Grapevine (Vitis vinifera) is one of the main fruit crops worldwide. In 2020, the total surface area planted with vines was estimated at 7.3 million hectares. Diverse pathogens affect grapevine yield, fruit, and wine quality of which powdery mildew is the most important disease prior to harvest. Its causal agent is the biotrophic fungus Erysiphe necator, which generates a decrease in cluster weight, delays fruit ripening, and reduces photosynthetic and transpiration rates. In addition, powdery mildew induces metabolic reprogramming in its host, affecting primary metabolism. Most commercial grapevine cultivars are highly susceptible to powdery mildew; consequently, large quantities of fungicide are applied during the productive season. However, pesticides are associated with health problems, negative environmental impacts, and high costs for farmers. In paralleled, consumers are demanding more sustainable practices during food production. Therefore, new grapevine cultivars with genetic resistance to powdery mildew are needed for sustainable viticulture, while maintaining yield, fruit, and wine quality. Two main gene families confer resistance to powdery mildew in the Vitaceae, Run (Resistance to Uncinula necator) and Ren (Resistance to Erysiphe necator). This article reviews the powdery mildew resistance genes and loci and their use in grapevine breeding programs.

The increasing availability of omics data from non-model plant species has created a pressing need for centralized, user-friendly platforms that maximize the utility of these datasets in a FAIR manner. Here, we introduce PlantaeViz, a web-based tool designed for the integration, visualization, and analysis of multi-omics data across a wide range of plant species. PlantaeViz offers advanced functionalities, including gene catalogues built from curated literature, transcriptomic meta-analyses presented as gene expression atlases, gene co-expression and regulatory networks with on-the-fly ontology analyses, cistrome visualization and metabolomics-transcriptomics integration, among other tools, providing a robust framework for hypothesis generation and biological interpretation. Gene Cards applications, tailored to each plant species, provide both community-curated and automatically generated functional annotation information. One of the platform's core features is its big data approach: over 58,000 publicly available SRA transcriptomic samples have been processed and visualized to date. Significant efforts have been made in orthology assessment using multiple layers of evidence, as well as in the automatic classification and standardization of omics metadata through regular expressions and data mining. As a result, around 90% of transcriptomic runs have been successfully classified according to sample tissue. These data have been used to construct gene networks via computationally intensive methods based on diverse algorithms. We present a study case to illustrate the platform's integration and exploratory capabilities. PlantaeViz bridges genomics and functional knowledge between model and non-model plant species and aims to expand its species catalogue of species in the future, democratizing access to large-scale plant omics data. Further developments will include the incorporation of additional data types, and the implementation of new tools to further support plant research across diverse biological contexts.

Climate change poses a significant threat to agriculture, particularly in regions where increased drought periods, abnormal heat, and intensified pest pressure threaten crop productivity. Viticulture, as one of the most economically important crops, is highly vulnerable to these challenges. Understanding the molecular mechanisms underlying drought responses in grapevines is essential for developing innovative molecular breeding strategies aimed at enhancing drought tolerance, improving cultivar resilience, and promoting agricultural sustainability. In this context, transcriptomic meta-analyses have proven valuable for uncovering global regulatory trends, gene co-expression networks and conserved biological responses across diverse conditions. As part of this study, 1107 public transcriptomic datasets from Illumina (631 runs) and ABI SOLID (476 runs) platforms were searched, reclassified and reanalyzed in the latest T2T genome assembly, in order to construct condition, cultivar and tissue-specific gene expression atlases associated with drought stress in grapevine. To facilitate exploration of this data, a web-based application, the Hydric Stress Atlas App (https://plantaeviz.tomsbiolab.com/vitviz/hydric_atlas/), was developed, as part of the Vitis module within the PlantaeViz platform. Together with this tool, we generated a whole-genome co-expression network using the same datasets (https://plantaeviz.tomsbiolab.com/vitviz/networks/non_agg_gcns/T2T/hydric_stress_TI/). This water stress condition-dependent GCN allows to explore and visualize gene co-expression relationships related to stress and identify network hubs holding novel drought stress regulators. We manually curated experimental metadata, and enabled the classification of transcriptomic data by cultivar, tissue, and drought tolerance. Finally, candidate genes associated with drought tolerance were identified via network topology analysis. These genes can be further used as molecular markers, or characterized via gene editing or cisgenesis, providing insights into their molecular roles in drought tolerance. This resource contributes to a deeper understanding of grapevine drought responses, offering a pathway for sustainable viticulture and innovative biotechnological solutions to address climate-related challenges.