A prion-like protein regulator of seed germination undergoes hydration-dependent phase separation.

Many organisms evolved strategies to survive desiccation. Plant seeds protect dehydrated embryos from various stressors and can lay dormant for millennia. Hydration is the key trigger to initiate germination, but the mechanism by which seeds sense water remains unresolved. We identified an uncharacterized Arabidopsis thaliana prion-like protein we named FLOE1, which phase separates upon hydration and allows the embryo to sense water stress. We demonstrate that biophysical states of FLOE1 condensates modulate its biological function in vivo in suppressing seed germination under unfavorable environments. We find intragenic, intraspecific, and interspecific natural variation in FLOE1 expression and phase separation and show that intragenic variation is associated with adaptive germination strategies in natural populations. This combination of molecular, organismal, and ecological studies uncovers FLOE1 as a tunable environmental sensor with direct implications for the design of drought-resistant crops, in the face of climate change.

Linking Genes to Shape in Plants Using Morphometrics.

A transition from qualitative to quantitative descriptors of morphology has been facilitated through the growing field of morphometrics, representing the conversion of shapes and patterns into numbers. The analysis of plant form at the macromorphological scale using morphometric approaches quantifies what is commonly referred to as a phenotype. Quantitative phenotypic analysis of individuals with contrasting genotypes in turn provides a means to establish links between genes and shapes. The path from a gene to a morphological phenotype is, however, not direct, with instructive information progressing both across multiple scales of biological complexity and through nonintuitive feedback, such as mechanical signals. In this review, we explore morphometric approaches used to perform whole-plant phenotyping and quantitative approaches in capture processes in the mesoscales, which bridge the gaps between genes and shapes in plants. Quantitative frameworks involving both the computational simulation and the discretization of data into networks provide a putative path to predicting emergent shape from underlying genetic programs.

Publisher Correction: Extensive signal integration by the phytohormone protein network.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Extensive signal integration by the phytohormone protein network.

Plant hormones coordinate responses to environmental cues with developmental programs1, and are fundamental for stress resilience and agronomic yield2. The core signalling pathways underlying the effects of phytohormones have been elucidated by genetic screens and hypothesis-driven approaches, and extended by interactome studies of select pathways3. However, fundamental questions remain about how information from different pathways is integrated. Genetically, most phenotypes seem to be regulated by several hormones, but transcriptional profiling suggests that hormones trigger largely exclusive transcriptional programs4. We hypothesized that protein-protein interactions have an important role in phytohormone signal integration. Here, we experimentally generated a systems-level map of the Arabidopsis phytohormone signalling network, consisting of more than 2,000 binary protein-protein interactions. In the highly interconnected network, we identify pathway communities and hundreds of previously unknown pathway contacts that represent potential points of crosstalk. Functional validation of candidates in seven hormone pathways reveals new functions for 74% of tested proteins in 84% of candidate interactions, and indicates that a large majority of signalling proteins function pleiotropically in several pathways. Moreover, we identify several hundred largely small-molecule-dependent interactions of hormone receptors. Comparison with previous reports suggests that noncanonical and nontranscription-mediated receptor signalling is more common than hitherto appreciated.

Cellular and gene expression patterns associated with root bifurcation in Selaginella.

The roots of lycophytes branch through dichotomy or bifurcation, during which the root apex splits into two daughter roots. This is morphologically distinct from lateral root (LR) branching in the extant euphyllophytes, with LRs developing along the root axis at different distances from the apex. Although the process of root bifurcation is poorly understood, such knowledge can be important, because it may represent an evolutionarily ancient strategy that roots recruited to form new stem cells or meristems. In this study, we examined root bifurcation in the lycophyte Selaginella moellendorffii. We characterized an in vitro developmental time frame based on repetitive apex bifurcations, allowing us to sample different stages of dichotomous root branching and analyze the root meristem and root branching in S. moellendorffii at the microscopic and transcriptomic level. Our results showed that, in contrast to previous assumptions, initial cells (ICs) in the root meristem are mostly not tetrahedral but rather show an irregular shape. Tracking down the early stages of root branching argues for the occurrence of a symmetric division of the single IC, resulting in two apical stem cells that initiate root meristem bifurcation. Moreover, we generated a S. moellendorffii root branching transcriptome that resulted in the delineation of a subset of core meristem genes. The occurrence of multiple putative orthologs of meristem genes in this dataset suggests the presence of conserved pathways in the control of meristem and root stem cell establishment or maintenance.

Nitric oxide sensing in plants is mediated by proteolytic control of group VII ERF transcription factors.

Nitric oxide (NO) is an important signaling compound in prokaryotes and eukaryotes. In plants, NO regulates critical developmental transitions and stress responses. Here, we identify a mechanism for NO sensing that coordinates responses throughout development based on targeted degradation of plant-specific transcriptional regulators, the group VII ethylene response factors (ERFs). We show that the N-end rule pathway of targeted proteolysis targets these proteins for destruction in the presence of NO, and we establish them as critical regulators of diverse NO-regulated processes, including seed germination, stomatal closure, and hypocotyl elongation. Furthermore, we define the molecular mechanism for NO control of germination and crosstalk with abscisic acid (ABA) signaling through ERF-regulated expression of ABSCISIC ACID INSENSITIVE5 (ABI5). Our work demonstrates how NO sensing is integrated across multiple physiological processes by direct modulation of transcription factor stability and identifies group VII ERFs as central hubs for the perception of gaseous signals in plants.

Temperature variability is integrated by a spatially embedded decision-making center to break dormancy in Arabidopsis seeds.

Plants perceive and integrate information from the environment to time critical transitions in their life cycle. Some mechanisms underlying this quantitative signal processing have been described, whereas others await discovery. Seeds have evolved a mechanism to integrate environmental information by regulating the abundance of the antagonistically acting hormones abscisic acid (ABA) and gibberellin (GA). Here, we show that hormone metabolic interactions and their feedbacks are sufficient to create a bistable developmental fate switch in Arabidopsis seeds. A digital single-cell atlas mapping the distribution of hormone metabolic and response components revealed their enrichment within the embryonic radicle, identifying the presence of a decision-making center within dormant seeds. The responses to both GA and ABA were found to occur within distinct cell types, suggesting cross-talk occurs at the level of hormone transport between these signaling centers. We describe theoretically, and demonstrate experimentally, that this spatial separation within the decision-making center is required to process variable temperature inputs from the environment to promote the breaking of dormancy. In contrast to other noise-filtering systems, including human neurons, the functional role of this spatial embedding is to leverage variability in temperature to transduce a fate-switching signal within this biological system. Fluctuating inputs therefore act as an instructive signal for seeds, enhancing the accuracy with which plants are established in ecosystems, and distributed computation within the radicle underlies this signal integration mechanism.

The Transcription Factor ATHB5 Affects GA-Mediated Plasticity in Hypocotyl Cell Growth during Seed Germination.

Gibberellic acid (GA)-mediated cell expansion initiates the seed-to-seedling transition in plants and is repressed by DELLA proteins. Using digital single-cell analysis, we identified a cellular subdomain within the midhypocotyl, whose expansion drives the final step of this developmental transition under optimal conditions. Using network inference, the transcription factor ATHB5 was identified as a genetic factor whose localized expression promotes GA-mediated expansion specifically within these cells. Both this protein and its putative growth-promoting target EXPANSIN3 are repressed by DELLA, and coregulated at single-cell resolution during seed germination. The cellular domains of hormone sensitivity were explored within the Arabidopsis (Arabidopsis thaliana) embryo by putting seeds under GA-limiting conditions and quantifying cellular growth responses. The middle and upper hypocotyl have a greater requirement for GA to promote cell expansion than the lower embryo axis. Under these conditions, germination was still completed following enhanced growth within the radicle and lower axis. Under GA-limiting conditions, the athb5 mutant did not show a phenotype at the level of seed germination, but it did at a cellular level with reduced cell expansion in the hypocotyl relative to the wild type. These data reveal that the spatiotemporal cell expansion events driving this transition are not determinate, and the conditional use of GA-ATHB5-mediated hypocotyl growth under optimal conditions may be used to optionally support rapid seedling growth. This study demonstrates that multiple genetic and spatiotemporal cell expansion mechanisms underlie the seed to seedling transition in Arabidopsis.

Accuracy in Quantitative 3D Image Analysis.

Quantitative 3D imaging is becoming an increasingly popular and powerful approach to investigate plant growth and development. With the increased use of 3D image analysis, standards to ensure the accuracy and reproducibility of these data are required. This commentary highlights how image acquisition and postprocessing can introduce artifacts into 3D image data and proposes steps to increase both the accuracy and reproducibility of these analyses. It is intended to aid researchers entering the field of 3D image processing of plant cells and tissues and to help general readers in understanding and evaluating such data.

Digital Single-Cell Analysis of Plant Organ Development Using 3DCellAtlas.

Diverse molecular networks underlying plant growth and development are rapidly being uncovered. Integrating these data into the spatial and temporal context of dynamic organ growth remains a technical challenge. We developed 3DCellAtlas, an integrative computational pipeline that semiautomatically identifies cell types and quantifies both 3D cellular anisotropy and reporter abundance at single-cell resolution across whole plant organs. Cell identification is no less than 97.8% accurate and does not require transgenic lineage markers or reference atlases. Cell positions within organs are defined using an internal indexing system generating cellular level organ atlases where data from multiple samples can be integrated. Using this approach, we quantified the organ-wide cell-type-specific 3D cellular anisotropy driving Arabidopsis thaliana hypocotyl elongation. The impact ethylene has on hypocotyl 3D cell anisotropy identified the preferential growth of endodermis in response to this hormone. The spatiotemporal dynamics of the endogenous DELLA protein RGA, expansin gene EXPA3, and cell expansion was quantified within distinct cell types of Arabidopsis roots. A significant regulatory relationship between RGA, EXPA3, and growth was present in the epidermis and endodermis. The use of single-cell analyses of plant development enables the dynamics of diverse regulatory networks to be integrated with 3D organ growth.

Quantitative analysis of the 3D cell shape changes driving soybean germination.

Seed germination is central to plant establishment and is the starting point for the majority of world agriculture. This transition from seed to seedling has been extensively studied at an organ level, while few studies have examined the cellular events which underlie it. Reports in the model species Arabidopsis have identified a radicle-derived wave of cell expansion underlying the germination process. Whether this spatiotemporal pattern of cell expansion is specific to this model plant or conserved in other species remains unknown. Here we examined the 3D cell anisotropy driving germination in soybean. By examining changes in cell shape at two positions along the length of the axis over time, preferential growth was observed in the portion of the axis closest to the radicle. A gradient of cell size was observed across the cortical cell layers of the soybean axis, and differences in starting cell size translated into differential relative growth rates across cell layers where larger cells showed greater relative growth rates than smaller cells. Differences in cell position-specific cell anisotropy were also observed. These data demonstrate that a radicle-derived growth pattern is present in the crop species soybean, and reveal the presence of a complex cellular organization in this hypocotyl which show cell type-specific anisotropy diving germination.

Variability in seeds: biological, ecological, and agricultural implications.

Variability is observed in biology across multiple scales, ranging from populations, individuals, and cells to the molecular components within cells. This review explores the sources and roles of this variability across these scales, focusing on seeds. From a biological perspective, the role and the impact this variability has on seed behaviour and adaptation to the environment is discussed. The consequences of seed variability on agricultural production systems, which demand uniformity, are also examined. We suggest that by understanding the basis and underlying mechanisms of variability in seeds, strategies to increase seed population uniformity can be developed, leading to enhanced agricultural production across variable climatic conditions.

Homeostatic response to hypoxia is regulated by the N-end rule pathway in plants.

Plants and animals are obligate aerobes, requiring oxygen for mitochondrial respiration and energy production. In plants, an unanticipated decline in oxygen availability (hypoxia), as caused by roots becoming waterlogged or foliage submergence, triggers changes in gene transcription and messenger RNA translation that promote anaerobic metabolism and thus sustain substrate-level ATP production. In contrast to animals, oxygen sensing has not been ascribed to a mechanism of gene regulation in response to oxygen deprivation in plants. Here we show that the N-end rule pathway of targeted proteolysis acts as a homeostatic sensor of severe low oxygen levels in Arabidopsis, through its regulation of key hypoxia-response transcription factors. We found that plants lacking components of the N-end rule pathway constitutively express core hypoxia-response genes and are more tolerant of hypoxic stress. We identify the hypoxia-associated ethylene response factor group VII transcription factors of Arabidopsis as substrates of this pathway. Regulation of these proteins by the N-end rule pathway occurs through a characteristic conserved motif at the amino terminus initiating with Met-Cys. Enhanced stability of one of these proteins, HRE2, under low oxygen conditions improves hypoxia survival and reveals a molecular mechanism for oxygen sensing in plants via the evolutionarily conserved N-end rule pathway. SUB1A-1, a major determinant of submergence tolerance in rice, was shown not to be a substrate for the N-end rule pathway despite containing the N-terminal motif, indicating that it is uncoupled from N-end rule pathway regulation, and that enhanced stability may relate to the superior tolerance of Sub1 rice varieties to multiple abiotic stresses.

Mechanical constraints imposed by 3D cellular geometry and arrangement modulate growth patterns in the Arabidopsis embryo.

Morphogenesis occurs in 3D space over time and is guided by coordinated gene expression programs. Here we use postembryonic development in Arabidopsis plants to investigate the genetic control of growth. We demonstrate that gene expression driving the production of the growth-stimulating hormone gibberellic acid and downstream growth factors is first induced within the radicle tip of the embryo. The center of cell expansion is, however, spatially displaced from the center of gene expression. Because the rapidly growing cells have very different geometry from that of those at the tip, we hypothesized that mechanical factors may contribute to this growth displacement. To this end we developed 3D finite-element method models of growing custom-designed digital embryos at cellular resolution. We used this framework to conceptualize how cell size, shape, and topology influence tissue growth and to explore the interplay of geometrical and genetic inputs into growth distribution. Our simulations showed that mechanical constraints are sufficient to explain the disconnect between the experimentally observed spatiotemporal patterns of gene expression and early postembryonic growth. The center of cell expansion is the position where genetic and mechanical facilitators of growth converge. We have thus uncovered a mechanism whereby 3D cellular geometry helps direct where genetically specified growth takes place.

The decision to germinate is regulated by divergent molecular networks in spores and seeds.

Dispersal is a key step in land plant life cycles, usually via formation of spores or seeds. Regulation of spore- or seed-germination allows control over the timing of transition from one generation to the next, enabling plant dispersal. A combination of environmental and genetic factors determines when seed germination occurs. Endogenous hormones mediate this decision in response to the environment. Less is known about how spore germination is controlled in earlier-evolving nonseed plants. Here, we present an in-depth analysis of the environmental and hormonal regulation of spore germination in the model bryophyte Physcomitrella patens (Aphanoregma patens). Our data suggest that the environmental signals regulating germination are conserved, but also that downstream hormone integration pathways mediating these responses in seeds were acquired after the evolution of the bryophyte lineage. Moreover, the role of abscisic acid and diterpenes (gibberellins) in germination assumed much greater importance as land plant evolution progressed. We conclude that the endogenous hormone signalling networks mediating germination in response to the environment may have evolved independently in spores and seeds. This paves the way for future research about how the mechanisms of plant dispersal on land evolved.

Systems analysis of plant functional, transcriptional, physical interaction, and metabolic networks.

Physiological responses, developmental programs, and cellular functions rely on complex networks of interactions at different levels and scales. Systems biology brings together high-throughput biochemical, genetic, and molecular approaches to generate omics data that can be analyzed and used in mathematical and computational models toward uncovering these networks on a global scale. Various approaches, including transcriptomics, proteomics, interactomics, and metabolomics, have been employed to obtain these data on the cellular, tissue, organ, and whole-plant level. We summarize progress on gene regulatory, cofunction, protein interaction, and metabolic networks. We also illustrate the main approaches that have been used to obtain these networks, with specific examples from Arabidopsis thaliana, and describe the pros and cons of each approach.

Arabidopsis PYR/PYL/RCAR receptors play a major role in quantitative regulation of stomatal aperture and transcriptional response to abscisic acid.

Abscisic acid (ABA) is a key hormone for plant growth, development, and stress adaptation. Perception of ABA through four types of receptors has been reported. We show here that impairment of ABA perception through the PYRABACTIN RESISTANCE1 (PYR1)/PYR1-LIKE (PYL)/REGULATORY COMPONENTS OF ABA RECEPTORS (RCAR) branch reduces vegetative growth and seed production and leads to a severe open stomata and ABA-insensitive phenotype, even though other branches for ABA perception remain functional. An Arabidopsis thaliana sextuple mutant impaired in six PYR/PYL receptors, namely PYR1, PYL1, PYL2, PYL4, PYL5, and PYL8, was able to germinate and grow even on 100 µM ABA. Whole-rosette stomatal conductance (Gst) measurements revealed that leaf transpiration in the sextuple pyr/pyl mutant was higher than in the ABA-deficient aba3-1 or ABA-insensitive snrk2.6 mutants. The gradually increasing Gst values of plants lacking three, four, five, and six PYR/PYLs indicate quantitative regulation of stomatal aperture by this family of receptors. The sextuple mutant lacked ABA-mediated activation of SnRK2s, and ABA-responsive gene expression was dramatically impaired as was reported in snrk2.2/2.3/2.6. In summary, these results show that ABA perception by PYR/PYLs plays a major role in regulation of seed germination and establishment, basal ABA signaling required for vegetative and reproductive growth, stomatal aperture, and transcriptional response to the hormone.

AtMYB93 is a novel negative regulator of lateral root development in Arabidopsis.

Plant root system plasticity is critical for survival in changing environmental conditions. One important aspect of root architecture is lateral root development, a complex process regulated by hormone, environmental and protein signalling pathways. Here we show, using molecular genetic approaches, that the MYB transcription factor AtMYB93 is a novel negative regulator of lateral root development in Arabidopsis. We identify AtMYB93 as an interaction partner of the lateral-root-promoting ARABIDILLO proteins. Atmyb93 mutants have faster lateral root developmental progression and enhanced lateral root densities, while AtMYB93-overexpressing lines display the opposite phenotype. AtMYB93 is expressed strongly, specifically and transiently in the endodermal cells overlying early lateral root primordia and is additionally induced by auxin in the basal meristem of the primary root. Furthermore, Atmyb93 mutant lateral root development is insensitive to auxin, indicating that AtMYB93 is required for normal auxin responses during lateral root development. We propose that AtMYB93 is part of a novel auxin-induced negative feedback loop stimulated in a select few endodermal cells early during lateral root development, ensuring that lateral roots only develop when absolutely required. Putative AtMYB93 homologues are detected throughout flowering plants and represent promising targets for manipulating root systems in diverse crop species.

Transcriptional dynamics of two seed compartments with opposing roles in Arabidopsis seed germination.

Seed germination is a critical stage in the plant life cycle and the first step toward successful plant establishment. Therefore, understanding germination is of important ecological and agronomical relevance. Previous research revealed that different seed compartments (testa, endosperm, and embryo) control germination, but little is known about the underlying spatial and temporal transcriptome changes that lead to seed germination. We analyzed genome-wide expression in germinating Arabidopsis (Arabidopsis thaliana) seeds with both temporal and spatial detail and provide Web-accessible visualizations of the data reported (vseed.nottingham.ac.uk). We show the potential of this high-resolution data set for the construction of meaningful coexpression networks, which provide insight into the genetic control of germination. The data set reveals two transcriptional phases during germination that are separated by testa rupture. The first phase is marked by large transcriptome changes as the seed switches from a dry, quiescent state to a hydrated and active state. At the end of this first transcriptional phase, the number of differentially expressed genes between consecutive time points drops. This increases again at testa rupture, the start of the second transcriptional phase. Transcriptome data indicate a role for mechano-induced signaling at this stage and subsequently highlight the fates of the endosperm and radicle: senescence and growth, respectively. Finally, using a phylotranscriptomic approach, we show that expression levels of evolutionarily young genes drop during the first transcriptional phase and increase during the second phase. Evolutionarily old genes show an opposite pattern, suggesting a more conserved transcriptome prior to the completion of germination.

Functional network construction in Arabidopsis using rule-based machine learning on large-scale data sets.

The meta-analysis of large-scale postgenomics data sets within public databases promises to provide important novel biological knowledge. Statistical approaches including correlation analyses in coexpression studies of gene expression have emerged as tools to elucidate gene function using these data sets. Here, we present a powerful and novel alternative methodology to computationally identify functional relationships between genes from microarray data sets using rule-based machine learning. This approach, termed "coprediction," is based on the collective ability of groups of genes co-occurring within rules to accurately predict the developmental outcome of a biological system. We demonstrate the utility of coprediction as a powerful analytical tool using publicly available microarray data generated exclusively from Arabidopsis thaliana seeds to compute a functional gene interaction network, termed Seed Co-Prediction Network (SCoPNet). SCoPNet predicts functional associations between genes acting in the same developmental and signal transduction pathways irrespective of the similarity in their respective gene expression patterns. Using SCoPNet, we identified four novel regulators of seed germination (ALTERED SEED GERMINATION5, 6, 7, and 8), and predicted interactions at the level of transcript abundance between these novel and previously described factors influencing Arabidopsis seed germination. An online Web tool to query SCoPNet has been developed as a community resource to dissect seed biology and is available at http://www.vseed.nottingham.ac.uk/.