Constrained to develop within the seed, the plant embryo must adapt its shape and size to fit the space available. Here, we demonstrate how this adjustment shapes metabolism of photosynthetic embryo. Noninvasive NMR-based imaging of the developing oilseed rape (Brassica napus) seed illustrates that, following embryo bending, gradients in lipid concentration became established. These were correlated with the local photosynthetic electron transport rate and the accumulation of storage products. Experimentally induced changes in embryo morphology and/or light supply altered these gradients and were accompanied by alterations in both proteome and metabolome. Tissue-specific metabolic models predicted that the outer cotyledon and hypocotyl/radicle generate the bulk of plastidic reductant/ATP via photosynthesis, while the inner cotyledon, being enclosed by the outer cotyledon, is forced to grow essentially heterotrophically. Under field-relevant highlight conditions, major contribution of the ribulose-1,5-bisphosphate carboxylase/oxygenase-bypass to seed storage metabolism is predicted for the outer cotyledon and the hypocotyl/radicle only. Differences between in vitro-versus in planta-grown embryos suggest that metabolic heterogeneity of embryo is not observable by in vitro approaches. We conclude that in vivo metabolic fluxes are locally regulated and connected to seed architecture, driving the embryo toward an efficient use of available light and space.

Advances in mass spectrometry (MS) have made comprehensive lipidomics analysis of complex tissues relatively commonplace. These compositional analyses, although able to resolve hundreds of molecular species of lipids in single extracts, lose the original cellular context from which these lipids are derived. Recently, high-resolution MS of individual lipid droplets from seed tissues indicated organelle-to-organelle variation in lipid composition, suggesting that heterogeneity of lipid distributions at the cellular level may be prevalent. Here, we employed matrix-assisted laser desorption/ ionization-MS imaging (MALDI-MSI) approaches to visualize lipid species directly in seed tissues of upland cotton (Gossypium hirsutum). MS imaging of cryosections of mature cotton embryos revealed a distinct, heterogeneous distribution of molecular species of triacylglycerols and phosphatidylcholines, the major storage and membrane lipid classes in cotton embryos. Other lipids were imaged, including phosphatidylethanolamines, phosphatidic acids, sterols, and gossypol, indicating the broad range of metabolites and applications for this chemical visualization approach. We conclude that comprehensive lipidomics images generated by MALDI-MSI report accurate, relative amounts of lipid species in plant tissues and reveal previously unseen differences in spatial distributions providing for a new level of understanding in cellular biochemistry.

The visualization community has developed to date many intuitions and understandings of how to judge the quality of views in visualizing data. The computation of a visualization's quality and usefulness ranges from measuring clutter and overlap, up to the existence and perception of specific (visual) patterns. This survey attempts to report, categorize and unify the diverse understandings and aims to establish a common vocabulary that will enable a wide audience to understand their differences and subtleties. For this purpose, we present a commonly applicable quality metric formalization that should detail and relate all constituting parts of a quality metric. We organize our corpus of reviewed research papers along the data types established in the information visualization community: multi-and high-dimensional, relational, sequential, geospatial and text data. For each data type, we select the visualization subdomains in which quality metrics are an active research field and report their findings, reason on the underlying concepts, describe goals and outline the constraints and requirements. One central goal of this survey is to provide guidance on future research opportunities for the field and outline how different visualization communities could benefit from each other by applying or transferring knowledge to their respective subdomain. Additionally, we aim to motivate the visualization community to compare computed measures to the perception of humans.

We present the results of a controlled experiment to investigate the performance of different temporal glyph designs in a small multiple setting. Analyzing many time series at once is a common yet difficult task in many domains, for example in network monitoring. Several visualization techniques have, thus, been proposed in the literature. Among these, iconic displays or glyphs are an appropriate choice because of their expressiveness and effective use of screen space. Through a controlled experiment, we compare the performance of four glyphs that use different combinations of visual variables to encode two properties of temporal data: a) the position of a data point in time and b) the quantitative value of this data point. Our results show that depending on tasks and data density, the chosen glyphs performed differently. Line Glyphs are generally a good choice for peak and trend detection tasks but radial encodings are more effective for reading values at specific temporal locations. From our qualitative analysis we also contribute implications for designing temporal glyphs for small multiple settings.