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The development of multicellular organisms relies on the coordinated control of cell divisions leading to proper patterning and growth (1-3). The molecular mechanisms underlying pattern formation, particularly the regulation of formative cell divisions, remain poorly understood. In Arabidopsis, formative divisions generating the root ground tissue are controlled by SHORTROOT (SHR) and SCARECROW (SCR) (4-6). Here we show, using cell-type-specific transcriptional effects of SHR and SCR combined with data from chromatin immunoprecipitation-based microarray experiments, that SHR regulates the spatiotemporal activation of specific genes involved in cell division. Coincident with the onset of a specific formative division, SHR and SCR directly activate a D-type cyclin; furthermore, altering the expression of this cyclin resulted in formative division defects. Our results indicate that proper pattern formation is achieved through transcriptional regulation of specific cell-cycle genes in a cell-type- and developmental-stage-specific context. Taken together, we provide evidence for a direct link between developmental regulators, specific components of the cell-cycle machinery and organ patterning., Growth and patterning are key processes that govern the development of multicellular organisms. In some cases, like early Drosophila embryogenesis (7), these are independent. However, in many animals and plants, [...]

The integration of 3D bioprinting into plant science and biotechnology is revolutionizing research and applications. While many high-throughput techniques have advanced plant biology, replicating the complex 3D organization and cellular environments of plant tissues remains a significant challenge. Traditional 2D culture systems fall short of capturing the necessary spatial context for accurate studies of cell behavior, gene expression, and tissue development. Additionally, the lack of precise simulation of plant microenvironments limits control over cellular interactions and responses to external stimuli. Recent advancements in 3D bioprinting address these limitations by allowing precise control over cell positioning and biomaterial arrangement, thereby better replicating natural plant environments. This enables more accurate studies of gene expression, developmental processes, and stress responses. The technology also enhances our ability to test genetic modifications and biotechnological interventions, advancing crop improvement, sustainable agriculture, and precision breeding. This review examines the current state of 3D bioprinting in plant science, discusses its limitations, and explores its potential to transform research and applications in the field., Competing Interests: Declaration of Competing Interest Rosangela Sozzani reports a relationship with Raleigh Biosciences that includes board membership. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Understanding root development is critical for enhancing plant growth and health, and advanced technologies are essential for unraveling the complexities of these processes. In this review, we highlight select technological innovations in the study of root development, with a focus on the transformative impact of single-cell gene expression analysis. We provide a high-level overview of recent advancements, illustrating how single-cell RNA sequencing (scRNA-seq) has become a pivotal tool in plant biology. scRNA-seq has revolutionized root biology by enabling detailed, cell-specific analysis of gene expression. This has allowed researchers to create comprehensive root atlases, predict cell development, and map gene regulatory networks (GRNs) with unprecedented precision. Complementary technologies, such as multimodal profiling and bioinformatics, further enrich our understanding of cellular dynamics and gene interactions. Innovations in imaging and modeling, combined with genetic tools like CRISPR, continue to deepen our knowledge of root formation and function. Moreover, the integration of these technologies with advanced biosensors and microfluidic devices has advanced our ability to study plant-microbe interactions and phytohormone signaling at high resolution. These tools collectively provide a more comprehensive understanding of root system architecture and its regulation by environmental factors. As these technologies evolve, they promise to drive further breakthroughs in plant science, with substantial implications for agriculture and sustainability., Competing Interests: Conflict of interest statement. None declared., (© The Author(s) 2024. Published by Oxford University Press on behalf of American Society of Plant Biologists. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Gene expression in Arabidopsis is regulated by more than 1,900 transcription factors (TFs), which have been identified genome-wide by the presence of well-conserved DNA-binding domains. Activator TFs contain activation domains (ADs) that recruit coactivator complexes; however, for nearly all Arabidopsis TFs, we lack knowledge about the presence, location and transcriptional strength of their ADs 1 . To address this gap, here we use a yeast library approach to experimentally identify Arabidopsis ADs on a proteome-wide scale, and find that more than half of the Arabidopsis TFs contain an AD. We annotate 1,553 ADs, the vast majority of which are, to our knowledge, previously unknown. Using the dataset generated, we develop a neural network to accurately predict ADs and to identify sequence features that are necessary to recruit coactivator complexes. We uncover six distinct combinations of sequence features that result in activation activity, providing a framework to interrogate the subfunctionalization of ADs. Furthermore, we identify ADs in the ancient AUXIN RESPONSE FACTOR family of TFs, revealing that AD positioning is conserved in distinct clades. Our findings provide a deep resource for understanding transcriptional activation, a framework for examining function in intrinsically disordered regions and a predictive model of ADs., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

All differentiated root cells derive from stem cells spatially organized within the stem cell niche (SCN), a microenvironment located within the root tip. Here, we compiled recent advances in the understanding of how the SCN drives the establishment and maintenance of cell types. The quiescent center (QC) is widely recognized as the primary driver of cell fate determination, but it is recently considered a convergence center of multiple signals. Cell identity of the cortex endodermis initials is mainly driven by the regulatory feedback loops between transcription factors (TFs), acting as mobile signals between neighboring cells, including the QC. As exemplified in the vascular initials, the precise spatial expression of these regulatory TFs is connected with a dynamic hormonal interplay. Thus, stem cell maintenance and cell differentiation are regulated by a plethora of signals forming a complex, multilevel regulatory network. Integrating the transcriptional and post-translational regulations, protein-protein interactions, and mobile signals into models will be fundamental for the comprehensive understanding of SCN maintenance and differentiation., Competing Interests: Declaration of Competing Interest None., (Copyright © 2024. Published by Elsevier Ltd.)

Uneven global distribution of phosphate rock deposits and the supply chains to transport phosphorus (P) make P fertilizers vulnerable to exogenous shocks, including commodity market shocks; extreme weather events or natural disasters; and geopolitical instability, such as trade disputes, disruption of shipping routes, and war. Understanding bidirectional risk transmission (global-to-local and local-to-global) in P supply and consumption chains is thus essential. Ignoring P system interdependencies and associated risks could have major impacts on critical infrastructure operations and increase the vulnerability of global food systems. We highlight recent unanticipated events and cascading effects that have impacted P markets globally. We discuss the need to account for exogenous shocks in local assessments of P flows, policies, and infrastructure design choices. We also provide examples of how accounting for undervalued global risks to the P industry can hasten the transition to a sustainable P future. For example, leveraging internal P recycling loops, improving plant P use efficiency, and utilizing legacy soil P all enhance system resiliency in the face of exogenous shocks and long-term anticipated threats. Strategies applied at the local level, which are embedded within national and global policy systems, can have global-scale impacts in derisking the P supply chain., Competing Interests: The authors declare no competing financial interest., (© 2024 The Authors. Published by American Chemical Society.)

Competing Interests: Conflict of interest statement. None declared.

Phosphorus is essential to plant growth and agricultural crop yields, yet the challenges associated with phosphorus fertilization in agriculture, such as aquatic runoff pollution and poor phosphorus bioavailability, are increasingly difficult to manage. Comprehensively understanding the dynamics of phosphorus uptake and signaling mechanisms will inform the development of strategies to address these issues. This review describes regulatory mechanisms used by specific tissues in the root apical meristem to sense and take up phosphate from the rhizosphere. The major regulatory mechanisms and related hormone crosstalk underpinning phosphate starvation responses, cellular phosphate homeostasis, and plant adaptations to phosphate starvation are also discussed, along with an overview of the major mechanism of plant systemic phosphate starvation responses. Finally, this review discusses recent promising genetic engineering strategies for improving crop phosphorus use and computational approaches that may help further design strategies for improved plant phosphate acquisition. The mechanisms and approaches presented include a wide variety of species including not only Arabidopsis but also crop species such as Oryza sativa (rice), Glycine max (soybean), and Triticum aestivum (wheat) to address both general and species-specific mechanisms and strategies. The aspects of phosphorus deficiency responses and recently employed strategies of improving phosphate acquisition that are detailed in this review may provide insights into the mechanisms or phenotypes that may be targeted in efforts to improve crop phosphorus content and plant growth in low phosphorus soils., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Molecular biology aims to understand cellular responses and regulatory dynamics in complex biological systems. However, these studies remain challenging in non-model species due to poor functional annotation of regulatory proteins. To overcome this limitation, we develop a multi-layer neural network that determines protein functionality directly from the protein sequence. We annotate kinases and phosphatases in Glycine max. We use the functional annotations from our neural network, Bayesian inference principles, and high resolution phosphoproteomics to infer phosphorylation signaling cascades in soybean exposed to cold, and identify Glyma.10G173000 (TOI5) and Glyma.19G007300 (TOT3) as key temperature regulators. Importantly, the signaling cascade inference does not rely upon known kinase motifs or interaction data, enabling de novo identification of kinase-substrate interactions. Conclusively, our neural network shows generalization and scalability, as such we extend our predictions to Oryza sativa, Zea mays, Sorghum bicolor, and Triticum aestivum. Taken together, we develop a signaling inference approach for non-model species leveraging our predicted kinases and phosphatases., (© 2023. The Author(s).)

The architecture of the rice inflorescence is an important determinant of crop yield. The length of the inflorescence and the number of branches are among the key factors determining the number of spikelets, and thus grains, that a plant will develop. In particular, the timing of the identity transition from indeterminate branch meristem to determinate spikelet meristem governs the complexity of the inflorescence. In this context, the ALOG gene TAWAWA1 (TAW1) has been shown to delay the transition to determinate spikelet development in Oryza sativa (rice). Recently, by combining precise laser microdissection of inflorescence meristems with RNA-seq, we observed that two ALOG genes, OsG1-like 1 (OsG1L1) and OsG1L2, have expression profiles similar to that of TAW1. Here, we report that osg1l1 and osg1l2 loss-of-function CRISPR mutants have similar phenotypes to the phenotype of the previously published taw1 mutant, suggesting that these genes might act on related pathways during inflorescence development. Transcriptome analysis of the osg1l2 mutant suggested interactions of OsG1L2 with other known inflorescence architecture regulators and the data sets were used for the construction of a gene regulatory network (GRN), proposing interactions among genes potentially involved in controlling inflorescence development in rice. In this GRN, we selected the homeodomain-leucine zipper transcription factor encoding the gene OsHOX14 for further characterization. The spatiotemporal expression profiling and phenotypical analysis of CRISPR loss-of-function mutants of OsHOX14 suggests that the proposed GRN indeed serves as a valuable resource for the identification of new proteins involved in rice inflorescence development., (© 2023 The Authors. The Plant Journal published by Society for Experimental Biology and John Wiley & Sons Ltd.)

Proteins are rapidly and dynamically post-transcriptionally modified as cells respond to changes in their environment. For example, protein phosphorylation is mediated by kinases while dephosphorylation is mediated by phosphatases. Quantifying and predicting interactions between kinases, phosphatases, and target proteins over time will aid the study of signaling cascades under a variety of environmental conditions. Here, we describe methods to statistically analyze label-free phosphoproteomic data and infer posttranscriptional regulatory networks over time. We provide an R-based method that can be used to normalize and analyze label-free phosphoproteomic data using variance stabilizing normalization and a linear mixed model across multiple time points and conditions. We also provide a method to infer regulator-target interactions over time using a discretization scheme followed by dynamic Bayesian modeling computations to validate our conclusions. Overall, this pipeline is designed to perform functional analyses and predictions of phosphoproteomic signaling cascades., (© 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

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., (© American Society of Plant Biologists 2022. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Capturing cell-to-cell signals in a three-dimensional (3D) environment is key to studying cellular functions. A major challenge in the current culturing methods is the lack of accurately capturing multicellular 3D environments. In this study, we established a framework for 3D bioprinting plant cells to study cell viability, cell division, and cell identity. We established long-term cell viability for bioprinted Arabidopsis and soybean cells. To analyze the generated large image datasets, we developed a high-throughput image analysis pipeline. Furthermore, we showed the cell cycle reentry of bioprinted cells for which the timing coincides with the induction of core cell cycle genes and regeneration-related genes, ultimately leading to microcallus formation. Last, the identity of bioprinted Arabidopsis root cells expressing endodermal markers was maintained for longer periods. The framework established here paves the way for a general use of 3D bioprinting for studying cellular reprogramming and cell cycle reentry toward tissue regeneration.

Two hemibiotrophic pathogens, Colletotrichum acutatum (Ca) and C . gloeosporioides (Cg), cause anthracnose fruit rot and anthracnose crown rot in strawberry ( Fragaria × ananassa Duchesne), respectively. Both Ca and Cg can initially infect through a brief biotrophic phase, which is associated with the production of intracellular primary hyphae that can infect host cells without causing cell death and establishing hemibiotrophic infection (HBI) or quiescent (latent infections) in leaf tissues. The Ca and Cg HBI in nurseries and subsequent distribution of asymptomatic infected transplants to fruit production fields is the major source of anthracnose epidemics in North Carolina. In the absence of complete resistance, strawberry varieties with good fruit quality showing rate-reducing resistance have frequently been used as a source of resistance to Ca and Cg. However, the molecular mechanisms underlying the rate-reducing resistance or susceptibility to Ca and Cg are still unknown. We performed comparative transcriptome analyses to examine how rate-reducing resistant genotype NCS 10-147 and susceptible genotype 'Chandler' respond to Ca and Cg and identify molecular events between 0 and 48 h after the pathogen-inoculated and mock-inoculated leaf tissues. Although plant response to both Ca and Cg at the same timepoint was not similar, more genes in the resistant interaction were upregulated at 24 hpi with Ca compared with those at 48 hpi. In contrast, a few genes were upregulated in the resistant interaction at 48 hpi with Cg. Resistance response to both Ca and Cg was associated with upregulation of MLP-like protein 44, LRR receptor-like serine/threonine-protein kinase, and auxin signaling pathway, whereas susceptibility was linked to modulation of the phenylpropanoid pathway. Gene regulatory network inference analysis revealed candidate transcription factors (TFs) such as GATA5 and MYB-10, and their downstream targets were upregulated in resistant interactions. Our results provide valuable insights into transcriptional changes during resistant and susceptible interactions, which can further facilitate assessing candidate genes necessary for resistance to two hemibiotrophic Colletotrichum spp. in strawberry., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Adhikari, Aryal, Redpath, Van den Broeck, Ashrafi, Philbrick, Jacobs, Sozzani and Louws.)

Grafting has been adopted for a wide range of crops to enhance productivity and resilience; for example, grafting of Solanaceous crops couples disease-resistant rootstocks with scions that produce high-quality fruit. However, incompatibility severely limits the application of grafting and graft incompatibility remains poorly understood. In grafts, immediate incompatibility results in rapid death, but delayed incompatibility can take months or even years to manifest, creating a significant economic burden for perennial crop production. To gain insight into the genetic mechanisms underlying this phenomenon, we developed a model system using heterografting of tomato (Solanum lycopersicum) and pepper (Capsicum annuum). These grafted plants express signs of anatomical junction failure within the first week of grafting. By generating a detailed timeline for junction formation, we were able to pinpoint the cellular basis for this delayed incompatibility. Furthermore, we inferred gene regulatory networks for compatible self-grafts and incompatible heterografts based on these key anatomical events, which predict core regulators for grafting. Finally, we examined the role of vascular development in graft formation and uncovered SlWOX4 as a potential regulator of graft compatibility. Following this predicted regulator up with functional analysis, we show that Slwox4 homografts fail to form xylem bridges across the junction, demonstrating that indeed, SlWOX4 is essential for vascular reconnection during grafting, and may function as an early indicator of graft failure., (© The Author(s) 2021. Published by Oxford University Press on behalf of American Society of Plant Biologists.)

Analyzing protein movement dynamics and their regulation has shown to be important in the study of cell fate decisions. Such analyses can be performed with scanning fluorescence correlation spectroscopy (scanning FCS), a versatile imaging methodology that has been applied in the animal kingdom and recently adapted to the plant kingdom. Specifically, scanning FCS allows for qualitatively capturing protein movement across barriers, such as the active transport through plasmodesmata, the analysis of protein movement rates, and the quantification of the stoichiometry of protein complexes, composed of one or more different proteins. Importantly, the quantifiable data generated with scanning FCS can be used to inform computational models, enhancing model simulations of in vivo events, such as cell fate decisions, during plant development., (© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

In the plant meristem, tissue-wide maturation gradients are coordinated with specialized cell networks to establish various developmental phases required for indeterminate growth. Here, we used single-cell transcriptomics to reconstruct the protophloem developmental trajectory from the birth of cell progenitors to terminal differentiation in the Arabidopsis thaliana root. PHLOEM EARLY DNA-BINDING-WITH-ONE-FINGER (PEAR) transcription factors mediate lineage bifurcation by activating guanosine triphosphatase signaling and prime a transcriptional differentiation program. This program is initially repressed by a meristem-wide gradient of PLETHORA transcription factors. Only the dissipation of PLETHORA gradient permits activation of the differentiation program that involves mutual inhibition of early versus late meristem regulators. Thus, for phloem development, broad maturation gradients interface with cell-type-specific transcriptional regulators to stage cellular differentiation.

Hydrogel encapsulation has been widely utilized in the study of fundamental cellular mechanisms and has been shown to provide a better representation of the complex in vivo microenvironment in natural biological conditions of mammalian cells. In this review, we provide a background into the adoption of hydrogel encapsulation methods in the study of mammalian cells, highlight some key findings that may aid with the adoption of similar methods for the study of plant cells, including the potential challenges and considerations, and discuss key findings of studies that have utilized these methods in plant sciences., Competing Interests: The authors declare that they have no competing interests regarding the publication of this article., (Copyright © 2021 Srikumar Krishnamoorthy et al.)

Brassinosteroids (BRs) are plant steroid hormones that regulate cell division and stress response. Here we use a systems biology approach to integrate multi-omic datasets and unravel the molecular signaling events of BR response in Arabidopsis. We profile the levels of 26,669 transcripts, 9,533 protein groups, and 26,617 phosphorylation sites from Arabidopsis seedlings treated with brassinolide (BL) for six different lengths of time. We then construct a network inference pipeline called Spatiotemporal Clustering and Inference of Omics Networks (SC-ION) to integrate these data. We use our network predictions to identify putative phosphorylation sites on BES1 and experimentally validate their importance. Additionally, we identify BRONTOSAURUS (BRON) as a transcription factor that regulates cell division, and we show that BRON expression is modulated by BR-responsive kinases and transcription factors. This work demonstrates the power of integrative network analysis applied to multi-omic data and provides fundamental insights into the molecular signaling events occurring during BR response., (© 2021. The Author(s).)

Understanding stem cell regulatory circuits is the next challenge in plant biology, as these cells are essential for tissue growth and organ regeneration in response to stress. In the Arabidopsis primary root apex, stem cell-specific transcription factors BRAVO and WOX5 co-localize in the quiescent centre (QC) cells, where they commonly repress cell division so that these cells can act as a reservoir to replenish surrounding stem cells, yet their molecular connection remains unknown. Genetic and biochemical analysis indicates that BRAVO and WOX5 form a transcription factor complex that modulates gene expression in the QC cells to preserve overall root growth and architecture. Furthermore, by using mathematical modelling we establish that BRAVO uses the WOX5/BRAVO complex to promote WOX5 activity in the stem cells. Our results unveil the importance of transcriptional regulatory circuits in plant stem cell development., (© 2021 The Authors. Published under the terms of the CC BY 4.0 license.)

Quantitative plant biology is an interdisciplinary field that builds on a long history of biomathematics and biophysics. Today, thanks to high spatiotemporal resolution tools and computational modelling, it sets a new standard in plant science. Acquired data, whether molecular, geometric or mechanical, are quantified, statistically assessed and integrated at multiple scales and across fields. They feed testable predictions that, in turn, guide further experimental tests. Quantitative features such as variability, noise, robustness, delays or feedback loops are included to account for the inner dynamics of plants and their interactions with the environment. Here, we present the main features of this ongoing revolution, through new questions around signalling networks, tissue topology, shape plasticity, biomechanics, bioenergetics, ecology and engineering. In the end, quantitative plant biology allows us to question and better understand our interactions with plants. In turn, this field opens the door to transdisciplinary projects with the society, notably through citizen science., Competing Interests: The authors declare that there is no conflict of interest., (© The Author(s), 2021. Published by Cambridge University Press in association with The John Innes Centre 2021.)

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 WUSCHEL-RELATED HOMEOBOX 5 (WOX5) and SHORTROOT (SHR), regulate divisions in the root stem cell niche. However, how these proteins coordinately function to establish systemic behaviour is not well understood. We propose a non-cell autonomous role for WOX5 in the cortex endodermis initial (CEI) and identify a regulator, ANGUSTIFOLIA (AN3)/GRF-INTERACTING FACTOR 1, that coordinates CEI divisions. Here, we show with a multi-scale hybrid model integrating ordinary differential equations (ODEs) and agent-based modeling that quiescent center (QC) and CEI divisions have different dynamics. Specifically, by combining continuous models to describe regulatory networks and agent-based rules, we model systemic behaviour, which led us to predict cell-type-specific expression dynamics of SHR, SCARECROW, WOX5, AN3 and CYCLIND6;1, and experimentally validate CEI cell divisions. Conclusively, our results show an interdependency between CEI and QC divisions., Competing Interests: The authors declare no conflict of interest., (© The Author(s) 2021.)

The strawberry Fra a 1 proteins belong to the class 10 Pathogenesis-Related (PR-10) superfamily. In strawberry, a large number of members have been identified, but only a limited number is expressed in the fruits. In this organ, Fra a 1.01 and Fra a 1.02 are the most abundant Fra proteins in the green and red fruits, respectively, however, their function remains unknown. To know the function of Fra a 1.02 we have generated transgenic lines that silence this gene, and performed metabolomics, RNA-Seq, and hormonal assays. Previous studies associated Fra a 1.02 to strawberry fruit color, but the analysis of anthocyanins in the ripe fruits showed no diminution in their content in the silenced lines. Gene ontology (GO) analysis of the genes differentially expressed indicated that oxidation/reduction was the most represented biological process. Redox state was not apparently altered since no changes were found in ascorbic acid and glutathione (GSH) reduced/oxidized ratio, but GSH content was reduced in the silenced fruits. In addition, a number of glutathione-S-transferases (GST) were down-regulated as result of Fra a 1.02-silencing. Another highly represented GO category was transport which included a number of ABC and MATE transporters. Among the regulatory genes differentially expressed WRKY33.1 and WRKY33.2 were down-regulated, which had previously been assigned a role in strawberry plant defense. A reduced expression of the VQ23 gene and a diminished content of the hormones JA, SA, and IAA were also found. These data might indicate that Fra a 1.02 participates in the defense against pathogens in the ripe strawberry fruits.

Gene expression data analysis and the prediction of causal relationships within gene regulatory networks (GRNs) have guided the identification of key regulatory factors and unraveled the dynamic properties of biological systems. However, drawing accurate and unbiased conclusions requires a comprehensive understanding of relevant tools, computational methods, and their workflows. The topics covered in this chapter encompass the entire workflow for GRN inference including: (1) experimental design; (2) RNA sequencing data processing; (3) differentially expressed gene (DEG) selection; (4) clustering prior to inference; (5) network inference techniques; and (6) network visualization and analysis. Moreover, this chapter aims to present a workflow feasible and accessible for plant biologists without a bioinformatics or computer science background. To address this need, TuxNet, a user-friendly graphical user interface that integrates RNA sequencing data analysis with GRN inference, is chosen for the purpose of providing a detailed tutorial., (© 2021. Springer Science+Business Media, LLC, part of Springer Nature.)

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., Competing Interests: The authors declare no competing interest., (Copyright © 2020 the Author(s). Published by PNAS.)

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., Competing Interests: The authors declare no competing interest.

Plant responses to environmental and intrinsic signals are tightly controlled by multiple transcription factors (TFs). These TFs and their regulatory connections form gene regulatory networks (GRNs), which provide a blueprint of the transcriptional regulations underlying plant development and environmental responses. This review provides examples of experimental methodologies commonly used to identify regulatory interactions and generate GRNs. Additionally, this review describes network inference techniques that leverage gene expression data to predict regulatory interactions. These computational and experimental methodologies yield complex networks that can identify new regulatory interactions, driving novel hypotheses. Biological properties that contribute to the complexity of GRNs are also described in this review. These include network topology, network size, transient binding of TFs to DNA, and competition between multiple upstream regulators. Finally, this review highlights the potential of machine learning approaches to leverage gene expression data to predict phenotypic outputs., (Copyright © 2020 Van den Broeck, Gordon, Inzé, Williams and Sozzani.)

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.

FaMADS9 is the strawberry (Fragaria x ananassa) gene that exhibits the highest homology to the tomato (Solanum lycopersicum) RIN gene. Transgenic lines were obtained in which FaMADS9 was silenced. The fruits of these lines did not show differences in basic parameters, such as fruit firmness or colour, but exhibited lower Brix values in three of the four independent lines. The gene ontology MapMan category that was most enriched among the differentially expressed genes in the receptacles at the white stage corresponded to the regulation of transcription, including a high percentage of transcription factors and regulatory proteins associated with auxin action. In contrast, the most enriched categories at the red stage were transport, lipid metabolism and cell wall. Metabolomic analysis of the receptacles of the transformed fruits identified significant changes in the content of maltose, galactonic acid-1,4-lactone, proanthocyanidins and flavonols at the green/white stage, while isomaltose, anthocyanins and cuticular wax metabolism were the most affected at the red stage. Among the regulatory genes that were differentially expressed in the transgenic receptacles were several genes previously linked to flavonoid metabolism, such as MYB10, DIV, ZFN1, ZFN2, GT2, and GT5, or associated with the action of hormones, such as abscisic acid, SHP, ASR, GTE7 and SnRK2.7. The inference of a gene regulatory network, based on a dynamic Bayesian approach, among the genes differentially expressed in the transgenic receptacles at the white and red stages, identified the genes KAN1, DIV, ZFN2 and GTE7 as putative targets of FaMADS9. A MADS9-specific CArG box was identified in the promoters of these genes., (© 2019 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.)

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., (© 2019 The Authors The Plant Journal © 2019 John Wiley & Sons Ltd.)

Imaging technologies have been used to understand plant genetic and developmental processes, from the dynamics of gene expression to tissue and organ morphogenesis. Although the field has advanced incredibly in recent years, gaps remain in identifying fine and dynamic spatiotemporal intervals of target processes, such as changes to gene expression in response to abiotic stresses. Lightsheet microscopy is a valuable tool for such studies due to its ability to perform long-term imaging at fine intervals of time and at low photo-toxicity of live vertically oriented seedlings. In this chapter, we describe a detailed method for preparing and imaging Arabidopsis thaliana seedlings for lightsheet microscopy via a Multi-Sample Imaging Growth Chamber (MAGIC), which allows simultaneous imaging of at least four samples. This method opens new avenues for acquiring imaging data at a high temporal resolution, which can be eventually probed to identify key regulatory time points and any spatial dependencies of target developmental processes., (© 2020 Elsevier Inc. All rights reserved.)

Fluorescence microscopy can produce large quantities of data that reveal the spatiotemporal behavior of gene expression at the cellular level in plants. Automated or semi-automated image analysis methods are required to extract data from these images. These data are helpful in revealing spatial and/or temporal-dependent processes that influence development in the meristematic region of plant roots. Tracking spatiotemporal gene expression in the meristem requires the processing of multiple microscopy imaging channels (one channel used to image root geometry which serves as a reference for relating locations within the root, and one or more channels used to image fluorescent gene expression signals). Many automated image analysis methods rely on the staining of cell walls with fluorescent dyes to capture cellular geometry and overall root geometry. However, in long time-course imaging experiments, dyes may fade which hinders spatial assessment in image analysis. Here, we describe a procedure for analyzing 3D microscopy images to track spatiotemporal gene expression signals using the MATLAB-based BioVision Tracker software. This software requires either a fluorescence image or a brightfield image to analyze root geometry and a fluorescence image to capture and track temporal changes in gene expression., (© 2020 Elsevier Inc. All rights reserved.)

Stem cells are responsible for generating all of the differentiated cells, tissues, and organs in a multicellular organism and, thus, play a crucial role in cell renewal, regeneration, and organization. A number of stem cell type-specific genes have a known role in stem cell maintenance, identity, and/or division. Yet, how genes expressed across different stem cell types, referred to here as stem-cell-ubiquitous genes, contribute to stem cell regulation is less understood. Here, we find that, in the Arabidopsis root, a stem-cell-ubiquitous gene, TESMIN-LIKE CXC2 (TCX2), controls stem cell division by regulating stem cell-type specific networks. Development of a mathematical model of TCX2 expression allows us to show that TCX2 orchestrates the coordinated division of different stem cell types. Our results highlight that genes expressed across different stem cell types ensure cross-communication among cells, allowing them to divide and develop harmonically together.

Exposure of plants to abiotic stresses, whether individually or in combination, triggers dynamic changes to gene regulation. These responses induce distinct changes in phenotypic characteristics, enabling the plant to adapt to changing environments. For example, iron deficiency and heat stress have been shown to alter root development by reducing primary root growth and reducing cell proliferation, respectively. Currently, identifying the dynamic temporal coordination of genetic responses to combined abiotic stresses remains a bottleneck. This is, in part, due to an inability to isolate specific intervals in developmental time where differential activity in plant stress responses plays a critical role. Here, we observed that iron deficiency, in combination with temporary heat stress, suppresses the expression of iron deficiency-responsive pPYE::LUC (POPEYE::luciferase) and pBTS::LUC (BRUTUS::luciferase) reporter genes. Moreover, root growth was suppressed less under combined iron deficiency and heat stress than under either single stress condition. To further explore the interaction between pathways, we also created a computer vision pipeline to extract, analyze, and compare high-dimensional dynamic spatial and temporal cellular data in response to heat and iron deficiency stress conditions at high temporal resolution. Specifically, we used fluorescence light sheet microscopy to image Arabidopsis thaliana roots expressing CYCB1;1:GFP, a marker for cell entry into mitosis, every 20 min for 24 h exposed to either iron sufficiency, iron deficiency, heat stress, or combined iron deficiency and heat stress. Our pipeline extracted spatiotemporal metrics from these time-course data. These metrics showed that the persistency and timing of CYCB1;1:GFP signal were uniquely different under combined iron deficiency and heat stress conditions versus the single stress conditions. These metrics also indicated that the spatiotemporal characteristics of the CYCB1;1:GFP signal under combined stress were more dissimilar to the control response than the response seen under iron deficiency for the majority of the 24-h experiment. Moreover, the combined stress response was less dissimilar to the control than the response seen under heat stress. This indicated that pathways activated when the plant is exposed to both iron deficiency and heat stress affected CYCB1;1:GFP spatiotemporal function antagonistically., (Copyright © 2019 Buckner, Madison, Chou, Matthiadis, Melvin, Sozzani, Williams and Long.)

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 exhibits 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, providing a mechanism for cellular competence for auxin signaling., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Plant developmental plasticity relies on the activities of meristems, regions where stem cells continuously produce new cells [1]. The lateral root cap (LRC) is the outermost tissue of the root meristem [1], and it is known to play an important role during root development [2-6]. In particular, it has been shown that mechanical or genetic ablation of LRC cells affect meristem size [7, 8]; however, the molecular mechanisms involved are unknown. Root meristem size and, consequently, root growth depend on the position of the transition zone (TZ), a boundary that separates dividing from differentiating cells [9, 10]. The interaction of two phytohormones, cytokinin and auxin, is fundamental in controlling the position of the TZ [9, 10]. Cytokinin via the ARABIDOPSIS RESPONSE REGULATOR 1 (ARR1) control auxin distribution within the meristem, generating an instructive auxin minimum that positions the TZ [10]. We identify a cytokinin-dependent molecular mechanism that acts in the LRC to control the position of the TZ and meristem size. We show that auxin levels within the LRC cells depends on PIN-FORMED 5 (PIN5), a cytokinin-activated intracellular transporter that pumps auxin from the cytoplasm into the endoplasmic reticulum, and on irreversible auxin conjugation mediated by the IAA-amino synthase GRETCHEN HAGEN 3.17 (GH3.17). By titrating auxin in the LRC, the PIN5 and the GH3.17 genes control auxin levels in the entire root meristem. Overall, our results indicate that the LRC serves as an auxin sink that, under the control of cytokinin, regulates meristem size and root growth., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

To create a three-dimensional structure, plants rely on oriented cell divisions and cell elongation. Oriented cell divisions are specifically important in procambium cells of the root to establish the different vascular cell types [1, 2]. These divisions are in part controlled by the auxin-controlled TARGET OF MONOPTEROS5 (TMO5) and LONESOME HIGHWAY (LHW) transcription factor complex [3-7]. Loss-of-function of tmo5 or lhw clade members results in strongly reduced vascular cell file numbers, whereas ectopic expression of both TMO5 and LHW can ubiquitously induce periclinal and radial cell divisions in all cell types of the root meristem. TMO5 and LHW interact only in young xylem cells, where they promote expression of two direct target genes involved in the final step of cytokinin (CK) biosynthesis, LONELY GUY3 (LOG3) and LOG4 [8, 9] Therefore, CK was hypothesized to act as a mobile signal from the xylem to trigger divisions in the neighboring procambium cells [3, 6]. To unravel how TMO5/LHW-dependent cytokinin regulates cell proliferation, we analyzed the transcriptional responses upon simultaneous induction of both transcription factors. Using inferred network analysis, we identified AT2G28510/DOF2.1 as a cytokinin-dependent downstream target gene. We further showed that DOF2.1 controls specific procambium cell divisions without inducing other cytokinin-dependent effects such as the inhibition of vascular differentiation. In summary, our results suggest that DOF2.1 and its closest homologs control vascular cell proliferation, thus leading to radial expansion of the root., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Plants integrate a wide range of cellular, developmental, and environmental signals to regulate complex patterns of gene expression. Recent advances in genomic technologies enable differential gene expression analysis at a systems level, allowing for improved inference of the network of regulatory interactions between genes. These gene regulatory networks, or GRNs, are used to visualize the causal regulatory relationships between regulators and their downstream target genes. Accordingly, these GRNs can represent spatial, temporal, and/or environmental regulations and can identify functional genes. This review summarizes recent computational approaches applied to different types of gene expression data to infer GRNs in the context of plant growth and development. Three stages of GRN inference are described: first, data collection and analysis based on the dataset type; second, network inference application based on data availability and proposed hypotheses; and third, validation based on in silico, in vivo, and in planta methods. In addition, this review relates data collection strategies to biological questions, organizes inference algorithms based on statistical methods and data types, discusses experimental design considerations, and provides guidelines for GRN inference with an emphasis on the benefits of integrative approaches, especially when a priori information is limited. Finally, this review concludes that computational frameworks integrating large-scale heterogeneous datasets are needed for a more accurate (e.g. fewer false interactions), detailed (e.g. discrimination between direct versus indirect interactions), and comprehensive (e.g. genetic regulation under various conditions and spatial locations) inference of GRNs., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

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 cambium 1 . 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 factors 4 -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.

Automated tracking of spatiotemporal gene expression using in vivo microscopy images have given great insight into understanding developmental processes in multicellular organisms. Many existing analysis tools rely on the fluorescent tagging of cell wall or cell nuclei localized proteins to assess position, orientation, and overall shape of an organism; information necessary for determining locations of gene expression activity. Particularly in plants, organism lines that have fluorescent tags can take months to develop, which can be time consuming and costly. We propose an automated solution for analyzing spatial characteristics of gene expression without the necessity of fluorescent tagged cell walls or cell nuclei. Our solution indicates, segments, and tracks gene expression using a fluorescent imaging channel of a light sheet microscope while determining gene expression location within an organism from a Brightfield (non-fluorescent) imaging channel. We use the images obtained from the Arabidopsis thaliana root as a proof of concept for our solution by studying the effects of heat shock stress on CYCLIN B1 protein production.