The diverse effects of the plant hormone ethylene on development and growth are shaped by the actions of a master regulator of transcription, EIN3.

Here, we present the draft genome of Rhizobium rhizogenes strain ATCC 15834. The genome contains 7,070,307 bp in 43 scaffolds. R. rhizogenes, also known as Agrobacterium rhizogenes, is a plant pathogen that causes hairy root disease. This hairy root induction has been used in biotechnology for the generation of transgenic root cultures.

Plant organs consist of multiple cell types that do not operate in isolation, but communicate with each other to maintain proper functions. Here, we extract models specific to three developmental stages of eight root cell types or tissue layers in Arabidopsis thaliana based on a state-of-the-art constraint-based modeling approach with all publicly available transcriptomics and metabolomics data from this system to date. We integrate these models into a multi-cell root model which we investigate with respect to network structure, distribution of fluxes, and concordance to transcriptomics and proteomics data. From a methodological point, we show that the coupling of tissue-specific models in a multi-tissue model yields a higher specificity of the interconnected models with respect to network structure and flux distributions. We use the extracted models to predict and investigate the flux of the growth hormone indole-3-actetate and its antagonist, trans-Zeatin, through the root. While some of predictions are in line with experimental evidence, constraints other than those coming from the metabolic level may be necessary to replicate the flow of indole-3-actetate from other simulation studies. Therefore, our work provides the means for data-driven multi-tissue metabolic model extraction of other Arabidopsis organs in the constraint-based modeling framework.

The multinational Arabidopsis research community is highly collaborative and over the past thirty years these activities have been documented by the Multinational Arabidopsis Steering Committee (MASC). Here, we (a) highlight recent research advances made with the reference plant Arabidopsis thaliana; (b) provide summaries from recent reports submitted by MASC subcommittees, projects and resources associated with MASC and from MASC country representatives; and (c) initiate a call for ideas and foci for the "fourth decadal roadmap," which will advise and coordinate the global activities of the Arabidopsis research community.

Abstract Background Biological processes occur on a vast range of time scales, and many of them occur concurrently. As a result, system-wide measurements of gene expression have the potential to capture many of these processes simultaneously. The challenge however, is to separate these processes and time scales in the data. In many cases the number of processes and their time scales is unknown. This issue is particularly relevant to developmental biologists, who are interested in processes such as growth, segmentation and differentiation, which can all take place simultaneously, but on different time scales. Results We introduce a flexible and statistically rigorous method for detecting different time scales in time-series gene expression data, by identifying expression patterns that are temporally shifted between replicate datasets. We apply our approach to a Saccharomyces cerevisiae cell-cycle dataset and an Arabidopsis thaliana root developmental dataset. In both datasets our method successfully detects processes operating on several different time scales. Furthermore we show that many of these time scales can be associated with particular biological functions. Conclusions The spatiotemporal modules identified by our method suggest the presence of multiple biological processes, acting at distinct time scales in both the Arabidopsis root and yeast. Using similar large-scale expression datasets, the identification of biological processes acting at multiple time scales in many organisms is now possible.

Heavy metals such as zinc are essential for plant growth, but toxic at high concentrations. Despite our knowledge of the molecular mechanisms of heavy metal uptake by plants, experimentally addressing the real-time whole-plant dynamics of heavy metal uptake and partitioning has remained a challenge. To overcome this, we applied a high sensitivity gamma-ray imaging system to image uptake and transport of radioactive ⁶⁵Zn in whole-plant assays of Arabidopsis thaliana and the Zn hyperaccumulator Arabidopsis halleri. We show that our system can be used to quantitatively image and measure uptake and root-to-shoot translocation dynamics of zinc in real time. In the metal hyperaccumulator Arabidopsis halleri, ⁶⁵Zn uptake and transport from its growth media to the shoot occurs rapidly and on time scales similar to those reported in rice. In transgenic A. halleri plants in which expression of the zinc transporter gene HMA4 is suppressed by RNAi, ⁶⁵Zn uptake is completely abolished.

In the summer of 2021, we held a community workshop at the International Congress of Arabidopsis Research (ICAR) aimed at early career researchers and focused on values-based lab leadership. Here, we elaborate on ideas emerging from the workshop that we hope will allow current and future group leaders to reflect on and adjust to the rapidly evolving nature of the academic scientific enterprise.

Abscisic acid (ABA) is a drought stress signaling molecule, and simple methods for detecting its levels could benefit agriculture. Here, we present proof-of-concept detection for ABA in aqueous solutions by the use of a mixture of Cyanine 5.5 (Cy5.5) fluorophore- and BHQ3 quencher-conjugated endogenous ABA receptor pyrabactin resistance 1 like proteins (PYL3). These dye-conjugated PYL3 protein form dimers in solutions without ABA and monomerize upon ABA binding. When they are in dimers, fluorescence of Cy5.5 is either nearly completely quenched by the BHQ3 or 20% quenched by another Cy5.5. Consequently, mixtures of equal amounts of the two protein conjugates were used to detect ABA in aqueous solution. As the ABA concentration increased from <1 μM to 1 mM, the intensity of fluorescence detected at around 680 nm from the mixture was more than doubled as a result of ABA-induced monomerization, which leads to halt of quenching and recovery of fluorescence of Cy5.5 in monomers. Kinetic modeling was used to simulate the fluorescence response from the mixture and the results generally agree with the experimentally observed trend. This work demonstrates that fluorescence measurements of a single dissociation reaction in one spectral region are adequate to assess the ABA concentration of a solution.

Background

Asymmetric cell divisions are formative divisions that generate daughter cells of distinct identity. These divisions are coordinated by either extrinsic ('niche-controlled') or intrinsic regulatory mechanisms and are fundamentally important in plant development.

Scope

This review describes how asymmetric cell divisions are regulated during development and in different cell types in both the root and the shoot of plants. It further highlights ways in which omics and modelling approaches have been used to elucidate these regulatory mechanisms. For example, the regulation of embryonic asymmetric divisions is described, including the first divisions of the zygote, formative vascular divisions and divisions that give rise to the root stem cell niche. Asymmetric divisions of the root cortex endodermis initial, pericycle cells that give rise to the lateral root primordium, procambium, cambium and stomatal cells are also discussed. Finally, a perspective is provided regarding the role of other hormones or regulatory molecules in asymmetric divisions, the presence of segregated determinants and the usefulness of modelling approaches in understanding network dynamics within these very special cells.

Conclusions

Asymmetric cell divisions define plant development. High-throughput genomic and modelling approaches can elucidate their regulation, which in turn could enable the engineering of plant traits such as stomatal density, lateral root development and wood formation.

Understanding the impact of elevated CO₂ (eCO₂ ) in global agriculture is important given climate change projections. Breeding climate-resilient crops depends on genetic variation within naturally varying populations. The effect of genetic variation in response to eCO₂ is poorly understood, especially in crop species. We describe the different ways in which Solanum lycopersicum and its wild relative S. pennellii respond to eCO₂ , from cell anatomy, to the transcriptome, and metabolome. We further validate the importance of translational regulation as a potential mechanism for plants to adaptively respond to rising levels of atmospheric CO₂ .