Publications by authors named "Benjamin Cole"

Introduction: The agriculture genomics community has numerous data submission standards available, but the standards for describing and storing single-cell (SC, e.g., scRNA- seq) data are comparatively underdeveloped.

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For plants adapted to bright light, a decrease in the amount of light received can be detrimental to their growth and survival. Consequently, in response to shade from surrounding vegetation, they initiate a suite of molecular and morphological changes known as the shade avoidance response through which stems and petioles elongate in search for light. Under sunlight-night cycles, the plant's responsiveness to shade varies across the day, being maximal at dusk time.

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The symbiotic interaction of plants with arbuscular mycorrhizal (AM) fungi is ancient and widespread. Plants provide AM fungi with carbon in exchange for nutrients and water, making this interaction a prime target for crop improvement. However, plant-fungal interactions are restricted to a small subset of root cells, precluding the application of most conventional functional genomic techniques to study the molecular bases of these interactions.

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Single-cell and single-nucleus RNA-sequencing technologies capture the expression of plant genes at an unprecedented resolution. Therefore, these technologies are gaining traction in plant molecular and developmental biology for elucidating the transcriptional changes across cell types in a specific tissue or organ, upon treatments, in response to biotic and abiotic stresses, or between genotypes. Despite the rapidly accelerating use of these technologies, collective and standardized experimental and analytical procedures to support the acquisition of high-quality data sets are still missing.

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Background And Objectives: Nearly all genetic analyses of Parkinson disease (PD) have been in populations of European ancestry. We sought to test the ability of a machine learning method to extract accurate PD diagnoses from an electronic medical record (EMR) system, to see whether genetic variants identified in European populations generalize to individuals of African and Hispanic ancestries, and to compare the rates of PD across ancestries.

Methods: A machine learning method using natural language processing was applied to EMRs of US veterans participating in the VA Million Veteran Program (MVP) to identify individuals with PD.

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Climate change is globally affecting rainfall patterns, necessitating the improvement of drought tolerance in crops. is a relatively drought-tolerant cereal. Functional stay-green sorghum genotypes can maintain green leaf area and efficient grain filling during terminal post-flowering water deprivation, a period of ~10 weeks.

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Plant response to pathogen infection varies within a leaf, yet this heterogeneity is not well resolved. We expose Arabidopsis to Pseudomonas syringae or mock treatment and profile >11,000 individual cells using single-cell RNA sequencing. Integrative analysis of cell populations from both treatments identifies distinct pathogen-responsive cell clusters exhibiting transcriptional responses ranging from immunity to susceptibility.

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For plants adapted to bright light, a decrease in the amount of light received can be detrimental to their growth and survival. Consequently, in response to shade from surrounding vegetation, they initiate a suite of molecular and morphological changes known as the shade avoidance response (SAR) through which stems and petioles elongate in search for light. Under sunlight-night cycles, the plant's responsiveness to shade varies across the day, being maximal at dusk time.

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We review how a data infrastructure for the Plant Cell Atlas might be built using existing infrastructure and platforms. The Human Cell Atlas has developed an extensive infrastructure for human and mouse single cell data, while the European Bioinformatics Institute has developed a Single Cell Expression Atlas, that currently houses several plant data sets. We discuss issues related to appropriate ontologies for describing a plant single cell experiment.

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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.

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Background: Genetically predicted leukocyte telomere length (LTL) has been evaluated in several studies of childhood and adult cancer. We test whether genetically predicted longer LTL is associated with germ cell tumours (GCT) in children and adults.

Methods: Paediatric GCT samples were obtained from a Children's Oncology Group study and state biobank programs in California and Michigan (N = 1413 cases, 1220 biological parents and 1022 unrelated controls).

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In all multicellular organisms, transcriptional networks orchestrate organ development. The Arabidopsis root, with its simple structure and indeterminate growth, is an ideal model for investigating the spatiotemporal transcriptional signatures underlying developmental trajectories. To map gene expression dynamics across root cell types and developmental time, we built a comprehensive, organ-scale atlas at single-cell resolution.

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The shifts in adaptive strategies revealed by ecological succession and the mechanisms that facilitate these shifts are fundamental to ecology. These adaptive strategies could be particularly important in communities of arbuscular mycorrhizal fungi (AMF) mutualistic with sorghum, where strong AMF succession replaces initially ruderal species with competitive ones and where the strongest plant response to drought is to manage these AMF. Although most studies of agriculturally important fungi focus on parasites, the mutualistic symbionts, AMF, constitute a research system of human-associated fungi whose relative simplicity and synchrony are conducive to experimental ecology.

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With growing populations and pressing environmental problems, future economies will be increasingly plant-based. Now is the time to reimagine plant science as a critical component of fundamental science, agriculture, environmental stewardship, energy, technology and healthcare. This effort requires a conceptual and technological framework to identify and map all cell types, and to comprehensively annotate the localization and organization of molecules at cellular and tissue levels.

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To understand and engineer plant metabolism, we need a comprehensive and accurate annotation of all metabolic information across plant species. As a step towards this goal, we generated genome-scale metabolic pathway databases of 126 algal and plant genomes, ranging from model organisms to crops to medicinal plants (https://plantcyc.org).

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Progress in sequencing, microfluidics, and analysis strategies has revolutionized the granularity at which multicellular organisms can be studied. In particular, single-cell transcriptomics has led to fundamental new insights into animal biology, such as the discovery of new cell types and cell type-specific disease processes. However, the application of single-cell approaches to plants, fungi, algae, or bacteria (environmental organisms) has been far more limited, largely due to the challenges posed by polysaccharide walls surrounding these species' cells.

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Histones belong to a family of highly conserved proteins in eukaryotes. They pack DNA into nucleosomes as functional units of chromatin. Post-translational modifications (PTMs) of histones, which are highly dynamic and can be added or removed by enzymes, play critical roles in regulating gene expression.

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Traditional manual gating strategies are often time-intensive, place a high burden on the analyzer, and are susceptible to bias between analyzers. Several automated gating methods have shown to exceed performance of manual gating for a limited number of cell subsets. However, many of the automated algorithms still require significant manual interventions or have yet to demonstrate their utility in large datasets.

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Extant research suggests that individuals employ traditional moral heuristics to support their observed altruistic behavior; yet findings have largely been limited to inductive extrapolation and rely on relatively few traditional frames in so doing, namely, deontology in organizational behavior and virtue theory in law and economics. Given that these and competing moral frames such as utilitarianism can manifest as identical behavior, we develop a moral framing instrument-the Philosophical Moral-Framing Measure (PMFM)-to expand and distinguish traditional frames associated and disassociated with observed altruistic behavior. The validation of our instrument based on 1015 subjects in 3 separate real stakes scenarios indicates that heuristic forms of deontology, virtue-theory, and utilitarianism are strongly related to such behavior, and that egoism is an inhibitor.

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Plants are continuously exposed to diurnal fluctuations in light and temperature, and spontaneous changes in their physical or biotic environment. The circadian clock coordinates regulation of gene expression with a 24 h period, enabling the anticipation of these events. We used RNA sequencing to characterize the Brachypodium distachyon transcriptome under light and temperature cycles, as well as under constant conditions.

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Drought is the most important environmental stress limiting crop yields. The C4 cereal sorghum [ (L.) Moench] is a critical food, forage, and emerging bioenergy crop that is notably drought-tolerant.

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Plant xylem cells conduct water and mineral nutrients. Although most plant cells are totipotent, xylem cells are unusual and undergo terminal differentiation. Many genes regulating this process are well characterized, including the Vascular-related NAC Domain 7 (VND7), MYB46, and MYB83 transcription factors, which are proposed to act in interconnected feedforward loops (FFLs).

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Single-cell transcriptome profiling of heterogeneous tissues can provide high-resolution windows into developmental dynamics and environmental responses, but its application to plants has been limited. Here, we used the high-throughput Drop-seq approach to profile >12,000 cells from Arabidopsis roots. This identified numerous distinct cell types, covering all major root tissues and developmental stages, and illuminated specific marker genes for these populations.

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