Multicellular development produces patterns of specialized cell types. Yet, it is often unclear how individual cells within a field of identical cells initiate the patterning process. Using live imaging, quantitative image analyses and modeling, we show that during Arabidopsis thaliana sepal development, fluctuations in the concentration of the transcription factor ATML1 pattern a field of identical epidermal cells to differentiate into giant cells interspersed between smaller cells. We find that ATML1 is expressed in all epidermal cells. However, its level fluctuates in each of these cells. If ATML1 levels surpass a threshold during the G2 phase of the cell cycle, the cell will likely enter a state of endoreduplication and become giant. Otherwise, the cell divides. Our results demonstrate a fluctuation-driven patterning mechanism for how cell fate decisions can be initiated through a random yet tightly regulated process.DOI: http://dx.doi.org/10.7554/eLife.19131.001

Plants, along with other multicellular organisms, have evolved specialized regulatory mechanisms to achieve proper tissue growth and morphogenesis. During development, growing tissues generate specialized cell types and complex patterns necessary for establishing the function of the organ. Tissue growth is a tightly regulated process that yields highly reproducible outcomes. Nevertheless, the underlying cellular and molecular behaviors are often stochastic. Thus, how does stochasticity, together with strict genetic regulation, give rise to reproducible tissue development? This review draws examples from plants as well as other systems to explore stochasticity in plant cell division, growth, and patterning. We conclude that stochasticity is often needed to create small differences between identical cells, which are amplified and stabilized by genetic and mechanical feedback loops to begin cell differentiation. These first few differentiating cells initiate traditional patterning mechanisms to ensure regular development.

Growth of tissues is highly reproducible; yet, growth of individual cells in a tissue is highly variable, and neighboring cells can grow at different rates. We analyzed the growth of epidermal cell lineages in the Arabidopsis (Arabidopsis thaliana) sepal to determine how the growth curves of individual cell lineages relate to one another in a developing tissue. To identify underlying growth trends, we developed a continuous displacement field to predict spatially averaged growth rates. We showed that this displacement field accurately describes the growth of sepal cell lineages and reveals underlying trends within the variability of in vivo cellular growth. We found that the tissue, individual cell lineages, and cell walls all exhibit growth rates that are initially low, accelerate to a maximum, and decrease again. Accordingly, these growth curves can be represented by sigmoid functions. We examined the relationships among the cell lineage growth curves and surprisingly found that all lineages reach the same maximum growth rate relative to their size. However, the cell lineages are not synchronized; each cell lineage reaches this same maximum relative growth rate but at different times. The heterogeneity in observed growth results from shifting the same underlying sigmoid curve in time and scaling by size. Thus, despite the variability in growth observed in our study and others, individual cell lineages in the developing sepal follow similarly shaped growth curves.

As scientists, we are at least as excited about the open questions—the things we don’t know—as the discoveries. Here, we asked 15 experts to describe the most compelling open questions in plant cell biology. These are their questions: How are organelle identity, domains, and boundaries maintained under the continuous flux of vesicle trafficking and membrane remodeling? Is the plant cortical microtubule cytoskeleton a mechanosensory apparatus? How are the cellular pathways of cell wall synthesis, assembly, modification, and integrity sensing linked in plants? Why do plasmodesmata open and close? Is there retrograde signaling from vacuoles to the nucleus? How do root cells accommodate fungal endosymbionts? What is the role of cell edges in plant morphogenesis? How is the cell division site determined? What are the emergent effects of polyploidy on the biology of the cell, and how are any such "rules" conditioned by cell type? Can mechanical forces trigger new cell fates in plants? How does a single differentiated somatic cell reprogram and gain pluripotency? How does polarity develop de-novo in isolated plant cells? What is the spectrum of cellular functions for membraneless organelles and intrinsically disordered proteins? How do plants deal with internal noise? How does order emerge in cells and propagate to organs and organisms from complex dynamical processes? We hope you find the discussions of these questions thought provoking and inspiring.

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The societal challenges posed by a growing human population and climate change necessitate technical advances in plant science. Plant research makes vital contributions to society by advancing technologies that improve agricultural food production, biological energy capture and conversion, and human health. However, the plant biology community lacks a comprehensive understanding of molecular machinery, including their locations within cells, distributions and variations among different cell types, and real‐time dynamics. Fortunately, rapid advances in molecular methods, imaging, proteomics, and metabolomics made in the last decade afford unprecedented opportunities to develop a molecular‐level map of plant cells with high temporal and spatial resolution. The Plant Cell Atlas (PCA) initiative aims to generate a resource that will provide fresh insight into poorly understood aspects of plant cell structure and organization and enable the discovery of new cellular compartments and features. The PCA will be a community resource (http://www.plantcellatlas.org/) that describes the state of various plant cell types and integrates high‐resolution spatio‐temporal information of nucleic acids, proteins, and metabolites within plant cells. This first PCA initiative workshop convened scientists passionate about developing a comprehensive PCA to brainstorm about the state of the field, recent advances, the development of tools, and the future directions of this initiative. The workshop featured invited talks to share initial data, along with broader ideas for the PCA. Additionally, breakout sessions were organized around topics including the conceptual goals of the PCA, technical challenges, and community wants and needs. These activities connected scientists with diverse expertise and sparked important discussions about how to leverage and extend leading‐edge technologies and develop new techniques. A major outcome of the workshop was that the community wishes to redefine concepts of plant cell types and tissues quantitatively. A long‐term goal is to delineate all molecules within the cell at high spatio‐temporal resolution, obtain information about interacting molecular networks, and identify the contribution of these networks to development of the organism as a whole. As a first step, we wish to create comprehensive cellular and subcellular biomolecular maps of transcripts, proteins, and metabolites, track the dynamic interactions of these molecules intra‐ and intercellularly, discern complete states and transitions of specialized cell types, and integrate these disparate data points to generate testable models of cellular function. Ultimately, the PCA initiative will have a substantial positive impact by empowering a broad, diverse group of scientists to forge exciting paths in the field of plant science, facilitating connections with interested stakeholders beyond the scientific community, and enabling new agricultural technologies for a sustainable future.

Multicellular development produces patterns of specialized cell types. Yet, it is often unclear how individual cells within a field of identical cells initiate the patterning process. Using live imaging, quantitative image analyses and modeling, we show that during Arabidopsis thaliana sepal development, fluctuations in the concentration of the transcription factor ATML1 pattern a field of identical epidermal cells to differentiate into giant cells interspersed between smaller cells. We find that ATML1 is expressed in all epidermal cells. However, its level fluctuates in each of these cells. If ATML1 levels surpass a threshold during the G2 phase of the cell cycle, the cell will likely enter a state of endoreduplication and become giant. Otherwise, the cell divides. Our results demonstrate a fluctuation-driven patterning mechanism for how cell fate decisions can be initiated through a random yet tightly regulated process.