Modeling proteomics data for investigating plant response to environmental stress

模拟蛋白质组学数据以研究植物对环境胁迫的反应

• 批准号: NE/K011138/1
• 负责人: Steven Rushton
• 金额: $ 4.3万
• 依托单位: Newcastle University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2013
• 资助国家: 英国
• 起止时间: 2013 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FK011138%2F1
• 关键词: Modeling; proteomics; data; investigating; plant

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.

在过去的十年里，我们检测基因及其产物（蛋白质）表达的能力以及基因表达差异如何与生物体特征（例如植物生长）的差异相关的能力有了大规模的提高。目前的技术使我们能够及时观察基因表达和蛋白质生产的快照。从这样的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在一起。虽然这些粗略的途径表明哪些基因对特定特征很重要，但它并不能完全解释系统功能-每个基因的表达如何相互关联。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非常重要。在多个时间点拍摄的快照的帮助下，路径然后成为表达网络中的组件。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，但它们以前没有结合起来，而且缺乏同时具备这两种技能的研究人员。该项目旨在填补知识和技能方面的这些空白。首席信息官在“组学技术”方面拥有丰富的经验，他将接受最先进的生物系统分析建模方法的培训。然后，这项培训将使Co-I能够开发多元和结构方程建模方法，以在基因和蛋白质表达水平上研究系统功能。最后，这些新的方法将被用来分析环境变化和变化之间的关系，在基因-表型网络使用一个大型数据库，与该Co-I已经产生了与纳弗顿生态农业集团（NEFG）。该项目预计将产生创新的方法，基因表达数据分析，有利于更广泛的研究社区，并提高英国在环境信息学的领导地位。此外，它将促进多学科研究界之间的知识交流和进一步的长期合作框架。

项目成果

Modelling pathways to Rubisco degradation: a structural equation network modelling approach.

• DOI: 10.1371/journal.pone.0087597
• 发表时间: 2014
• 期刊: PloS one
• 影响因子: 3.7
• 作者: Tétard-Jones C;Gatehouse AM;Cooper J;Leifert C;Rushton S
• 通讯作者: Rushton S