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Inferring phenotypic outcomes from genomic features is both a promise and challenge for systems biology. Using gene expression data to predict phenotypic outcomes, and functionally validating the genes with predictive powers are two challenges we address in this study. We applied an evolutionarily informed machine learning approach to predict phenotypes based on transcriptome responses shared both within and across species. Specifically, we exploited the phenotypic diversity in nitrogen use efficiency and evolutionarily conserved transcriptome responses to nitrogen treatments across Arabidopsis accessions and maize varieties. We demonstrate that using evolutionarily conserved nitrogen responsive genes is a biologically principled approach to reduce the feature dimensionality in machine learning that ultimately improved the predictive power of our gene-to-trait models. Further, we functionally validated seven candidate transcription factors with predictive power for NUE outcomes in Arabidopsis and one in maize. Moreover, application of our evolutionarily informed pipeline to other species including rice and mice models underscores its potential to uncover genes affecting any physiological or clinical traits of interest across biology, agriculture, or medicine., Predicting complex phenotypes from genomic information is still a challenge. Here, the authors use an evolutionarily informed machine learning approach within and across species to predict genes affecting nitrogen utilization in crops, and show their approach is also useful in mammalian systems.

The ability to accurately predict the causal relationships from transcription factors to genes would greatly enhance our understanding of transcriptional dynamics. This could lead to applications in which one or more transcription factors could be manipulated to effect a change in genes leading to the enhancement of some desired trait. Here we present a method called OutPredict that constructs a model for each gene based on time series (and other) data and that predicts gene's expression in a previously unseen subsequent time point. The model also infers causal relationships based on the most important transcription factors for each gene model, some of which have been validated from previous physical experiments. The method benefits from known network edges and steady-state data to enhance predictive accuracy. Our results across B. subtilis, Arabidopsis, E.coli, Drosophila and the DREAM4 simulated in silico dataset show improved predictive accuracy ranging from 40% to 60% over other state-of-the-art methods. We find that gene expression models can benefit from the addition of steady-state data to predict expression values of time series. Finally, we validate, based on limited available data, that the influential edges we infer correspond to known relationships significantly more than expected by chance or by state-of-the-art methods.

We discuss how both nitrogen and water availability combine to impact plant biological responses at the molecular, transcriptomic, and physiological level., Nitrogen (N) and water (W) are crucial inputs for plant survival as well as costly resources for agriculture. Given their importance, the molecular mechanisms that plants rely on to signal changes in either N or W status have been under intense scrutiny. However, how plants sense and respond to the combination of N and W signals at the molecular level has received scant attention. The purpose of this review is to shed light on what is currently known about how plant responses to N are impacted by W status. We review classic studies which detail how N and W combinations have both synergistic and antagonistic effects on key plant traits, such as root architecture and stomatal aperture. Recent molecular studies of N and W interactions show that mutations in genes involved in N metabolism affect drought responses, and vice versa. Specifically, perturbing key N signaling genes may lead to changes in drought-responsive gene expression programs, which is supported by a meta-analysis we conduct on available transcriptomic data. Additionally, we cite studies that show how combinatorial transcriptional responses to N and W status might drive crop phenotypes. Through these insights, we suggest research strategies that could help to develop crops adapted to marginal soils depleted in both N and W, an important task in the face of climate change.

As sessile organisms, plants are finely tuned to respond dynamically to developmental, circadian, and environmental cues. Genome-wide studies investigating these types of cues have uncovered the intrinsically different ways they can impact gene expression over time. Recent advances in single cell sequencing and time-based bioinformatic algorithms are now beginning to reveal the dynamics of these time-based responses within individual cells and plant tissues. Here, we review what these techniques have revealed about the spatiotemporal nature of gene regulation, paying particular attention to the three distinct ways in which plant tissues are time sensitive. (i) First, we discuss how studying plant cell identity can reveal developmental trajectories hidden in pseudotime. (ii) Next, we present evidence which indicates that plant cell types keep their own local time through tissue specific regulation of the circadian clock. (iii) Finally, we review what determines the speed of environmental signaling responses, and how they can be contingent on developmental and circadian time. By these means, this review sheds light on how these different scales of time-based responses can act with tissue and cell-type specificity to elicit changes in whole plant systems.

Charting a temporal path in gene networks requires linking early transcription factor (TF)-triggered events to downstream effects. We scale-up a cell-based TF-perturbation assay to identify direct regulated targets of 33 nitrogen (N)-early response TFs encompassing 88% of N-responsive Arabidopsis genes. We uncover a duality where each TF is an inducer and repressor, and in vitro cis-motifs are typically specific to regulation directionality. Validated TF-targets (71,836) are used to refine precision of a time-inferred root network, connecting 145 N-responsive TFs and 311 targets. These data are used to chart network paths from direct TF1-regulated targets identified in cells to indirect targets responding only in planta via Network Walking. We uncover network paths from TGA1 and CRF4 to direct TF2 targets, which in turn regulate 76% and 87% of TF1 indirect targets in planta, respectively. These results have implications for N-use and the approach can reveal temporal networks for any biological system., Temporal control of transcriptional networks enables organisms to adapt to changing environment. Here, the authors use a scaled-up cell-based assay to identify direct targets of nitrogen-early responsive transcription factors and validate a network path mediating dynamic nitrogen signaling in Arabidopsis.

Plants need to cope with strong variations of nitrogen availability in the soil. Although many molecular players are being discovered concerning how plants perceive NO3− provision, it is less clear how plants recognize a lack of nitrogen. Following nitrogen removal, plants activate their nitrogen starvation response (NSR), which is characterized by the activation of very high-affinity nitrate transport systems (NRT2.4 and NRT2.5) and other sentinel genes involved in N remobilization such as GDH3. Using a combination of functional genomics via transcription factor perturbation and molecular physiology studies, we show that the transcription factors belonging to the HHO subfamily are important regulators of NSR through two potential mechanisms. First, HHOs directly repress the high-affinity nitrate transporters, NRT2.4 and NRT2.5. hho mutants display increased high-affinity nitrate transport activity, opening up promising perspectives for biotechnological applications. Second, we show that reactive oxygen species (ROS) are important to control NSR in wild-type plants and that HRS1 and HHO1 overexpressors and mutants are affected in their ROS content, defining a potential feed-forward branch of the signaling pathway. Taken together, our results define the relationships of two types of molecular players controlling the NSR, namely ROS and the HHO transcription factors. This work (i) up opens perspectives on a poorly understood nutrient-related signaling pathway and (ii) defines targets for molecular breeding of plants with enhanced NO3− uptake.

Deciphering gene regulatory networks (GRNs) is both a promise and challenge of systems biology. The promise lies in identifying key transcription factors (TFs) that enable an organism to react to changes in its environment. The challenge lies in validating GRNs that involve hundreds of TFs with hundreds of thousands of interactions with their genome-wide targets experimentally determined by high-throughput sequencing. To address this challenge, we developed ConnecTF, a species-independent, web-based platform that integrates genome-wide studies of TF–target binding, TF–target regulation, and other TF-centric omic datasets and uses these to build and refine validated or inferred GRNs. We demonstrate the functionality of ConnecTF by showing how integration within and across TF–target datasets uncovers biological insights. Case study 1 uses integration of TF–target gene regulation and binding datasets to uncover TF mode-of-action and identify potential TF partners for 14 TFs in abscisic acid signaling. Case study 2 demonstrates how genome-wide TF–target data and automated functions in ConnecTF are used in precision/recall analysis and pruning of an inferred GRN for nitrogen signaling. Case study 3 uses ConnecTF to chart a network path from NLP7, a master TF in nitrogen signaling, to direct secondary TF2s and to its indirect targets in a Network Walking approach. The public version of ConnecTF (https://ConnecTF.org) contains 3,738,278 TF–target interactions for 423 TFs in Arabidopsis, 839,210 TF–target interactions for 139 TFs in maize (Zea mays), and 293,094 TF–target interactions for 26 TFs in rice (Oryza sativa). The database and tools in ConnecTF will advance the exploration of GRNs in plant systems biology applications for model and crop species.

International audience; Nitrogen (N) is an essential macronutrient for plants, and a major limiting factor for plant growth and crop production. Nitrate is the main source of N available for plants in agricultural soils and in many natural environments. Sustaining agricultural productivity is of paramount importance in the current scenario of increasing world population, diversification of crop uses, and climate change. Plant productivity for major crops around the world is still supported by excess application of N-based fertilizers with detrimental economic and environmental impacts. Thus, understanding how plants regulate nitrate uptake and metabolism is key for developing new crops with enhanced N use efficiency (NUE) and to cope with future world food demands. The study of plant responses to nitrate has gained considerable interest over the last thirty years. This review provides an overview of key findings in nitrate research, spanning biochemistry, molecular genetics, genomics and systems biology. We discuss how we reached our current understanding of nitrate transport, local and systemic nitrate sensing/signaling, and the regulatory networks underlying nitrate-controlled outputs in plants. We hope this summary serves not only as a time-line and information repository, but also as a base to outline important open questions for future research.

Chromatin modification has gained increased attention for its role in the regulation of plant responses to environmental changes, but the specific mechanisms and molecular players remain elusive. Here, we show that the Arabidopsis (Arabidopsis thaliana) histone methyltransferase SET DOMAIN GROUP8 (SDG8) mediates genome-wide changes in H3K36 methylation at specific genomic loci functionally relevant to nitrate treatments. Moreover, we show that the specific H3K36 methyltransferase encoded by SDG8 is required for canonical RNA processing, and that RNA isoform switching is more prominent in the sdg8-5 deletion mutant than in the wild type. To demonstrate that SDG8-mediated regulation of RNA isoform expression is functionally relevant, we examined a putative regulatory gene, CONSTANS, CO-like, and TOC1 101 (CCT101), whose nitrogen-responsive isoform-specific RNA expression is mediated by SDG8. We show by functional expression in shoot cells that the different RNA isoforms of CCT101 encode distinct regulatory proteins with different effects on genome-wide transcription. We conclude that SDG8 is involved in plant responses to environmental nitrogen supply, affecting multiple gene regulatory processes including genome-wide histone modification, transcriptional regulation, and RNA processing, and thereby mediating developmental and metabolic processes related to nitrogen use.

Dynamic reprogramming of gene regulatory networks (GRNs) enables organisms to rapidly respond to environmental perturbation. However, the underlying transient interactions between transcription factors (TFs) and genome-wide targets typically elude biochemical detection. Here, we capture both stable and transient TF-target interactions genome-wide within minutes after controlled TF nuclear import using time-series chromatin immunoprecipitation (ChIP-seq) and/or DNA adenine methyltransferase identification (DamID-seq). The transient TF-target interactions captured uncover the early mode-of-action of NIN-LIKE PROTEIN 7 (NLP7), a master regulator of the nitrogen signaling pathway in plants. These transient NLP7 targets captured in root cells using temporal TF perturbation account for 50% of NLP7-regulated genes not detectably bound by NLP7 in planta. Rapid and transient NLP7 binding activates early nitrogen response TFs, which we validate to amplify the NLP7-initiated transcriptional cascade. Our approaches to capture transient TF-target interactions genome-wide can be applied to validate dynamic GRN models for any pathway or organism of interest., Conventional methods cannot reveal transient transcription factors (TFs) and targets interactions. Here, Alvarez et al. capture both stable and transient TF-target interactions by time-series ChIP-seq and/or DamID-seq in a cell-based TF perturbation system and show NLP7 as a master TF to initiate a rapid nitrogen-response cascade.

Plant responses to multiple stimuli must be integrated to trigger transcriptional cascades that lead to changes in plant metabolism and development. Light (L) and nitrogen (N) are two signaling pathways that are intimately connected to each other and to plant energy status. Here, we describe the functional role of the WRKY1 transcription factor in mediating the regulation between L and N signaling pathways in Arabidopsis thaliana. WRKY1 participates in genome-wide transcriptional reprogramming in leaves in response to individual and combined L and N signals. A regulatory network was identified, consisting of 724 genes regulated by WRKY1 and involved in both N and L signaling pathways. The loss of WRKY1 gene function has marked effects on the L and N response of genes involved in N uptake and assimilation (primary metabolism) as well as stress response pathways (secondary metabolism). Our results support a model in which WRKY1 enables plants to activate genes involved in the recycling of cellular carbon resources when L is limiting but N is abundant, and up-regulate amino acid metabolism genes when both L and N are limiting. In this potential energy conservation mechanism, WRKY1 integrates responses to N and light-energy status to trigger changes in plant metabolism.SummaryBased on transcriptome analysis, the WRKY1 transcription factor mediates regulation of nitrogen and light signaling pathways in a potential energy conservation mechanism.

Changes in nutrient dose have dramatic effects on gene expression and development. One outstanding question is whether organisms respond to changes in absolute nutrient amount (moles) vs. its concentration in water (molarity). This question is particularly relevant to plants, as soil drying can alter nutrient concentration, without changing its absolute amount. To compare the effects of amount vs. concentration, we expose rice to a factorial matrix varying the dose of nitrogen (N) and water (W) over a range of combinations, and quantify transcriptome and phenotype responses. Using linear models, we identify distinct dose responses to either N-moles, W-volume, N-molarity (N/W), or their synergistic interaction (N×W). Importantly, genes whose expression patterns are best explained by N-dose and W interactions (N/W or N×W) in seedlings are associated with crop outcomes in replicated field trials. Such N-by-W responsive genes may assist future efforts to develop crops resilient to increasingly arid, low nutrient soils., Scarcity of water and nutrients limit crop yields. Here Swift et al. show that gene expression in rice responds differently to changes in the absolute amount of nitrogen available compared to nitrogen concentration and identify expression profiles associated with crop performance in arid, low-nutrient soils.

The ability to accurately predict the causal relationships from transcription factors to genes would greatly enhance our understanding of transcriptional dynamics. This could lead to applications in which one or more transcription factors could be manipulated to effect a change in genes leading to the enhancement of some desired trait. Here we present a method called OutPredict that constructs a model for each gene based on time series (and other) data and that predicts gene's expression in a previously unseen subsequent time point. The model also infers causal relationships based on the most important transcription factors for each gene model, some of which have been validated from previous physical experiments. The method benefits from known network edges and steady-state data to enhance predictive accuracy. Our results across B. subtilis, Arabidopsis, E.coli, Drosophila and the DREAM4 simulated in silico dataset show improved predictive accuracy ranging from 40% to 60% over other state-of-the-art methods. We find that gene expression models can benefit from the addition of steady-state data to predict expression values of time series. Finally, we validate, based on limited available data, that the influential edges we infer correspond to known relationships significantly more than expected by chance or by state-of-the-art methods.

Plants need to cope with strong variations in the nitrogen content of the soil solution. Although many molecular actors are being discovered concerning how plants perceive NO3- provision, it is less clear how plants recognize a lack of Nitrogen. Indeed, following N removal plants activate their Nitrogen Starvation Response (NSR) being characterized in particular by the activation of very high affinity nitrate transport systems (NRT2.4, NRT2.5) and other sentinel genes such as GDH3. Here we show using a combination of functional genomics (via TF perturbation) and molecular physiology studies, that the GARP Transcription Factors (TFs) belonging the HHO sub-family are important regulators of the NSR through two potential mechanisms. First, HHOs directly repress NRT2.4 and NRT2.5 high-affinity nitrate transporters. Genotypes affected in HHO genes (mutants and overexpressors) display modified high-affinity nitrate transport activities opening interesting perspectives in biotechnology applications. Second, we show that Reactive Oxygen Species (ROS) are important to control NSR in wild type plants and that HRS1 and HHO1 overexpressors are affected in their ROS content, defining a potential feedforward branch of the signaling pathway. Taken together our results define two new classes of molecular actors in the control of NSR including ROS and the first transcription factors to date. This work (i) opens perspectives on a poorly understood nutrient related signaling pathway, and (ii) defines targets for molecular breeding of plants with enhanced NO3- uptake.

Shaping of root architecture is a quintessential developmental response that involves the concerted action of many different cell types, is highly dynamic, and underpins root plasticity. To determine to what extent the environmental regulation of lateral root development is a product of cell-type preferential activities, we tracked transcriptomic responses to two different treatments that both change root development in Arabidopsis thaliana at an unprecedented level of temporal detail. We found that individual transcripts are expressed with a very high degree of temporal and spatial specificity, yet biological processes are commonly regulated, in a mechanism we term response nonredundancy. Using causative gene network inference to compare the genes regulated in different cell types and during responses to nitrogen and a biotic interaction, we found that common transcriptional modules often regulate the same gene families but control different individual members of these families, specific to response and cell type. This reinforces that the activity of a gene cannot be defined simply as molecular function; rather, it is a consequence of spatial location, expression timing, and environmental responsiveness.

Plants form the basis of the food webs that sustain animal life. Exogenous factors, such as nutrients and sunlight, and endogenous factors, such as hormones, cooperate to control both the growth and the development of plants. We assessed how Arabidopsis thaliana integrated nutrient and hormone signaling pathways to control root growth and development by investigating the effects of combinatorial treatment with the nutrients nitrate and ammonium; the hormones auxin, cytokinin, and abscisic acid; and all binary combinations of these factors. We monitored and integrated short-term genome-wide changes in gene expression over hours and longterm effects on root development and architecture over several days. Our analysis revealed trends in nutrient and hormonal signal cross-talk and feedback, including responses that exhibited logic gate behavior, which means that they were triggered only when specific combinations of signals were present. From the data, we developed a multivariate network model comprising the signaling molecules, the early gene expression modulation, and the subsequent changes in root phenotypes. This multivariate network model pinpoints several genes that play key roles in the control of root development and may help understand how eukaryotes manage multifactorial signaling inputs.

Phenotypic plasticity is presumed to be involved in adaptive change toward species diversification. We thus examined how candidate genes underlying natural variation across populations might also mediate plasticity within an individual. Our implementation of an integrative "plasticity space" approach revealed that the root plasticity of a single Arabidopsis accession exposed to distinct environments broadly recapitulates the natural variation "space." Genome-wide association mapping identified the known gene PHOSPHATE 1 (PHO1) and other genes such as Root System Architecture 1 (RSA1) associated with differences in root allometry, a highly plastic trait capturing the distribution of lateral roots along the primary axis. The response of mutants in the Columbia-0 background suggests their involvement in signaling key modulators of root development including auxin, abscisic acid, and nitrate. Moreover, genotype-by-environment interactions for the PHO1 and RSA1 genes in Columbia-0 phenocopy the root allometry of other natural variants. This finding supports a role for plasticity responses in phenotypic evolution in natural environments.

International audience; The dynamic nature of gene regulatory networks allows cells to rapidly respond to environmental change. However, the underlying temporal connections are missed, even in kinetic studies, as transcription factor (TF) binding within at least one time point is required to identify primary targets. The TF-regulated but unbound genes are dismissed as secondary targets. Instead, we report that these genes comprise transient TF-target interactions most relevant to rapid signal transduction. We temporally perturbed a master TF (Basic Leucine Zipper 1, bZIP1) and the nitrogen (N) signal it transduces and integrated TF regulation and binding data from the same cell samples. Our enabling approach could identify primary TF targets based solely on gene regulation, in the absence of TF binding. We uncovered three classes of primary TF targets: (i) poised (TF-bound but not TF-regulated), (ii) stable (TF-bound and TF-regulated), and (iii) transient (TF-regulated but not TF-bound), the largest class. Unexpectedly, the transient bZIP1 targets are uniquely relevant to rapid N signaling in planta, enriched in dynamic N-responsive genes, and regulated by TF and N signal interactions. These transient targets include early N responders nitrate transporter 2.1 and NIN-like protein 3, bound by bZIP1 at 1-5 min, but not at later time points following TF perturbation. Moreover, promoters of these transient targets are uniquely enriched with cis-regulatory motifs coinherited with bZIP1 binding sites, suggesting a recruitment role for bZIP1. This transient mode of TF action supports a classic, but forgotten, "hit-and-run" transcription model, which enables a "catalyst TF" to activate a large set of targets within minutes of signal perturbation.

International audience; Members of the plant NITRATE TRANSPORTER 1/PEPTIDE TRANSPORTER (NRT1/PTR) family display protein sequence homology with the SLC15/PepT/PTR/POT family of peptide transporters in animals. In comparison to their animal and bacterial counterparts, these plant proteins transport a wide variety of substrates: nitrate, peptides, amino acids, dicarboxylates, glucosinolates, IAA, and ABA. The phylogenetic relationship of the members of the NRT1/PTR family in 31 fully sequenced plant genomes allowed the identification of unambiguous clades, defining eight subfamilies. The phylogenetic tree was used to determine a unified nomenclature of this family named NPF, for NRT1/PTR FAMILY. We propose that the members should be named accordingly: NPFX.Y, where X denotes the subfamily and Y the individual member within the species.

International audience; Phenotypic plasticity is presumed to be involved in adaptive change toward species diversification. We thus examined how candidate genes underlying natural variation across populations might also mediate plasticity within an individual. Our implementation of an integrative "plasticity space" approach revealed that the root plasticity of a single Arabidopsis accession exposed to distinct environments broadly recapitulates the natural variation "space." Genome-wide association mapping identified the known gene PHOSPHATE 1 (PHO1) and other genes such as Root System Architecture 1 (RSA1) associated with differences in root allometry, a highly plastic trait capturing the distribution of lateral roots along the primary axis. The response of mutants in the Columbia-0 background suggests their involvement in signaling key modulators of root development including auxin, abscisic acid, and nitrate. Moreover, genotype-by-environment interactions for the PHO1 and RSA1 genes in Columbia-0 phenocopy the root allometry of other natural variants. This finding supports a role for plasticity responses in phenotypic evolution in natural environments.

International audience; : The goal of systems biology is to generate models for predicting how a system will react under untested conditions or in response to genetic perturbations. This paper discusses experimental and analytical approaches to deriving causal relationships in gene regulatory networks.

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.

As sessile organisms, root plasticity enables plants to forage for and acquire nutrients in a fluctuating underground environment. Here, we use genetic and genomic approaches in a “split-root” framework—in which physically isolated root systems of the same plant are challenged with different nitrogen (N) environments—to investigate how systemic signaling affects genome-wide reprogramming and root development. The integration of transcriptome and root phenotypes enables us to identify distinct mechanisms underlying “N economy” (i.e., N supply and demand) of plants as a system. Under nitrate-limited conditions, plant roots adopt an “active-foraging strategy”, characterized by lateral root outgrowth and a shared pattern of transcriptome reprogramming, in response to either local or distal nitrate deprivation. By contrast, in nitrate-replete conditions, plant roots adopt a “dormant strategy”, characterized by a repression of lateral root outgrowth and a shared pattern of transcriptome reprogramming, in response to either local or distal nitrate supply. Sentinel genes responding to systemic N signaling identified by genome-wide comparisons of heterogeneous vs. homogeneous split-root N treatments were used to probe systemic N responses in Arabidopsis mutants impaired in nitrate reduction and hormone synthesis and also in decapitated plants. This combined analysis identified genetically distinct systemic signaling underlying plant N economy: ( i ) N supply, corresponding to a long-distance systemic signaling triggered by nitrate sensing; and ( ii ) N demand, experimental support for the transitive closure of a previously inferred nitrate–cytokinin shoot–root relay system that reports the nitrate demand of the whole plant, promoting a compensatory root growth in nitrate-rich patches of heterogeneous soil.

A novel result of the current research is the development and implementation of a unique functional phylogenomic approach that explores the genomic origins of seed plant diversification. We first use 22,833 sets of orthologs from the nuclear genomes of 101 genera across land plants to reconstruct their phylogenetic relationships. One of the more salient results is the resolution of some enigmatic relationships in seed plant phylogeny, such as the placement of Gnetales as sister to the rest of the gymnosperms. In using this novel phylogenomic approach, we were also able to identify overrepresented functional gene ontology categories in genes that provide positive branch support for major nodes prompting new hypotheses for genes associated with the diversification of angiosperms. For example, RNA interference (RNAi) has played a significant role in the divergence of monocots from other angiosperms, which has experimental support in Arabidopsis and rice. This analysis also implied that the second largest subunit of RNA polymerase IV and V (NRPD2) played a prominent role in the divergence of gymnosperms. This hypothesis is supported by the lack of 24nt siRNA in conifers, the maternal control of small RNA in the seeds of flowering plants, and the emergence of double fertilization in angiosperms. Our approach takes advantage of genomic data to define orthologs, reconstruct relationships, and narrow down candidate genes involved in plant evolution within a phylogenomic view of species' diversification., Author Summary Understanding the genetic and genomic basis of plant diversification has been a major goal of evolutionary biologists since Darwin first pondered his “abominable mystery,” the rapid diversification of the angiosperms in the fossil record. We develop and deploy a functional phylogenomic approach that helps identify genes and biological processes putatively involved in species diversification. We assembled a matrix of 22,833 orthologs from 150 species to reconstruct seed plant phylogenetic relationships and to identify gene sets with a unique evolutionary signal. Our analysis of overrepresented biological processes in these sets narrowed down possible genetic mechanisms underlying plant adaptation and diversification. The phylogenetic relationships we uncovered support the hypothesis that gnetophytes are closely related to the rest of the gymnosperms at the base of the living seed plants. We also found that genes involved in post-transcriptional silencing via RNA interference (RNAi)—increasingly important in understanding plant evolution—are significantly represented early in angiosperm and gymnosperm divergence, with an apparent loss of specific classes of small interfering RNAs (siRNA) in gymnosperms. Our functional phylogenomic approach can be applied to any taxa with available sequences to enhance our knowledge of the evolutionary processes underlying biodiversity in general.

In plants, root nitrate uptake systems are under systemic feedback repression by the N satiety of the whole organism, thus adjusting the N acquisition capacity to the N demand for growth; however, the underlying molecular mechanisms are largely unknown. We previously isolated the Arabidopsis high nitrogen-insensitive 9-1 ( hni9-1 ) mutant, impaired in the systemic feedback repression of the root nitrate transporter NRT2.1 by high N supply. Here, we show that HNI9 encodes Arabidopsis INTERACT WITH SPT6 (AtIWS1), an evolutionary conserved component of the RNA polymerase II complex. HNI9/AtIWS1 acts in roots to repress NRT2.1 transcription in response to high N supply. At a genomic level, HNI9/AtIWS1 is shown to play a broader role in N signaling by regulating several hundred N-responsive genes in roots. Repression of NRT2.1 transcription by high N supply is associated with an HNI9/AtIWS1-dependent increase in histone H3 lysine 27 trimethylation at the NRT2.1 locus. Our findings highlight the hypothesis that posttranslational chromatin modifications control nutrient acquisition in plants.

International audience; ABSTRACT: BACKGROUND: Nitrate, acting as both a nitrogen source and a signaling molecule, controls many aspects of plant development. However, gene networks involved in plant adaptation to fluctuating nitrate environments have not yet been identified. RESULTS: Here we use time-series transcriptome data to decipher gene relationships and consequently to build core regulatory networks involved in Arabidopsis root adaptation to nitrate provision. The experimental approach has been to monitor genome-wide responses to nitrate at 3, 6, 9, 12, 15 and 20 minutes, using Affymetrix ATH1 gene chips. This high-resolution time course analysis demonstrated that the previously known primary nitrate response is actually preceded by a very fast gene expression modulation, involving genes and functions needed to prepare plants to use or reduce nitrate. A state-space model inferred from this microarray time-series data successfully predicts gene behavior in unlearnt conditions. CONCLUSIONS: The experiments and methods allow us to propose a temporal working model for nitrate-driven gene networks. This network model is tested both in silico and experimentally. For example, the over-expression of a predicted gene hub encoding a transcription factor induced early in the cascade indeed leads to the modification of the kinetic nitrate response of sentinel genes such as NIR, NIA2, and NRT1.1, and several other transcription factors. The potential nitrate /hormone connections implicated by this time-series data is also evaluated.

One of the major challenges of plant biology is to understand and model plant molecular networks coordinating growth and development, in response to nutritional cues. Further, the predictions and/or the genetic modifications of these responses would have the potential of providing solutions to tweak

Background: Nitrogen and light are two major regulators of plant metabolism and development. While genes involved in the control of each of these signals have begun to be identified, regulators that integrate gene responses to nitrogen and light signals have yet to be determined. Here, we evaluate the role of bZIP1, a transcription factor involved in light and nitrogen sensing, by exposing wild-type (WT) and bZIP1 T-DNA null mutant plants to a combinatorial space of nitrogen (N) and light (L) treatment conditions and performing transcriptome analysis. We use ANOVA analysis combined with clustering and Boolean modeling, to evaluate the role of bZIP1 in mediating L and N signaling genome-wide.Results: This transcriptome analysis demonstrates that a mutation in the bZIP1 gene can alter the L and/or N-regulation of several gene clusters. More surprisingly, the bZIP1 mutation can also trigger N and/or L regulation of genes that are not normally controlled by these signals in WT plants. This analysis also reveals that bZIP1 can, to a large extent, invert gene regulation (e.g., several genes induced by N in WT plants are repressed by N in the bZIP1 mutant).Conclusion: These findings demonstrate that the bZIP1 mutation triggers a genome-wide de-regulation in response to L and/or N signals that range from i) a reduction of the L signal effect, to ii) unlocking gene regulation in response to L and N combinations. This systems biology approach demonstrates that bZIP1 tunes L and N signaling relationships genome-wide, and can suppress regulatory mechanisms hypothesized to be needed at different developmental stages and/or environmental conditions. Fil: Obertello, Mariana. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular "Dr. Héctor N. Torres"; Argentina. New York University; Estados Unidos Fil: Krouk, Gabriel. New York University; Estados Unidos. Centre National de la Recherche Scientifique; Francia Fil: Katari, Manpreet S.. New York University; Estados Unidos Fil: Runko, Suzan J.. New York University; Estados Unidos Fil: Coruzzi, Gloria M.. New York University; Estados Unidos

Background Genome level analyses have enhanced our view of phylogenetics in many areas of the tree of life. With the production of whole genome DNA sequences of hundreds of organisms and large-scale EST databases a large number of candidate genes for inclusion into phylogenetic analysis have become available. In this work, we exploit the burgeoning genomic data being generated for plant genomes to address one of the more important plant phylogenetic questions concerning the hierarchical relationships of the several major seed plant lineages (angiosperms, Cycadales, Gingkoales, Gnetales, and Coniferales), which continues to be a work in progress, despite numerous studies using single, few or several genes and morphology datasets. Although most recent studies support the notion that gymnosperms and angiosperms are monophyletic and sister groups, they differ on the topological arrangements within each major group. Methodology We exploited the EST database to construct a supermatrix of DNA sequences (over 1,200 concatenated orthologous gene partitions for 17 taxa) to examine non-flowering seed plant relationships. This analysis employed programs that offer rapid and robust orthology determination of novel, short sequences from plant ESTs based on reference seed plant genomes. Our phylogenetic analysis retrieved an unbiased (with respect to gene choice), well-resolved and highly supported phylogenetic hypothesis that was robust to various outgroup combinations. Conclusions We evaluated character support and the relative contribution of numerous variables (e.g. gene number, missing data, partitioning schemes, taxon sampling and outgroup choice) on tree topology, stability and support metrics. Our results indicate that while missing characters and order of addition of genes to an analysis do not influence branch support, inadequate taxon sampling and limited choice of outgroup(s) can lead to spurious inference of phylogeny when dealing with phylogenomic scale data sets. As expected, support and resolution increases significantly as more informative characters are added, until reaching a threshold, beyond which support metrics stabilize, and the effect of adding conflicting characters is minimized.

Background The availability of sequences from whole genomes to reconstruct the tree of life has the potential to enable the development of phylogenomic hypotheses in ways that have not been before possible. A significant bottleneck in the analysis of genomic-scale views of the tree of life is the time required for manual curation of genomic data into multi-gene phylogenetic matrices. Results To keep pace with the exponentially growing volume of molecular data in the genomic era, we have developed an automated technique, ASAP (Automated Simultaneous Analysis Phylogenetics), to assemble these multigene/multi species matrices and to evaluate the significance of individual genes within the context of a given phylogenetic hypothesis. Conclusion Applications of ASAP may enable scientists to re-evaluate species relationships and to develop new phylogenomic hypotheses based on genome-scale data.

Systems biology requires mathematical tools not only to analyse large genomic datasets, but also to explore large experimental spaces in a systematic yet economical way. We demonstrate that two-factor combinatorial design (CD), shown to be useful in software testing, can be used to design a small set of experiments that would allow biologists to explore larger experimental spaces. Further, the results of an initial set of experiments can be used to seed further 'Adaptive' CD experimental designs. As a proof of principle, we demonstrate the usefulness of this Adaptive CD approach by analysing data from the effects of six binary inputs on the regulation of genes in the N-assimilation pathway of Arabidopsis. This CD approach identified the more important regulatory signals previously discovered by traditional experiments using far fewer experiments, and also identified examples of input interactions previously unknown. Tests using simulated data show that Adaptive CD suffers from fewer false positives than traditional experimental designs in determining decisive inputs, and succeeds far more often than traditional or random experimental designs in determining when genes are regulated by input interactions. We conclude that Adaptive CD offers an economical framework for discovering dominant inputs and interactions that affect different aspects of genomic outputs and organismal responses.

For many systems in biology, genes, pathways, or metabolites are regulated or synthesized in response to multiple “input” signals. Herein, we describe how combinatorial design can be used to define a small set of experiments that will effectively explore the effects of all possible combinations

The effect of nutrients on plant growth and development has been studied for over 350 years since the experiments of van Helmont in 1648 (6). Recent studies on nutrient effects in plants have involved separating their role as building blocks of organic matter or cofactors from their potential role

Glutamate dehydrogenase (GDH) is ubiquitous to all organisms, yet its role in higher plants remains enigmatic. To better understand the role of GDH in plant nitrogen metabolism, we have characterized an Arabidopsis mutant (gdh1-1) defective in one of two GDH gene products and have studied GDH1 gene expression. GDH1 mRNA accumulates to highest levels in dark-adapted or sucrose-starved plants, and light or sucrose treatment each repress GDH1 mRNA accumulation. These results suggest that the GDH1 gene product functions in the direction of glutamate catabolism under carbon-limiting conditions. Low levels of GDH1 mRNA present in leaves of light-grown plants can be induced by exogenously supplied ammonia. Under such conditions of carbon and ammonia excess, GDH1 may function in the direction of glutamate biosynthesis. The Arabidopsis gdh-deficient mutant allele gdh1-1 cosegregates with the GDH1 gene and behaves as a recessive mutation. The gdh1-1 mutant displays a conditional phenotype in that seedling growth is specifically retarded on media containing exogenously supplied inorganic nitrogen. These results suggest that GDH1 plays a nonredundant role in ammonia assimilation under conditions of inorganic nitrogen excess. This notion is further supported by the fact that the levels of mRNA for GDH1 and chloroplastic glutamine synthetase (GS2) are reciprocally regulated by light.

Here, we characterize a cDNA encoding a glutamine-dependent asparagine synthetase (ASN1) from Arabidopsis thaliana and assess the effects of metabolic regulation on ASN1 mRNA levels. Sequence analysis shows that the predicted ASN1 peptide contains a purF-type glutamine-binding domain. Southern blot experiments and cDNA clone analysis suggest that ASN1 is the only gene encoding glutamine-dependent asparagine synthetase in A. thaliana. The ASN1 gene is expressed predominantly in shoot tissues, where light has a negative effect on its mRNA accumulation. This negative effect of light on ASN1 mRNA levels was shown to be mediated, at least in part, via the photoreceptor phytochrome. We also investigated whether light-induced changes in nitrogen to carbon ratios might exert a metabolic regulation of the ASN1 mRNA accumulation. These experiments demonstrated that the accumulation of ASN1 mRNA in dark-grown plants is strongly repressed by the presence of exogenous sucrose. Moreover, this sucrose repression of ASN1 expression can be partially rescued by supplementation with exogenous amino acids such as asparagine, glutamine, and glutamate. These findings suggest that the expression of the ASN1 gene is under the metabolic control of the nitrogen to carbon ratio in cells. This is consistent with the fact that asparagine, synthesized by the ASN1 gene product, is a favored compound for nitrogen storage and nitrogen transport in dark-grown plants. We have put forth a working model suggesting that when nitrogen to carbon ratios are high, the gene product of ASN1 functions to re-direct the flow of nitrogen into asparagine, which acts as a shunt for storage and/or long-distance transport of nitrogen.

Here, we monitor the effects of ectopic overexpression of genes for pea asparagine synthetase (AS1) in transgenic tobacco (Nicotiana tabacum). The AS genes of pea and tobacco are normally expressed only during the dark phase of the diurnal growth cycle and specifically in phloem cells. A hybrid gene was constructed in which a pea AS1 cDNA was fused to the cauliflower mosaic virus 35S promoter. The 35S-AS1 gene was therefore ectopically expressed in all cell types in transgenic tobacco and constitutively expressed at high levels in both the light and the dark. Northern analysis demonstrated that the 35S-AS1 transgene was constitutively expressed at high levels in leaves of several independent transformants. Furthermore, amino acid analysis revealed a 10- to 100-fold increase in free asparagine in leaves of transgenic 35S-AS1 plants (construct z127) compared with controls. Plant growth analyses showed increases (although statistically insignificant) in growth phenotype during the vegetative stage of growth in 35S-AS1 transgenic lines. The 35S-AS1 construct was further modified by deletion of the glutamine-binding domain of the enzyme (gln[delta]AS1; construct z167). By analogy to animal AS, we reasoned that inhibition of glutamine-dependent AS activity might enhance the ammonia-dependent AS activity. The 3- to 19-fold increase in asparagine levels in the transgenic plants expressing gln[delta]AS1 compared with wild type suggests that the novel AS holoenzyme present in the transgenic plants (gln[delta]AS1 homodimer) has enhanced ammonia-dependent activity. These data indicate that manipulation of AS expression in transgenic plants causes an increase in nitrogen assimilation into asparagine, which in turn produces effects on plant growth and asparagine biosynthesis.

We have examined the expression of a member of the multigene family encoding the small subunit (rbcS) of ribulose-1,5-bisphosphate carboxylase in various tissues of pea. The rbcS gene, pPS-2.4, was characterized by DNA sequence analysis and 5' and 3' end mapping of its mRNA transcript. rbcS polypeptides were shown to be differentially present in various tissues of light- and dark-grown plants. Northern analysis shows that compared with green leaves, the level of rbcS mRNA is reduced to approximately 50% in pericarps, 8% in petals and seeds, and 1-3% in etiolated leaves, stems, and roots. 5' S1 nuclease mapping of total rbcS mRNA was used to quantitate the relative amount of pPS-2.4 gene-specific transcripts in each tissue. pPS-2.4 mRNA accounts for approximately 30-35% of total rbcS transcripts in green leaves, but only 5-10% in pericarps, 15-20% in seeds, and is below detection in petals and etiolated leaves. We conclude that the pPS-2.4 gene is expressed in a tissue-specific, light-regulated fashion and that transcriptional controls of individual rbcS genes vary.

Background: Histone methylation modifies the epigenetic state of target genes to regulate gene expression in the context of developmental and environmental changes. Previously, we used a positive genetic screen to identify an Arabidopsis mutant, cli186, which was impaired in carbon and light signaling. Here, we report a deletion of the Arabidopsis histone methyltransferase SDG8 in this mutant (renamed sdg8-5), which provides a unique opportunity to study the global function of a specific histone methyltransferase within a multicellular organism. Results: To assess the specific role of SDG8, we examine how the global histone methylation patterns and transcriptome were altered in the sdg8-5 deletion mutant compared to wild type, within the context of transient light and carbon treatments. Our results reveal that the sdg8 deletion is associated with a significant reduction of H3K36me3, preferentially towards the 3′ end of the gene body, accompanied by a reduction in gene expression. We uncover 728 direct targets of SDG8 that have altered methylation in the sdg8-5 mutant and are also bound by SDG8. As a group, this set of SDG8 targets is enriched in specific biological processes including defense, photosynthesis, nutrient metabolism and energy metabolism. Importantly, 64% of these SDG8 targets are responsive to light and/or carbon signals. Conclusions: The histone methyltransferase SDG8 functions to regulate the H3K36 methylation of histones associated with gene bodies in Arabidopsis. The H3K36me3 mark in turn is associated with high-level expression of a specific set of light and/or carbon responsive genes involved in photosynthesis, metabolism and energy production. Fil: Li, Ying. University of New York; Estados Unidos Fil: Mukherjee, Indrani. University of New York; Estados Unidos Fil: Thum, Karen E. University of New York; Estados Unidos Fil: Tanurdzic, Milos. Cold Spring Harbor; Estados Unidos. University of Queensland; Australia Fil: Katari, Manpreet S. University of New York; Estados Unidos Fil: Obertello, Mariana. University of New York; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular "Dr. Héctor N. Torres"; Argentina Fil: Edwards, Molly B. University of New York; Estados Unidos Fil: McCombie, W Richard. Cold Spring Harbor; Estados Unidos Fil: Martienssen, Robert A. Cold Spring Harbor; Estados Unidos Fil: Coruzzi, Gloria M. University of New York; Estados Unidos