Identification of Putative Stage-Specific Grapevine Berry Biomarkers and Omics Data Integration into Networks      

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.

The Grapevine Expression Atlas Reveals a Deep Transcriptome Shift Driving the Entire Plant into a Maturation Program

“…Microarray analysis revealed that samples with unique characteristics (such as pollen grains and leaves undergoing senescence) were clearly distinguishable at the transcriptomic level from all other samples, which grouped more according to their maturity and developmental stage than their organ or tissue identity, as also supported by the in silico analysis of RNA-seq data. Previous studies have focused mostly on berry development and ripening (Zamboni et al, 2010;Zenoni et al, 2010;Tornielli et al, 2012), but our transcriptomic atlas presents a comprehensive grapevine transcriptome.…”

“…previously been identified as a positive biomarker of withering in Corvina berries (Zamboni et al, 2010). Several transcripts encoding stress response, ethylene response, and protein recycling functions were strongly represented in mature/woody samples, along with a population of (predominantly zinc finger) transcription factors, suggesting that significant transcriptional reprogramming is required for the transition to the mature phase.…”

“…Topics 3 and 5 were characterized by the strong expression of genes related to carbohydrate metabolism (particularly starch and sugar), but remarkably no genes representing secondary metabolism were included. Topics 3 and 5 also included stress response genes relevant to dehydration and/or pathogens, which characterize berry ripening and withering (Davies and Robinson, 2000;Zamboni et al, 2010). Topic 5 also included the high-level expression of polyubiquitin, protease, and proteasome subunit genes, representing the transcriptional control of protein degradation and recycling during withering, where dehydration and sugar concentration lead to significant physiological changes.…”

“…Putative molecular biomarkers (i.e., transcripts whose presence or absence defines the samples in a given class) were identified by applying four distinct two-class O2PLS-DA models, using in each case the observations from one class as a reference and grouping the other three observations in one unique class (Zamboni et al, 2010). An S-plot (Wiklund et al, 2008) was then used to select putative biomarkers within the first (positive biomarkers) and last (negative biomarkers) percentiles (Figures 4B and 4C;see Supplemental Data Set 3 online).…”

Alteration of the Interconversion of Pyruvate and Malate in the Plastid or Cytosol of Ripening Tomato Fruit Invokes Diverse Consequences on Sugar But Similar Effects on Cellular Organic Acid, Metabolism, and Transitory Starch Accumulation

“…Insights into the genetic mechanisms that mediate fruit ripening-related processes, such as cell wall metabolism, pigment synthesis, and sugar metabolism, have resulted from studies that collectively span a wide range of plant species and indicate that they are broadly conserved (Seymour et al, 2008;Moing et al, 2011;Zhang et al, 2011). However, certain speciesspecific differences exist in the dynamics of other metabolite pools across ripening, with, for example, grape (Vitis vinifera), strawberry (Fragaria 3 ananassa), prune (Prunus domestica), and pepper (Capsicum annuum) displaying slightly different metabolic programs from tomato (Solanum lycopersicum; Zamboni et al, 2010;Lombardo et al, 2011;Osorio et al, 2011Osorio et al, , 2012Zhang et al, 2011). This fact notwithstanding, tomato has become the primary experimental model in which to study the development and ripening of fleshy fruits (Giovannoni, 2004;Fernandez et al, 2009).…”