A knowledge base for Vitis vinifera functional analysis

Vitis vinifera (Grapevine) is the most important fruit species in the modern world. Wine and table grapes sales contribute significantly to the economy of major wine producing countries. The most relevant goals in wine production concern quality and safety. In order to significantly improve the achievement of these objectives and to gain biological knowledge about cultivars, a genomic approach is the most reliable strategy. The recent grapevine genome sequencing offers the opportunity to study the potential roles of genes and microRNAs in fruit maturation and other physiological and pathological processes. Although several systems allowing the analysis of plant genomes have been reported, none of them has been designed specifically for the functional analysis of grapevine genomes of cultivars under environmental stress in connection with microRNA data

A COMPASS for VESPUCCI: a FAIR way to explore the grapevine transcriptomic landscape

7openInternationalSuccessfully integrating transcriptomic experiments is a challenging task with the ultimate goal of analyzing gene expression data in the broader context of all available measurements, all from a single point of access. In its second major release VESPUCCI, the integrated database of gene expression data for grapevine, has been updated to be FAIR-compliant, employing standards and created with open-source technologies. It includes all public grapevine gene expression experiments from both microarray and RNA-seq platforms. Transcriptomic data can be accessed in multiple ways through the newly developed COMPASS GraphQL interface, while the expression values are normalized using different methodologies to flexibly satisfy different analysis requirements. Sample annotations are manually curated and use standard formats and ontologies. The updated version of VESPUCCI provides easy querying and analyzing of integrated grapevine gene expression (meta)data and can be seamlessly embedded in any analysis workflow or tools. VESPUCCI is freely accessible and offers several ways of interaction, depending on the specific goals and purposes and/or user expertise; an overview can be found at https://vespucci.readthedocs.io/.openMoretto M.; Sonego P.; Pilati S.; Matus J.T.; Costantini L.; Malacarne G.; Engelen K.Moretto, M.; Sonego, P.; Pilati, S.; Matus, J.T.; Costantini, L.; Malacarne, G.; Engelen, K

Constructing Integrated Networks for Identifying New Secondary Metabolic Pathway Regulators in Grapevine: Recent Applications and Future Opportunities

Representing large biological data as networks is becoming increasingly adopted for predicting gene function while elucidating the multifaceted organization of life processes. In grapevine (Vitis vinifera L.), network analyses have been mostly adopted to contribute to the understanding of the regulatory mechanisms that control berry composition. Whereas, some studies have used gene co-expression networks to find common pathways and putative targets for transcription factors related to development and metabolism, others have defined networks of primary and secondary metabolites for characterizing the main metabolic differences between cultivars throughout fruit ripening. Lately, proteomic-related networks and those integrating genome-wide analyses of promoter regulatory elements have also been generated. The integration of all these data in multilayered networks allows building complex maps of molecular regulation and interaction. This perspective article describes the currently available network data and related resources for grapevine. With the aim of illustrating data integration approaches into network construction and analysis in grapevine, we searched for berry-specific regulators of the phenylpropanoid pathway. We generated a composite network consisting of overlaying maps of co-expression between structural and transcription factor genes, integrated with the presence of promoter cis-binding elements, microRNAs, and long non-coding RNAs (lncRNA). This approach revealed new uncharacterized transcription factors together with several microRNAs potentially regulating different steps of the phenylpropanoid pathway, and one particular lncRNA compromising the expression of nine stilbene synthase (STS) genes located in chromosome 10. Application of network-based approaches into multi-omics data will continue providing supplementary resources to address important questions regarding grapevine fruit quality and compositio

miRVIT: A Novel miRNA Database and Its Application to Uncover Vitis Responses to Flavescence dorée Infection

Micro(mi)RNAs play crucial roles in plant developmental processes and in defense responses to biotic and abiotic stresses. In the last years, many works on small RNAs in grapevine (Vitis spp.) were published, and several conserved and putative novel grapevine-specific miRNAs were identified. In order to reorganize the high quantity of available data, we produced “miRVIT,” the first database of all novel grapevine miRNA candidates characterized so far, and still not deposited in miRBase. To this aim, each miRNA accession was renamed, repositioned in the last version of the grapevine genome, and compared with all the novel and conserved miRNAs detected in grapevine. Conserved and novel miRNAs cataloged in miRVIT were then used for analyzing Vitis vinifera plants infected by Flavescence dorée (FD), one of the most severe phytoplasma diseases affecting grapevine. The analysis of small RNAs from healthy, recovered (plants showing spontaneous and stable remission of symptoms), and FD-infected “Barbera” grapevines showed that FD altered the expression profiles of several miRNAs, including those involved in cell development and photosynthesis, jasmonate signaling, and disease resistance response. The application of miRVIT in a biological context confirmed the effectiveness of the followed approach, especially for the identification of novel miRNA candidates in grapevine. miRVIT database is available at http://mirvit.ipsp.cnr.it.Highlights: The application of the newly produced database of grapevine novel miRNAs to the analysis of plants infected by Flavescence dorée reveals key roles of miRNAs in photosynthesis and jasmonate signaling

Integrating gene expression data to infer how biological changes drive transcriptional responses

The work presented in this Ph.D. thesis is two sided. The first part describes a series of tools to integrate gene expression data, while the second one describes how to mathematically model them. The first part explains the methodology used to integrate publicly available transcriptomic data, the creation of a series of software tools that implement this methodology, and their application to create collections of gene expression data (compendia) for several prokaryote species and one eukaryote (the crop plant Vitis vinifera). Compendia are gene expression matrices in which every row is a gene of the species of interest while columns represent the different conditions in which genes have been measured. They provide a rich source of information for systems biology applications. Besides being the result of the first part of this Ph.D. project, gene expression compendia are the starting point for the second part, with the purpose of facilitating biological knowledge discovery drawing inference from mathematical models. We develop and discuss two complementary models. The first one uses a Bayesian approach, in which we model a probability distribution over an underlying true change in expression for a given gene in response to a given condition. The second one uses Boolean networks to model structural information about the known genetic mechanisms of response to stimuli. Boolean networks are used to fit a distribution over steady-states of cells in measured samples. These models may be used for various types of statistical inference and decision making. They can serve to formulate statistically sound hypothesis about stimuli/signals that better explain observed changes in gene expression, or about the inherent variability of a gene (independently from the conditions in which it is measured), or to find complex patterns of co-expression