How to integrate wet lab and bioinformatics procedures for wine DNA admixture analysis and compositional profiling: Case studies and perspectives

2019 
The varietal authentication of wines is fundamental for assessing wine quality, and it is part of its compositional profiling. The availability of historical, cultural and chemical composition information is extremely important for quality evaluation. DNA-based techniques are a powerful tool for proving the varietal composition of a wine. SSR-amplification of genomic residual Vitis vinifera DNA, namely Wine DNA Fingerprinting (WDF) is able to produce strong, analytical evidence concerning the monovarietal nature of a wine, and for blended wines by generating the probability of the presence/absence of a certain variety, all in association with a dedicated bioinformatics elaboration of genotypes associated with possible varietal candidates. Together with WDF we could exploit Bioinformatics techniques, due to the number of grape genomes grown. In this paper, the use of WDF and the development of a bioinformatics tool for allelic data validation, retrieved from the amplification of 7 to 10 SSRs markers in the Vitis vinifera genome, are reported. The wines were chosen based on increasing complexity; from monovarietal, experimental ones, to commercial monovarietals, to blended commercial wines. The results demonstrate that WDF, after calculation of different distance matrices and Neighbor-Joining input data, followed by Principal Component Analysis (PCA) can effectively describe the varietal nature of wines. In the unknown blended wines the WDF profiles were compared to possible varietal candidates (Merlot, Pinot Noir, Cabernet Sauvignon and Zinfandel), and the output graphs show the most probable varieties used in the blend as closeness to the tested wine. This pioneering work should be meant as to favor in perspective the multidisciplinary building-up of on-line databanks and bioinformatics toolkits on wine. The paper concludes with a discussion on an integrated decision support system based on bioinformatics, chemistry and cultural data to assess wine quality.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    67
    References
    7
    Citations
    NaN
    KQI
    []