Diel growth cycle of isolated leaf discs analyzed with a novel, high-throughput three-dimensional imaging method is identical to that of intact leaves

Investigation of sugar signaling behaviors involved in sucrose-induced senescence initiation and progression in N. tabacum

Sugar is involved in initiating leaf senescence. However, its regulatory role, especially as a signal in the senescence process, is unclear. Therefore, this study was designed to illustrate how sugar stimulates the onset of leaf senescence and controls sugar homeostasis through the T6P-SnRK (sucrose non-fermenting (SNF)-related kinase) and HXK (hexokinase) signaling pathways. We used a leaf disc system detached from fully expanded leaves of Nicotiana tabacum cv. K326 and designed a time-course study (days 3, 5, 7, and 9) with exogenously gradient concentrations (0, 30, 60, 90, 120, and 150 mM) of sucrose (Suc) treatment to identify how Suc application affects sugar metabolism and induces senescence. Our results revealed that early decreases of Fv/Fm and increases in electrolyte leakage responded to Suc on day 3. Furthermore, a substantial increase in lipid peroxidation and up-regulated expression of senescence marker genes (NtSAG12) (except 60 mM on day 3) responded sequentially by day 5. The glucose, G6P, and HXK contents were first induced by Suc on day 3 and then repressed from day 5 to day 7. However, exogenous Suc treatment significantly improved the TPS content and the subsequent precursor T6P from day 3 to day 7. Following exogenous Suc treatments, the transcript level of NtSnRK1 was markedly down-regulated from day 3 to day 7. On the other hand, a linear regression analysis demonstrated that the T6P-NtSnRK1 signaling pathway was strongly associated with senescence initiation, and was accompanied by membrane degradation and NtCP1/NtSAG12 up-regulation by day 3. The T6P-NtSnRK1 signaling pathway experienced membrane and chloroplast degradation by day 5. HXK functioned as a metabolic enzyme promoting Glc-G6P and as a Glc sensor, accelerating the initiation of senescence through the HXK-dependent pathway by repressing PSII by day 3 and the senescence process through the Glycolytic pathway by day 7. These physiological, biochemical, and molecular analyses demonstrate that exogenous Suc regulates T6P accumulation, inducing senescence through the NtSnRK signaling pathway. These results illustrate the role of Suc and the transition of the sugar signaling pathway during the progression of senescence initiation.

Mathematical Modeling Reveals That Sucrose Regulates Leaf Senescence via Dynamic Sugar Signaling Pathways

Sucrose (Suc) accumulation is one of the key indicators of leaf senescence onset, but little is known about its regulatory role. Here, we found that application of high (120–150 mM) and low levels (60 mM) of Suc to young leaf (YL) and fully expanded leaf (FEL) discs, respectively, decreased chlorophyll content and maximum photosynthetic efficiency. Electrolyte leakage and malondialdehyde levels increased at high Suc concentrations (90–120 mM in YL and 60 and 150 mM in FEL discs). In FEL discs, the senescence-associated gene NtSAG12 showed a gradual increase in expression with increased Suc application; in contrast, in YL discs, NtSAG12 was upregulated with low Suc treatment (60 mM) but downregulated at higher levels of Suc. In YL discs, trehalose-6-phosphate (T6P) accumulated at a low half-maximal effective concentration (EC50) of Suc (1.765 mM). However, T6P levels declined as trehalose 6 phosphate synthase (TPS) content decreased, resulting in the maximum velocity of sucrose non-fermenting-1-related protein kinase (SnRK) and hexokinase (HXK) occurring at higher level of Suc. We therefore speculated that senescence was induced by hexose accumulation. In FEL discs, the EC50 of T6P occurred at a low concentration of Suc (0.9488 mM); T6P levels progressively increased with higher TPS content, which inhibited SnRK activity with a dissociation constant (K_d) of 0.001475 U/g. This confirmed that the T6P–SnRK complex induced senescence in detached FEL discs.

Robotic Technologies for High-Throughput Plant Phenotyping: Contemporary Reviews and Future Perspectives

Phenotyping plants is an essential component of any effort to develop new crop varieties. As plant breeders seek to increase crop productivity and produce more food for the future, the amount of phenotype information they require will also increase. Traditional plant phenotyping relying on manual measurement is laborious, time-consuming, error-prone, and costly. Plant phenotyping robots have emerged as a high-throughput technology to measure morphological, chemical and physiological properties of large number of plants. Several robotic systems have been developed to fulfill different phenotyping missions. In particular, robotic phenotyping has the potential to enable efficient monitoring of changes in plant traits over time in both controlled environments and in the field. The operation of these robots can be challenging as a result of the dynamic nature of plants and the agricultural environments. Here we discuss developments in phenotyping robots, and the challenges which have been overcome and others which remain outstanding. In addition, some perspective applications of the phenotyping robots are also presented. We optimistically anticipate that autonomous and robotic systems will make great leaps forward in the next 10 years to advance the plant phenotyping research into a new era.

Recent developments and potential of robotics in plant eco-phenotyping

Automated acquisition of plant eco-phenotypic information can serve as a decision-making basis for precision agricultural management and can also provide detailed insights into plant growth status, pest management, water and fertilizer management for plant breeders and plant physiologists. Because the microscopic components and macroscopic morphology of plants will be affected by the ecological environment, research on plant eco-phenotyping is more meaningful than the study of single-plant phenotyping. To achieve high-throughput acquisition of phenotyping information, the combination of high-precision sensors and intelligent robotic platforms have become an emerging research focus. Robotic platforms and automated systems are the important carriers of phenotyping monitoring sensors that enable large-scale screening. Through the diverse design and flexible systems, an efficient operation can be achieved across a range of experimental and field platforms. The combination of robot technology and plant phenotyping monitoring tools provides the data to inform novel artificial intelligence (AI) approaches that will provide steppingstones for new research breakthroughs. Therefore, this article introduces robotics and eco-phenotyping and examines research significant to this novel domain of plant eco-phenotyping. Given the monitoring scenarios of phenotyping information at different scales, the used intelligent robot technology, efficient automation platform, and advanced sensor equipment are summarized in detail. We further discuss the challenges posed to current research as well as the future developmental trends in the application of robot technology and plant eco-phenotyping. These include the use of collected data for AI applications and high-bandwidth data transfer, and large well-structured (meta) data storage approaches in plant sciences and agriculture.

A Proposed Methodology to Analyze Plant Growth and Movement from Phenomics Data

Image analysis of developmental processes in plants reveals both growth and organ movement. This study proposes a methodology to study growth and movement. It includes the standard acquisition of internal and external reference points and coordinates, coordinates transformation, curve fitting and the corresponding statistical analysis. Several species with different growth habits were used including Antirrhinum majus, A. linkianum, Petunia x hybrida and Fragaria x ananassa. Complex growth patterns, including gated growth, could be identified using a generalized additive model. Movement, and in some cases, growth, could not be adjusted to curves due to drastic changes in position. The area under the curve was useful in order to identify the initial stage of growth of an organ, and its growth rate. Organs displayed either continuous movements during the day with gated day/night periods of maxima, or sharp changes in position coinciding with day/night shifts. The movement was dependent on light in petunia and independent in F. ananassa. Petunia showed organ movement in both growing and fully-grown organs, while A. majus and F. ananassa showed both leaf and flower movement patterns linked to growth. The results indicate that different mathematical fits may help quantify growth rate, growth duration and gating. While organ movement may complicate image and data analysis, it may be a surrogate method to determine organ growth potential.

Leaf Disc Assays for Rapid Measurement of Antioxidant Activity

Antioxidant levels are key parameters for studies of food quality, stress responses, and plant health. Herein, we have demonstrated that excised leaf disc has both radical scavenging activity and reducing power, and used this concept to develop 2,2-diphenyl-1-picrylhydrazyl (DPPH), 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS), and potassium permanganate reduction (PPR) leaf disc assays. Reaction time and reagent concentration for these assays were optimized using leaves from spinach, kale, collards, mustard, and watermelon. Further, these assays were validated for linearity and intra-assay precision. Ultra-high performance liquid chromatography coupled to an electrospray quadrupole time-of-flight mass spectrometer (UPLC/ESI-HR-QTOFMS) was used for phytochemical profiling and studying relative abundances of certain phenolic compounds in various leaf discs suspended and cell-free extracts. The mass spectral analysis showed that leaf disc suspended methanolic extracts had almost same phytochemical profiles to those of cell-free extracts. The DPPH leaf disc assay demonstrated better radical scavenging potential than the conventional cell-free extract method. By contrast, the observed antioxidant activity values in ABTS and PPR leaf disc assays were lower than those of conventional cell-free extract-based methods. In conclusion, the developed leaf disc assays are simple and rapid for the qualitative and comparative assessment of the antioxidant potential of leaf samples, as well as can be a good alternative to conventional cell-free extract based methods.

A high-throughput stereo-imaging system for quantifying rape leaf traits during the seedling stage

BACKGROUND

The fitness of the rape leaf is closely related to its biomass and photosynthesis. The study of leaf traits is significant for improving rape leaf production and optimizing crop management. Canopy structure and individual leaf traits are the major indicators of quality during the rape seedling stage. Differences in canopy structure reflect the influence of environmental factors such as water, sunlight and nutrient supply. The traits of individual rape leaves traits indicate the growth period of the rape as well as its canopy shape.

RESULTS

We established a high-throughput stereo-imaging system for the reconstruction of the three-dimensional canopy structure of rape seedlings from which leaf area and plant height can be extracted. To evaluate the measurement accuracy of leaf area and plant height, 66 rape seedlings were randomly selected for automatic and destructive measurements. Compared with the manual measurements, the mean absolute percentage error of automatic leaf area and plant height measurements was 3.68 and 6.18%, respectively, and the squares of the correlation coefficients (R2) were 0.984 and 0.845, respectively. Compared with the two-dimensional projective imaging method, the leaf area extracted using stereo-imaging was more accurate. In addition, a semi-automatic image analysis pipeline was developed to extract 19 individual leaf shape traits, including 11 scale-invariant traits, 3 inner cavity related traits, and 5 margin-related traits, from the images acquired by the stereo-imaging system. We used these quantified traits to classify rapes according to three different leaf shapes: mosaic-leaf, semi-mosaic-leaf, and round-leaf. Based on testing of 801 seedling rape samples, we found that the leave-one-out cross validation classification accuracy was 94.4, 95.6, and 94.8% for stepwise discriminant analysis, the support vector machine method and the random forest method, respectively.

CONCLUSIONS

In this study, a nondestructive and high-throughput stereo-imaging system was developed to quantify canopy three-dimensional structure and individual leaf shape traits with improved accuracy, with implications for rape phenotyping, functional genomics, and breeding.

Optimizing experimental procedures for quantitative evaluation of crop plant performance in high throughput phenotyping systems

Detailed and standardized protocols for plant cultivation in environmentally controlled conditions are an essential prerequisite to conduct reproducible experiments with precisely defined treatments. Setting up appropriate and well defined experimental procedures is thus crucial for the generation of solid evidence and indispensable for successful plant research. Non-invasive and high throughput (HT) phenotyping technologies offer the opportunity to monitor and quantify performance dynamics of several hundreds of plants at a time. Compared to small scale plant cultivations, HT systems have much higher demands, from a conceptual and a logistic point of view, on experimental design, as well as the actual plant cultivation conditions, and the image analysis and statistical methods for data evaluation. Furthermore, cultivation conditions need to be designed that elicit plant performance characteristics corresponding to those under natural conditions. This manuscript describes critical steps in the optimization of procedures for HT plant phenotyping systems. Starting with the model plant Arabidopsis, HT-compatible methods were tested, and optimized with regard to growth substrate, soil coverage, watering regime, experimental design (considering environmental inhomogeneities) in automated plant cultivation and imaging systems. As revealed by metabolite profiling, plant movement did not affect the plants' physiological status. Based on these results, procedures for maize HT cultivation and monitoring were established. Variation of maize vegetative growth in the HT phenotyping system did match well with that observed in the field. The presented results outline important issues to be considered in the design of HT phenotyping experiments for model and crop plants. It thereby provides guidelines for the setup of HT experimental procedures, which are required for the generation of reliable and reproducible data of phenotypic variation for a broad range of applications.

Dissecting the phenotypic components of crop plant growth and drought responses based on high-throughput image analysis

Significantly improved crop varieties are urgently needed to feed the rapidly growing human population under changing climates. While genome sequence information and excellent genomic tools are in place for major crop species, the systematic quantification of phenotypic traits or components thereof in a high-throughput fashion remains an enormous challenge. In order to help bridge the genotype to phenotype gap, we developed a comprehensive framework for high-throughput phenotype data analysis in plants, which enables the extraction of an extensive list of phenotypic traits from nondestructive plant imaging over time. As a proof of concept, we investigated the phenotypic components of the drought responses of 18 different barley (Hordeum vulgare) cultivars during vegetative growth. We analyzed dynamic properties of trait expression over growth time based on 54 representative phenotypic features. The data are highly valuable to understand plant development and to further quantify growth and crop performance features. We tested various growth models to predict plant biomass accumulation and identified several relevant parameters that support biological interpretation of plant growth and stress tolerance. These image-based traits and model-derived parameters are promising for subsequent genetic mapping to uncover the genetic basis of complex agronomic traits. Taken together, we anticipate that the analytical framework and analysis results presented here will be useful to advance our views of phenotypic trait components underlying plant development and their responses to environmental cues.

Integrated Analysis Platform: An Open-Source Information System for High-Throughput Plant Phenotyping

High-throughput phenotyping is emerging as an important technology to dissect phenotypic components in plants. Efficient image processing and feature extraction are prerequisites to quantify plant growth and performance based on phenotypic traits. Issues include data management, image analysis, and result visualization of large-scale phenotypic data sets. Here, we present Integrated Analysis Platform (IAP), an open-source framework for high-throughput plant phenotyping. IAP provides user-friendly interfaces, and its core functions are highly adaptable. Our system supports image data transfer from different acquisition environments and large-scale image analysis for different plant species based on real-time imaging data obtained from different spectra. Due to the huge amount of data to manage, we utilized a common data structure for efficient storage and organization of data for both input data and result data. We implemented a block-based method for automated image processing to extract a representative list of plant phenotypic traits. We also provide tools for build-in data plotting and result export. For validation of IAP, we performed an example experiment that contains 33 maize (Zea mays 'Fernandez') plants, which were grown for 9 weeks in an automated greenhouse with nondestructive imaging. Subsequently, the image data were subjected to automated analysis with the maize pipeline implemented in our system. We found that the computed digital volume and number of leaves correlate with our manually measured data in high accuracy up to 0.98 and 0.95, respectively. In summary, IAP provides a multiple set of functionalities for import/export, management, and automated analysis of high-throughput plant phenotyping data, and its analysis results are highly reliable.

Cell to whole-plant phenotyping: the best is yet to come

Imaging and image processing have revolutionized plant phenotyping and are now a major tool for phenotypic trait measurement. Here we review plant phenotyping systems by examining three important characteristics: throughput, dimensionality, and resolution. First, whole-plant phenotyping systems are highlighted together with advances in automation that enable significant throughput increases. Organ and cellular level phenotyping and its tools, often operating at a lower throughput, are then discussed as a means to obtain high-dimensional phenotypic data at elevated spatial and temporal resolution. The significance of recent developments in sensor technologies that give access to plant morphology and physiology-related traits is shown. Overall, attention is focused on spatial and temporal resolution because these are crucial aspects of imaging procedures in plant phenotyping systems.

Carbohydrate control over carotenoid build-up is conditional on fruit ontogeny in clementine fruits

The final contents of primary and secondary metabolites of the ripe fruit depend on metabolic processes that are tightly regulated during fruit ontogeny. Carbohydrate supply during fruit development is known to influence these processes but, with respect to secondary metabolites, we do not really know whether this influence is direct or indirect. Here, we hypothesized that the sensitivity of clementine fruit metabolism to carbohydrate supply was conditional on fruit developmental stage. We applied treatments increasing fruit load reversibly or irreversibly at three key stages of clementine (Citrus clementina Hort. ex Tan.) fruit development: early after cell division, at the onset of fruit coloration (color break) and near maturity. The highest fruit load obtained by early defoliation (irreversible) had the highest impact on fruit growth, maturity and metabolism, followed by the highest fruit load obtained by early shading (reversible). Final fruit size decreased by 21 and 18% in these early irreversible and reversible treatments, respectively. Soluble sugars decreased by 18% in the early irreversible treatment, whereas organic acids increased by 46 and 29% in these early irreversible and reversible treatments, respectively. Interestingly, total carotenoids increased by 50 and 18%, respectively. Changes in leaf starch content and photosynthesis supported that these early treatments triggered a carbon starvation in the young fruits, with irreversible effects. Furthermore, our observations on the early treatments challenge the common view that carbohydrate supply influences positively carotenoid accumulation in fruits. We propose that early carbon starvation irreversibly promotes carotenoid accumulation.

Development of a configurable growth chamber with a computer vision system to study circadian rhythm in plants

Plant development is the result of an endogenous morphogenetic program that integrates environmental signals. The so-called circadian clock is a set of genes that integrates environmental inputs into an internal pacing system that gates growth and other outputs. Study of circadian growth responses requires high sampling rates to detect changes in growth and avoid aliasing. We have developed a flexible configurable growth chamber comprising a computer vision system that allows sampling rates ranging between one image per 30 s to hours/days. The vision system has a controlled illumination system, which allows the user to set up different configurations. The illumination system used emits a combination of wavelengths ensuring the optimal growth of species under analysis. In order to obtain high contrast of captured images, the capture system is composed of two CCD cameras, for day and night periods. Depending on the sample type, a flexible image processing software calculates different parameters based on geometric calculations. As a proof of concept we tested the system in three different plant tissues, growth of petunia- and snapdragon (Antirrhinum majus) flowers and of cladodes from the cactus Opuntia ficus-indica. We found that petunia flowers grow at a steady pace and display a strong growth increase in the early morning, whereas Opuntia cladode growth turned out not to follow a circadian growth pattern under the growth conditions imposed. Furthermore we were able to identify a decoupling of increase in area and length indicating that two independent growth processes are responsible for the final size and shape of the cladode.

High-to-low CO2 acclimation reveals plasticity of the photorespiratory pathway and indicates regulatory links to cellular metabolism of Arabidopsis

BACKGROUND

Photorespiratory carbon metabolism was long considered as an essentially closed and nonregulated pathway with little interaction to other metabolic routes except nitrogen metabolism and respiration. Most mutants of this pathway cannot survive in ambient air and require CO(2)-enriched air for normal growth. Several studies indicate that this CO(2) requirement is very different for individual mutants, suggesting a higher plasticity and more interaction of photorespiratory metabolism as generally thought. To understand this better, we examined a variety of high- and low-level parameters at 1% CO(2) and their alteration during acclimation of wild-type plants and selected photorespiratory mutants to ambient air.

METHODOLOGY AND PRINCIPAL FINDINGS

The wild type and four photorespiratory mutants of Arabidopsis thaliana (Arabidopsis) were grown to a defined stadium at 1% CO(2) and then transferred to normal air (0.038% CO(2)). All other conditions remained unchanged. This approach allowed unbiased side-by-side monitoring of acclimation processes on several levels. For all lines, diel (24 h) leaf growth, photosynthetic gas exchange, and PSII fluorescence were monitored. Metabolite profiling was performed for the wild type and two mutants. During acclimation, considerable variation between the individual genotypes was detected in many of the examined parameters, which correlated with the position of the impaired reaction in the photorespiratory pathway.

CONCLUSIONS

Photorespiratory carbon metabolism does not operate as a fully closed pathway. Acclimation from high to low CO(2) was typically steady and consistent for a number of features over several days, but we also found unexpected short-term events, such as an intermittent very massive rise of glycine levels after transition of one particular mutant to ambient air. We conclude that photorespiration is possibly exposed to redox regulation beyond known substrate-level effects. Additionally, our data support the view that 2-phosphoglycolate could be a key regulator of photosynthetic-photorespiratory metabolism as a whole.

A novel mesh processing based technique for 3D plant analysis

BACKGROUND

In recent years, imaging based, automated, non-invasive, and non-destructive high-throughput plant phenotyping platforms have become popular tools for plant biology, underpinning the field of plant phenomics. Such platforms acquire and record large amounts of raw data that must be accurately and robustly calibrated, reconstructed, and analysed, requiring the development of sophisticated image understanding and quantification algorithms. The raw data can be processed in different ways, and the past few years have seen the emergence of two main approaches: 2D image processing and 3D mesh processing algorithms. Direct image quantification methods (usually 2D) dominate the current literature due to comparative simplicity. However, 3D mesh analysis provides the tremendous potential to accurately estimate specific morphological features cross-sectionally and monitor them over-time.

RESULT

In this paper, we present a novel 3D mesh based technique developed for temporal high-throughput plant phenomics and perform initial tests for the analysis of Gossypium hirsutum vegetative growth. Based on plant meshes previously reconstructed from multi-view images, the methodology involves several stages, including morphological mesh segmentation, phenotypic parameters estimation, and plant organs tracking over time. The initial study focuses on presenting and validating the accuracy of the methodology on dicotyledons such as cotton but we believe the approach will be more broadly applicable. This study involved applying our technique to a set of six Gossypium hirsutum (cotton) plants studied over four time-points. Manual measurements, performed for each plant at every time-point, were used to assess the accuracy of our pipeline and quantify the error on the morphological parameters estimated.

CONCLUSION

By directly comparing our automated mesh based quantitative data with manual measurements of individual stem height, leaf width and leaf length, we obtained the mean absolute errors of 9.34%, 5.75%, 8.78%, and correlation coefficients 0.88, 0.96, and 0.95 respectively. The temporal matching of leaves was accurate in 95% of the cases and the average execution time required to analyse a plant over four time-points was 4.9 minutes. The mesh processing based methodology is thus considered suitable for quantitative 4D monitoring of plant phenotypic features.

Diel patterns of leaf and root growth: endogenous rhythmicity or environmental response?

Plants are sessile organisms forced to adjust to their surrounding environment. In a single plant the photoautotrophic shoot is exposed to pronounced environmental variations recurring in a day-night 24 h (diel) cycle, whereas the heterotrophic root grows in a temporally less fluctuating environment. The contrasting habitats of shoots and roots are reflected in different diel growth patterns and their responsiveness to environmental stimuli. Differences between diel leaf growth patterns of mono- and dicotyledonous plants correspond to their different organization and placement of growth zones. In monocots, heterotrophic growth zones are organized linearly and protected from the environment by sheaths of older leaves. In contrast, photosynthetically active growth zones of dicot leaves are exposed directly to the environment and show characteristic, species-specific diel growth patterns. It is hypothesized that the different exposure to environmental constraints and simultaneously the sink/source status of the growing organs may have induced distinct endogenous control of diel growth patterns in roots and leaves of monocot and dicot plants. Confronted by strong temporal fluctuations in environment, the circadian clock may facilitate robust intrinsic control of leaf growth in dicot plants.

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.

Circadian control of root elongation and C partitioning in Arabidopsis thaliana

Plants grow in a light/dark cycle. We have investigated how growth is buffered against the resulting changes in the carbon supply. Growth of primary roots of Arabidopsis seedlings was monitored using time-resolved video imaging. The average daily rate of growth is increased in longer light periods or by addition of sugars. It responds slowly over days when the conditions are changed. The momentary rate of growth exhibits a robust diel oscillation with a minimum 8-9 h after dawn and a maximum towards the end of the night. Analyses with starch metabolism mutants show that starch turnover is required to maintain growth at night. A carbon shortfall leads to an inhibition of growth, which is not immediately reversed when carbon becomes available again. The diel oscillation persists in continuous light and is strongly modified in clock mutants. Central clock functions that depend on CCA1/LHY are required to set an appropriate rate of starch degradation and maintain a supply of carbon to support growth through to dawn, whereas ELF3 acts to decrease growth in the light period and promote growth in the night. Thus, while the overall growth rate depends on the carbon supply, the clock orchestrates diurnal carbon allocation and growth.

High-throughput phenotyping of multicellular organisms: finding the link between genotype and phenotype

High-throughput phenotyping approaches (phenomics) are being combined with genome-wide genetic screens to identify alterations in phenotype that result from gene inactivation. Here we highlight promising technologies for 'phenome-scale' analyses in multicellular organisms.

Monitoring the regulation of gene expression in a growing organ using a fluid mechanics formalism

Background

Technological advances have enabled the accurate quantification of gene expression, even within single cell types. While transcriptome analyses are routinely performed, most experimental designs only provide snapshots of gene expression. Molecular mechanisms underlying cell fate or positional signalling have been revealed through these discontinuous datasets. However, in developing multicellular structures, temporal and spatial cues, known to directly influence transcriptional networks, get entangled as the cells are displaced and expand. Access to an unbiased view of the spatiotemporal regulation of gene expression occurring during development requires a specific framework that properly quantifies the rate of change of a property in a moving and expanding element, such as a cell or an organ segment.

Results

We show how the rate of change in gene expression can be quantified by combining kinematics and real-time polymerase chain reaction data in a mechanistic model which considers any organ as a continuum. This framework was applied in order to assess the developmental regulation of the two reference genes Actin11 and Elongation Factor 1-β in the apex of poplar root. The growth field was determined by time-lapse photography and transcript density was obtained at high spatial resolution. The net accumulation rates of the transcripts of the two genes were found to display highly contrasted developmental profiles. Actin11 showed pulses of up and down regulation in the accelerating and decelerating parts of the growth zone while the dynamic of EF1β were much slower. This framework provides key information about gene regulation in a developing organ, such as the location, the duration and the intensity of gene induction/repression.

Conclusions

We demonstrated that gene expression patterns can be monitored using the continuity equation without using mutants or reporter constructions. Given the rise of imaging technologies, this framework in our view opens a new way to dissect the molecular basis of growth regulation, even in non-model species or complex structures.

Simultaneous phenotyping of leaf growth and chlorophyll fluorescence via GROWSCREEN FLUORO allows detection of stress tolerance in Arabidopsis thaliana and other rosette plants

Stress caused by environmental factors evokes dynamic changes in plant phenotypes. In this study, we deciphered simultaneously the reaction of plant growth and chlorophyll fluorescence related parameters using a novel approach which combines existing imaging technologies (GROWSCREEN FLUORO). Three different abiotic stress situations were investigated demonstrating the benefit of this approach to distinguish between effects related to (1) growth, (2) chlorophyll-fluorescence, or (3) both of these aspects of the phenotype. In a drought stress experiment with more than 500 plants, poly(ADP-ribose) polymerase (PARP) deficient lines of Arabidopsis thaliana (L.) Heynh showed increased relative growth rates (RGR) compared with C24 wild-type plants. In chilling stress, growth of PARP and C24 lines decreased rapidly, followed by a decrease in F_v/F_m. Here, PARP-plants showed a more pronounced decrease of F_v/F_m than C24, which can be interpreted as a more efficient strategy for survival in mild chilling stress. Finally, the reaction of Nicotiana tabacum L. to altered spectral composition of the intercepted light was monitored as an example of a moderate stress situation that affects chlorophyll-fluorescence related, but not growth-related parameters. The examples investigated in this study show the capacity for improved plant phenotyping based on an automated and simultaneous evaluation of growth and photosynthesis at high throughput.