Identifying Developmental Patterns in Structured Plant Phenotyping Data.

Technological breakthroughs concerning both sensors and robotized plant phenotyping platforms have totally renewed the plant phenotyping paradigm in the last two decades. This has impacted both the nature and the throughput of data with the availability of data at high-throughput from the tissular to the whole plant scale. Sensor outputs often take the form of 2D or 3D images or time series of such images from which traits are extracted while organ shapes, shoot or root system architectures can be deduced. Despite this change of paradigm, many phenotyping studies often ignore the structure of the plant and therefore loose the information conveyed by the temporal and spatial patterns emerging from this structure. The developmental patterns of plants often take the form of succession of well-differentiated phases, stages or zones depending on the temporal, spatial or topological indexing of data. This entails the use of hierarchical statistical models for their identification.The objective here is to show potential approaches for analyzing structured plant phenotyping data using state-of-the-art methods combining probabilistic modeling, statistical inference and pattern recognition. This approach is illustrated using five different examples at various scales that combine temporal and topological index parameters, and development and growth variables obtained using prospective or retrospective measurements.

Leaf Production and Expansion: A Generalized Response to Drought Stresses from Cells to Whole Leaf Biomass-A Case Study in the Tomato Compound Leaf.

It is clearly established that there is not a unique response to soil water deficit but that there are as many responses as soil water deficit characteristics: Drought intensity, drought duration, and drought position during plant cycle. For a same soil water deficit, responses can also differ on plant genotype within a same species. In spite of this variability, at least for leaf production and expansion processes, robust tendencies can be extracted from the literature when similar watering regimes are compared. Here, we present response curves and multi-scale dynamics analyses established on tomato plants exposed to different soil water deficit treatments. Results reinforce the trends already observed for other species: Reduction in plant leaf biomass under water stress was due to reduction in individual leaf biomass and areas whereas leaf production and specific leaf area were not affected. The dynamics of leaf expansion was modified both at the leaf and cell scales. Cell division and expansion were reduced by drought treatments as well as the endoreduplication process. Combining response curves analyses together with dynamic analyses of tomato compound leaf growth at different scales not only corroborate results on simple leaf responses to drought but also increases our knowledge on the cellular mechanisms behind leaf growth plasticity.

Are compound leaves more complex than simple ones? A multi-scale analysis.

Background and Aims: The question of which cellular mechanisms determine the variation in leaf size has been addressed mainly in plants with simple leaves. It is addressed here in tomato taking into consideration the expected complexity added by the several lateral appendages making up the compound leaf, the leaflets. Methods: Leaf and leaflet areas, epidermal cell number and areas, and endoreduplication (co-) variations were analysed in Solanum lycopersicum considering heteroblastic series in a wild type (Wva106) and an antisense mutant, the Pro35S:Slccs52AAS line, and upon drought treatments. All plants were grown in an automated phenotyping platform, PHENOPSIS, adapted to host plants grown in 7 L pots. Key Results: Leaf area, leaflet area and cell number increased with leaf rank until reaching a plateau. In contrast, cell area slightly decreased and endoreduplication did not follow any trend. In the transgenic line, leaf area, leaflet areas and cell number of basal leaves were lower than in the wild type, but higher in upper leaves. Reciprocally, cell area was higher in basal leaves and lower in upper leaves. When scaled up at the whole sympodial unit, all these traits did not differ significantly between the transgenic line and the wild type. In response to drought, leaf area was reduced, with a clear dose effect that was also reported for all size-related traits, including endoreduplication. Conclusions: These results provide evidence that all leaflets have the same cellular phenotypes as the leaf they belong to. Consistent with results reported for simple leaves, they show that cell number rather than cell size determines the final leaf areas and that endoreduplication can be uncoupled from leaf and cell sizes. Finally, they re-question a whole-plant control of cell division and expansion in leaves when the Wva106 and the Pro35S:Slccs52AAS lines are compared.

SIAMESE-RELATED1 Is Regulated Posttranslationally and Participates in Repression of Leaf Growth under Moderate Drought.

The plant cell cycle is tightly regulated by factors that integrate endogenous cues and environmental signals to adapt plant growth to changing conditions. Under drought, cell division in young leaves is blocked by an active mechanism, reducing the evaporative surface and conserving energy resources. The molecular function of cyclin-dependent kinase-inhibitory proteins (CKIs) in regulating the cell cycle has already been well studied, but little is known about their involvement in cell cycle regulation under adverse growth conditions. In this study, we show that the transcript of the CKI gene SIAMESE-RELATED1 (SMR1) is quickly induced under moderate drought in young Arabidopsis (Arabidopsis thaliana) leaves. Functional characterization further revealed that SMR1 inhibits cell division and affects meristem activity, thereby restricting the growth of leaves and roots. Moreover, we demonstrate that SMR1 is a short-lived protein that is degraded by the 26S proteasome after being ubiquitinated by a Cullin-RING E3 ubiquitin ligase. Consequently, overexpression of a more stable variant of the SMR1 protein leads to a much stronger phenotype than overexpression of the native SMR1. Under moderate drought, both the SMR1 transcript and SMR1 protein accumulate. Despite this induction, smr1 mutants do not show overall tolerance to drought stress but do show less growth inhibition of young leaves under drought. Surprisingly, the growth-repressive hormone ethylene promotes SMR1 induction, but the classical drought hormone abscisic acid does not.

Measurement of Arabidopsis thaliana Plant Traits Using the PHENOPSIS Phenotyping Platform.

High-throughput phenotyping of plant traits is a powerful tool to further our understanding of plant growth and its underlying physiological, molecular, and genetic determinisms. This protocol describes the methodology of a standard phenotyping experiment in PHENOPSIS automated platform, which was engineered in INRA-LEPSE (https://www6.montpellier.inra.fr/lepse) and custom-made by Optimalog company. The seminal method was published by Granier et al. (2006). The platform is used to explore and test various ecophysiological hypotheses (Tisné et al., 2010; Baerenfaller et al., 2012; Vile et al., 2012; Bac-Molenaar et al., 2015; Rymaszewski et al., 2017). Here, the focus concerns the preparation and management of experiments, as well as measurements of growth-related traits (e.g., projected rosette area, total leaf area and growth rate), water status-related traits (e.g., leaf dry matter content and relative water content), and plant architecture-related traits (e.g., stomatal density and index and lamina/petiole ratio). Briefly, a completely randomized (block) design is set up in the growth chamber. Next, the substrate is prepared, its initial water content is measured and pots are filled. Seeds are sown onto the soil surface and germinated prior to the experiment. After germination, soil watering and image (visible, infra-red, fluorescence) acquisition are planned by the user and performed by the automaton. Destructive measurements may be performed during the experiment. Data extraction from images and estimation of growth-related trait values involves semi-automated procedures and statistical processing.

Stress-Related Gene Expression Reflects Morphophysiological Responses to Water Deficit.

Acclimation to water deficit (WD) enables plants to maintain growth under unfavorable environmental conditions, although the mechanisms are not completely understood. In this study, the natural variation of long-term acclimation to moderate and severe soil WD was investigated in 18 Arabidopsis (Arabidopsis thaliana) accessions using PHENOPSIS, an automated phenotyping platform. Soil water content was adjusted at an early stage of plant development and maintained at a constant level until reproductive age was achieved. The accessions were selected based on the expression levels of ANNEXIN1, a drought-related marker. Severe WD conditions had a greater effect on most of the measured morphophysiological traits than moderate WD conditions. Multivariate analyses indicated that trait responses associated with plant size and water management drove most of the variation. Accessions with similar responses at these two levels were grouped in clusters that displayed different response strategies to WD The expression levels of selected stress-response genes revealed large natural variation under WD conditions. Responses of morphophysiological traits, such as projected rosette area, transpiration rate, and rosette water content, were correlated with changes in the expression of stress-related genes, such as NINE-CIS-EPOXYCAROTENOID DIOXYGENASE3 and N-MYC DOWNREGULATED-LIKE1 (NDL1), in response to WD Interestingly, the morphophysiological acclimation response to WD also was reflected in the gene expression levels (most notably those of NDL1, CHALCONE SYNTHASE, and MYB DOMAIN PROTEIN44) in plants cultivated under well-watered conditions. Our results may lead to the development of biomarkers and predictors of plant morphophysiological responses based on gene expression patterns.

Identifying developmental phases in the Arabidopsis thaliana rosette using integrative segmentation models.

The change in leaf size and shape during ontogeny associated with heteroblastic development is a composite trait for which extensive spatiotemporal data can be acquired using phenotyping platforms. However, only part of the information contained in such data is exploited, and developmental phases are usually defined using a selected organ trait. We here introduce new methods for identifying developmental phases in the Arabidopsis rosette using various traits and minimum a priori assumptions. A pipeline of analysis was developed combining image analysis and statistical models to integrate morphological, shape, dimensional and expansion dynamics traits for the successive leaves of the Arabidopsis rosette. Dedicated segmentation models called semi-Markov switching models were built for selected genotypes in order to identify rosette developmental phases. Four successive developmental phases referred to as seedling, juvenile, transition and adult were identified for the different genotypes. We show that the degree of covering of the leaf abaxial surface with trichomes is insufficient to define these developmental phases. Using our pipeline of analysis, we were able to identify the supplementary seedling phase and to uncover the structuring role of various leaf traits. This enabled us to compare on a more objective basis the vegetative development of Arabidopsis mutants.

Genome-wide association mapping of time-dependent growth responses to moderate drought stress in Arabidopsis.

Large areas of arable land are often confronted with irregular rainfall resulting in limited water availability for part(s) of the growing seasons, which demands research for drought tolerance of plants. Natural variation was observed for biomass accumulation upon controlled moderate drought stress in 324 natural accessions of Arabidopsis. Improved performance under drought stress was correlated with early flowering and lack of vernalization requirement, indicating overlap in the regulatory networks of flowering time and drought response or correlated responses of these traits to natural selection. In addition, plant size was negatively correlated with relative water content (RWC) independent of the absolute water content (WC), indicating a prominent role for soluble compounds. Growth in control and drought conditions was determined over time and was modelled by an exponential function. Genome-wide association (GWA) mapping of temporal plant size data and of model parameters resulted in the detection of six time-dependent quantitative trait loci (QTLs) strongly associated with drought. Most QTLs would not have been identified if plant size was determined at a single time point. Analysis of earlier reported gene expression changes upon drought enabled us to identify for each QTL the most likely candidates.

Phenotyping oilseed rape growth-related traits and their responses to water deficit: the disturbing pot size effect.

Following the recent development of high-throughput phenotyping platforms for plant research, the number of individual plants grown together in a same experiment has raised, sometimes at the expense of pot size. However, root restriction in excessively small pots affects plant growth and carbon partitioning, and may interact with other stresses targeted in these experiments. In work reported here, we investigated the interactive effects of pot size and soil water deficit on multiple growth-related traits from the cellular to the whole-plant scale in oilseed rape (Brassica napus L.). The effects of pot size on responses to water deficit and allometric relationships revealed strong, multilevel interactions between pot size and watering regime. Notably, water deficit increased the root:shoot ratio in large pots, but not in small pots. At the cellular scale, water deficit decreased epidermal leaf cell area in large pots, but not in small pots. These results were consistent with changes in the level of endoreduplication factor in leaf cells. Our study illustrates the disturbing interaction of pot size with water deficit and raises the need to carefully consider this factor in the frame of the current development of high-throughput phenotyping experiments.

Genome-wide association mapping of growth dynamics detects time-specific and general quantitative trait loci.

Growth is a complex trait determined by the interplay between many genes, some of which play a role at a specific moment during development whereas others play a more general role. To identify the genetic basis of growth, natural variation in Arabidopsis rosette growth was followed in 324 accessions by a combination of top-view imaging, high-throughput image analysis, modelling of growth dynamics, and end-point fresh weight determination. Genome-wide association (GWA) mapping of the temporal growth data resulted in the detection of time-specific quantitative trait loci (QTLs), whereas mapping of model parameters resulted in another set of QTLs related to the whole growth curve. The positive correlation between projected leaf area (PLA) at different time points during the course of the experiment suggested the existence of general growth factors with a function in multiple developmental stages or with prolonged downstream effects. Many QTLs could not be identified when growth was evaluated only at a single time point. Eleven candidate genes were identified, which were annotated to be involved in the determination of cell number and size, seed germination, embryo development, developmental phase transition, or senescence. For eight of these, a mutant or overexpression phenotype related to growth has been reported, supporting the identification of true positives. In addition, the detection of QTLs without obvious candidate genes implies the annotation of novel functions for underlying genes.

Quantifying spatial heterogeneity of chlorophyll fluorescence during plant growth and in response to water stress.

BACKGROUND: Effects of abiotic and biotic stresses on plant photosynthetic performance lead to fitness and yield decrease. The maximum quantum efficiency of photosystem II (F v/F m) is a parameter of chlorophyll fluorescence (ChlF) classically used to track changes in photosynthetic performance. Despite recent technical and methodological advances in ChlF imaging, the spatio-temporal heterogeneity of F v/F m still awaits for standardized and accurate quantification. RESULTS: We developed a method to quantify the dynamics of spatial heterogeneity of photosynthetic efficiency through the distribution-based analysis of F v/F m values. The method was applied to Arabidopsis thaliana grown under well-watered and severe water deficit (survival rate of 40%). First, whole-plant F v/F m shifted from unimodal to bimodal distributions during plant development despite a constant mean F v/F m under well-watered conditions. The establishment of a bimodal distribution of F v/F m reflects the occurrence of two types of leaf regions with contrasted photosynthetic efficiency. The distance between the two modes (called S) quantified the whole-plant photosynthetic heterogeneity. The weighted contribution of the most efficient/healthiest leaf regions to whole-plant performance (called W max) quantified the spatial efficiency of a photosynthetically heterogeneous plant. Plant survival to water deficit was associated to high S values, as well as with strong and fast recovery of W max following soil rewatering. Hence, during stress surviving plants had higher, but more efficient photosynthetic heterogeneity compared to perishing plants. Importantly, S allowed the discrimination between surviving and perishing plants four days earlier than the mean F v/F m. A sensitivity analysis from simulated dynamics of F v/F m showed that parameters indicative of plant tolerance and/or stress intensity caused identifiable changes in S and W max. Finally, an independent comparison of six Arabidopsis accessions grown under well-watered conditions indicated that S and W max are related to the genetic variability of growth. CONCLUSIONS: The distribution-based analysis of ChlF provides an efficient tool for quantifying photosynthetic heterogeneity and performance. S and W max are good indicators to estimate plant survival under water stress. Our results suggest that the dynamics of photosynthetic heterogeneity are key components of plant growth and tolerance to stress.

Heterosis and inbreeding depression of epigenetic Arabidopsis hybrids.

We have addressed the possible epigenetic contribution to heterosis using epigenetic inbred lines (epiRILs) with varying levels and distributions of DNA methylation. One line consistently displayed parent-of-origin heterosis for growth-related traits. Genome-wide transcription profiling followed by a candidate gene approach revealed 33 genes with altered regulation in crosses of this line that could contribute to the observed heterosis. Although none of the candidate genes could explain hybrid vigour, we detected intriguing, hybrid-specific transcriptional regulation of the RPP5 gene, encoding a growth suppressor. RPP5 displayed intermediate transcript levels in heterotic hybrids; surprisingly however, with global loss of fitness of their F2 progeny, we observed striking under-representation of the hybrid-like intermediate levels. Thus, in addition to genetic factors contributing to heterosis, our results strongly suggest that epigenetic diversity and epigenetic regulation of transcription play a role in hybrid vigour and inbreeding depression, and also in the absence of parental genetic diversity.

Multivariate genetic analysis of plant responses to water deficit and high temperature revealed contrasting adaptive strategies.

How genetic factors control plant performance under stressful environmental conditions is a central question in ecology and for crop breeding. A multivariate framework was developed to examine the genetic architecture of performance-related traits in response to interacting environmental stresses. Ecophysiological and life history traits were quantified in the Arabidopsis thaliana Ler × Cvi mapping population exposed to constant soil water deficit and high air temperature. The plasticity of the genetic variance-covariance matrix (G-matrix) was examined using mixed-effects models after regression into principal components. Quantitative trait locus (QTL) analysis was performed on the predictors of genotype effects and genotype by environment interactions (G × E). Three QTLs previously identified for flowering time had antagonistic G × E effects on carbon acquisition and the other traits (phenology, growth, leaf morphology, and transpiration). This resulted in a size-dependent response of water use efficiency (WUE) to high temperature but not soil water deficit, indicating that most of the plasticity of carbon acquisition and WUE to temperature is controlled by the loci that control variation of development, size, growth, and transpiration. A fourth QTL, MSAT2.22, controlled the response of carbon acquisition to specific combinations of watering and temperature irrespective of plant size and development, growth, and transpiration rate, which resulted in size-independent plasticity of WUE. These findings highlight how the strategies to optimize plant performance may differ in response to water deficit and high temperature (or their combination), and how different G × E effects could be targeted to improve plant tolerance to these stresses.

Phenotyping and beyond: modelling the relationships between traits.

Plant phenotyping technology has become more advanced with the capacity to measure many morphological and physiological traits on a given individual. With increasing automation, getting access to various traits on a high number of genotypes over time raises the need to develop systems for data storage and analyses, all congregating into plant phenotyping pipelines. In this review, we highlight several studies that illustrate the latest advances in plant multi-trait phenotyping and discuss future needs to ensure the best use of all these quantitative data. We assert that the next challenge is to disentangle how plant traits are embedded in networks of dependencies (and independencies) by modelling the relationships between them and how these are affected by genetics and environment.

Phenotyping the kinematics of leaf development in flowering plants: recommendations and pitfalls.

Leaves of flowering plants are produced from the shoot apical meristem at regular intervals and they grow according to a developmental program that is determined by both genetic and environmental factors. Detailed frameworks for multiscale dynamic analyses of leaf growth have been developed in order to identify and interpret phenotypic differences caused by either genetic or environmental variations. They revealed that leaf growth dynamics are non-linearly and nonhomogeneously distributed over the lamina, in the leaf tissues and cells. The analysis of the variability in leaf growth, and its underlying processes, has recently gained momentum with the development of automated phenotyping platforms that use various technologies to record growth at different scales and at high throughput. These modern tools are likely to accelerate the characterization of gene function and the processes that underlie the control of shoot development. Combined with powerful statistical analyses, trends have emerged that may have been overlooked in low throughput analyses. However, in many examples, the increase in throughput allowed by automated platforms has led to a decrease in the spatial and/or temporal resolution of growth analyses. Concrete examples presented here indicate that simplification of the dynamic leaf system, without consideration of its spatial and temporal context, can lead to important misinterpretations of the growth phenotype.

A common genetic basis to the origin of the leaf economics spectrum and metabolic scaling allometry.

Many facets of plant form and function are reflected in general cross-taxa scaling relationships. Metabolic scaling theory (MST) and the leaf economics spectrum (LES) have each proposed unifying frameworks and organisational principles to understand the origin of botanical diversity. Here, we test the evolutionary assumptions of MST and the LES using a cross of two genetic variants of Arabidopsis thaliana. We show that there is enough genetic variation to generate a large fraction of variation in the LES and MST scaling functions. The progeny sharing the parental, naturally occurring, allelic combinations at two pleiotropic genes exhibited the theorised optimum ¾ allometric scaling of growth rate and intermediate leaf economics. Our findings: (1) imply that a few pleiotropic genes underlie many plant functional traits and life histories; (2) unify MST and LES within a common genetic framework and (3) suggest that observed intermediate size and longevity in natural populations originate from stabilising selection to optimise physiological trade-offs.

Systems-based analysis of Arabidopsis leaf growth reveals adaptation to water deficit.

Leaves have a central role in plant energy capture and carbon conversion and therefore must continuously adapt their development to prevailing environmental conditions. To reveal the dynamic systems behaviour of leaf development, we profiled Arabidopsis leaf number six in depth at four different growth stages, at both the end-of-day and end-of-night, in plants growing in two controlled experimental conditions: short-day conditions with optimal soil water content and constant reduced soil water conditions. We found that the lower soil water potential led to reduced, but prolonged, growth and an adaptation at the molecular level without a drought stress response. Clustering of the protein and transcript data using a decision tree revealed different patterns in abundance changes across the growth stages and between end-of-day and end-of-night that are linked to specific biological functions. Correlations between protein and transcript levels depend on the time-of-day and also on protein localisation and function. Surprisingly, only very few of >1700 quantified proteins showed diurnal abundance fluctuations, despite strong fluctuations at the transcript level.

Tackling drought stress: receptor-like kinases present new approaches.

Global climate change and a growing population require tackling the reduction in arable land and improving biomass production and seed yield per area under varying conditions. One of these conditions is suboptimal water availability. Here, we review some of the classical approaches to dealing with plant response to drought stress and we evaluate how research on RECEPTOR-LIKE KINASES (RLKs) can contribute to improving plant performance under drought stress. RLKs are considered as key regulators of plant architecture and growth behavior, but they also function in defense and stress responses. The available literature and analyses of available transcript profiling data indeed suggest that RLKs can play an important role in optimizing plant responses to drought stress. In addition, RLK pathways are ideal targets for nontransgenic approaches, such as synthetic molecules, providing a novel strategy to manipulate their activity and supporting translational studies from model species, such as Arabidopsis thaliana, to economically useful crops.

Structural assessment of the impact of environmental constraints on Arabidopsis thaliana leaf growth: a 3D approach.

Light and soil water content affect leaf surface area expansion through modifications in epidermal cell numbers and area, while effects on leaf thickness and mesophyll cell volumes are far less documented. Here, three-dimensional imaging was applied in a study of Arabidopsis thaliana leaf growth to determine leaf thickness and the cellular organization of mesophyll tissues under moderate soil water deficit and two cumulative light conditions. In contrast to surface area, thickness was highly conserved in response to water deficit under both low and high cumulative light regimes. Unlike epidermal and palisade mesophyll tissues, no reductions in cell number were observed in the spongy mesophyll; cells had rather changed in volume and shape. Furthermore, leaf features of a selection of genotypes affected in leaf functioning were analysed. The low-starch mutant pgm had very thick leaves because of unusually large palisade mesophyll cells, together with high levels of photosynthesis and stomatal conductance. By means of an open stomata mutant and a 9-cis-epoxycarotenoid dioxygenase overexpressor, it was shown that stomatal conductance does not necessarily have a major impact on leaf dimensions and cellular organization, pointing to additional mechanisms for the control of CO(2) diffusion under high and low stomatal conductance, respectively.

Arabidopsis growth under prolonged high temperature and water deficit: independent or interactive effects?

High temperature (HT) and water deficit (WD) are frequent environmental constraints restricting plant growth and productivity. These stresses often occur simultaneously in the field, but little is known about their combined impacts on plant growth, development and physiology. We evaluated the responses of 10 Arabidopsis thaliana natural accessions to prolonged elevated air temperature (30 °C) and soil WD applied separately or in combination. Plant growth was significantly reduced under both stresses and their combination was even more detrimental to plant performance. The effects of the two stresses were globally additive, but some traits responded specifically to one but not the other stress. Root allocation increased in response to WD, while reproductive allocation, hyponasty and specific leaf area increased under HT. All the traits that varied in response to combined stresses also responded to at least one of them. Tolerance to WD was higher in small-sized accessions under control temperature and HT and in accessions with high biomass allocation to root under control conditions. Accessions that originate from sites with higher temperature have less stomatal density and allocate less biomass to the roots when cultivated under HT. Independence and interaction between stresses as well as the relationships between traits and stress responses are discussed.