed, tables of gene expression values can be downloaded for further exploration, including, for instance, the determination of differentially expressed genes. The BEB implementation is based on open-source computational technologies that can be deployed for other organisms. In this case, the new implementation will be limited only by the number of transcriptomic experiments that are incorporated into the platform. To demonstrate the usability and value of BEB, we analyzed gene expression patterns across different conditions, with a focus on secondary metabolite gene clusters, chromosome-wide gene expression, previously described virulence factors, and reference genes, providing the first comprehensive expression overview of these groups of genes in this relevant fungal phytopathogen. We expect this tool to be broadly useful in B. cinerea research, providing a basis for comparative transcriptomics and candidate gene identification for functional assays.