Simulations of virtual plants reveal a role for SERRATE in the response of leaf development to light in Arabidopsis thaliana

Large-scale characterization of drought pattern: a continent-wide modelling approach applied to the Australian wheatbelt--spatial and temporal trends

Plant response to drought is complex, so that traits adapted to a specific drought type can confer disadvantage in another drought type. Understanding which type(s) of drought to target is of prime importance for crop improvement. Modelling was used to quantify seasonal drought patterns for a check variety across the Australian wheatbelt, using 123 yr of weather data for representative locations and managements. Two other genotypes were used to simulate the impact of maturity on drought pattern. Four major environment types summarized the variability in drought pattern over time and space. Severe stress beginning before flowering was common (44% of occurrences), with (24%) or without (20%) relief during grain filling. High variability occurred from year to year, differing with geographical region. With few exceptions, all four environment types occurred in most seasons, for each location, management system and genotype. Applications of such environment characterization are proposed to assist breeding and research to focus on germplasm, traits and genes of interest for target environments. The method was applied at a continental scale to highly variable environments and could be extended to other crops, to other drought-prone regions around the world, and to quantify potential changes in drought patterns under future climates.

Systems Modeling at Multiple Levels of Regulation: Linking Systems and Genetic Networks to Spatially Explicit Plant Populations

Selection and adaptation of individuals to their underlying environments are highly dynamical processes, encompassing interactions between the individual and its seasonally changing environment, synergistic or antagonistic interactions between individuals and interactions amongst the regulatory genes within the individual. Plants are useful organisms to study within systems modeling because their sedentary nature simplifies interactions between individuals and the environment, and many important plant processes such as germination or flowering are dependent on annual cycles which can be disrupted by climate behavior. Sedentism makes plants relevant candidates for spatially explicit modeling that is tied in with dynamical environments. We propose that in order to fully understand the complexities behind plant adaptation, a system that couples aspects from systems biology with population and landscape genetics is required. A suitable system could be represented by spatially explicit individual-based models where the virtual individuals are located within time-variable heterogeneous environments and contain mutable regulatory gene networks. These networks could directly interact with the environment, and should provide a useful approach to studying plant adaptation.

Expression-based functional investigation of the organ-specific microRNAs in Arabidopsis

MicroRNAs (miRNAs) play a pivotal role in plant development. The expression patterns of the miRNA genes significantly influence their regulatory activities. By utilizing small RNA (sRNA) high-throughput sequencing (HTS) data, the miRNA expression patterns were investigated in four organs (flowers, leaves, roots and seedlings) of Arabidopsis. Based on a set of criteria, dozens of organ-specific miRNAs were discovered. A dominant portion of the organ-specific miRNAs identified from the ARGONAUTE 4-enriched sRNA HTS libraries were highly expressed in flowers. Additionally, the expression of the precursors of the organ-specific miRNAs was analyzed. Degradome sequencing data-based approach was employed to identify the targets of the organ-specific miRNAs. The miRNA–target interactions were used for network construction. Subnetwork analysis unraveled some novel regulatory cascades, such as the feedback regulation mediated by miR161, the potential self-regulation of the genes miR172, miR396, miR398 and miR860, and the miR863-guided cleavage of the SERRATE transcript. Our bioinformatics survey expanded the organ-specific miRNA–target list in Arabidopsis, and could deepen the biological view of the miRNA expression and their regulatory roles.

Modelling the size and composition of fruit, grain and seed by process-based simulation models

Understanding what determines the size and composition of fruit, grain and seed in response to the environment and genotype is challenging, as these traits result from several linked processes controlled at different levels of organization, from the subcellular to the crop level, with subtle interactions occurring at or between the levels of organization. Process-based simulation models (PBSMs) implement algorithms to simulate metabolic and biophysical aspects of cell, tissue and organ behaviour. In this review, fruit, grain and seed PBSMs describing the main phases of growth, development and storage metabolism are discussed. From this concurrent work, it is possible to identify generic storage organ processes which can be modelled similarly for fruit, grain and seed. Spatial heterogeneity at the tissue and whole-plant level is found to be a key consideration in modelling the effects of the environment and genotype on fruit, grain and seed end-use value. In the future, PBSMs may well become the main link between studies at the molecular and whole-plant levels. To bridge this phenotype-to-genotype gap, future models need to remain plastic without becoming overparameterized.

Environment characterization as an aid to wheat improvement: interpreting genotype-environment interactions by modelling water-deficit patterns in North-Eastern Australia

Genotype-environment interactions (GEI) limit genetic gain for complex traits such as tolerance to drought. Characterization of the crop environment is an important step in understanding GEI. A modelling approach is proposed here to characterize broadly (large geographic area, long-term period) and locally (field experiment) drought-related environmental stresses, which enables breeders to analyse their experimental trials with regard to the broad population of environments that they target. Water-deficit patterns experienced by wheat crops were determined for drought-prone north-eastern Australia, using the APSIM crop model to account for the interactions of crops with their environment (e.g. feedback of plant growth on water depletion). Simulations based on more than 100 years of historical climate data were conducted for representative locations, soils, and management systems, for a check cultivar, Hartog. The three main environment types identified differed in their patterns of simulated water stress around flowering and during grain-filling. Over the entire region, the terminal drought-stress pattern was most common (50% of production environments) followed by a flowering stress (24%), although the frequencies of occurrence of the three types varied greatly across regions, years, and management. This environment classification was applied to 16 trials relevant to late stages testing of a breeding programme. The incorporation of the independently-determined environment types in a statistical analysis assisted interpretation of the GEI for yield among the 18 representative genotypes by reducing the relative effect of GEI compared with genotypic variance, and helped to identify opportunities to improve breeding and germplasm-testing strategies for this region.

Are the common assimilate pool and trophic relationships appropriate for dealing with the observed plasticity of grapevine development?

BACKGROUND AND AIMS

Models based on the consideration of plant development as the result of source-sink relationships between organs suffer from an inherent lack of quantification of the effect of trophic competition on organ growth processes. The 'common assimilate pool theory' underlying many such models is highly debatable.

METHODS

Six experiments were carried out in a greenhouse and outdoors with two grapevine cultivars and with 12 management systems, resulting in different types of plant architecture. Ten variables were used to quantify the impact of variations in assimilate supply and topological distances between sources and sinks on organogenesis, morphogenesis and biomass growth.

KEY RESULTS

A hierarchy of the responses of these processes to variations in assimilate supply was identified. Organ size seemed to be independent of assimilate supply, whereas both organogenesis and biomass growth were affected by variations in assimilate supply. Lower levels of organ biomass growth in response to the depletion of assimilate supplies seemed to be the principal mechanism underlying the plasticity of plant development in different environments. Defoliation or axis ablation resulted in changes in the relationship between growth processes and assimilate supply, highlighting the influence of non-trophic determinants. The findings cast doubt on the relevance of 'the common assimilate pool theory' for modelling the development of grapevine.

CONCLUSIONS

The results of this study suggest new formalisms for increasing the ability of models to take plant plasticity into account. The combination of an ecophysiological model for morphogenesis taking environmental signals into account and a biomass driven model for organogenesis and biomass allocation taking the topological distances between the sources and the sinks into account appears to be a promising approach. Moreover, in order to simulate the impact of agronomic practices, it will be necessary to take into account the non-trophic determinants of plant development such as hormonal signaletics.

Simulating the yield impacts of organ-level quantitative trait loci associated with drought response in maize: a "gene-to-phenotype" modeling approach

Under drought, substantial genotype-environment (G x E) interactions impede breeding progress for yield. Identifying genetic controls associated with yield response is confounded by poor genetic correlations across testing environments. Part of this problem is related to our inability to account for the interplay of genetic controls, physiological traits, and environmental conditions throughout the crop cycle. We propose a modeling approach to bridge this "gene-to-phenotype" gap. For maize under drought, we simulated the impact of quantitative trait loci (QTL) controlling two key processes (leaf and silk elongation) that influence crop growth, water use, and grain yield. Substantial G x E interaction for yield was simulated for hypothetical recombinant inbred lines (RILs) across different seasonal patterns of drought. QTL that accelerated leaf elongation caused an increase in crop leaf area and yield in well-watered or preflowering water deficit conditions, but a reduction in yield under terminal stresses (as such "leafy" genotypes prematurely exhausted the water supply). The QTL impact on yield was substantially enhanced by including pleiotropic effects of these QTL on silk elongation and on consequent grain set. The simulations obtained illustrated the difficulty of interpreting the genetic control of yield for genotypes influenced only by the additive effects of QTL associated with leaf and silk growth. The results highlight the potential of integrative simulation modeling for gene-to-phenotype prediction and for exploiting G x E interactions for complex traits such as drought tolerance.

Estimation of light interception in research environments: a joint approach using directional light sensors and 3D virtual plants applied to sunflower (Helianthus annuus) and Arabidopsis thaliana in natural and artificial conditions

Light interception is a major factor influencing plant development and biomass production. Several methods have been proposed to determine this variable, but its calculation remains difficult in artificial environments with heterogeneous light. We propose a method that uses 3D virtual plant modelling and directional light characterisation to estimate light interception in highly heterogeneous light environments such as growth chambers and glasshouses. Intercepted light was estimated by coupling an architectural model and a light model for different genotypes of the rosette species Arabidopsis thaliana (L.) Heynh and a sunflower crop. The model was applied to plants of contrasting architectures, cultivated in isolation or in canopy, in natural or artificial environments, and under contrasting light conditions. The model gave satisfactory results when compared with observed data and enabled calculation of light interception in situations where direct measurements or classical methods were inefficient, such as young crops, isolated plants or artificial conditions. Furthermore, the model revealed that A. thaliana increased its light interception efficiency when shaded. To conclude, the method can be used to calculate intercepted light at organ, plant and plot levels, in natural and artificial environments, and should be useful in the investigation of genotype-environment interactions for plant architecture and light interception efficiency.

A model-based analysis of the dynamics of carbon balance at the whole-plant level in Arabidopsis thaliana

Arabidopsis thaliana (L.) Heynh. is used as a model plant in many research projects. However, few models simulate its growth at the whole-plant scale. The present study describes the first model of Arabidopsis growth integrating organogenesis, morphogenesis and carbon-partitioning processes for aerial and subterranean parts of the plant throughout its development. The objective was to analyse competition among sinks as they emerge from patterns of plant structural development. The model was adapted from the GreenLab model and was used to estimate organ sink strengths by optimisation against biomass measurements. Dry biomass production was calculated by a radiation use efficiency-based approach. Organogenesis processes were parameterised based on experimental data. The potential of this model for growth analysis was assessed using the Columbia ecotype, which was grown in standard environmental conditions. Three phases were observed in the overall time course of trophic competition within the plant. In the vegetative phase, no competition was observed. In the reproductive phase, competition increased with a strong increase when lateral inflorescences developed. Roots and internodes and structures bearing siliques were strong sinks and had a similar impact on competition. The application of the GreenLab model to the growth analysis of A. thaliana provides new insights into source-sink relationships as functions of phenology and morphogenesis.

Dissecting external effects on logistic-based growth: equations, analytical solutions and applications

Characteristic growth patterns of individual organs are, to a large extent, determined by genetic factors, but can also be affected by intra-plant competition for resources and by environmental conditions. The current study proposes a dynamical system for modelling this dual control for logistic-based growth. The state of the system is defined by two state variables: size (s), and developmental age (α). The intrinsic properties of the system are represented by the potential relative growth rate as a function of α. This formulation allows dissection of the external effects on the system dynamics into two components: one that changes the duration of growth without affecting the final size and one that affects the final size without much effect on the duration. The former component determines the relationship between α and time, while the latter determines the effect on the system trajectory, s(α). The presented dynamical system is simpler and has a wider range of potential applications than the system proposed by Thornley and France (2005) for modelling logistic growth under resource limitation. The current approach can be also useful in ecology and in comparative studies of different genotypes and their responses to environmental conditions.

Relative contributions of light interception and radiation use efficiency to the reduction of maize productivity under cold temperatures

Maize (Zea mays L.) is a chill-susceptible crop cultivated in northern latitude environments. The detrimental effects of cold on growth and photosynthetic activity have long been established. However, a general overview of how important these processes are with respect to the reduction of productivity reported in the field is still lacking. In this study, a model-assisted approach was used to dissect variations in productivity under suboptimal temperatures and quantify the relative contributions of light interception (PAR_c) and radiation use efficiency (RUE) from emergence to flowering. A combination of architectural and light transfer models was used to calculate light interception in three field experiments with two cold-tolerant lines and at two sowing dates. Model assessment confirmed that the approach was suitable to infer light interception. Biomass production was strongly affected by early sowings. RUE was identified as the main cause of biomass reduction during cold events. Furthermore, PAR_c explained most of the variability observed at flowering, its relative contributions being more or less important according to the climate experienced. Cold temperatures resulted in lower PAR_c, mainly because final leaf length and width were significantly reduced for all leaves emerging after the first cold occurrence. These results confirm that virtual plants can be useful as fine phenotyping tools. A scheme of action of cold on leaf expansion, light interception and radiation use efficiency is discussed with a view towards helping breeders define relevant selection criteria.