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.
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•Condensation of transcription factors to attenuate hormone response•Mechanism for nucleo-cytoplasmic partitioning of transcription factors
ARF transcription factors mediate the activity of the phytohormone auxin, regulating every aspect of plant development. Powers et al. determine that some ARFs undergo phase transition to form large-order cytoplasmic protein assemblies that limit auxin responsiveness in a developmentally relevant context, illustrating a strong link between condensate formation and biological function.
Recent advances in single-cell proteomics for animal systems could be adapted for plants to increase our understanding of plant development, response to stimuli, and cell-to-cell signaling.
•GRNs represent causal relationships among regulators and their downstream genes.•Biological hypothesis drives data collection and the subsequent inferred GRN.•Inference methods use spatial, ...temporal, and environmental condition data types.•Combining multiple methods provides a better GRN inference than a single method.•GRN inference should incorporate heterogeneous data with gene expression data.
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.
In this study we implement eight lightning parameterizations in the Community Atmospheric Model (CAM5), evaluate the performance of the parameterizations in the present climate, and test the ...sensitivity of future lightning activity to the choice of parameterization. In the present day, the annual mean lightning flash densities in simulations constrained by reanalysis data show the highest spatial correlation to satellite observations for parameterizations based either on cloud top height (0.83) or cold cloud depth (0.80). Under future scenarios using representative concentration pathways, changes in global mean lightning flash density are highly sensitive to the parameterization chosen, with cloud top height schemes, a cold cloud depth scheme, and a scheme based on convective mass flux projecting large increases (36% to 45%), a mild increase (12.6%), and a decrease (−6.7%) in lightning flash density, respectively, under the RCP8.5 scenario, which causes a 3.4 K warming between 1996–2005 and 2079–2088.
Key Points
Out of eight parameterizations, future lightning flash density (LFD) is projected to change by a median of 3.7% per K warming under RCP8.5
Cold cloud depth and cloud top height schemes perform comparably well in present day, but future projections differ (3.7 versus 12.7% per K)
No scheme tested simulates the 1996‐2008 time series of area mean LFD with a correlation coefficient greater than 0.45 with the OBS
Myosins are evolutionarily conserved motor proteins that interact with actin filaments to regulate organelle transport, cytoplasmic streaming and cell growth. Plant-specific class XI myosin proteins ...direct cell division and root organogenesis. However, the roles of plant-specific class VIII myosin proteins in plant growth and development are less understood. Here, we investigated the function of an auxin-regulated class VIII myosin, Arabidopsis thaliana MYOSIN 1 (ATM1), using genetics, transcriptomics and live cell microscopy. ATM1 is associated with the plasma membrane and plasmodesmata within the root apical meristem (RAM). Loss of ATM1 function results in decreased RAM size and reduced cell proliferation in a sugar-dependent manner. Auxin signaling and transcriptional responses were dampened in atm1-1 roots. Complementation of atm1-1 with a tagged ATM1 driven under the native ATM1 promoter restored root growth and cell cycle progression. Genetic analyses of atm1-1 seedlings with HEXOKINASE 1 (HXK1) and TARGET OF RAPAMYCIN COMPLEX 1 (TORC1) overexpression lines indicate that ATM1 is downstream of TOR. Collectively, these results provide previously unreported evidence that ATM1 functions to influence cell proliferation in primary roots in response to auxin and sugar cues.
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.
Assessing the impact of future anthropogenic carbon emissions is currently impeded by uncertainties in our knowledge of equilibrium climate sensitivity to atmospheric carbon dioxide doubling. ...Previous studies suggest 3 kelvin (K) as the best estimate, 2 to 4.5 K as the 66% probability range, and nonzero probabilities for much higher values, the latter implying a small chance of high-impact climate changes that would be difficult to avoid. Here, combining extensive sea and land surface temperature reconstructions from the Last Glacial Maximum with climate model simulations, we estimate a lower median (2.3 K) and reduced uncertainty (1.7 to 2.6 K as the 66% probability range, which can be widened using alternate assumptions or data subsets). Assuming that paleoclimatic constraints apply to the future, as predicted by our model, these results imply a lower probability of imminent extreme climatic change than previously thought.
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.
Understanding the systems-level actions of transcriptional responses to hormones provides insight into how the genome is reprogrammed in response to environmental stimuli. Here, we investigated the ...signalling pathway of the hormone jasmonic acid (JA), which controls a plethora of critically important processes in plants and is orchestrated by the transcription factor MYC2 and its closest relatives in Arabidopsis thaliana. We generated an integrated framework of the response to JA, which spans from the activity of master and secondary regulatory transcription factors, through gene expression outputs and alternative splicing, to protein abundance changes, protein phosphorylation and chromatin remodelling. We integrated time-series transcriptome analysis with (phospho)proteomic data to reconstruct gene regulatory network models. These enabled us to predict previously unknown points of crosstalk of JA to other signalling pathways and to identify new components of the JA regulatory mechanism, which we validated through targeted mutant analysis. These results provide a comprehensive understanding of how a plant hormone remodels cellular functions and plant behaviour, the general principles of which provide a framework for analyses of cross-regulation between other hormone and stress signalling pathways.
How plants determine the final size of growing cells is an important, yet unresolved, issue. Root hairs provide an excellent model system with which to study this as their final cell size is ...remarkably constant under constant environmental conditions. Previous studies have demonstrated that a basic helix-loop helix transcription factor ROOT HAIR DEFECTIVE 6-LIKE 4 (RSL4) promotes root hair growth, but how hair growth is terminated is not known. In this study, we demonstrate that a trihelix transcription factor GT-2-LIKE1 (GTL1) and its homolog DF1 repress root hair growth in
Our transcriptional data, combined with genome-wide chromatin-binding data, show that GTL1 and DF1 directly bind the
promoter and regulate its expression to repress root hair growth. Our data further show that GTL1 and RSL4 regulate each other, as well as a set of common downstream genes, many of which have previously been implicated in root hair growth. This study therefore uncovers a core regulatory module that fine-tunes the extent of root hair growth by the orchestrated actions of opposing transcription factors.
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