Comparison of predictive methods and biological validation for qPCR reference genes in sunflower leaf senescence transcript analysis.

The selection and validation of reference genes constitute a key point for gene expression analysis based on qPCR, requiring efficient normalization approaches. In this work, the expression profiles of eight genes were evaluated to identify novel reference genes for transcriptional studies associated to the senescence process in sunflower. Three alternative strategies were applied for the evaluation of gene expression stability in leaves of different ages and exposed to different treatments affecting the senescence process: algorithms implemented in geNorm, BestKeeper software, and the fitting of a statistical linear mixed model (LMModel). The results show that geNorm suggested the use of all combined genes, although identifying α-TUB1 as the most stable expressing gene. BestKeeper revealed α-TUB and ß-TUB as stable genes, scoring ß-TUB as the most stable one. The statistical LMModel identified α-TUB, actin, PEP, and EF-1α as stable genes in this order. The model-based approximation allows not only the estimation of systematic changes in gene expression, but also the identification of sources of random variation through the estimation of variance components, considering the experimental design applied. Validation of α-TUB and EF-1α as reference genes for expression studies of three sunflower senescence associated genes showed that the first one was more stable for the assayed conditions. We conclude that, when biological replicates are available, LMModel allows a more reliable selection under the assayed conditions. This study represents the first analysis of identification and validation of genuine reference genes for use as internal control in qPCR expression studies in sunflower, experimentally validated throughout six different controlled leaf senescence conditions.

Genetic variability for leaf growth rate and duration under water deficit in sunflower: analysis of responses at cell, organ, and plant level.

Plants under water deficit reduce leaf growth, thereby reducing transpiration rate at the expense of reduced photosynthesis. The objective of this work was to analyse the response of leaf growth to water deficit in several sunflower genotypes in order to identify and quantitatively describe sources of genetic variability for this trait that could be used to develop crop varieties adapted to specific scenarios. The genetic variability of the response of leaf growth to water deficit was assessed among 18 sunflower (Helianthus annuus L.) inbred lines representing a broad range of genetic diversity. Plants were subjected to long-term, constant-level, water-deficit treatments, and the response to water deficit quantified by means of growth models at cell-, leaf-, and plant-scale. Significant variation among lines was found for the response of leaf expansion rate and of leaf growth duration, with an equal contribution of these responses to the variability in the reduction of leaf area. Increased leaf growth duration under water deficit is usually suggested to be caused by changes in the activity of cell-wall enzymes, but the present results suggest that the duration of epidermal cell division plays a key role in this response. Intrinsic genotypic responses of rate and duration at a cellular scale were linked to genotypic differences in whole-plant leaf area profile to water deficit. The results suggest that rate and duration responses are the result of different physiological mechanisms, and therefore capable of being combined to increase the variability in leaf area response to water deficit.

Rewatering plants after a long water-deficit treatment reveals that leaf epidermal cells retain their ability to expand after the leaf has apparently reached its final size.

BACKGROUND AND AIMS: Leaves expand during a given period of time until they reach their final size and form, which is called determinate growth. Duration of leaf expansion is stable when expressed in thermal-time and in the absence of stress, and consequently it is often proposed that it is controlled by a robust programme at the plant scale. The usual hypothesis is that growth cessation occurs when cell expansion becomes limited by an irreversible tightening of cell wall, and that leaf size is fixed once cell expansion ceases. The objective of this paper was to test whether leaf expansion could be restored by rewatering plants after a long soil water-deficit period. METHODS: Four experiments were performed on two different species (Arabidopsis thaliana and Helianthus annuus) in which the area of leaves that had apparently reached their final size was measured upon reversal of water stresses of different intensities and durations. KEY RESULTS: Re-growth of leaves that had apparently reached their final size occurred in both species, and its magnitude depended only on the time elapsed from growth cessation to rewatering. Leaf area increased up to 186% in A. thaliana and up to 88% in H. annuus after rewatering, with respect to the leaves of plants that remained under water deficit. Re-growth was accounted for by cell expansion. Increase in leaf area represented actual growth and not only a reversible change due to increased turgor. CONCLUSIONS: After the leaf has ceased to grow, leaf cells retain their ability to expand for several days before leaf size becomes fixed. A response window was identified in both species, during which the extent of leaf area recovery decreased with time after the 'initial' leaf growth cessation. These results suggest that re-growth after rewatering of leaves having apparently attained their final size could be a generalized phenomenon, at least in dicotyledonous plants.

Assessing the Efficiency of Phenotyping Early Traits in a Greenhouse Automated Platform for Predicting Drought Tolerance of Soybean in the Field.

Conventional field phenotyping for drought tolerance, the most important factor limiting yield at a global scale, is labor-intensive and time-consuming. Automated greenhouse platforms can increase the precision and throughput of plant phenotyping and contribute to a faster release of drought tolerant varieties. The aim of this work was to establish a framework of analysis to identify early traits which could be efficiently measured in a greenhouse automated phenotyping platform, for predicting the drought tolerance of field grown soybean genotypes. A group of genotypes was evaluated, which showed variation in their drought susceptibility index (DSI) for final biomass and leaf area. A large number of traits were measured before and after the onset of a water deficit treatment, which were analyzed under several criteria: the significance of the regression with the DSI, phenotyping cost, earliness, and repeatability. The most efficient trait was found to be transpiration efficiency measured at 13 days after emergence. This trait was further tested in a second experiment with different water deficit intensities, and validated using a different set of genotypes against field data from a trial network in a third experiment. The framework applied in this work for assessing traits under different criteria could be helpful for selecting those most efficient for automated phenotyping.

Kinetic Modeling of Sunflower Grain Filling and Fatty Acid Biosynthesis.

Grain growth and oil biosynthesis are complex processes that involve various enzymes placed in different sub-cellular compartments of the grain. In order to understand the mechanisms controlling grain weight and composition, we need mathematical models capable of simulating the dynamic behavior of the main components of the grain during the grain filling stage. In this paper, we present a non-structured mechanistic kinetic model developed for sunflower grains. The model was first calibrated for sunflower hybrid ACA855. The calibrated model was able to predict the theoretical amount of carbohydrate equivalents allocated to the grain, grain growth and the dynamics of the oil and non-oil fraction, while considering maintenance requirements and leaf senescence. Incorporating into the model the serial-parallel nature of fatty acid biosynthesis permitted a good representation of the kinetics of palmitic, stearic, oleic, and linoleic acids production. A sensitivity analysis showed that the relative influence of input parameters changed along grain development. Grain growth was mostly affected by the specific growth parameter (µ') while fatty acid composition strongly depended on their own maximum specific rate parameters. The model was successfully applied to two additional hybrids (MG2 and DK3820). The proposed model can be the first building block toward the development of a more sophisticated model, capable of predicting the effects of environmental conditions on grain weight and composition, in a comprehensive and quantitative way.

A whole-plant analysis of the dynamics of expansion of individual leaves of two sunflower hybrids.

Common features in the time-course of expansion of leaves which considerably differed in final area, due to phytomer position, growing conditions and genotype, were identified. Leaf development consisted of two phases of exponential growth, followed by a third phase of continuous decrease of the relative expansion rate. The rate and the duration of the first exponential phase were common to all phytomers, growing conditions and genotypes. Leaves differed in the rate and the duration of the second exponential phase. The decrease of the relative expansion rate during the third phase depended on neither genotype nor growing conditions. It was phytomer-dependent and was deduced from the rate of the second phase via a parameter common to all cases studied. Differences in final leaf area among growing conditions were linked to different expansion rates during the second exponential phase. The duration of the phases at any given phytomer position was the same for the two hybrids in different growing conditions. The dates of developmental events (initiation, end of the two exponential phases, full expansion), and the rate of the second exponential phase, were related to phytomer position, defining a strict pattern of leaf development at the whole plant level. Using this framework simplified the analysis of the response of leaf expansion to genotype and environment.