Evidence map›Paper›PMID 30753217›Full record

ArticlePloS one2019

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

Rita Vignani, Pietro Liò, Monica Scali

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Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Rita VignaniDepartment of Life Science, University of Siena, Siena, Italy.ORCID 0000-0002-7024-5965
Pietro LiòComputer Laboratory, University of Cambridge, Cambridge, United Kingdom.
Monica ScaliDepartment of Life Science, University of Siena, Siena, Italy.ORCID 0000-0002-8551-8823

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Microsatellite RepeatsComputational BiologyDNA FingerprintingDNA, PlantGenetic MarkersPhylogenyPrincipal Component AnalysisVitisWineDNA, PlantGenetic Markers

Identifiers

PMID30753217
PMCPMC6376920

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.