Slicing across Kingdoms: Regeneration in Plants and Animals

Multicellular organisms possessing relatively long life spans are subjected to diverse, constant, and often intense intrinsic and extrinsic challenges to their survival. Animal and plant tissues wear out as part of normal physiological functions and can be lost to predators, disease, and injury. Both kingdoms survive this wide variety of insults by strategies that include the maintenance of adult stem cells or the induction of stem cell potential in differentiated cells. Repatterning mechanisms often deploy embryonic genes, but the question remains in both plants and animals whether regeneration invokes embryogenesis, generic patterning mechanisms, or unique circuitry comprised of well-established patterning genes

Predicting genome-wide redundancy using machine learning

<p>Abstract</p> <p>Background</p> <p>Gene duplication can lead to genetic redundancy, which masks the function of mutated genes in genetic analyses. Methods to increase sensitivity in identifying genetic redundancy can improve the efficiency of reverse genetics and lend insights into the evolutionary outcomes of gene duplication. Machine learning techniques are well suited to classifying gene family members into redundant and non-redundant gene pairs in model species where sufficient genetic and genomic data is available, such as <it>Arabidopsis thaliana</it>, the test case used here.</p> <p>Results</p> <p>Machine learning techniques that combine multiple attributes led to a dramatic improvement in predicting genetic redundancy over single trait classifiers alone, such as BLAST E-values or expression correlation. In withholding analysis, one of the methods used here, Support Vector Machines, was two-fold more precise than single attribute classifiers, reaching a level where the majority of redundant calls were correctly labeled. Using this higher confidence in identifying redundancy, machine learning predicts that about half of all genes in <it>Arabidopsis </it>showed the signature of predicted redundancy with at least one but typically less than three other family members. Interestingly, a large proportion of predicted redundant gene pairs were relatively old duplications (e.g., Ks > 1), suggesting that redundancy is stable over long evolutionary periods.</p> <p>Conclusions</p> <p>Machine learning predicts that most genes will have a functionally redundant paralog but will exhibit redundancy with relatively few genes within a family. The predictions and gene pair attributes for <it>Arabidopsis </it>provide a new resource for research in genetics and genome evolution. These techniques can now be applied to other organisms.</p

Regulation of Leaf Maturation by Chromatin-Mediated Modulation of Cytokinin Responses

SummaryPlant shoots display indeterminate growth, while their evolutionary decedents, the leaves, are determinate. Determinate leaf growth is conditioned by the CIN-TCP transcription factors, which promote leaf maturation and are negatively regulated by miR319 in leaf primordia. Here we show that CIN-TCPs reduce leaf sensitivity to cytokinin (CK), a phytohormone implicated in inhibition of differentiation in the shoot. We identify the SWI/SNF chromatin remodeling ATPase BRAHMA (BRM) as a genetic mediator of CIN-TCP activities and CK responses. An interactome screen further revealed that SWI/SNF complex components including BRM preferentially interacted with basic-helix-loop-helix (bHLH) transcription factors and the bHLH-related CIN-TCPs. Indeed, TCP4 and BRM interacted in planta. Both TCP4 and BRM bound the promoter of an inhibitor of CK responses, ARR16, and induced its expression. Reconstituting ARR16 levels in leaves with reduced CIN-TCP activity restored normal growth. Thus, CIN-TCP and BRM together promote determinate leaf growth by stage-specific modification of CK responses

A map of cell type-specific auxin responses

In plants, changes in local auxin concentrations can trigger a range of developmental processes as distinct tissues respond differently to the same auxin stimulus. However, little is known about how auxin is interpreted by individual cell types. We performed a transcriptomic analysis of responses to auxin within four distinct tissues of the Arabidopsis thaliana root and demonstrate that different cell types show competence for discrete responses. The majority of auxin-responsive genes displayed a spatial bias in their induction or repression. The novel data set was used to examine how auxin influences tissue-specific transcriptional regulation of cell-identity markers. Additionally, the data were used in combination with spatial expression maps of the root to plot a transcriptomic auxin-response gradient across the apical and basal meristem. The readout revealed a strong correlation for thousands of genes between the relative response to auxin and expression along the longitudinal axis of the root. This data set and comparative analysis provide a transcriptome-level spatial breakdown of the response to auxin within an organ where this hormone mediates many aspects of development

SREBP1c-CRY1 signalling represses hepatic glucose production by promoting FOXO1 degradation during refeeding

SREBP1c is a key lipogenic transcription factor activated by insulin in the postprandial state. Although SREBP1c appears to be involved in suppression of hepatic gluconeogenesis, the molecular mechanism is not thoroughly understood. Here we show that CRY1 is activated by insulin-induced SREBP1c and decreases hepatic gluconeogenesis through FOXO1 degradation, at least, at specific circadian time points. SREBP1c−/− and CRY1−/− mice show higher blood glucose than wild-type (WT) mice in pyruvate tolerance tests, accompanied with enhanced expression of PEPCK and G6Pase genes. CRY1 promotes degradation of nuclear FOXO1 by promoting its binding to the ubiquitin E3 ligase MDM2. Although SREBP1c fails to upregulate CRY1 expression in db/db mice, overexpression of CRY1 attenuates hyperglycaemia through reduction of hepatic FOXO1 protein and gluconeogenic gene expression. These data suggest that insulin-activated SREBP1c downregulates gluconeogenesis through CRY1-mediated FOXO1 degradation and that dysregulation of hepatic SREBP1c-CRY1 signalling may contribute to hyperglycaemia in diabetic animals

Essential Regulation of Cell Bioenergetics by Constitutive InsP3 Receptor Ca2+ Transfer to Mitochondria

SummaryMechanisms that regulate cellular metabolism are a fundamental requirement of all cells. Most eukaryotic cells rely on aerobic mitochondrial metabolism to generate ATP. Nevertheless, regulation of mitochondrial activity is incompletely understood. Here we identified an unexpected and essential role for constitutive InsP3R-mediated Ca2+ release in maintaining cellular bioenergetics. Macroautophagy provides eukaryotes with an adaptive response to nutrient deprivation that prolongs survival. Constitutive InsP3R Ca2+ signaling is required for macroautophagy suppression in cells in nutrient-replete media. In its absence, cells become metabolically compromised due to diminished mitochondrial Ca2+ uptake. Mitochondrial uptake of InsP3R-released Ca2+ is fundamentally required to provide optimal bioenergetics by providing sufficient reducing equivalents to support oxidative phosphorylation. Absence of this Ca2+ transfer results in enhanced phosphorylation of pyruvate dehydrogenase and activation of AMPK, which activates prosurvival macroautophagy. Thus, constitutive InsP3R Ca2+ release to mitochondria is an essential cellular process that is required for efficient mitochondrial respiration and maintenance of normal cell bioenergetics

First Plant Cell Atlas symposium report

The Plant Cell Atlas (PCA) community hosted a virtual symposium on December 9 and 10, 2021 on single cell and spatial omics technologies. The conference gathered almost 500 academic, industry, and government leaders to identify the needs and directions of the PCA community and to explore how establishing a data synthesis center would address these needs and accelerate progress. This report details the presentations and discussions focused on the possibility of a data synthesis center for a PCA and the expected impacts of such a center on advancing science and technology globally. Community discussions focused on topics such as data analysis tools and annotation standards; computational expertise and cyber-infrastructure; modes of community organization and engagement; methods for ensuring a broad reach in the PCA community; recruitment, training, and nurturing of new talent; and the overall impact of the PCA initiative. These targeted discussions facilitated dialogue among the participants to gauge whether PCA might be a vehicle for formulating a data synthesis center. The conversations also explored how online tools can be leveraged to help broaden the reach of the PCA (i.e., online contests, virtual networking, and social media stakeholder engagement) and decrease costs of conducting research (e.g., virtual REU opportunities). Major recommendations for the future of the PCA included establishing standards, creating dashboards for easy and intuitive access to data, and engaging with a broad community of stakeholders. The discussions also identified the following as being essential to the PCA’s success: identifying homologous cell-type markers and their biocuration, publishing datasets and computational pipelines, utilizing online tools for communication (such as Slack), and user-friendly data visualization and data sharing. In conclusion, the development of a data synthesis center will help the PCA community achieve these goals by providing a centralized repository for existing and new data, a platform for sharing tools, and new analytical approaches through collaborative, multidisciplinary efforts. A data synthesis center will help the PCA reach milestones, such as community-supported data evaluation metrics, accelerating plant research necessary for human and environmental health