Discovering Causal Relationships in Grapevine Expression Data to Expand Gene Networks. A Case Study: Four Networks Related to Climate Change

Abstract

In recent years the scientific community has been heavily engaged in studying the grapevine response to climate change. Final goal is the identification of key genetic traits to be used in grapevine breeding and the setting of agronomic practices to improve climatic resilience. The increasing availability of transcriptomic studies, describing gene expression in many tissues and developmental, or treatment conditions, have allowed the implementation of gene expression compendia, which enclose a huge amount of information. The mining of transcriptomic data represents an effective approach to expand a known local gene network (LGN) by finding new related genes. We recently published a pipeline based on the iterative application of the PC-algorithm, named NES2RA, to expand gene networks in Escherichia coli and Arabidopsis thaliana. Here, we propose the application of this method to the grapevine transcriptomic compendium Vespucci, in order to expand four LGNs related to the grapevine response to climate change. Two networks are related to the secondary metabolic pathways for anthocyanin and stilbenoid synthesis, involved in the response to solar radiation, whereas the other two are signaling networks, related to the hormones abscisic acid and ethylene, possibly involved in the regulation of cell water balance and cuticle transpiration. The expansion networks produced by NES2RA algorithm have been evaluated by comparison with experimental data and biological knowledge on the identified genes showing fairly good consistency of the results. In addition, the algorithm was effective in retaining only the most significant interactions among the genes providing a useful framework for experimental validation. The application of the NES2RA to Vitis vinifera expression data by means of the BOINC-based implementation is available upon request (valter.cavecchia@cnr.it).

The Rpv3-3 haplotype and stilbenoid induction mediate downy mildew resistance in a grapevine interspecific population

“…The time dependent regulation of different inducible stilbenes upon abiotic and biotic stresses was reported to be at least transcriptional (e.g., Vannozzi et al, 2012;Höll et al, 2013;Wong et al, 2016) and coordinated by the action of both MYB and WRKY transcription factors (Malacarne et al, 2018;Vannozzi et al, 2018;Jeandet et al, 2019;Jiang et al, 2019). In the present work additional MYB genes were associated with stilbenoid formation; in particular, the known R2R3-MYB C2 repressors of phenylpropanoid levels (Cavallini et al, 2015) were located along the regions on LG4 and LG17 controlling some monomeric and dimeric stilbenoids, respectively.…”

The Rpv3-3 Haplotype and Stilbenoid Induction Mediate Downy Mildew Resistance in a Grapevine Interspecific Population

“…The time dependent regulation of different inducible stilbenes upon abiotic and biotic stresses was reported to be at least transcriptional (e.g., Vannozzi et al, 2012 ; Höll et al, 2013 ; Wong et al, 2016 ) and coordinated by the action of both MYB and WRKY transcription factors (Malacarne et al, 2018 ; Vannozzi et al, 2018 ; Jeandet et al, 2019 ; Jiang et al, 2019 ). In the present work additional MYB genes were associated with stilbenoid formation; in particular, the known R2R3-MYB C2 repressors of phenylpropanoid levels (Cavallini et al, 2015 ) were located along the regions on LG4 and LG17 controlling some monomeric and dimeric stilbenoids, respectively.…”

A Computing System for Discovering Causal Relationships Among Human Genes to Improve Drug Repositioning

“…The TN-GRID platform, which runs on a virtual server in the Data Center of the University of Trento, hosted the NES 2 RA algorithm [10], [11] which has been already used to calculate gene network expansions in plants and microor- ganisms, such as A. thaliana, E.coli and V. vinifera [10], [13]. NES 2 RA [11] outperformed the state of the art algorithm ARACNE [14] in the task of network expansion.…”