Modeling proteomics data for investigating plant response to environmental stress

在过去的十年中，我们在检测基因及其产物（蛋白质）的表达以及基因表达差异如何与生物体特征（例如植物生长）的差异相关联的能力方面有了很大的提高。目前的技术使我们能够在某一时刻观察到基因表达和蛋白质生产的快照。然后，从这样一个快照中获得的信息可以用来创建一个粗略的表达途径——将表达基因的功能与生物体的特征联系起来。尽管这些粗略的途径表明哪些基因对某一特定特征很重要，但它并不能完全解释系统功能——每个基因的表达是如何相互关联的。这对于理解基因和蛋白质之间的相互作用如何调节整个系统的功能是很重要的。然后，在多个时间点拍摄的快照的帮助下，路径成为表达网络中的组成部分。为了创建表达网络，现在需要在基因表达数据建模的创新方法方面取得重大进展。虽然数据建模和基因表达分析是互补的技术，但它们以前没有被结合起来，而且缺乏具有这两种技能的研究人员。本项目旨在填补这些知识和技能方面的空白。在组学技术方面拥有丰富经验的首席研究员将接受最先进的生物系统分析建模方法方面的培训。该培训将使Co-I能够开发多变量和结构方程建模方法，以研究基因和蛋白质表达水平的系统功能。最后，这些新方法将用于分析环境变化与基因-表型网络变化之间的关系，使用Co-I与纳弗顿生态农业集团（NEFG）共同制作的大型数据库。该项目预计将产生有利于更广泛的研究社区的基因表达数据分析的创新方法，并加强英国在环境信息学方面的领导地位。此外，它将促进知识交流，并进一步推动多学科研究界之间的长期合作框架。

Over the last decade, there has been large scale improvement in our ability to detect the expression of genes and their products (proteins) and how differences in gene expression are associated with differences in an organisms' characteristics (e.g. plant growth). Current technology allows us to observe a snapshot of gene expression and protein production at a moment in time. The information from such a snapshot can then be used to create a crude pathway of expression - linking together the functions of the expressed genes to the characteristics of the organism. Although these crude pathways indicate which genes are important for a particular characteristic, it doesn't fully explain system function - how the expression of each gene is related to each other. This is important for understanding how interactions between genes and proteins regulate the function of the whole system. Pathways then become components within a network of expression, aided by snapshots that are taken at multiple time-points. To create networks of expression, a major development in innovative approaches to modelling gene expression data is now needed. Although data modelling and gene expression analysis are complementary techniques, they have not previously been combined and there is a lack of researchers with both skill sets. This project seeks to fill these gaps in knowledge and skills. The Co-I, who has extensive experience in 'Omics technologies) will be trained in state-of-the art modelling approaches for the analysis of biological systems. This training will then enable the Co-I to develop multivariate and structural equation modelling approaches to investigate system function at the level of gene and protein expression. Finally, these novel approaches will be used to analyze the relationship between environmental change and change in gene - phenotype networks using a large database with which the Co-I has produced with Nafferton Ecological Farming Group (NEFG).This project is expected to generate innovative approaches to gene expression data analysis of benefit to the wider researcher community, and enhance UK leadership in environmental informatics. Furthermore, it will promote the knowledge exchange and further long-term collaborative frameworks between multi-disciplinary research communities.