近年来,科学界一直致力于研究葡萄藤对气候变化的响应。最终目标是确定葡萄育种中使用的关键遗传性状,并制定农艺措施以提高气候适应力。转录组学研究的日益普及,描述许多组织和发育中的基因表达,或治疗条件,允许基因表达简编的实施,其中包含了大量的信息。转录组数据的挖掘代表了通过寻找新的相关基因来扩展已知的局部基因网络(LGN)的有效方法。我们最近发布了一个基于PC算法迭代应用的管道,NES2RA,扩大大肠杆菌和拟南芥的基因网络。这里,我们建议将这种方法应用于葡萄转录组学纲要Vespucci,以扩大与葡萄藤对气候变化响应相关的四个LGN。两个网络与花色苷和二苯乙烯类合成的次级代谢途径有关,参与对太阳辐射的反应,而另外两个是信令网络,与激素脱落酸和乙烯有关,可能参与细胞水分平衡和角质层蒸腾的调节。通过与实验数据和鉴定基因的生物学知识进行比较,对NES2RA算法产生的扩展网络进行了评估,结果具有相当好的一致性。此外,该算法仅有效保留了基因之间最重要的相互作用,为实验验证提供了有用的框架。根据要求,可以通过基于BOINC的实现将NES2RA应用于葡萄表达数据(valter。cavecchia@cnr。it).
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).