Enhanced Y1H assays for Arabidopsis

Dynamics of ER stress-induced gene regulation in plants

Endoplasmic reticulum (ER) stress is a potentially lethal condition that is induced by the abnormal accumulation of unfolded or misfolded secretory proteins in the ER. In eukaryotes, ER stress is managed by the unfolded protein response (UPR) through a tightly regulated, yet highly dynamic, reprogramming of gene transcription. Although the core principles of the UPR are similar across eukaryotes, unique features of the plant UPR reflect the adaptability of plants to their ever-changing environments and the need to balance the demands of growth and development with the response to environmental stressors. The past decades have seen notable progress in understanding the mechanisms underlying ER stress sensing and signalling transduction pathways, implicating the UPR in the effects of physiological and induced ER stress on plant growth and crop yield. Facilitated by sequencing technologies and advances in genetic and genomic resources, recent efforts have driven the discovery of transcriptional regulators and elucidated the mechanisms that mediate the dynamic and precise gene regulation in response to ER stress at the systems level.

Recent advances in exploring transcriptional regulatory landscape of crops

Crop breeding entails developing and selecting plant varieties with improved agronomic traits. Modern molecular techniques, such as genome editing, enable more efficient manipulation of plant phenotype by altering the expression of particular regulatory or functional genes. Hence, it is essential to thoroughly comprehend the transcriptional regulatory mechanisms that underpin these traits. In the multi-omics era, a large amount of omics data has been generated for diverse crop species, including genomics, epigenomics, transcriptomics, proteomics, and single-cell omics. The abundant data resources and the emergence of advanced computational tools offer unprecedented opportunities for obtaining a holistic view and profound understanding of the regulatory processes linked to desirable traits. This review focuses on integrated network approaches that utilize multi-omics data to investigate gene expression regulation. Various types of regulatory networks and their inference methods are discussed, focusing on recent advancements in crop plants. The integration of multi-omics data has been proven to be crucial for the construction of high-confidence regulatory networks. With the refinement of these methodologies, they will significantly enhance crop breeding efforts and contribute to global food security.

Dissection of the IDA promoter identifies WRKY transcription factors as abscission regulators in Arabidopsis

Plants shed organs such as leaves, petals, or fruits through the process of abscission. Monitoring cues such as age, resource availability, and biotic and abiotic stresses allow plants to abscise organs in a timely manner. How these signals are integrated into the molecular pathways that drive abscission is largely unknown. The INFLORESCENCE DEFICIENT IN ABSCISSION (IDA) gene is one of the main drivers of floral organ abscission in Arabidopsis and is known to transcriptionally respond to most abscission-regulating cues. By interrogating the IDA promoter in silico and in vitro, we identified transcription factors that could potentially modulate IDA expression. We probed the importance of ERF- and WRKY-binding sites for IDA expression during floral organ abscission, with WRKYs being of special relevance to mediate IDA up-regulation in response to biotic stress in tissues destined for separation. We further characterized WRKY57 as a positive regulator of IDA and IDA-like gene expression in abscission zones. Our findings highlight the promise of promoter element-targeted approaches to modulate the responsiveness of the IDA signaling pathway to harness controlled abscission timing for improved crop productivity.

Multi-omics Resources for Understanding Gene Regulation in Response to ER Stress in Plants

Proteotoxic stress of the endoplasmic reticulum (ER) is a potentially lethal condition that ensues when the biosynthetic capacity of the ER is overwhelmed. A sophisticated and largely conserved signaling, known as the unfolded protein response (UPR), is designed to monitor and alleviate ER stress. In plants, the emerging picture of gene regulation by the UPR now appears to be more complex than ever before, requiring multi-omics-enabled network-level approaches to be untangled. In the past decade, with an increasing access and decreasing costs of next-generation sequencing (NGS) and high-throughput protein-DNA interaction (PDI) screening technologies, multitudes of global molecular measurements, known as omics, have been generated and analyzed by the research community to investigate the complex gene regulation of plant UPR. In this chapter, we present a comprehensive catalog of omics resources at different molecular levels (transcriptomes, protein-DNA interactomes, and networks) along with the introduction of key concepts in experimental and computational tools in data generation and analyses. This chapter will serve as a starting point for both experimentalists and bioinformaticians to explore diverse omics datasets for their biological questions in the plant UPR, with likely applications also in other species for conserved mechanisms.

Large-scale identification of novel transcriptional regulators of the aliphatic glucosinolate pathway in Arabidopsis

Aliphatic glucosinolates are a large group of plant secondary metabolites characteristic of Brassicaceae, including the model plant Arabidopsis. The diverse and complex degradation products of aliphatic glucosinolates contribute to plant responses to herbivory, pathogen attack, and environmental stresses. Most of the biosynthesis genes in the aliphatic glucosinolate pathway have been cloned in Arabidopsis, and the research focus has recently shifted to the regulatory mechanisms controlling aliphatic glucosinolate accumulation. Up till now, more than 40 transcriptional regulators have been identified as regulating the aliphatic glucosinolate pathway, but many more novel regulators likely remain to be discovered based on research evidence over the past decade. In the current study, we took a systemic approach to functionally test 155 candidate transcription factors in Arabidopsis identified by yeast one-hybrid assay, and successfully validated at least 30 novel regulators that could significantly influence the accumulation of aliphatic glucosinolates in our experimental set-up. We also showed that the regulators of the aliphatic glucosinolate pathway have balanced positive and negative effects, and glucosinolate metabolism and plant development can be coordinated. Our work is the largest scale effort so far to validate transcriptional regulators of a plant secondary metabolism pathway, and provides new insights into how the highly diverse plant secondary metabolism is regulated at the transcriptional level.

Paired yeast one-hybrid assays to detect DNA-binding cooperativity and antagonism across transcription factors

Cooperativity and antagonism between transcription factors (TFs) can drastically modify their binding to regulatory DNA elements. While mapping these relationships between TFs is important for understanding their context-specific functions, existing approaches either rely on DNA binding motif predictions, interrogate one TF at a time, or study individual TFs in parallel. Here, we introduce paired yeast one-hybrid (pY1H) assays to detect cooperativity and antagonism across hundreds of TF-pairs at DNA regions of interest. We provide evidence that a wide variety of TFs are subject to modulation by other TFs in a DNA region-specific manner. We also demonstrate that TF-TF relationships are often affected by alternative isoform usage and identify cooperativity and antagonism between human TFs and viral proteins from human papillomaviruses, Epstein-Barr virus, and other viruses. Altogether, pY1H assays provide a broadly applicable framework to study how different functional relationships affect protein occupancy at regulatory DNA regions.

Enhanced Yeast One-Hybrid Assays to Study Protein-DNA Interactions

The specificity in gene regulation is controlled by interactions between transcription factors (TFs) and genomic DNA regions such as promoters and enhancers. Enhanced yeast one-hybrid (eY1H) assays are among the methods used for high-throughput detection of transcription factor-DNA interactions. Here, we describe the procedure for screening interactions between DNA regions of interest ("DNA-baits") and an array of transcription factors ("TF-preys"), after DNA-bait and TF-prey yeast strains have been generated. Using a high-density array robotic platform, this method can be used to screen interactions between multiple DNA regions and >1000 TFs within a single experiment.

De novo stem cell establishment in meristems requires repression of organ boundary cell fate

Stem cells play important roles in animal and plant biology, as they sustain morphogenesis and tissue replenishment following aging or injury. In plants, stem cells are embedded in multicellular structures called meristems. The formation of new meristems is essential for the plastic expansion of the highly branched shoot and root systems. In particular, axillary meristems (AMs) that produce lateral shoots arise from the division of boundary domain cells at the leaf base. The CUP-SHAPED COTYLEDON (CUC) genes are major determinants of the boundary domain and are required for AM initiation. However, how AMs get structured and how stem cells become established de novo remain elusive. Here, we show that two NGATHA-LIKE (NGAL) transcription factors, DEVELOPMENT-RELATED PcG TARGET IN THE APEX4 (DPA4)/NGAL3 and SUPPRESSOR OF DA1-1 7 (SOD7)/NGAL2, redundantly repress CUC expression in initiating AMs of Arabidopsis thaliana. Ectopic boundary fate leads to abnormal growth and organization of the AM and prevents de novo stem cell establishment. Floral meristems of the dpa4 sod7 double mutant show a similar delay in de novo stem cell establishment. Altogether, while boundary fate is required for the initiation of AMs, our work reveals how it is later repressed to allow proper meristem establishment and de novo stem cell niche formation.

Understanding of the various aspects of gene regulatory networks related to crop improvement

The hierarchical relationship between transcription factors, associated proteins, and their target genes is defined by a gene regulatory network (GRN). GRNs allow us to understand how the genotype and environment of a plant are incorporated to control the downstream physiological responses. During plant growth or environmental acclimatization, GRNs are diverse and can be differently regulated across tissue types and organs. An overview of recent advances in the development of GRN that speed up basic and applied plant research is given here. Furthermore, the overview of genome and transcriptome involving GRN research along with the exciting advancement and application are discussed. In addition, different approaches to GRN predictions were elucidated. In this review, we also describe the role of GRN in crop improvement, crop plant manipulation, stress responses, speed breeding and identifying genetic variations/locus. Finally, the challenges and prospects of GRN in plant biology are discussed.

Transcriptional competition shapes proteotoxic ER stress resolution

Through dynamic activities of conserved master transcription factors (mTFs), the unfolded protein response (UPR) relieves proteostasis imbalance of the endoplasmic reticulum (ER), a condition known as ER stress^1,2. Because dysregulated UPR is lethal, the competence for fate changes of the UPR mTFs must be tightly controlled^3,4. However, the molecular mechanisms underlying regulatory dynamics of mTFs remain largely elusive. Here, we identified the abscisic acid-related regulator G-class bZIP TF2 (GBF2) and the cis-regulatory element G-box as regulatory components of the plant UPR led by the mTFs, bZIP28 and bZIP60. We demonstrate that, by competing with the mTFs at G-box, GBF2 represses UPR gene expression. Conversely, a gbf2 null mutation enhances UPR gene expression and suppresses the lethality of a bzip28 bzip60 mutant in unresolved ER stress. By demonstrating that GBF2 functions as a transcriptional repressor of the UPR, we address the long-standing challenge of identifying shared signalling components for a better understanding of the dynamic nature and complexity of stress biology. Furthermore, our results identify a new layer of UPR gene regulation hinged upon an antagonistic mTFs-GFB2 competition for proteostasis and cell fate determination.

ORA47 is a transcriptional regulator of a general stress response hub

Transcriptional regulators of the general stress response (GSR) reprogram the expression of selected genes to transduce informational signals into cellular events, ultimately manifested in a plant's ability to cope with environmental challenges. Identification of the core GSR regulatory proteins will uncover the principal modules and their mode of action in the establishment of adaptive responses. To define the GSR regulatory components, we employed a yeast-one-hybrid assay to identify the protein(s) binding to the previously established functional GSR motif, termed the rapid stress response element (RSRE). This led to the isolation of octadecanoid-responsive AP2/ERF-domain transcription factor 47 (ORA47), a methyl jasmonate inducible protein. Subsequently, ORA47 transcriptional activity was confirmed using the RSRE-driven luciferase (LUC) activity assay performed in the ORA47 loss- and gain-of-function lines introgressed into the 4xRSRE::Luc background. In addition, the prime contribution of CALMODULIN-BINDING TRANSCRIPTIONAL ACTIVATOR3 (CAMTA3) protein in the induction of RSRE was reaffirmed by genetic studies. Moreover, exogenous application of methyl jasmonate led to enhanced levels of ORA47 and CAMTA3 transcripts, as well as the induction of RSRE::LUC activity. Metabolic analyses illustrated the reciprocal functional inputs of ORA47 and CAMTA3 in increasing JA levels. Lastly, transient assays identified JASMONATE ZIM-domain1 (JAZ1) as a repressor of RSRE::LUC activity. Collectively, the present study provides fresh insight into the initial features of the mechanism that transduces informational signals into adaptive responses. This mechanism involves the functional interplay between the JA biosynthesis/signaling cascade and the transcriptional reprogramming that potentiates GSR. Furthermore, these findings offer a window into the role of intraorganellar communication in the establishment of adaptive responses.

Single-cell genomics in plants: current state, future directions, and hurdles to overcome

Single-cell genomics has the potential to revolutionize the study of plant development and tissue-specific responses to environmental stimuli by revealing heretofore unknown players and gene regulatory processes. Here, I focus on the current state of single-cell genomics in plants, emerging technologies and applications, in addition to outlining possible future directions for experiments. I describe approaches to enable cheaper and larger experiments and technologies to measure multiple types of molecules to better model and understand cell types and their different states and trajectories throughout development. Lastly, I discuss the inherent limitations of single-cell studies and the technological hurdles that need to be overcome to widely apply single-cell genomics in crops to generate the greatest possible knowledge gain.

Cis-regulatory sequences in plants: Their importance, discovery, and future challenges

The identification and characterization of cis-regulatory DNA sequences and how they function to coordinate responses to developmental and environmental cues is of paramount importance to plant biology. Key to these regulatory processes are cis-regulatory modules (CRMs), which include enhancers and silencers. Despite the extraordinary advances in high-quality sequence assemblies and genome annotations, the identification and understanding of CRMs, and how they regulate gene expression, lag significantly behind. This is especially true for their distinguishing characteristics and activity states. Here, we review the current knowledge on CRMs and breakthrough technologies enabling identification, characterization, and validation of CRMs; we compare the genomic distributions of CRMs with respect to their target genes between different plant species, and discuss the role of transposable elements harboring CRMs in the evolution of gene expression. This is an exciting time to study cis-regulomes in plants; however, significant existing challenges need to be overcome to fully understand and appreciate the role of CRMs in plant biology and in crop improvement.

Spatiotemporal analysis identifies ABF2 and ABF3 as key hubs of endodermal response to nitrate

Nitrate is a nutrient and a potent signal that impacts global gene expression in plants. However, the regulatory factors controlling temporal and cell type-specific nitrate responses remain largely unknown. We assayed nitrate-responsive transcriptome changes in five major root cell types of the Arabidopsis thaliana root as a function of time. We found that gene-expression response to nitrate is dynamic and highly localized and predicted cell type-specific transcription factor (TF)-target interactions. Among cell types, the endodermis stands out as having the largest and most connected nitrate-regulatory gene network. ABF2 and ABF3 are major hubs for transcriptional responses in the endodermis cell layer. We experimentally validated TF-target interactions for ABF2 and ABF3 by chromatin immunoprecipitation followed by sequencing and a cell-based system to detect TF regulation genome-wide. Validated targets of ABF2 and ABF3 account for more than 50% of the nitrate-responsive transcriptome in the endodermis. Moreover, ABF2 and ABF3 are involved in nitrate-induced lateral root growth. Our approach offers an unprecedented spatiotemporal resolution of the root response to nitrate and identifies important components of cell-specific gene regulatory networks.

Arabidopsis bioinformatics: tools and strategies

The sequencing of the Arabidopsis thaliana genome 21 years ago ushered in the genomics era for plant research. Since then, an incredible variety of bioinformatic tools permit easy access to large repositories of genomic, transcriptomic, proteomic, epigenomic and other '-omic' data. In this review, we cover some more recent tools (and highlight the 'classics') for exploring such data in order to help formulate quality, testable hypotheses, often without having to generate new experimental data. We cover tools for examining gene expression and co-expression patterns, undertaking promoter analyses and gene set enrichment analyses, and exploring protein-protein and protein-DNA interactions. We will touch on tools that integrate different data sets at the end of the article.

Multi-omics network-based functional annotation of unknown Arabidopsis genes

Unraveling gene function is pivotal to understanding the signaling cascades that control plant development and stress responses. As experimental profiling is costly and labor intensive, there is a clear need for high-confidence computational annotation. In contrast to detailed gene-specific functional information, transcriptomics data are widely available for both model and crop species. Here, we describe a novel automated function prediction method, which leverages complementary information from multiple expression datasets by analyzing study-specific gene co-expression networks. First, we benchmarked the prediction performance on recently characterized Arabidopsis thaliana genes, and showed that our method outperforms state-of-the-art expression-based approaches. Next, we predicted biological process annotations for known (n = 15 790) and unknown (n = 11 865) genes in A. thaliana and validated our predictions using experimental protein-DNA and protein-protein interaction data (covering >220 000 interactions in total), obtaining a set of high-confidence functional annotations. Our method assigned at least one validated annotation to 5054 (42.6%) unknown genes, and at least one novel validated function to 3408 (53.0%) genes with computational annotations only. These omics-supported functional annotations shed light on a variety of developmental processes and molecular responses, such as flower and root development, defense responses to fungi and bacteria, and phytohormone signaling, and help fill the information gap on biological process annotations in Arabidopsis. An in-depth analysis of two context-specific networks, modeling seed development and response to water deprivation, shows how previously uncharacterized genes function within the respective networks. Moreover, our automated function prediction approach can be applied in future studies to facilitate gene discovery for crop improvement.

A genome-scale TF-DNA interaction network of transcriptional regulation of Arabidopsis primary and specialized metabolism

Plant metabolism is more complex relative to individual microbes. In single-celled microbes, transcriptional regulation by single transcription factors (TFs) is sufficient to shift primary metabolism. Corresponding genome-level transcriptional regulatory maps of metabolism reveal the underlying design principles responsible for these shifts as a model in which master regulators largely coordinate specific metabolic pathways. Plant primary and specialized metabolism occur within innumerable cell types, and their reactions shift depending on internal and external cues. Given the importance of plants and their metabolites in providing humanity with food, fiber, and medicine, we set out to develop a genome-scale transcriptional regulatory map of Arabidopsis metabolic genes. A comprehensive set of protein-DNA interactions between Arabidopsis thaliana TFs and gene promoters in primary and specialized metabolic pathways were mapped. To demonstrate the utility of this resource, we identified and functionally validated regulators of the tricarboxylic acid (TCA) cycle. The resulting network suggests that plant metabolic design principles are distinct from those of microbes. Instead, metabolism appears to be transcriptionally coordinated via developmental- and stress-conditional processes that can coordinate across primary and specialized metabolism. These data represent the most comprehensive resource of interactions between TFs and metabolic genes in plants.

Large-scale data analysis for robotic yeast one-hybrid platforms and multi-disciplinary studies using GateMultiplex

BACKGROUND

Yeast one-hybrid (Y1H) is a common technique for identifying DNA-protein interactions, and robotic platforms have been developed for high-throughput analyses to unravel the gene regulatory networks in many organisms. Use of these high-throughput techniques has led to the generation of increasingly large datasets, and several software packages have been developed to analyze such data. We previously established the currently most efficient Y1H system, meiosis-directed Y1H; however, the available software tools were not designed for processing the additional parameters suggested by meiosis-directed Y1H to avoid false positives and required programming skills for operation.

RESULTS

We developed a new tool named GateMultiplex with high computing performance using C++. GateMultiplex incorporated a graphical user interface (GUI), which allows the operation without any programming skills. Flexible parameter options were designed for multiple experimental purposes to enable the application of GateMultiplex even beyond Y1H platforms. We further demonstrated the data analysis from other three fields using GateMultiplex, the identification of lead compounds in preclinical cancer drug discovery, the crop line selection in precision agriculture, and the ocean pollution detection from deep-sea fishery.

CONCLUSIONS

The user-friendly GUI, fast C++ computing speed, flexible parameter setting, and applicability of GateMultiplex facilitate the feasibility of large-scale data analysis in life science fields.

Gibberellins Inhibit Flavonoid Biosynthesis and Promote Nitrogen Metabolism in Medicago truncatula

Bioactive gibberellic acids (GAs) are diterpenoid plant hormones that are biosynthesized through complex pathways and control various aspects of growth and development. Although GA biosynthesis has been intensively studied, the downstream metabolic pathways regulated by GAs have remained largely unexplored. We investigated Tnt1 retrotransposon insertion mutant lines of Medicago truncatula with a dwarf phenotype by forward and reverse genetics screening and phylogenetic, molecular, biochemical, proteomic and metabolomic analyses. Three Tnt1 retrotransposon insertion mutant lines of the gibberellin 3-beta-dioxygenase 1 gene (GA3ox1) with a dwarf phenotype were identified, in which the synthesis of GAs (GA₃ and GA₄) was inhibited. Phenotypic analysis revealed that plant height, root and petiole length of ga3ox1 mutants were shorter than those of the wild type (Medicago truncatula ecotype R108). Leaf size was also much smaller in ga3ox1 mutants than that in wild-type R108, which is probably due to cell-size diminution instead of a decrease in cell number. Proteomic and metabolomic analyses of ga3ox1/R108 leaves revealed that in the ga3ox1 mutant, flavonoid isoflavonoid biosynthesis was significantly up-regulated, while nitrogen metabolism was down-regulated. Additionally, we further demonstrated that flavonoid and isoflavonoid biosynthesis was induced by prohexadione calcium, an inhibitor of GA3ox enzyme, and inhibited by exogenous GA₃. In contrast, nitrogen metabolism was promoted by exogenous GA₃ but inhibited by prohexadione calcium. The results of this study further demonstrated that GAs play critical roles in positively regulating nitrogen metabolism and transport and negatively regulating flavonoid biosynthesis through GA-mediated signaling pathways in leaves.

A cellular expression map of epidermal and subepidermal cell layer-enriched transcription factor genes integrated with the regulatory network in Arabidopsis shoot apical meristem

Transcriptional control of gene expression is an exquisitely regulated process in both animals and plants. Transcription factors (TFs) and the regulatory networks that drive the expression of TF genes in epidermal and subepidermal cell layers in Arabidopsis are unexplored. Here, we identified 65 TF genes enriched in the epidermal and subepidermal cell layers of the shoot apical meristem (SAM). To determine the cell type specificity in different stages of Arabidopsis development, we made YFP based transcriptional fusion constructs by taking a 3-kb upstream noncoding region above the translation start site. Here, we report that for ~52% (22/42) TF genes, we detected transcription activity. TF genes derived from epidermis show uniform expression in early embryo development; however, in the late globular stage, their transcription activity is suppressed in the inner cell layers. Expression patterns linked to subepidermal cell layer identity were apparent in the postembryonic development. Potential upstream regulators that could modulate the activity of epidermal and subepidermal cell layer-enriched TF genes were identified using enhanced yeast-one-hybrid (eY1H) assay and validated. This study describes the activation of TF genes in epidermal and subepidermal cell layers in embryonic and postembryonic development of Arabidopsis shoot apex.

A temporal hierarchy underpins the transcription factor-DNA interactome of the maize UPR

Adverse environmental conditions reduce crop productivity and often increase the load of unfolded or misfolded proteins in the endoplasmic reticulum (ER). This potentially lethal condition, known as ER stress, is buffered by the unfolded protein response (UPR), a set of signaling pathways designed to either recover ER functionality or ignite programmed cell death. Despite the biological significance of the UPR to the life of the organism, the regulatory transcriptional landscape underpinning ER stress management is largely unmapped, especially in crops. To fill this significant knowledge gap, we performed a large-scale systems-level analysis of the protein-DNA interaction (PDI) network in maize (Zea mays). Using 23 promoter fragments of six UPR marker genes in a high-throughput enhanced yeast one-hybrid assay, we identified a highly interconnected network of 262 transcription factors (TFs) associated with significant biological traits and 831 PDIs underlying the UPR. We established a temporal hierarchy of TF binding to gene promoters within the same family as well as across different families of TFs. Cistrome analysis revealed the dynamic activities of a variety of cis-regulatory elements (CREs) in ER stress-responsive gene promoters. By integrating the cistrome results into a TF network analysis, we mapped a subnetwork of TFs associated with a CRE that may contribute to UPR management. Finally, we validated the role of a predicted network hub gene using the Arabidopsis system. The PDIs, TF networks, and CREs identified in our work are foundational resources for understanding transcription-regulatory mechanisms in the stress responses and crop improvement.

Bioinformatic Tools in Arabidopsis Research

Bioinformatic tools are now an everyday part of a plant researcher's collection of protocols. They allow almost instantaneous access to large data sets encompassing genomes, transcriptomes, proteomes, epigenomes, and other "-omes," which are now being generated with increasing speed and decreasing cost. With the appropriate queries, such tools can generate quality hypotheses, sometimes without the need for new experimental data. In this chapter, we will investigate some of the tools used for examining gene expression and coexpression patterns, performing promoter analyses and functional classification enrichment for sets of genes, and exploring protein-protein and protein-DNA interactions in Arabidopsis. We will also cover additional tools that allow integration of data from several sources for improved hypothesis generation.

A bipartite transcription factor module controlling expression in the bundle sheath of Arabidopsis thaliana

C₄ photosynthesis evolved repeatedly from the ancestral C₃ state, improving photosynthetic efficiency by ~50%. In most C₄ lineages, photosynthesis is compartmented between mesophyll and bundle sheath cells, but how gene expression is restricted to these cell types is poorly understood. Using the C₃ model Arabidopsis thaliana, we identified cis-elements and transcription factors driving expression in bundle sheath strands. Upstream of the bundle sheath preferentially expressed MYB76 gene, we identified a region necessary and sufficient for expression containing two cis-elements associated with the MYC and MYB families of transcription factors. MYB76 expression is reduced in mutant alleles for these transcription factors. Moreover, downregulated genes shared by both mutants are preferentially expressed in the bundle sheath. Our findings are broadly relevant for understanding the spatial patterning of gene expression, provide specific insights into mechanisms associated with the evolution of C₄ photosynthesis and identify a short tuneable sequence for manipulating gene expression in the bundle sheath.

A network of transcriptional repressors modulates auxin responses

The regulation of signalling capacity, combined with the spatiotemporal distribution of developmental signals themselves, is pivotal in setting developmental responses in both plants and animals¹. The hormone auxin is a key signal for plant growth and development that acts through the AUXIN RESPONSE FACTOR (ARF) transcription factors^2-4. A subset of these, the conserved class A ARFs⁵, are transcriptional activators of auxin-responsive target genes that are essential for regulating auxin signalling throughout the plant lifecycle^2,3. Although class A ARFs have tissue-specific expression patterns, how their expression is regulated is unknown. Here we show, by investigating chromatin modifications and accessibility, that loci encoding these proteins are constitutively open for transcription. Through yeast one-hybrid screening, we identify the transcriptional regulators of the genes encoding class A ARFs from Arabidopsis thaliana and demonstrate that each gene is controlled by specific sets of transcriptional regulators. Transient transformation assays and expression analyses in mutants reveal that, in planta, the majority of these regulators repress the transcription of genes encoding class A ARFs. These observations support a scenario in which the default configuration of open chromatin enables a network of transcriptional repressors to regulate expression levels of class A ARF proteins and modulate auxin signalling output throughout development.

Network-based approaches for understanding gene regulation and function in plants

Expression reprogramming directed by transcription factors is a primary gene regulation underlying most aspects of the biology of any organism. Our views of how gene regulation is coordinated are dramatically changing thanks to the advent and constant improvement of high-throughput profiling and transcriptional network inference methods: from activities of individual genes to functional interactions across genes. These technical and analytical advances can reveal the topology of transcriptional networks in which hundreds of genes are hierarchically regulated by multiple transcription factors at systems level. Here we review the state of the art of experimental and computational methods used in plant biology research to obtain large-scale datasets and model transcriptional networks. Examples of direct use of these network models and perspectives on their limitations and future directions are also discussed.

FRS7 and FRS12 recruit NINJA to regulate expression of glucosinolate biosynthesis genes

The sessile lifestyle of plants requires accurate physiology adjustments to be able to thrive in a changing environment. Plants integrate environmental timing signals to control developmental and stress responses. Here, we identified Far1 Related Sequence (FRS) 7 and FRS12, two transcriptional repressors that accumulate in short-day conditions, as regulators of Arabidopsis glucosinolate (GSL) biosynthesis. Loss of function of FRS7 and FRS12 results in plants with increased amplitudes of diurnal expression of GSL pathway genes. Protein interaction analyses revealed that FRS7 and FRS12 recruit the NOVEL INTERACTOR OF JAZ (NINJA) to assemble a transcriptional repressor complex. Genetic and molecular evidence demonstrated that FRS7, FRS12 and NINJA jointly regulate the expression of GSL biosynthetic genes, and thus constitute a molecular mechanism that modulates specialized metabolite accumulation.

Towards understanding the hierarchical nitrogen signalling network in plants

Nitrogen (N) is the most abundant mineral elements in plants, and the application of inorganic N fertilizer makes huge contribution to the crop production and global food security. However, low N use efficiency (NUE) and overapplication of N fertilizers causes ever-growing environmental problems. Understanding the molecular mechanisms of N sensing and signalling in plants will provide molecular basis for NUE improvement of crops. Forward genetics screening and functional analysis have characterized the NRT1.1-NLP centered N signalling pathway at the cellular level. With the incorporation of systems biology approaches, a preliminary N regulatory network has been delineated. Meanwhile, long-distance N signalling has also been unveiled at the whole plant level. This review highlights most recent understanding of the N signalling network in plants, and also discusses how to further integrate hierarchical regulation of N signalling in plants.

Specification and regulation of vascular tissue identity in the Arabidopsis embryo

Development of plant vascular tissues involves tissue identity specification, growth, pattern formation and cell-type differentiation. Although later developmental steps are understood in some detail, it is still largely unknown how the tissue is initially specified. We used the early Arabidopsis embryo as a simple model to study this process. Using a large collection of marker genes, we found that vascular identity was specified in the 16-cell embryo. After a transient precursor state, however, there was no persistent uniform tissue identity. Auxin is intimately connected to vascular tissue development. We found that, although an AUXIN RESPONSE FACTOR5/MONOPTEROS (ARF5/MP)-dependent auxin response was required, it was not sufficient for tissue specification. We therefore used a large-scale enhanced yeast one-hybrid assay to identify potential regulators of vascular identity. Network and functional analysis of candidate regulators suggest that vascular identity is under robust, complex control. We found that one candidate regulator, the G-class bZIP transcription factor GBF2, can modulate vascular gene expression by tuning MP output through direct interaction. Our work uncovers components of a gene regulatory network that controls the initial specification of vascular tissue identity.

A PXY-Mediated Transcriptional Network Integrates Signaling Mechanisms to Control Vascular Development in Arabidopsis

The cambium and procambium generate the majority of biomass in vascular plants. These meristems constitute a bifacial stem cell population from which xylem and phloem are specified on opposing sides by positional signals. The PHLOEM INTERCALATED WITH XYLEM (PXY) receptor kinase promotes vascular cell division and organization. However, how these functions are specified and integrated is unknown. Here, we mapped a putative PXY-mediated transcriptional regulatory network comprising 690 transcription factor-promoter interactions in Arabidopsis (Arabidopsis thaliana). Among these interactions was a feedforward loop containing transcription factors WUSCHEL HOMEOBOX RELATED14 (WOX14) and TARGET OF MONOPTEROS6 (TMO6), each of which regulates the expression of the gene encoding a third transcription factor, LATERAL ORGAN BOUNDARIES DOMAIN4 (LBD4). PXY signaling in turn regulates the WOX14, TMO6, and LBD4 feedforward loop to control vascular proliferation. Genetic interaction between LBD4 and PXY suggests that LBD4 marks the phloem-procambium boundary, thus defining the shape of the vascular bundle. These data collectively support a mechanism that influences the recruitment of cells into the phloem lineage, and they define the role of PXY signaling in this context in determining the arrangement of vascular tissue.

A novel synthetic-genetic-array-based yeast one-hybrid system for high discovery rate and short processing time

Eukaryotic gene expression is often tightly regulated by interactions between transcription factors (TFs) and their DNA cis targets. Yeast one-hybrid (Y1H) is one of the most extensively used methods to discover these interactions. We developed a high-throughput meiosis-directed yeast one-hybrid system using the Magic Markers of the synthetic genetic array analysis. The system has a transcription factor–DNA interaction discovery rate twice as high as the conventional diploid-mating approach and a processing time nearly one-tenth of the haploid-transformation method. The system also offers the highest accuracy in identifying TF–DNA interactions that can be authenticated in vivo by chromatin immunoprecipitation. With these unique features, this meiosis-directed Y1H system is particularly suited for constructing novel and comprehensive genome-scale gene regulatory networks for various organisms.

Proteome-wide, Structure-Based Prediction of Protein-Protein Interactions/New Molecular Interactions Viewer

Determining the complete Arabidopsis (Arabidopsis thaliana) protein-protein interaction network is essential for understanding the functional organization of the proteome. Numerous small-scale studies and a couple of large-scale ones have elucidated a fraction of the estimated 300,000 binary protein-protein interactions in Arabidopsis. In this study, we provide evidence that a docking algorithm has the ability to identify real interactions using both experimentally determined and predicted protein structures. We ranked 0.91 million interactions generated by all possible pairwise combinations of 1,346 predicted structure models from an Arabidopsis predicted "structure-ome" and found a significant enrichment of real interactions for the top-ranking predicted interactions, as shown by cosubcellular enrichment analysis and yeast two-hybrid validation. Our success rate for computationally predicted, structure-based interactions was 63% of the success rate for published interactions naively tested using the yeast two-hybrid system and 2.7 times better than for randomly picked pairs of proteins. This study provides another perspective in interactome exploration and biological network reconstruction using protein structural information. We have made these interactions freely accessible through an improved Arabidopsis Interactions Viewer and have created community tools for accessing these and ∼2.8 million other protein-protein and protein-DNA interactions for hypothesis generation by researchers worldwide. The Arabidopsis Interactions Viewer is freely available at http://bar.utoronto.ca/interactions2/.

Screening Arrayed Libraries with DNA and Protein Baits to Identify Interacting Proteins

Molecular interactions are an integral part of the regulatory mechanisms controlling gene expression. The yeast one- and two-hybrid systems (Y1H/Y2H) have been widely used by many laboratories to detect DNA-protein (Y1H) and protein-protein interactions (Y2H). The development of efficient cloning systems have promoted the generation of large open reading frame (ORF) clone collections (libraries) for several organisms. Functional analyses of such large collections require the establishment of adequate protocols. Here, we describe a simple straightforward procedure for high-throughput screenings of arrayed libraries with DNA or protein baits that can be carried out by one person with minimal labor and not requiring robotics. The protocol can also be scaled up or down and is compatible with several library formats. Procedures to make yeast stocks for long-term storage (tube and microplate formats) are also provided.

Options and Considerations When Using a Yeast One-Hybrid System

Comprehensive mapping of protein-DNA interactions is essential to uncover the mechanisms involved in gene regulation. However, the data generated has been sparse given the number of regulatory elements and transcription factors (TFs) encoded in the genomes of metazoan organisms. Yeast one-hybrid (Y1H) assays provide a powerful "DNA-centered" method, complementary to "TF-centered" methods such as chromatin immunoprecipitation, to identify the TFs that can bind a DNA sequence of interest. Here, we present different technical variations that should be considered when using a Y1H system, including the type of DNA sequence to test, source of TF clones, as well as types of vectors and screening format. Finally, we discuss limitations of the assay and future challenges.

A Standardized Synthetic Eucalyptus Transcription Factor and Promoter Panel for Re-engineering Secondary Cell Wall Regulation in Biomass and Bioenergy Crops

Re-engineering of transcriptional networks regulating secondary cell wall formation may allow the improvement of plant biomass in widely grown plantation crops such as Eucalyptus. However, there is currently a scarcity of freely available standardized biological parts (e.g., Phytobricks) compatible with Type IIS assembly approaches from forest trees, and there is a need to accelerate transcriptional network inference in nonmodel biomass crops. Here we describe the design and synthesis of a versatile three-panel biological parts collection of 221 secondary cell wall-related Eucalyptus grandis transcription factor coding sequences and 65 promoters that are compatible with GATEWAY, Golden Gate, MoClo, and GoldenBraid DNA assembly methods and generally conform to accepted Phytobrick syntaxes. This freely available resource is intended to accelerate synthetic biology applications in multiple plant biomass crops and enable reconstruction of secondary cell wall transcriptional networks using high-throughput assays such as DNA affinity purification sequencing (DAP-seq) and enhanced yeast one-hybrid (eY1H) screening.

High-Throughput Yeast One-Hybrid Screens Using a Cell Surface gLUC Reporter

Gene-centered yeast one-hybrid (Y1H) screens using arrayed genome-wide transcription factor (TF) clone collections provide a simple and effective strategy to identify TF-promoter interactions using a DNA fragment as bait. In an effort to improve the assay we recently developed a Y1H system that uses a cell surface Gaussia luciferase reporter (gLUC59). Compared to other available methods, this luciferase-based strategy requires a shorter processing time, enhances the throughput and improves result analysis of gene-centered Y1H screens. Here, we described the procedure to perform high-throughput screens using this novel strategy, which involves a protocol for mating two haploid yeast strains carrying an arrayed TF clone collection and a promoter::gLUC59 reporter, respectively, and a protocol for analyzing gLUC59 activity in the resulting diploid cells. © 2019 by John Wiley & Sons, Inc.

ARF5/MONOPTEROS directly regulates miR390 expression in the Arabidopsis thaliana primary root meristem

The root meristem is organized around a quiescent center (QC) surrounded by stem cells that generate all cell types of the root. In the transit-amplifying compartment, progeny of stem cells further divides prior to differentiation. Auxin controls the size of this transit-amplifying compartment via auxin response factors (ARFs) that interact with auxin response elements (AuxREs) in the promoter of their targets. The microRNA miR390 regulates abundance of ARF2, ARF3, and ARF4 by triggering the production of trans-acting (ta)-siRNA from the TAS3 precursor. This miR390/TAS3/ARF regulatory module confers sensitivity and robustness to auxin responses in diverse developmental contexts and organisms. Here, we show that miR390 is expressed in the transit-amplifying compartment of the root meristem where it modulates response to exogenous auxin. We show that a single AuxRE located in miR390 promoter is necessary for miR390 expression in this compartment and identify that ARF5/MONOPTEROS (MP) binds miR390 promoter via the AuxRE. We show that interfering with ARF5/MP-dependent auxin signaling attenuates miR390 expression in the transit-amplifying compartment of the root meristem. Our results show that ARF5/MP regulates directly the expression of miR390 in the root meristem. We propose that ARF5, miR390, and the ta-siRNAs-regulated ARFs modulate the response of the transit-amplifying region of the meristem to exogenous auxin.

Mobile PEAR transcription factors integrate positional cues to prime cambial growth

Apical growth in plants initiates upon seed germination, whereas radial growth is primed only during early ontogenesis in procambium cells and activated later by the vascular cambium¹. Although it is not known how radial growth is organized and regulated in plants, this system resembles the developmental competence observed in some animal systems, in which pre-existing patterns of developmental potential are established early on^2,3. Here we show that in Arabidopsis the initiation of radial growth occurs around early protophloem-sieve-element cell files of the root procambial tissue. In this domain, cytokinin signalling promotes the expression of a pair of mobile transcription factors-PHLOEM EARLY DOF 1 (PEAR1) and PHLOEM EARLY DOF 2 (PEAR2)-and their four homologues (DOF6, TMO6, OBP2 and HCA2), which we collectively name PEAR proteins. The PEAR proteins form a short-range concentration gradient that peaks at protophloem sieve elements, and activates gene expression that promotes radial growth. The expression and function of PEAR proteins are antagonized by the HD-ZIP III proteins, well-known polarity transcription factors⁴-the expression of which is concentrated in the more-internal domain of radially non-dividing procambial cells by the function of auxin, and mobile miR165 and miR166 microRNAs. The PEAR proteins locally promote transcription of their inhibitory HD-ZIP III genes, and thereby establish a negative-feedback loop that forms a robust boundary that demarks the zone of cell division. Taken together, our data establish that during root procambial development there exists a network in which a module that links PEAR and HD-ZIP III transcription factors integrates spatial information of the hormonal domains and miRNA gradients to provide adjacent zones of dividing and more-quiescent cells, which forms a foundation for further radial growth.

Preparation of Plant Material for Analysis of Protein-Nucleic Acid Interactions by FRET-FLIM

DNA-binding proteins are involved in the dynamic regulation of various cellular processes such as recombination, replication, and transcription. For investigating dynamic assembly and disassembly of molecular complexes in living cells, fluorescence microscopy represents a tremendous tool in biology. A fluorescence resonance energy transfer (FRET) approach coupled to fluorescence lifetime imaging microscopy (FLIM) has been used recently to monitor protein-DNA associations in plant cells. With this approach, the donor fluorophore is a GFP-tagged binding partner expressed in plant cells. A Sytox® Orange treatment converts nuclear nucleic acids to FRET acceptors. A decrease of GFP lifetime is due to FRET between donor and acceptor, indicating close association of the GFP binding partner and Sytox® Orange-stained DNA. In this chapter, we present a step-by-step protocol for the transient expression in N. benthamiana of GFP-tagged proteins and the fixation and permeabilization procedures used for the preparation of plant material aimed at detecting protein-nucleic acid interactions by FRET-FLIM measurements.

Transcriptional regulation of nitrogen-associated metabolism and growth

Nitrogen is an essential macronutrient for plant growth and basic metabolic processes. The application of nitrogen-containing fertilizer increases yield, which has been a substantial factor in the green revolution¹. Ecologically, however, excessive application of fertilizer has disastrous effects such as eutrophication². A better understanding of how plants regulate nitrogen metabolism is critical to increase plant yield and reduce fertilizer overuse. Here we present a transcriptional regulatory network and twenty-one transcription factors that regulate the architecture of root and shoot systems in response to changes in nitrogen availability. Genetic perturbation of a subset of these transcription factors revealed coordinate transcriptional regulation of enzymes involved in nitrogen metabolism. Transcriptional regulators in the network are transcriptionally modified by feedback via genetic perturbation of nitrogen metabolism. The network, genes and gene-regulatory modules identified here will prove critical to increasing agricultural productivity.

Complete substitution of a secondary cell wall with a primary cell wall in Arabidopsis

The bulk of a plant's biomass, termed secondary cell walls, accumulates in woody xylem tissues and is largely recalcitrant to biochemical degradation and saccharification¹. By contrast, primary cell walls, which are chemically distinct, flexible and generally unlignified², are easier to deconstruct. Thus, engineering certain primary wall characteristics into xylem secondary walls would be interesting to readily exploit biomass for industrial processing. Here, we demonstrated that by expressing AP2/ERF transcription factors from group IIId and IIIe in xylem fibre cells of mutants lacking secondary walls, we could generate plants with thickened cell wall characteristics of primary cell walls in the place of secondary cell walls. These unique, newly formed walls displayed physicochemical and ultrastructural features consistent with primary walls and had gene expression profiles illustrative of primary wall synthesis. These data indicate that the group IIId and IIIe AP2/ERFs are transcription factors regulating primary cell wall deposition and could form the foundation for exchanging one cell wall type for another in plants.

Molecular and epigenetic regulations and functions of the LAFL transcriptional regulators that control seed development

The LAFL (i.e. LEC1, ABI3, FUS3, and LEC2) master transcriptional regulators interact to form different complexes that induce embryo development and maturation, and inhibit seed germination and vegetative growth in Arabidopsis. Orthologous genes involved in similar regulatory processes have been described in various angiosperms including important crop species. Consistent with a prominent role of the LAFL regulators in triggering and maintaining embryonic cell fate, their expression appears finely tuned in different tissues during seed development and tightly repressed in vegetative tissues by a surprisingly high number of genetic and epigenetic factors. Partial functional redundancies and intricate feedback regulations of the LAFL have hampered the elucidation of the underpinning molecular mechanisms. Nevertheless, genetic, genomic, cellular, molecular, and biochemical analyses implemented during the last years have greatly improved our knowledge of the LALF network. Here we summarize and discuss recent progress, together with current issues required to gain a comprehensive insight into the network, including the emerging function of LEC1 and possibly LEC2 as pioneer transcription factors.

A stress-associated protein, AtSAP13, from Arabidopsis thaliana provides tolerance to multiple abiotic stresses

Members of Stress-Associated Protein (SAP) family in plants have been shown to impart tolerance to multiple abiotic stresses, however, their mode of action in providing tolerance to multiple abiotic stresses is largely unknown. There are 14 SAP genes in Arabidopsis thaliana containing A20, AN1, and Cys2-His2 zinc finger domains. AtSAP13, a member of the SAP family, carries two AN1 zinc finger domains and an additional Cys2-His2 domain. AtSAP13 transcripts showed upregulation in response to Cd, ABA, and salt stresses. AtSAP13 overexpression lines showed strong tolerance to toxic metals (AsIII, Cd, and Zn), drought, and salt stress. Further, transgenic lines accumulated significantly higher amounts of Zn, but less As and Cd accumulation in shoots and roots. AtSAP13 promoter-GUS fusion studies showed GUS expression predominantly in the vascular tissue, hydathodes, and the apical meristem and region of root maturation and elongation as well as the root hairs. At the subcellular level, the AtSAP13-eGFP fusion protein was found to localize in both nucleus and cytoplasm. Through yeast one-hybrid assay, we identified several AP2/EREBP family transcription factors that interacted with the AtSAP13 promoter. AtSAP13 and its homologues will be highly useful for developing climate resilient crops.

A Gene Regulatory Network for Cellular Reprogramming in Plant Regeneration

Wounding triggers organ regeneration in many plant species, and application of plant hormones, such as auxin and cytokinin, enhances their regenerative capacities in tissue culture. Recent studies have identified several key players mediating wound- and/or plant hormone-induced cellular reprogramming, but the global architecture of gene regulatory relationships underlying plant cellular reprogramming is still far from clear. In this study, we uncovered a gene regulatory network (GRN) associated with plant cellular reprogramming by using an enhanced yeast one-hybrid (eY1H) screen systematically to identify regulatory relationships between 252 transcription factors (TFs) and 48 promoters. Our network analyses suggest that wound- and/or hormone-invoked signals exhibit extensive cross-talk and regulate many common reprogramming-associated genes via multilayered regulatory cascades. Our data suggest that PLETHORA 3 (PLT3), ENHANCER OF SHOOT REGENERATION 1 (ESR1) and HEAT SHOCK FACTOR B 1 (HSFB1) act as critical nodes that have many overlapping targets and potentially connect upstream stimuli to downstream developmental decisions. Interestingly, a set of wound-inducible APETALA 2/ETHYLENE RESPONSE FACTORs (AP2/ERFs) appear to regulate these key genes, which, in turn, form feed-forward cascades that control downstream targets associated with callus formation and organ regeneration. In addition, we found another regulatory pathway, mediated by LATERAL ORGAN BOUNDARY/ASYMMETRIC LEAVES 2 (LOB/AS2) TFs, which probably plays a distinct but partially overlapping role alongside the AP2/ERFs in the putative gene regulatory cascades. Taken together, our findings provide the first global picture of the GRN governing plant cell reprogramming, which will serve as a valuable resource for future studies.

Construction of Arabidopsis Transcription Factor ORFeome Collections and Identification of Protein-DNA Interactions by High-Throughput Yeast One-Hybrid Screens

Identification of transcription factor (TF)-promoter interactions is key to understanding the basic molecular underpinnings of gene regulation. The complexity of gene regulation, however, is driven by the combined function of several TFs recruited to the promoter region, which often confounds the discovery of transcriptional regulatory mechanisms. Genome sequencing enabled the construction of TF-specific ORFeome clone collections that can be used to study TF function with unprecedented coverage. Among the recently developed methods, gene-centered yeast one-hybrid (Y1H) screens performed with these ORFeome collections provide a simple and reliable strategy to identify TF-promoter interactions. Here, we describe high-throughput cloning protocols used to generate a gold standard TF ORFeome collection for the model organism Arabidopsis thaliana. Furthermore, we outline the protocol to build a daughter clone collection suitable for the Y1H assay and a high-throughput Y1H screening procedure that enables rapid assessment of thousands TF-promoter interactions using a robotic platform. These protocols can be universally adopted to build ORFeome libraries and thus expand the usage of gene-centered Y1H screens or other alternative strategies for discovery and characterization of TF functions.

Network-Guided Discovery of Extensive Epistasis between Transcription Factors Involved in Aliphatic Glucosinolate Biosynthesis

Plants use diverse mechanisms influenced by vast regulatory networks of indefinite scale to adapt to their environment. These regulatory networks have an unknown potential for epistasis between genes within and across networks. To test for epistasis within an adaptive trait genetic network, we generated and tested 47 Arabidopsis thaliana double mutant combinations for 20 transcription factors, which all influence the accumulation of aliphatic glucosinolates, the defense metabolites that control fitness. The epistatic combinations were used to test if there is more or less epistasis depending on gene membership within the same or different phenotypic subnetworks. Extensive epistasis was observed between the transcription factors, regardless of subnetwork membership. Metabolite accumulation displayed antagonistic epistasis, suggesting the presence of a buffering mechanism. Epistasis affecting enzymatic estimated activity was highly conditional on the tissue and environment and shifted between both antagonistic and synergistic forms. Transcriptional analysis showed that epistasis shifts depend on how the trait is measured. Because the 47 combinations described here represent a small sampling of the potential epistatic combinations in this genetic network, there is potential for significantly more epistasis. Additionally, the main effect of the individual gene was not predictive of the epistatic effects, suggesting that there is a need for further studies.

Zebrafish Transcription Factor ORFeome for Gene Discovery and Regulatory Network Elucidation

The completion of the zebrafish genome sequence and advances in miniaturization and multiplexing were essential to the creation of techniques such as RNA-seq, ChIP-seq, and high-throughput behavioral and chemical screens. Multiplexing was also instrumental in the recent enhancement of the classic yeast one-hybrid interaction techniques to provide unprecedented discovery capabilities for protein-DNA interactions. Unfortunately its use for zebrafish research is currently hampered by the lack of an open reading frame (ORF) clone collection. As a first step toward a complete collection, we describe a small library of transcriptional regulatory proteins comprising 142 ORFs and its potential applications.

Specific Light-Up System for Protein and Metabolite Targets Triggered by Initiation Complex Formation

Gene regulation systems are mimicked by simple quantitative detection of non-nucleic acid molecular targets such as protein and metabolite. Here, we describe a one-tube, one-step real-time quantitative detection methodology for isothermal signal amplification of those targets. Using this system, real-time quantitative detection of thrombin and streptomycin, which were used as examples for protein and metabolite targets, was successfully demonstrated with detection limits of at most 50 pM and 75 nM, respectively. Notably, the dynamic range of target concentrations could be obtained for over four orders of magnitude. Thus, our method is expected to serve as a point-of-care or on-site test for medical diagnosis and food and environmental hygiene.

Novel cell surface luciferase reporter for high-throughput yeast one-hybrid screens

Gene-centered yeast one-hybrid (Y1H) screens provide a powerful and effective strategy to identify transcription factor (TF)-promoter interactions. While genome-wide TF ORFeome clone collections are increasingly available, screening protocols have limitations inherent to the properties of the enzymatic reaction used to identify interactions and to the procedure required to perform the assay in a high-throughput format. Here, we present the development and validation of a streamlined strategy for quantitative and fully automated gene-centered Y1H screens using a novel cell surface Gaussia luciferase reporter.

TransDetect Identifies a New Regulatory Module Controlling Phosphate Accumulation

Identifying transcription factor (TFs) cooperation controlling target gene expression is still an arduous challenge. The accuracy of current methods at genome scale significantly drops with the increase in number of genes, which limits their applicability to more complex genomes, like animals and plants. Here, we developed an algorithm, TransDetect, able to predict TF combinations controlling the expression level of a given gene. TransDetect was used to identify novel TF modules regulating the expression of Arabidopsis (Arabidopsis thaliana) phosphate transporter PHO1;H3 comprising MYB15, MYB84, bHLH35, and ICE1. These TFs were confirmed to interact between themselves and with the PHO1;H3 promoter. Phenotypic and genetic analyses of TF mutants enable the organization of these four TFs and PHO1;H3 in a new gene regulatory network controlling phosphate accumulation in zinc-dependent manner. This demonstrates the potential of TransDetect to extract directionality in nondynamic transcriptomes and to provide a blueprint to identify gene regulatory network involved in a given biological process.

Reverse engineering highlights potential principles of large gene regulatory network design and learning

Inferring transcriptional gene regulatory networks from transcriptomic datasets is a key challenge of systems biology, with potential impacts ranging from medicine to agronomy. There are several techniques used presently to experimentally assay transcription factors to target relationships, defining important information about real gene regulatory networks connections. These techniques include classical ChIP-seq, yeast one-hybrid, or more recently, DAP-seq or target technologies. These techniques are usually used to validate algorithm predictions. Here, we developed a reverse engineering approach based on mathematical and computer simulation to evaluate the impact that this prior knowledge on gene regulatory networks may have on training machine learning algorithms. First, we developed a gene regulatory networks-simulating engine called FRANK (Fast Randomizing Algorithm for Network Knowledge) that is able to simulate large gene regulatory networks (containing 10⁴ genes) with characteristics of gene regulatory networks observed in vivo. FRANK also generates stable or oscillatory gene expression directly produced by the simulated gene regulatory networks. The development of FRANK leads to important general conclusions concerning the design of large and stable gene regulatory networks harboring scale free properties (built ex nihilo). In combination with supervised (accepting prior knowledge) support vector machine algorithm we (i) address biologically oriented questions concerning our capacity to accurately reconstruct gene regulatory networks and in particular we demonstrate that prior-knowledge structure is crucial for accurate learning, and (ii) draw conclusions to inform experimental design to performed learning able to solve gene regulatory networks in the future. By demonstrating that our predictions concerning the influence of the prior-knowledge structure on support vector machine learning capacity holds true on real data (Escherichia coli K14 network reconstruction using network and transcriptomic data), we show that the formalism used to build FRANK can to some extent be a reasonable model for gene regulatory networks in real cells.

This work by Carré et al addresses central questions in biology, which are: how very large gene regulatory networks (GRNs) are organized, generate stable gene expression, and can be learnt using machine learning algorithms? In this work authors developed an algorithm able to simulate large GRNs. From these networks they simulate stable or oscillating gene expression and highlights some mathematical rules controlling such a collective (several thousands of genes) behavior. They discuss consequent hypothesis concerning the organization of GRNs in real cells. Using this simulation tool, authors also demonstrate that it’s likely possible to computationally learn GRNs from transcriptomic data and prior knowledge on the network (actual known connections issued from Yeast One Hybrid or ChIP Seq for instance). They particularly highlight the crucial importance of the prior knowledge structure in their capacity to learn large GRNs.