A big challenge in current systems biology research arises when different types of data must be accessed from separate sources and visualized using separate tools. The high cognitive load required to navigate such a workflow is detrimental to hypothesis generation. Accordingly, there is a need for a robust research platform that incorporates all data and provides integrated search, analysis, and visualization features through a single portal. Here, we present ePlant (http://bar.utoronto.ca/eplant), a visual analytic tool for exploring multiple levels of Arabidopsis thaliana data through a zoomable user interface. ePlant connects to several publicly available web services to download genome, proteome, interactome, transcriptome, and 3D molecular structure data for one or more genes or gene products of interest. Data are displayed with a set of visualization tools that are presented using a conceptual hierarchy from big to small, and many of the tools combine information from more than one data type. We describe the development of ePlant in this article and present several examples illustrating its integrative features for hypothesis generation. We also describe the process of deploying ePlant as an “app” on Araport. Building on readily available web services, the code for ePlant is freely available for any other biological species research

Summary922I.Introduction and a brief survey of 54 033 Arabidopsis publications922II.Arabidopsis reverse genetics: paving the way for gene function studies922III.Arabidopsis stock centers925IV.Databases and online tools925V.Cell biology926VI.Development927VII.Hormones928VIII.The plant immune system and Arabidopsis research929IX.Signaling in response to abiotic stress930X.Pumps, channels, transporters and the like931XI.Cell walls, starch and lipids932XII.Epigenetics and epigenomics: from genotype to phenotype933XIII.Natural variation and genome‐wide association studies934XIV.Gene regulatory networks934XV.Modeling, bioinformatics, systems biology935XVI.Synthetic biology936XVII.Conclusions and outlook937Acknowledgements937References937 Summary The year 2014 marked the 25th International Conference on Arabidopsis Research. In the 50 yr since the first International Conference on Arabidopsis Research, held in 1965 in Göttingen, Germany, > 54 000 papers that mention Arabidopsis thaliana in the title, abstract or keywords have been published. We present herein a citational network analysis of these papers, and touch on some of the important discoveries in plant biology that have been made in this powerful model system, and highlight how these discoveries have then had an impact in crop species. We also look to the future, highlighting some outstanding questions that can be readily addressed in Arabidopsis. Topics that are discussed include Arabidopsis reverse genetic resources, stock centers, databases and online tools, cell biology, development, hormones, plant immunity, signaling in response to abiotic stress, transporters, biosynthesis of cells walls and macromolecules such as starch and lipids, epigenetics and epigenomics, genome‐wide association studies and natural variation, gene regulatory networks, modeling and systems biology, and synthetic biology.

We describe a process for compositing a live performance of an actor into a virtual set wherein the actor is consistently illuminated by the virtual environment. The Light Stage used in this work is a two-meter sphere of inward-pointing RGB light emitting diodes focused on the actor, where each light can be set to an arbitrary color and intensity to replicate a real-world or virtual lighting environment. We implement a digital two-camera infrared matting system to composite the actor into the background plate of the environment without affecting the visible-spectrum illumination on the actor. The color reponse of the system is calibrated to produce correct color renditions of the actor as illuminated by the environment. We demonstrate moving-camera composites of actors into real-world environments and virtual sets such that the actor is properly illuminated by the environment into which they are composited.

Identifying sets of genes that are specifically expressed in certain tissues or in response to an environmental stimulus is useful for designing reporter constructs, generating gene expression markers, or for understanding gene regulatory networks. We have developed an easy-to-use online tool for defining a desired expression profile (a modification of our Expression Angler program), which can then be used to identify genes exhibiting patterns of expression that match this profile as closely as possible. Further, we have developed another online tool, Cistome, for predicting or exploring cis-elements in the promoters of sets of co-expressed genes identified by such a method, or by other methods. We present two use cases for these tools, which are freely available on the Bio-Analytic Resource at http://BAR.utoronto.ca.

SummaryImprovements in next‐generation sequencing technologies have resulted in dramatically reduced sequencing costs. This has led to an explosion of ‘‐seq’‐based methods, of which RNA sequencing (RNA‐seq) for generating transcriptomic data is the most popular. By analysing global patterns of gene expression in organs/tissues/cells of interest or in response to chemical or environmental perturbations, researchers can better understand an organism's biology. Tools designed to work with large RNA‐seq data sets enable analyses and visualizations to help generate hypotheses about a gene's function. We present here a user‐friendly RNA‐seq data exploration tool, called the ‘eFP‐Seq Browser’, that shows the read map coverage of a gene of interest in each of the samples along with ‘electronic fluorescent pictographic’ (eFP) images that serve as visual representations of expression levels. The tool also summarizes the details of each RNA‐seq experiment, providing links to archival databases and publications. It automatically computes the reads per kilobase per million reads mapped expression‐level summaries and point biserial correlation scores to sort the samples based on a gene's expression level or by how dissimilar the read map profile is from a gene splice variant, to quickly identify samples with the strongest expression level or where alternative splicing might be occurring. Links to the Integrated Genome Browser desktop visualization tool allow researchers to visualize and explore the details of RNA‐seq alignments summarized in eFP‐Seq Browser as coverage graphs. We present four cases of use of the eFP‐Seq Browser for ABI3,SR34,SR45a and U2AF65B, where we examine expression levels and identify alternative splicing. The URL for the browser is https://bar.utoronto.ca/eFP-Seq_Browser/.Open research badges This article has earned an Open Data Badge for making publicly available the digitally‐shareable data necessary to reproduce the reported results. Tool is at http://sps:urlprefix::https; RNA‐seq data at http://sps:urlprefix::https and http://sps:urlprefix::https. Code is available at http://sps:urlprefix::https

Bioinformatic tools have become part of the way plant researchers undertake investigations. Large data sets encompassing genomes, transcriptomes, proteomes, epigenomes, and other "-omes" that have been generated in the past decade may be easily accessed with such tools, such that hypotheses may be generated at the click of a mouse. In this chapter, we'll cover the use of bioinformatic tools available at the Bio-Analytic Resource for Plant Biology at http://bar.utoronto.ca for exploring gene expression and coexpression patterns, undertaking promoter analyses, performing functional classification enrichment analyses for sets of genes, and examining protein-protein interactions. We also touch on some newer bioinformatic tools that allow integration of data from several sources for improved hypothesis generation, both for Arabidopsis and translationally. Most of the data sets come from Arabidopsis, but useful BAR tools for other species will be mentioned where appropriate.

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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. This framework, called the Plant Cell Atlas (PCA), will be critical for understanding and engineering plant development, physiology and environmental responses. A workshop was convened to discuss the purpose and utility of such an initiative, resulting in a roadmap that acknowledges the current knowledge gaps and technical challenges, and underscores how the PCA initiative can help to overcome them.