Search

Brassinosteroids (BRs) and Target of Rapamycin Complex (TORC) are two major actors coordinating plant growth and stress responses. Brassinosteroids function through a signaling pathway to extensively regulate gene expression and TORC is known to regulate translation and autophagy. Recent studies have revealed connections between these two pathways, but a system-wide view of their interplay is still missing. We quantified the level of 23 975 transcripts, 11 183 proteins, and 27 887 phosphorylation sites in wild-type Arabidopsis thaliana and in mutants with altered levels of either BRASSINOSTEROID INSENSITIVE 2 (BIN2) or REGULATORY ASSOCIATED PROTEIN OF TOR 1B (RAPTOR1B), two key players in BR and TORC signaling, respectively. We found that perturbation of BIN2 or RAPTOR1B levels affects a common set of gene-products involved in growth and stress responses. Furthermore, we used the multi-omic data to reconstruct an integrated signaling network. We screened 41 candidate genes identified from the reconstructed network and found that loss of function mutants of many of these proteins led to an altered BR response and/or modulated autophagy activity. Altogether, these results establish a predictive network that defines different layers of molecular interactions between BR- or TORC-regulated growth and autophagy.

Plants must tightly regulate iron (Fe) sensing, acquisition, transport, mobilization, and storage to ensure sufficient levels of this essential micronutrient. POPEYE (PYE) is an iron responsive transcription factor that positively regulates the iron deficiency response, while also repressing genes essential for maintaining iron homeostasis. However, little is known about how PYE plays such contradictory roles. Under iron-deficient conditions, pPYE:GFP accumulates in the root pericycle while pPYE:PYE–GFP is localized to the nucleus in all Arabidopsis (Arabidopsis thaliana) root cells, suggesting that PYE may have cell-specific dynamics and functions. Using scanning fluorescence correlation spectroscopy and cell-specific promoters, we found that PYE–GFP moves between different cells and that the tendency for movement corresponds with transcript abundance. While localization to the cortex, endodermis, and vasculature is required to manage changes in iron availability, vasculature and endodermis localization of PYE–GFP protein exacerbated pye-1 defects and elicited a host of transcriptional changes that are detrimental to iron mobilization. Our findings indicate that PYE acts as a positive regulator of iron deficiency response by regulating iron bioavailability differentially across cells, which may trigger iron uptake from the surrounding rhizosphere and impact root energy metabolism.

Cross-regulation between hormone signaling pathways is indispensable for plant growth and development. However, the molecular mechanisms by which multiple hormones interact and co-ordinate activity need to be understood. Here, we generated a cross-regulation network explaining how hormone signals are integrated from multiple pathways in etiolated Arabidopsis (Arabidopsis thaliana) seedlings. To do so we comprehensively characterized transcription factor activity during plant hormone responses and reconstructed dynamic transcriptional regulatory models for six hormones; abscisic acid, brassinosteroid, ethylene, jasmonic acid, salicylic acid and strigolactone/karrikin. These models incorporated target data for hundreds of transcription factors and thousands of protein-protein interactions. Each hormone recruited different combinations of transcription factors, a subset of which were shared between hormones. Hub target genes existed within hormone transcriptional networks, exhibiting transcription factor activity themselves. In addition, a group of MITOGEN-ACTIVATED PROTEIN KINASES (MPKs) were identified as potential key points of cross-regulation between multiple hormones. Accordingly, the loss of function of one of these (MPK6) disrupted the global proteome, phosphoproteome and transcriptome during hormone responses. Lastly, we determined that all hormones drive substantial alternative splicing that has distinct effects on the transcriptome compared with differential gene expression, acting in early hormone responses. These results provide a comprehensive understanding of the common features of plant transcriptional regulatory pathways and how cross-regulation between hormones acts upon gene expression.

Myosins are evolutionarily conserved motor proteins that interact with actin filaments to regulate organelle transport, cytoplasmic streaming and cell growth. Plant-specific Class XI myosin proteins direct cell division and root organogenesis. However, the roles of plantspecific Class VIII myosin proteins in plant growth and development are less understood. Here, we investigated the function of an auxin-regulated Class VIII myosin, Arabidopsis thaliana Myosin 1 (ATM1), using genetics, transcriptomics, and live cell microscopy.ATM1is expressed in the primary root, adventitious roots and throughout lateral root development. ATM1 is a plasma membrane localized protein that is enriched in actively dividing cells in the root apical meristem (RAM). Loss ofATM1function results in impaired primary root growth due to decreased RAM size and reduced cell proliferation in a sugar-dependent manner. InATM1loss-of-function roots, columella reporter gene expression is diminished, and fewer columella stem cell divisions occur. In addition,atm1-1roots displayed reduced auxin responses and auxin marker gene expression. Complementation ofatm1-1with a tagged ATM1 driven under the nativeATM1promoter restored root growth and cell cycle progression in the root meristem. Collectively, these results provide novel evidence that ATM1 functions to influence cell proliferation and columella differentiation in primary roots in response to auxin and sugar cues.

Brassinosteroids (BRs) regulate plant growth, development, and stress responses by activating the core transcription factor BRI1-EMS-SUPPRESSOR1 (BES1), whose degradation occurs through the proteasome and autophagy pathways. The E3 ubiquitin ligase(s) that modify BES1 for autophagy-mediated degradation remain to be fully defined. Here, we identified an F-box family E3 ubiquitin ligase named BES1-ASSOCIATED F-BOX1 (BAF1) in Arabidopsis thaliana. BAF1 interacts with BES1 and mediates its ubiquitination and degradation. Our genetic data demonstrated that BAF1 inhibits BR signaling in a BES1-dependent manner. Moreover, BAF1 targets BES1 for autophagic degradation in a selective manner. BAF1-triggered selective autophagy of BES1 depends on the ubiquitin binding receptor DOMINANT SUPPRESSOR OF KAR2 (DSK2). Sucrose starvation-induced selective autophagy of BES1, but not bulk autophagy, was significantly compromised in baf1 mutant and BAF1-ΔF (BAF1 F-box decoy) overexpression plants, but clearly increased by BAF1 overexpression. The baf1 and BAF1-ΔF overexpression plants had increased BR-regulated growth but were sensitive to long-term sucrose starvation, while BAF1 overexpression plants had decreased BR-regulated growth but were highly tolerant of sucrose starvation. Our results not only established BAF1 as an E3 ubiquitin ligase that targets BES1 for degradation through selective autophagy pathway, but also revealed a mechanism for plants to reduce growth during sucrose starvation.

The receptor kinase FERONIA (FER) is a versatile regulator of plant growth and development, biotic and abiotic stress responses, and reproduction. To gain new insights into the molecular interplay of these processes and to identify new FER functions, we carried out quantitative transcriptome, proteome, and phosphoproteome profiling of Arabidopsis (Arabidopsis thaliana) wild-type and fer-4 loss-of-function mutant plants. Gene ontology terms for phytohormone signaling, abiotic stress, and biotic stress were significantly enriched among differentially expressed transcripts, differentially abundant proteins, and/or misphosphorylated proteins, in agreement with the known roles for FER in these processes. Analysis of multiomics data and subsequent experimental evidence revealed previously unknown functions for FER in endoplasmic reticulum (ER) body formation and glucosinolate biosynthesis. FER functions through the transcription factor NAI1 to mediate ER body formation. FER also negatively regulates indole glucosinolate biosynthesis, partially through NAI1. Furthermore, we found that a group of abscisic acid (ABA)-induced transcription factors is hypophosphorylated in the fer-4 mutant and demonstrated that FER acts through the transcription factor ABA INSENSITIVE5 (ABI5) to negatively regulate the ABA response during cotyledon greening. Our integrated omics study, therefore, reveals novel functions for FER and provides new insights into the underlying mechanisms of FER function.

The acquisition of quantitative information on plant development across a range of temporal and spatial scales is essential to understand the mechanisms of plant growth. Recent years have shown the emergence of imaging methodologies that enable the capture and analysis of plant growth, from the dynamics of molecules within cells to the measurement of morphometricand physiological traits in field-grown plants. In some instances, these imaging methods can be parallelized across multiple samples to increase throughput. When high throughput is combined with high temporal and spatial resolution, the resulting image-derived data sets could be combined with molecular large-scale data sets to enable unprecedented systems-level computational modeling. Such image-driven functional genomics studies may be expected to appear at an accelerating rate in the near future given the early success of the foundational efforts reviewed here. We present new imaging modalities and review how they have enabled a better understanding of plant growth from the microscopic to the macroscopic scale.

Eukaryotic precursor mRNAs often harbor noncoding introns that must be removed prior to translation. Accurate splicing of precursor messenger RNA depends on placement and assembly of small nuclear ribonucleoprotein (snRNP) sub-complexes of the spliceosome. Yeast (Saccharomyces cerevisiae) studies established a role in splice-site selection for PRE-RNA PROCESSING8 (PRP8), a conserved spliceosome scaffolding protein of the U5 snRNP. However, analogous splice-site selection studies in multicellular eukaryotes are lacking. Such studies are crucial for a comprehensive understanding of alternative splicing, which is extensive in plants and animals but limited in yeast. In this work, we describe an Arabidopsis (Arabidopsis thaliana) prp8a mutant that modulates splice-site selection. We isolated prp8a-14 from a screen for suppressors of pex14-6, which carries a splice-site mutation in the PEROXIN14 (PEX14) peroxisome biogenesis gene. To elucidate Arabidopsis PRP8A function in spliceosome fidelity, we combined prp8a-14 with various pex14 splice-site mutations and monitored the double mutants for physiological and molecular consequences of dysfunctional and functional peroxisomes that correspond to impaired and recovered splicing, respectively. prp8a-14 restored splicing and PEX14 function to alleles with mutations in the exonic guanine of the 5′-splice site but did not restore splicing or function to alleles with mutations in the intronic guanine of 5′- or 3′-splice sites. We used RNA-seq to reveal the systemic impact of prp8a-14 and found hundreds of differentially spliced transcripts and thousands of transcripts with significantly altered levels. Among differentially spliced transcripts, prp8a-14 significantly altered 5′- and 3′-splice-site utilization to favor sites resulting in shorter introns. This study provides a genetic platform for probing splicing in plants and hints at a role for plant PRP8 in splice-site selection.

Brassinosteroids (BR) and Target of Rapamycin Complex (TORC) are two major actors coordinating plant growth and stress responses. BRs function through a signaling pathway to extensively regulate gene expression and TORC is known to regulate translation and autophagy. Recent studies revealed that these two pathways crosstalk, but a system-wide view of their interplay is still missing. Thus, we quantified the level of 23,975 transcripts, 11,183 proteins, and 27,887 phosphorylation sites in wild-type Arabidopsis and in mutants with altered levels of either BRASSINOSTEROID INSENSITIVE 2 (BIN2) or REGULATORY ASSOCIATED PROTEIN OF TOR 1B (RAPTOR1B), two key players in BR and TORC signaling, respectively. We found that perturbation of BIN2 or RAPTOR1B levels affects a common set of gene-products involved in growth and stress responses. Furthermore, we used the multi-omic data to reconstruct an integrated signaling network. We screened 41 candidate genes identified from the reconstructed network and found that loss of function mutants of many of these proteins led to an altered BR response and/or modulated autophagy activity. Altogether, these results establish a predictive network that defines different layers of molecular interactions between BR-or TORC-regulated growth and autophagy.

flg22 is a 22-amino peptide released from bacterial flagellin, a Microbe-Associated Molecular Pattern (MAMP) that is recognized by the plant cell as a signal indicating that bacteria are present. On its own, flg22 initiates a rapid increase in cytoplasmic calcium, extracellular reactive oxygen species, and activation of a Mitogen Activated Protein Kinase (MAPK) cascade, all of which are activated within 15 minutes after the cell perceives flg22. Here we show a massive change in protein abundance and phosphorylation state of the Arabidopsis root cell proteome within this 15-minute duration in wildtype and a mutant deficient in G-protein coupled signaling. Integration of phosphoproteome with protein-protein interactome data followed by network topology analyses discovered that many of the flg22-induced phosphoproteome changes fall on proteins that comprise the G protein interactome and on the most highly populated hubs of the immunity network. Approximately 95% of the phosphorylation changes in the G-protein interactome depend on a functional heterotrimeric G protein complex, some occur on proteins that interact directly with components of G-coupled signal transduction. One of these is ATBα, a substrate-recognition sub-unit of the PP2A Ser/Thr phosphatase and an interactor to Arabidopsis thaliana REGULATOR OF G SIGNALING 1 protein (AtRGS1), a 7-transmembrane spanning modulator of the nucleotide-binding state of the core G protein complex. AtRGS1 is phosphorylated by BAK1, a component of the flg22 receptor, to initiate AtRGS1 endocytosis. A null mutation of ATBα confers high basal endocytosis of AtRGS1, suggesting sustained phosphorylated status. Loss of ATBα confers traits associated with loss of AtRGS1. Because the basal level of AtRGS1 is lower in the atbα null mutant in a proteasome-dependent manner, we propose that phosphorylation-dependent endocytosis of AtRGS1 is part of a mechanism to degrade AtRGS1 which then sustains activation of the G protein complex. Thus, the role of ATBα is now established as a central component of phosphorylation-dependent regulation of system dynamics in innate immunity.

Understanding the systems-level actions of transcriptional responses to hormones provides insight into how the genome is reprogrammed in response to environmental stimuli. Here, we investigated the signalling pathway of the hormone jasmonic acid (JA), which controls a plethora of critically important processes in plants and is orchestrated by the transcription factor MYC2 and its closest relatives in Arabidopsis thaliana. We generated an integrated framework of the response to JA, which spans from the activity of master and secondary regulatory transcription factors, through gene expression outputs and alternative splicing, to protein abundance changes, protein phosphorylation and chromatin remodelling. We integrated time-series transcriptome analysis with (phospho)proteomic data to reconstruct gene regulatory network models. These enabled us to predict previously unknown points of crosstalk of JA to other signalling pathways and to identify new components of the JA regulatory mechanism, which we validated through targeted mutant analysis. These results provide a comprehensive understanding of how a plant hormone remodels cellular functions and plant behaviour, the general principles of which provide a framework for analyses of cross-regulation between other hormone and stress signalling pathways., M.Z. was supported by a Deutsche Forschungsgemeinschaft (DFG) research fellowship (Za-730/1-1) and by the Salk Pioneer Postdoctoral Endowment Fund. M.G.L. was supported by an EU Marie Curie FP7 International Outgoing Fellowship (252475). In addition, this work was supported by the Mass Spectrometry Core of the Salk Institute with funding from NIH-NCI CCSG (P30 014195) and the Helmsley Center for Genomic Medicine. This work was supported by grants from the National Science Foundation (NSF) (MCB-1818160 and IOS-1759023 to J.W.W., MCB-1024999 to J.R.E.), the National Institutes of Health (R01GM120316), the Division of Chemical Sciences, Geosciences, and Biosciences, the Office of Basic Energy Sciences of the US Department of Energy (DE-FG02-04ER15517), and the Gordon and Betty Moore Foundation (GBMF3034). Research in the lab of R.S. was supported by grant BIO2016-77216-R (MINECO/FEDER) from the Ministry of Economy, Industry and Competitiveness.

Recent advances in single-cell proteomics for animal systems could be adapted for plants to increase our understanding of plant development, response to stimuli, and cell-to-cell signaling.

Brassinosteroids (BR) and Target of Rapamycin Complex (TORC) are two major processes coordinating plant growth and stress responses. BRs function through a signaling pathway to extensively regulate gene expression and TORC is known to regulate translation and autophagy. Recent studies revealed that these two pathways crosstalk, but a system-wide view of their interplay is still missing. Thus, we performed transcriptome, proteome, and phosphoproteome profiling of Arabidopsis mutants with altered levels of either BIN2 or RAPTOR1B, two key players in BR and TORC signaling, respectively. We found that perturbation of BIN2 or RAPTOR1B levels affects a common set of gene-products involved in growth and stress responses. Additionally, we performed Multiplexed Assay for Kinase Specificity (MAKS), which provided a system-wide view of direct BIN2 substrates. Furthermore, phosphoproteomic data was used to reconstruct a kinase-signaling network and to identify novel proteins dependent on BR and/or TORC signaling pathways. Loss of function mutants of many of these proteins led to an altered BR response and/or modulated autophagy activity. Altogether, these results provide genome-wide evidence for crosstalk between BR and TORC signaling and established a kinase signaling network that defines the molecular mechanisms of BR and TORC interactions in the regulation of plant growth/stress balance.

Protein activity, abundance, and stability can be regulated by posttranslational modification including ubiquitination. Ubiquitination is conserved among eukaryotes and plays a central role in modulating cellular function and yet we lack comprehensive catalogs of proteins that are modified by ubiquitin in plants. In this study, we describe an antibody-based approach to enrich peptides containing the di-glycine (diGly) remnant of ubiquitin and coupled that with isobaric labeling to enable quantification, from up to 16-multiplexed samples, for plant tissues. Collectively, we identified 7,130 diGly-modified lysine residues sites arising from 3,178 proteins in Arabidopsis primary roots. These data include ubiquitin proteasome dependent ubiquitination events as well as ubiquitination events associated with auxin treatment. Gene Ontology analysis indicated that ubiquitinated proteins are associated with numerous biological processes including hormone signaling, plant defense, protein homeostasis, and root morphogenesis. We determined the ubiquitinated lysine residues that directly regulate the stability of the transcription factors CRYPTOCHROME-INTERACTING BASIC-HELIX-LOOP-HELIX 1 (CIB1), CIB1 LIKE PROTEIN 2 (CIL2), and SENSITIVE TO PROTON RHIZOTOXICITY (STOP1) using site directed mutagenesis and in vivo degradation assays. These comprehensive site-level ubiquitinome profiles provide a wealth of data for future studies related to modulation of biological processes mediated by this posttranslational modification in plants.

Significance Proper elaboration of the plant body plan requires that cell division patterns are coordinated during development in complex tissues. Activation of cell cycle machinery is critical for this process, but it is not clear how or if this links to cell-to-cell communication networks that are important during development. Here we show that key cell divisions that generate the plant root are controlled by cell-to-cell signaling peptides which act through plant-specific receptor kinases to control expression of a specific cyclinD cell cycle regulatory gene. We show that cyclinD gene expression depends on both receptor signaling and the SHORT-ROOT transcription factor to ensure timely and robust cell division patterns., Cell division is often regulated by extracellular signaling networks to ensure correct patterning during development. In Arabidopsis, the SHORT-ROOT (SHR)/SCARECROW (SCR) transcription factor dimer activates CYCLIND6;1 (CYCD6;1) to drive formative divisions during root ground tissue development. Here, we show plasma-membrane-localized BARELY ANY MERISTEM1/2 (BAM1/2) family receptor kinases are required for SHR-dependent formative divisions and CYCD6;1 expression, but not SHR-dependent ground tissue specification. Root-enriched CLE ligands bind the BAM1 extracellular domain and are necessary and sufficient to activate SHR-mediated divisions and CYCD6;1 expression. Correspondingly, BAM-CLE signaling contributes to the restriction of formative divisions to the distal root region. Additionally, genetic analysis reveals that BAM-CLE and SHR converge to regulate additional cell divisions outside of the ground tissues. Our work identifies an extracellular signaling pathway regulating formative root divisions and provides a framework to explore this pathway in patterning and evolution.

Stem cells give rise to the entirety of cells within an organ. Maintaining stem cell identity and coordinately regulating stem cell divisions is crucial for proper development. In plants, mobile proteins, such as WOX5 and SHR, regulate divisions in the root stem cell niche (SCN). However, how these proteins coordinately function to establish systemic behavior is not well understood. We propose a non-cell autonomous role for WOX5 in the CEI and identify a regulator, AN3/GIF1, that coordinates CEI divisions. Here we show with a multiscale hybrid model integrating ODEs and agent-based modeling that QC and CEI divisions have different dynamics. Specifically, by combining continuous models to describe regulatory networks and agent-based rules, we model systemic behavior, which led us to predict cell-type-specific expression dynamics of SHR, SCR, WOX5, AN3, and CYCD6;1, and experimentally validate CEI cell divisions. Conclusively, our results show an interdependency between CEI and QC divisions.Thumbnail image

Stem cells divide and differentiate to form all of the specialized cell types in a multicellular organism. In the Arabidopsis root, stem cells are maintained in an undifferentiated state by a less mitotically active population of cells called the quiescent center (QC). Determining how the QC regulates the surrounding stem cell initials, or what makes the QC fundamentally different from the actively dividing initials, is important for understanding how stem cell divisions are maintained. Here we gained insight into the differences between the QC and the cortex endodermis initials (CEI) by studying the mobile transcription factor SHORTROOT (SHR) and its binding partner SCARECROW (SCR). We constructed an ordinary differential equation model of SHR and SCR in the QC and CEI which incorporated the stoichiometry of the SHR-SCR complex as well as upstream transcriptional regulation of SHR and SCR. Our model prediction, coupled with experimental validation, showed that high levels of the SHR-SCR complex are associated with more CEI division but less QC division. Furthermore, our model prediction allowed us to propose the putative upstream SHR regulators SEUSS and WUSCHEL-RELATED HOMEOBOX 5 and to experimentally validate their roles in QC and CEI division. In addition, our model established the timing of QC and CEI division and suggests that SHR repression of QC division depends on formation of the SHR homodimer. Thus, our results support that SHR-SCR protein complex stoichiometry and regulation of SHR transcription modulate the division timing of two different specialized cell types in the root stem cell niche.

Predicting gene regulatory networks (GRNs) from expression profiles is a common approach for identifying important biological regulators. Despite the increased use of inference methods, existing computational approaches often do not integrate RNA-sequencing data analysis, are not automated or are restricted to users with bioinformatics backgrounds. To address these limitations, we developed tuxnet, a user-friendly platform that can process raw RNA-sequencing data from any organism with an existing reference genome using a modified tuxedo pipeline (hisat 2 + cufflinks package) and infer GRNs from these processed data. tuxnet is implemented as a graphical user interface and can mine gene regulations, either by applying a dynamic Bayesian network (DBN) inference algorithm, genist, or a regression tree-based pipeline, rtp-star. We obtained time-course expression data of a PERIANTHIA (PAN) inducible line and inferred a GRN using genist to illustrate the use of tuxnet while gaining insight into the regulations downstream of the Arabidopsis root stem cell regulator PAN. Using rtp-star, we inferred the network of ATHB13, a downstream gene of PAN, for which we obtained wild-type and mutant expression profiles. Additionally, we generated two networks using temporal data from developmental leaf data and spatial data from root cell-type data to highlight the use of tuxnet to form new testable hypotheses from previously explored data. Our case studies feature the versatility of tuxnet when using different types of gene expression data to infer networks and its accessibility as a pipeline for non-bioinformaticians to analyze transcriptome data, predict causal regulations, assess network topology and identify key regulators.

Cell type-specific gene expression profiles are useful for understanding genes that are important for the development of different tissues and organs. Here, we describe how to perform fluorescence-activated cell sorting (FACS) on Arabidopsis root protoplasts to isolate specific cell types in the root. We then detail how to extract and process RNA from a very low number of cells (≥40 cells) for RNA sequencing (RNA seq). Finally, we describe how to process RNA seq data using TopHat and how to identify differentially expressed genes using PoissonSeq.

The Arabidopsis root meristem consists of populations of stem cells that surround the mitotically less active cells known as the Quiescent Center (QC). The QC maintains the stem cells in a non-cell-autonomous manner through the function of the transcription factor (TF) WUSCHEL-RELATED HOMEOBOX5 (WOX5), which is required for columella stem cell (CSC) maintenance. However, whether WOX5 has a regulatory role in any other adjacent stem cells is less understood. To this end, we identified a set of TFs downstream of WOX5 in both QC and Cortex Endodermis Initial (CEI) cells. We then utilized Gene Regulatory Network (GRN) inference to identify GRF-INTERACTING FACTOR 1 (GIF1) as a key gene involved in positive feedback and feedforward loops with WOX5 as well as another stem cell regulator, PERIANTHIA (PAN). Finally, we constructed an ordinary differential equation model based on this inferred GRN to simulate GIF1, PAN, and WOX5 expression over time, which suggests the precise temporal expression of WOX5 and GIF1 is important to sustain QC function.

Predicting gene regulatory networks (GRNs) from gene expression profiles has become a common approach for identifying important biological regulators. Despite the increase in the use of inference methods, existing computational approaches do not integrate RNA-sequencing data analysis, are often not automated, and are restricted to users with bioinformatics and programming backgrounds. To address these limitations, we have developed TuxNet, an integrated user-friendly platform, which, with just a few selections, allows to process raw RNA-sequencing data (using the Tuxedo pipeline) and infer GRNs from these processed data. TuxNet is implemented as a graphical user interface and, using expression data from any organism with an existing reference genome, can mine the regulations among genes either by applying a dynamic Bayesian network inference algorithm, GENIST, or a regression tree-based pipeline that uses spatiotemporal data, RTP-STAR. To illustrate the use of TuxNet while getting insight into the regulatory cascade downstream of the Arabidopsis root stem cell regulator PERIANTHIA (PAN), we obtained time course gene expression data of a PAN inducible line and inferred a GRN using GENIST. Using RTP-STAR, we then inferred the network of a PAN secondary downstream gene, ATHB13, for which we obtained wildtype and mutant expression profiles. Our case studies feature the versatility of TuxNet to infer networks using different types of gene expression data (i.e time course and steady-state data) as well as how inference networks are used to identify important regulators.SUMMARYTuxNet offers a simple interface for non-computational biologists to infer GRNs from raw RNA-seq data.

Morphogen-mediated patterning is a highly dynamic developmental process. To obtain an accurate understanding of morphogen gradients, biophysical parameters such as protein diffusivities must be quantifiedin vivo. The dorsal-ventral (DV) patterning of earlyDrosophilaembryos by the NF-κB homolog Dorsal (Dl) is an excellent system for understanding morphogen gradient formation. Dl gradient formation is controlled by the inhibitor Cactus/IκB (Cact), which regulates the nuclear import and diffusion of Dl protein. However, quantitative measurements of spatiotemporal Dl movement are currently lacking. Here, we use scanning fluorescence correlation spectroscopy to quantify the mobility of Dl. We find that the diffusivity of Dl varies along the DV axis, with lowest diffusivities on the ventral side, and the DV asymmetry in diffusivity is exclusive to the nuclei. Moreover, we also observe that nuclear export rates are lower in the ventral and lateral regions of the embryo. Both cross correlation spectroscopy measurements and a computational model of Dl/DNA binding suggest that DNA binding of Dl, which is more prevalent on the ventral side of the embryo, is correlated to a lower diffusivity and nuclear export rate. We propose that the variation in Dl/DNA binding along the DV axis is dependent on Cact binding Dl, which prevents Dl from binding DNA in dorsal and lateral regions of the embryo. Thus, our results highlight the complexity of morphogen gradient dynamics and the need for quantitative measurements of biophysical interactions in such systems.

How plants determine the final size of growing cells is an important, yet unresolved, issue. Root hairs provide an excellent model system with which to study this as their final cell size is remarkably constant under constant environmental conditions. Previous studies have demonstrated that a basic helix-loop helix transcription factor ROOT HAIR DEFECTIVE 6-LIKE 4 (RSL4) promotes root hair growth, but how hair growth is terminated is not known. In this study, we demonstrate that a trihelix transcription factor GT-2-LIKE1 (GTL1) and its homolog DF1 repress root hair growth in Arabidopsis. Our transcriptional data, combined with genome-wide chromatin-binding data, show that GTL1 and DF1 directly bind the RSL4 promoter and regulate its expression to repress root hair growth. Our data further show that GTL1 and RSL4 regulate each other, as well as a set of common downstream genes, many of which have previously been implicated in root hair growth. This study therefore uncovers a core regulatory module that fine-tunes the extent of root hair growth by the orchestrated actions of opposing transcription factors.

Cell type-specific gene expression profiles are useful for understanding genes that are important for the development of different tissues and organs. Here, we describe how to perform fluorescence-activated cell sorting (FACS) on Arabidopsis root protoplasts to isolate specific cell types in the root. We then detail how to extract and process RNA from a very low number of cells (≥40 cells) for RNA sequencing (RNA seq). Finally, we describe how to process RNA seq data using TopHat and how to identify differentially expressed genes using PoissonSeq.

As sessile organisms, plants continually modify their growth to adapt to changes in their environment. Here we show that significant changes in plasmodesmatal permeability underlie root responses to nutrient stress., Both plants and animals must contend with changes in their environment. The ability to respond appropriately to these changes often underlies the ability of the individual to survive. In plants, an early response to environmental stress is an alteration in plasmodesmatal permeability with accompanying changes in cell to cell signaling. However, the ways in which plasmodesmata are modified, the molecular players involved in this regulation, and the biological significance of these responses are not well understood. Here, we examine the effects of nutrient scarcity and excess on plasmodesmata-mediated transport in the Arabidopsis thaliana root and identify two CALLOSE SYNTHASES and two β-1,3-GLUCANASES as key regulators of these processes. Our results suggest that modification of plasmodesmata-mediated signaling underlies the ability of the plant to maintain root growth and properly partition nutrients when grown under conditions of excess nutrients.

How plants determine the final size of growing cells is an important, yet unresolved, issue. Root hairs provide an excellent model system with which to study this as their final cell size is remarkably constant under constant environmental conditions. Previous studies have demonstrated that a basic helix-loop helix transcription factor ROOT HAIR DEFECTIVE 6-LIKE 4 (RSL4) promotes root hair growth, but how hair growth is terminated is not known. In this study, we demonstrate that a trihelix transcription factor GT-2-LIKE1 (GTL1) and its homolog DF1 repress root hair growth in Arabidopsis. Our transcriptional data, combined with genome-wide chromatin-binding data, show that GTL1 and DF1 directly bind the RSL4 promoter and regulate its expression to repress root hair growth. Our data further show that GTL1 and RSL4 regulate each other, as well as a set of common downstream genes, many of which have previously been implicated in root hair growth. This study therefore uncovers a core regulatory module that fine-tunes the extent of root hair growth by the orchestrated actions of opposing transcription factors., Summary: Arabidopsis gtl1 df1 double mutants and tissue-specific overexpression of GTL1 and DF1 demonstrate that both GTL1 and DF1 negatively regulate root hair growth by directly repressing RSL4.

Identifying the transcription factors (TFs) and associated networks involved in stem cell regulation is key for understanding the initiation and growth of plant tissues and organs. Although many TFs have been shown to have a role in the Arabidopsis root stem cells, a comprehensive view of the transcriptional signature of the stem cells is lacking. In this work, we used spatial and temporal transcriptomic data to predict interactions among the genes involved in stem cell regulation. For this, we transcriptionally profiled several stem cell populations and developed a gene regulatory network (GRN) inference algorithm that combines clustering with Dynamic Bayesian Network (DBN) inference. We leveraged the topology of our networks to infer potential key regulators. The results presented in this work show that our combination of molecular biology approaches, computational biology and mathematical modeling was key to identify candidate factors that function in the stem cells. Specifically, through experimental validation and mathematical modeling, we identified PERIANTHIA (PAN) as an important molecular regulator of quiescent center (QC) function.

Scanning fluorescence correlation spectroscopy (scanning FCS) can be used to determine protein movement, oligomerization state, and protein-protein interaction. Here, we describe how to use the scanning FCS techniques of raster image correlation spectroscopy (RICS) and pair correlation function (pCF) to determine the rate and direction of protein movement. In addition, we detail how number and brightness (NB) and cross-correlation analyses can be used to determine oligomerization state and binding ratios of protein complexes. We specifically describe how to acquire suitable images for scanning FCS analysis using the model plant Arabidopsis and how to perform the various analyses using the SimFCS software.

The phytohormone auxin plays crucial roles in nearly every aspect of plant growth and development. The AUXIN RESPONSE FACTOR (ARF) transcription factor family regulates auxin-responsive gene expression and exhibit nuclear localization in regions of high auxin responsiveness. Here we show that the ARF7 and ARF19 proteins accumulate in micron-sized assemblies within the cytoplasm of tissues with attenuated auxin responsiveness. We found that the intrinsically disordered middle region and the folded PB1 interaction domain of ARFs drive protein assembly formation. Mutation of a single lysine within the PB1 domain abrogates cytoplasmic assemblies, promotes ARF nuclear localization, and results in an altered transcriptome and morphological defects. Our data suggest a model in which ARF nucleo-cytoplasmic partitioning regulates auxin responsiveness, thus providing a mechanism for cellular competence for auxin signaling.

It is known that auxin induces rapid gene expression changes throughout plant development, but how these transcriptional responses relate to changes in protein abundance is not well characterized. This report identifies early auxin responsive proteins in whole Arabidopsis seedlings using an isobaric tags for relative and absolute quantification-based quantitative proteomics approach. Approximately 25% of the detected proteins (1045 out of 4257 proteins) are auxin responsive, which is in line with the central role of auxin in the regulation of plant growth and development. Several well-known auxin pathway proteins are identified as differentially expressed, validating this quantitative proteomics approach. Additionally, functional categorization of these auxin responsive proteins indicates that rapid and complex metabolic changes occur in seedlings in response to auxin, including lipid metabolism. Altogether, these data describe novel auxin-regulated proteins and are an excellent resource for identifying new downstream signaling components related to auxin-mediated plant growth and development.

Scanning fluorescence correlation spectroscopy (scanning FCS) can be used to determine protein movement, oligomerization state, and protein-protein interaction. Here, we describe how to use the scanning FCS techniques of raster image correlation spectroscopy (RICS) and pair correlation function (pCF) to determine the rate and direction of protein movement. In addition, we detail how number and brightness (N&B) and cross-correlation analyses can be used to determine oligomerization state and binding ratios of protein complexes. We specifically describe how to acquire suitable images for scanning FCS analysis using the model plant Arabidopsis and how to perform the various analyses using the SimFCS software.

Identifying the transcription factors (TFs) and associated networks involved in stem cell regulation is essential for understanding the initiation and growth of plant tissues and organs. Although many TFs have been shown to have a role in the Arabidopsis root stem cells, a comprehensive view of the transcriptional signature of the stem cells is lacking. In this work, we used spatial and temporal transcriptomic data to predict interactions among the genes involved in stem cell regulation. To accomplish this, we transcriptionally profiled several stem cell populations and developed a gene regulatory network inference algorithm that combines clustering with dynamic Bayesian network inference. We leveraged the topology of our networks to infer potential major regulators. Specifically, through mathematical modeling and experimental validation, we identified PERIANTHIA (PAN) as an important molecular regulator of quiescent center function. The results presented in this work show that our combination of molecular biology, computational biology, and mathematical modeling is an efficient approach to identify candidate factors that function in the stem cells.

The presence of an auxin gradient in the Arabidopsis root is crucial for proper root development and importantly, for stem cell niche (SCN) maintenance. Subsequently, developmental pathways in the root SCN regulate the formation of the auxin gradient. Combinations of experimental data and computational modeling enable the identification of pathways involved in establishing and maintaining the auxin gradient. We describe how the predictive power of these computational models is used to find how genes and their interactions tightly control the formation of an auxin maximum in the SCN. In addition, we highlight known connections between signaling pathways involving auxin and controlling patterning and development in Arabidopsis.

'Conventional' (-)-sparteine adducts of lithium and sodium 1,1,1,3,3,3-hexamethyldisilazide (HMDS) were prepared and characterised, along with an unexpected and 'unconventional' hydroxyl-incorporated sodium sodiate, [(-)-sparteine x Na(mu-HMDS)Na x (-)-sparteine](+)[Na(4)(mu-HMDS)(4)(OH)](-)--the complex anion of which is the first inverse crown ether anion.