Abstract
The analysis of grapevine (Vitis vinifera) berries at the transcriptomic, proteomic, and metabolomic levels can provide great insight into the molecular events underlying berry development and postharvest drying (withering). However, the large and very different data sets produced by such investigations are difficult to integrate. Here, we report the identification of putative stage-specific biomarkers for berry development and withering and, to our knowledge, the first integrated systems-level study of these processes. Transcriptomic, proteomic, and metabolomic data were integrated using two different strategies, one hypothesis free and the other hypothesis driven. A multistep hypothesis-free approach was applied to data from four developmental stages and three withering intervals, with integration achieved using a hierarchical clustering strategy based on the multivariate bidirectional orthogonal projections to latent structures technique. This identified stage-specific functional networks of linked transcripts, proteins, and metabolites, providing important insights into the key molecular processes that determine the quality characteristics of wine. The hypothesis-driven approach was used to integrate data from three withering intervals, starting with subdata sets of transcripts, proteins, and metabolites. We identified transcripts and proteins that were modulated during withering as well as specific classes of metabolites that accumulated at the same time and used these to select subdata sets of variables. The multivariate bidirectional orthogonal projections to latent structures technique was then used to integrate the subdata sets, identifying variables representing selected molecular processes that take place specifically during berry withering. The impact of this holistic approach on our knowledge of grapevine berry development and withering is discussed.
Highlights
Grapevine is a commercially important fruit crop cultivated for the production of table grapes, juice, wine, distilled liquors and dry raisins
Class-specific variables and putative increasing and decreasing biomarkers were identified for each dataset using the O2PLS-discriminant analysis (DA) approach
Our results revealed that the multivariate O2PLS technique, which has previously been applied in a limited context known as OPLS to analyze the structure of metabolomic and metabonomic datasets and to identify putative biomarkers in such studies, can be a useful approach for the analysis of transcriptomic and proteomic datasets, which have distinct characteristics
Summary
Grapevine is a commercially important fruit crop cultivated for the production of table grapes, juice, wine, distilled liquors and dry raisins. The economic importance of grapevine has encouraged many researchers to study the physiological and molecular basis of berry development, those processes that affect wine quality (Conde et al, 2007). The availability of high-throughput analysis methods and a highquality draft of the grapevine genome sequence (Jallion et al, 2007) has led to the characterization of berry development at the levels of the transcriptome (Terrier et al, 2005; Waters et al, 2005; Deluc et al, 2007; Pilati et al, 2007), proteome (Giribaldi et al, 2007; Negri et al, 2008; Zhang et al, 2008; Grimplet et al, 2009) and metabolome (Conde et al, 2007). Withering has been investigated at the level of the transcriptome (Zamboni et al, 2008; Rizzini et al, 2009) and through the analysis of certain metabolites (Bellincontro et al, 2004; Bellincontro et al, 2006; Costantini et al, 2006), but no proteomic analysis of withering has previously been reported
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