The analysis of grapevine berries at the transcriptomic, proteomic and metabolomic levels can provide great insight into the molecular events underlying berry development and post-harvest drying (withering). However, the large and very different datasets produced by such investigations are difficult to integrate. Here we report the identification of putative stage-specific biomarkers for berry development and withering and 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 O2PLS 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 sub-datasets 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 sub-datasets of variables. The multivariate O2PLS technique was then used to integrate the sub-datasets, 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.
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