Identification of important genomic regions controlling resistance to biotic and abiotic stresses in Vitis sp. through QTL meta-analysis

In order to study the impact of climate change on Bordeaux grape varieties and to assess the behavior of candidate grape varieties potentially better adapted to the new climatic conditions, an experimental vineyard composed of 52 grape varieties was planted in 2009 at the INRAE Bordeaux Aquitaine center[1]. Among the many parameters studied since 2012, berry weight for each variety was measured weekly from mid-veraison to maturity, with four independent replicates. The kinetics obtained allowed to study berry growth, a key parameter in grape composition and yield.

The appearance of the Phylloxera pest in the 19th century in Europe caused dramatical damages in grapevine diversity. To mitigate these losses, grapevine growers resorted to using crosses of different Vitis species, such as 110 Richter (110R) (V. berlandieri x V. rupestris), which has been invaluable for studying adaptations to stress responses in vineyards. Recently, a high quality chromosome scale assembly of 110R was released, but the available gene models were predicted without using as evidence transcriptional sequences obtained from roots, that are crucial organs in rootstock, and they may express certain genes exclusively. Therefore, we employed RNA sequencing reads of 110R roots under different stress conditions to predict new gene models in each haplotype of 110R under different stresses.

Secondary (or specialised) metabolites such as terpenes and phenolic compounds are produced by plants for various roles which include defence against pathogens and herbivores, protection against abiotic stress, and plant signalling. Additionally, these metabolites influence grapevine quality traits such as colour, aroma, taste, and nutritional value. However, the biosynthesis of these metabolites is often complex and controlled by multiple genes which in grapevine are predominantly uncharacterised.

The main objective of the work was to develop a simple, robust and selective analytical tool that allows predicting the authenticity of Tempranillo wines from DOCa Rioja. The techniques of voltammetry and absorbance-transmission and fluorescence excitation emission matrix (A-TEEM) spectroscopy have been applied in combination with machine learning (ML) algorithms to classify red wines from DOCa Rioja according to region (Alavesa, Alta or Oriental) and category (young, crianza or reserva).

The use of barrels is a practice that improves the quality of wines. The porous structure of wood favors the accumulation of microorganisms that can deteriorate the quality of wines so that barrel cleaning and sanitizing treatments are essential. The burning of sulphur discs has been the most common practice in winemaking because ots biocide effect. Nevertheless, its effectiveness is still insufficient and it is harmful for human health.