Philippe Abbal

Generation of ESTs from grape berry at various developmental stages

Summary Expressed sequence tags (ESTs) are a main tool in functional genomics. In this paper, we report the construction of 3 unidirectional cDNA libraries from green, softening, and ripening grape berries. For each library, a set of 100 randomly selected clones were sequenced at their 3′ end. Two hundred seventy-five expressed sequence tags (ESTs) were thus generated, representing around 187,000 bp of independent cDNA. 78 % of clones demonstrated significant homology to previously deposited nucleotide and/or polypeptide sequences. Transcripts homologous to proteins with known or putative functions were classified into functional categories. Highly represented protein classes were cell wall proteins, ribosomal proteins, proteins involved in signal transduction, and ripening-related proteins. A significant proportion of the ESTs (12 %) demonstrated no significant homology to any deposited sequence. This proportion of novel plant genes was highest (19 %) at veraison, the transient period when the berry softens and irreversibly switches from an organic acid to a sugar-accumulating organ. Expression analysis of these ESTs will define the range of genes involved in the development of grape berry as a model of fleshy, acidic, phenols-rich, and non-climacteric fruit.

Molecular characterization and expression analysis of the Rab GTPase family in Vitis vinifera reveal the specific expression of a VvRabA protein

As a first step to investigate whether Rab GTPases are involved in grape berry development, the Vitis vinifera EST and gene databases were searched for members of the VvRab family. The grapevine genome was found to contain 26 VvRabs that could be distributed into all of the eight groups described in the literature for model plants. Genetic mapping was successfully performed; VvRabs were mostly located on independent chromosomes, apart from eight that were located on the as yet unassigned portions of the genome clustered in the ChrUn Random chromosome. Conserved and divergent regions between VvRab protein sequences were identified. Transcript expression of 11 VvRabs was analysed by real-time quantitative RT-PCR. Except for VvRabA5b, transcript expression was detected, in general, in all the organs investigated, but with different patterns. In grape berries, VvRab transcripts were expressed at all stages of fruit development, with different profiles, except in the case of members of the A family which displayed generally similar patterns. The response to growth regulators in cell cultures was generally specific to each VvRab, with a differential pattern of expression for ethylene, auxin, and abscisic acid according to the VvRab. Interestingly, and unexpectedly considering transcript expression, western blotting using a monoclonal antibody raised against AtRabA5c (ARA4) showed a specific expression in the exocarp of ripe grape berries, in all seven red and white berry varieties tested. By contrast, no expression was detected in any of the other organs or tissues investigated. This paper contains the first description of Rab GTPases in V. vinifera. The involvement of a specific VvRab in grape berry late development and the potential role of this Rab GTPase are discussed in relation to literature data.

A Decision Support System Coupling Fuzzy Logic and Probabilistic Graphical Approaches for the Agri-Food Industry: Prediction of Grape Berry Maturity.

Agri-food is one of the most important sectors of the industry and a major contributor to the global warming potential in Europe. Sustainability issues pose a huge challenge for this sector. In this context, a big issue is to be able to predict the multiscale dynamics of those systems using computing science. A robust predictive mathematical tool is implemented for this sector and applied to the wine industry being easily able to be generalized to other applications. Grape berry maturation relies on complex and coupled physicochemical and biochemical reactions which are climate dependent. Moreover one experiment represents one year and the climate variability could not be covered exclusively by the experiments. Consequently, harvest mostly relies on expert predictions. A big challenge for the wine industry is nevertheless to be able to anticipate the reactions for sustainability purposes. We propose to implement a decision support system so called FGRAPEDBN able to (1) capitalize the heterogeneous fragmented knowledge available including data and expertise and (2) predict the sugar (resp. the acidity) concentrations with a relevant RMSE of 7 g/l (resp. 0.44 g/l and 0.11 g/kg). FGRAPEDBN is based on a coupling between a probabilistic graphical approach and a fuzzy expert system.

Putative Vitis vinifera Rop- and Rab-GAP-, GEF-, and GDI-interacting proteins uncovered with novel methods for public genomic and EST database analysis

To understand how grapevine Rop and Rab proteins achieve their functional versatility in signalling, identification of the putative VvRop- and VvRab-interacting proteins was performed using newly designed tools. In this study, sequences encoding eight full-length proteins for VvRop GTPase-activating proteins (GAPs), five for VvRabGAPs, six for VvRop guanine nucleotide exchange factors (GEFs), one for VvRabGEF, five for VvRop GDP dissociation inhibitors (GDIs), and three for VvRabGDIs were identified. These proteins had a CRIB motif or PH domain, a TBC domain, a PRONE domain, a DENN domain, or GDI signatures, respectively. By bootstrap analysis, an unrooted consensus phylogenetic tree was constructed which indicated that VvRopGDIs and VvRopGEFs--but not VvRopGAP--belonged to the same clade, and that VvRabGEF1 protein was more closely related to VvRopGAPs than to the other putative VvRab-interacting proteins. Twenty-two genes out of 28 encoding putative VvRop- and VvRab-interacting proteins could be located on identified grapevine chromosomes. Generally one gene was anchored on one chromosome, but in some cases up to four genes were located on the same chromosome. Expression patterns of the genes encoding putative VvRop- and VvRab-interacting proteins were also examined using a newly developed tool based on public expressed sequence tag (EST) database analysis. Expression patterns were sometimes found to be specific to an organ or a developmental stage. Although some limitations exist, the use of EST database analysis is stressed, in particular in the case of species where expression data are obtained at high costs in terms of time and effort.

A probabilistic graphical model for describing the grape berry maturity

Dynamic Bayesian networks for coupling heterogeneous data and expertise knowledge.The modeling of grape berry maturity over the time tainted with uncertainty.Prediction of sugar, acidity and anthocyanin concentrations over the maturity. Grape berry maturation depends on complex and coupled physiological and biochemical reactions which are climate dependant. Moreover one experiment represents one year and the climate variability could not be covered exclusively by the experiments. Consequently, harvest mostly relies on expert prediction. A big challenge for the wine industry is nevertheless to be able to anticipate the reactions for sustainability purposes. We propose to implement a robust mathematical model able (1) to capitalize the heterogeneous fragmented available knowledge including data and expertise by means of probabilistic graphical approaches; and (2) to predict sugar, acidity and anthocyanin concentrations over the maturity.

A Bayesian Network to Prevent Mite Infestations in Rose Greenhouses

Abstract Mite infestation is a big threat for rose greenhouses. It is much easier to halt and destroy them if their future development can be predicted. Taking into account temperature, humidity, cropping practices, plant vigour and some other influent parameters, an expert is able to predict the future development of the mites. Unfortunately, not all greenhouses can call on an expert permanently to help them in their fight against mites. To help them we have developed a novel model to assess and anticipate mite invasions in greenhouses in the short term. The model, based on a Bayesian network, takes into account the environment and the parameters defining invasion status with their interactions Data have been collected using knowledge from horticultural experts. The model has been validated in real situations emanating from the field. We obtained a good correlation between forecasts and expert predictions for the 18 cases used in this study. Thus, using this model should help the growers to protect against mite outbreaks. It constitutes a framework for studies of other harmful pest invasions.