Fabio Fiorani

Future Scenarios for Plant Phenotyping

With increasing demand to support and accelerate progress in breeding for novel traits, the plant research community faces the need to accurately measure increasingly large numbers of plants and plant parameters. The goal is to provide quantitative analyses of plant structure and function relevant for traits that help plants better adapt to low-input agriculture and resource-limited environments. We provide an overview of the inherently multidisciplinary research in plant phenotyping, focusing on traits that will assist in selecting genotypes with increased resource use efficiency. We highlight opportunities and challenges for integrating noninvasive or minimally invasive technologies into screening protocols to characterize plant responses to environmental challenges for both controlled and field experimentation. Although technology evolves rapidly, parallel efforts are still required because large-scale phenotyping demands accurate reporting of at least a minimum set of information concerning experimental protocols, data management schemas, and integration with modeling. The journey toward systematic plant phenotyping has only just begun.

Characterization of Transformed Arabidopsis with Altered Alternative Oxidase Levels and Analysis of Effects on Reactive Oxygen Species in Tissue

The alternative oxidase (AOX) of plant mitochondria transfers electrons from the ubiquinone pool to oxygen without energy conservation. AOX can use reductant in excess of cytochrome pathway capacity, preventing reactive oxygen species (ROS) formation from an over-reduced ubiquinone pool, and thus may be involved in acclimation to oxidative stresses. The AOX connection with mitochondrial ROS has been investigated only in isolated mitochondria and suspension culture cells. To study ROS and AOX in whole plants, transformed lines of Arabidopsis (Arabidopsis thaliana) were generated: AtAOX1a overexpressors, AtAOX1a anti-sense plants, and overexpressors of a mutated, constitutively active AtAOX1a. In the presence of KCN, leaf tissue of either mutant or wild-type AOX overexpressors showed no increase in oxidative damage, whereas anti-sense lines had levels of damage greater than those observed for untransformed leaves. Similarly, ROS production increased markedly in anti-sense and untransformed, but not overexpressor, roots with KCN treatment. Thus, AOX functions in leaves and roots, as in suspension cells, to ameliorate ROS production when the cytochrome pathway is chemically inhibited. However, in contrast with suspension culture cells, no changes in leaf transcript levels of selected electron transport components or oxidative stress-related enzymes were detected under nonlimiting growth conditions, regardless of transformation type. Further, a microarray study using an anti-sense line showed AOX influences outside mitochondria, particularly in chloroplasts and on several carbon metabolism pathways. These results illustrate the value of expanding AOX transformant studies to whole tissues.

The Alternative Oxidase of Plant Mitochondria Is Involved in the Acclimation of Shoot Growth at Low Temperature. A Study of Arabidopsis AOX1a Transgenic Plants

The alternative oxidase (AOX) pathway of plant mitochondria uncouples respiration from mitochondrial ATP production and may ameliorate plant performance under stressful environmental conditions, such as cold temperatures, by preventing excess accumulation of reactive oxygen species. We tested this model in whole tissues by growing AtAOX1a-transformed Arabidopsis (Arabidopsis thaliana) plants at 12°C. For the first time, to our knowledge, in plants genetically engineered for AOX, we identified a vegetative shoot growth phenotype. Compared with wild type at day 21 after sowing, anti-sense and overexpressing lines showed, on average, 27% reduced leaf area and 25% smaller rosettes versus 30% increased leaf area and 33% larger rosette size, respectively. Lines overexpressing a mutated, constitutively active AOX1a showed smaller phenotypic effects. These phenotypic differences were not the result of a major alteration of the tissue redox state because the changes in levels of lipid peroxidation products, reflecting oxidative damage, and the expression of genes encoding antioxidant and electron transfer chain redox enzymes did not correspond with the shoot phenotypes. However, the observed phenotypes were correlated with the amount of total shoot anthocyanin at low temperature and with the transcription of the flavonoid pathway genes PAL1 and CHS. These results demonstrate that (1) AOX activity plays a role in shoot acclimation to low temperature in Arabidopsis, and that (2) AOX not only functions to prevent excess reactive oxygen species formation in whole tissues under stressful environmental conditions but also affects metabolism through more pervasive effects, including some that are extramitochondrial.

GROWSCREEN-Rhizo is a novel phenotyping robot enabling simultaneous measurements of root and shoot growth for plants grown in soil-filled rhizotrons

Root systems play an essential role in ensuring plant productivity. Experiments conducted in controlled environments and simulation models suggest that root geometry and responses of root architecture to environmental factors should be studied as a priority. However, compared with aboveground plant organs, roots are not easily accessible by non-invasive analyses and field research is still based almost completely on manual, destructive methods. Contributing to reducing the gap between laboratory and field experiments, we present a novel phenotyping system (GROWSCREEN-Rhizo), which is capable of automatically imaging roots and shoots of plants grown in soil-filled rhizotrons (up to a volume of ~18L) with a throughput of 60 rhizotrons per hour. Analysis of plants grown in this setup is restricted to a certain plant size (up to a shoot height of 80cm and root-system depth of 90cm). We performed validation experiments using six different species and for barley and maize, we studied the effect of moderate soil compaction, which is a relevant factor in the field. First, we found that the portion of root systems that is visible through the rhizotrons transparent plate is representative of the total root system. The percentage of visible roots decreases with increasing average root diameter of the plant species studied and depends, to some extent, on environmental conditions. Second, we could measure relatively minor changes in root-system architecture induced by a moderate increase in soil compaction. Taken together, these findings demonstrate the good potential of this methodology to characterise root geometry and temporal growth responses with relatively high spatial accuracy and resolution for both monocotyledonous and dicotyledonous species. Our prototype will allow the design of high-throughput screening methodologies simulating environmental scenarios that are relevant in the field and will support breeding efforts towards improved resource use efficiency and stability of crop yields.

Cold Nights Impair Leaf Growth and Cell Cycle Progression in Maize through Transcriptional Changes of Cell Cycle Genes

Low temperature inhibits the growth of maize (Zea mays) seedlings and limits yield under field conditions. To study the mechanism of cold-induced growth retardation, we exposed maize B73 seedlings to low night temperature (25°C /4°C, day/night) from germination until the completion of leaf 4 expansion. This treatment resulted in a 20% reduction in final leaf size compared to control conditions (25°C/18°C, day/night). A kinematic analysis of leaf growth rates in control and cold-treated leaves during daytime showed that cold nights affected both cell cycle time (+65%) and cell production (−22%). In contrast, the size of mature epidermal cells was unaffected. To analyze the effect on cell cycle progression at the molecular level, we identified through a bioinformatics approach a set of 43 cell cycle genes and analyzed their expression in proliferating, expanding, and mature cells of leaves exposed to either control or cold nights. This analysis showed that: (1) the majority of cell cycle genes had a consistent proliferation-specific expression pattern; and (2) the increased cell cycle time in the basal meristem of leaves exposed to cold nights was associated with differential expression of cell cycle inhibitors and with the concomitant down-regulation of positive regulators of cell division.

The art of growing plants for experimental purposes: a practical guide for the plant biologist

Every year thousands of experiments are conducted using plants grown under more-or-less controlled environmental conditions. The aim of many such experiments is to compare the phenotype of different species or genotypes in a specific environment, or to study plant performance under a range of suboptimal conditions. Our paper aims to bring together the minimum knowledge necessary for a plant biologist to set up such experiments and apply the environmental conditions that are appropriate to answer the questions of interest. We first focus on the basic choices that have to be made with regard to the experimental setup (e.g. where are the plants grown; what rooting medium; what pot size). Second, we present practical considerations concerning the number of plants that have to be analysed considering the variability in plant material and the required precision. Third, we discuss eight of the most important environmental factors for plant growth (light quantity, light quality, CO2, nutrients, air humidity, water, temperature and salinity); what critical issues should be taken into account to ensure proper growth conditions in controlled environments and which specific aspects need attention if plants are challenged with a certain a-biotic stress factor. Finally, we propose a simple checklist that could be used for tracking and reporting experimental conditions.

Probing the Reproducibility of Leaf Growth and Molecular Phenotypes: A Comparison of Three Arabidopsis Accessions Cultivated in Ten Laboratories

A major goal of the life sciences is to understand how molecular processes control phenotypes. Because understanding biological systems relies on the work of multiple laboratories, biologists implicitly assume that organisms with the same genotype will display similar phenotypes when grown in comparable conditions. We investigated to what extent this holds true for leaf growth variables and metabolite and transcriptome profiles of three Arabidopsis (Arabidopsis thaliana) genotypes grown in 10 laboratories using a standardized and detailed protocol. A core group of four laboratories generated similar leaf growth phenotypes, demonstrating that standardization is possible. But some laboratories presented significant differences in some leaf growth variables, sometimes changing the genotype ranking. Metabolite profiles derived from the same leaf displayed a strong genotype × environment (laboratory) component. Genotypes could be separated on the basis of their metabolic signature, but only when the analysis was limited to samples derived from one laboratory. Transcriptome data revealed considerable plant-to-plant variation, but the standardization ensured that interlaboratory variation was not considerably larger than intralaboratory variation. The different impacts of the standardization on phenotypes and molecular profiles could result from differences of temporal scale between processes involved at these organizational levels. Our findings underscore the challenge of describing, monitoring, and precisely controlling environmental conditions but also demonstrate that dedicated efforts can result in reproducible data across multiple laboratories. Finally, our comparative analysis revealed that small variations in growing conditions (light quality principally) and handling of plants can account for significant differences in phenotypes and molecular profiles obtained in independent laboratories.

A method to construct dose–response curves for a wide range of environmental factors and plant traits by means of a meta-analysis of phenotypic data

In the past, biologists have characterized the responses of a wide range of plant species to their environment. As a result, phenotypic data from hundreds of experiments are publicly available now. Unfortunately, this information is not structured in a way that enables quantitative and comparative analyses. We aim to fill this gap by building a large database which currently contains data on 1000 experiments and 800 species. This paper presents methodology to generalize across different experiments and species, taking the response of specific leaf area (SLA; leaf area:leaf mass ratio) to irradiance as an example. We show how to construct and quantify a normalized mean light-response curve, and subsequently test whether there are systematic differences in the form of the curve between contrasting subgroups of species. This meta-analysis is then extended to a range of other environmental factors important for plant growth as well as other phenotypic traits, using >5300 mean values. The present approach, which we refer to as meta-phenomics, represents a valuable tool in understanding the integrated response of plants to their environment and could serve as a benchmark for future phenotyping efforts as well as for modelling global change effects on both wild species and crops.

Imaging plants dynamics in heterogenic environments.

Noninvasive imaging sensors and computer vision approaches are key technologies to quantify plant structure, physiological status, and performance. Today, imaging sensors exploit a wide range of the electromagnetic spectrum, and they can be deployed to measure a growing number of traits, also in heterogenic environments. Recent advances include the possibility to acquire high-resolution spectra by imaging spectroscopy and classify signatures that might be informative of plant development, nutrition, health, and disease. Three-dimensional (3D) reconstruction of surfaces and volume is of particular interest, enabling functional and mechanistic analyses. While taking pictures is relatively easy, quantitative interpretation often remains challenging and requires integrating knowledge of sensor physics, image analysis, and complex traits characterizing plant phenotypes.

Non-invasive approaches for phenotyping of enhanced performance traits in bean

Plant phenotyping is an emerging discipline in plant biology. Quantitative measurements of functional and structural traits help to better understand gene-environment interactions and support breeding for improved resource use efficiency of important crops such as bean (Phaseolus vulgaris L.). Here we provide an overview of state-of-the-art phenotyping approaches addressing three aspects of resource use efficiency in plants: belowground roots, aboveground shoots and transport/allocation processes. We demonstrate the capacity of high-precision methods to measure plant function or structural traits non-invasively, stating examples wherever possible. Ideally, high-precision methods are complemented by fast and high-throughput technologies. High-throughput phenotyping can be applied in the laboratory using automated data acquisition, as well as in the field, where imaging spectroscopy opens a new path to understand plant function non-invasively. For example, we demonstrate how magnetic resonance imaging (MRI) can resolve root structure and separate root systems under resource competition, how automated fluorescence imaging (PAM fluorometry) in combination with automated shape detection allows for high-throughput screening of photosynthetic traits and how imaging spectrometers can be used to quantify pigment concentration, sun-induced fluorescence and potentially photosynthetic quantum yield. We propose that these phenotyping techniques, combined with mechanistic knowledge on plant structure-function relationships, will open new research directions in whole-plant ecophysiology and may assist breeding for varieties with enhanced resource use efficiency varieties.