水稻组学尺度多层次生物网络的构建与工具开发
发布时间：2018-08-11 19:35
【摘要】：植物基因型与表型间复杂的相互关系涉及到细胞内多种组分间的时空调控和代谢产物在不同细胞器或组织中的分布,一直是研究人员关注的热点和难点。传统的研究方法有数量性状基因定位(QTL)和全基因组关联分析(GWAS)。然而,QTL和GWAS没有考虑到分子间的调控关系,不能很好地解释性状与基因间相互作用关系的分子机制。整合多种组分间的调控关系包括代谢调控网络,蛋白质互作网络,基因调控网络等,构建多层次调控网络,探索定量研究复杂生物网络的新途径,能够为更好的理解和研究植物基因型和表现型之间的相互关系提供一种可能。本项目以水稻为研究对象,首先,从水稻基因组注释信息出发,拟利用一个半自动化的流程对现有生物学公共数据库的信息进行整合,完成水稻基因组尺度的代谢网络进行初步构建。我们开发了一种新的基于内共生学说的代谢网络空缺填补的方法(DEF),用于高精度的代谢网络空缺填补。然后,通过系统生物学的方法和实验手段对网络进行精细的修正和评估,包括化合物胞内价态的计算,反应方程式的配平,反应可逆性的预测,空缺的查找及填补。试图构建出第一个目前数据水平上最为完整的高质量的水稻基因组尺度的代谢网络。在此基础上,整合蛋白互作网络、转录调控网络的实验验证数据与预测数据,完成水稻多层次调控网络的初步构建。为了将构建好的基因组尺度多层次调控网络注释到亚细胞器中,我们还开发了一种新的高精度的用于植物蛋白质亚细胞定位预测的整合算法(PSI)。基于PSI的预测结果,我们将水稻组学尺度多层次生物调控网络注释到10个亚细胞器中。最后,完成水稻多层次基因调控网络数据库(RiceNetDB)及多层次生物调控网络3D展示工具的开发,期望本研究能够为水稻生物分子间调控机制的研究提供参考,有助于水稻基因型与表现型间关系的研究。
[Abstract]:The complex relationship between plant genotypes and phenotypes involves the temporal and spatial regulation of various components in cells and the distribution of metabolites in different organelles or tissues. Traditional research methods include quantitative trait gene mapping (QTL) and genome-wide association analysis (GWAS). However, QTLs and GWAS did not take into account the intermolecular regulatory relationship and could not explain the molecular mechanism of the interaction between traits and genes. Integrating the regulation and control relationships among various components, including metabolic regulation network, protein interaction network, gene regulation network and so on, to construct a multi-level regulatory network, and to explore new ways to quantitatively study complex biological networks. It provides a possibility to better understand and study the relationship between genotypes and phenotypes of plants. This project takes rice as the research object. First of all, from the rice genome annotation information, we plan to integrate the information of the existing public biological database by a semi-automatic process. The metabolic network of rice genome was constructed. A new metabolic network vacancy filling method based on INTERGROWTH theory (DEF),) is developed. Then, the network is revised and evaluated by the methods of system biology and experiment, including the calculation of the intracellular valence state of compounds, the balance of the reaction equation, the prediction of the reversibility of the reaction, and the searching and filling of the vacancy. This paper attempts to construct the first high quality genome scale metabolic network of rice at present data level. On this basis, the integrated protein interaction network, transcriptional regulatory network experimental verification data and prediction data, completed the preliminary construction of the multi-level regulatory network of rice. In order to annotate the constructed genome scale multilevel regulatory network into suborganelles, we have also developed a new integration algorithm, (PSI)., which can be used to predict the subcellular localization of plant proteins. Based on the prediction results of PSI, we annotated the multi-level biological regulatory network of rice genome into 10 suborganelles. Finally, the development of (RiceNetDB) and 3D display tool of multi-level biological regulation network is completed. It is expected that this study can provide a reference for the study of the mechanism of rice biomolecular regulation. It is helpful to study the relationship between genotypes and phenotypes of rice.
【学位授予单位】：浙江大学
【学位级别】：博士
【学位授予年份】：2016
【分类号】：Q943.2;Q811.4
本文编号：2178034
[Abstract]:The complex relationship between plant genotypes and phenotypes involves the temporal and spatial regulation of various components in cells and the distribution of metabolites in different organelles or tissues. Traditional research methods include quantitative trait gene mapping (QTL) and genome-wide association analysis (GWAS). However, QTLs and GWAS did not take into account the intermolecular regulatory relationship and could not explain the molecular mechanism of the interaction between traits and genes. Integrating the regulation and control relationships among various components, including metabolic regulation network, protein interaction network, gene regulation network and so on, to construct a multi-level regulatory network, and to explore new ways to quantitatively study complex biological networks. It provides a possibility to better understand and study the relationship between genotypes and phenotypes of plants. This project takes rice as the research object. First of all, from the rice genome annotation information, we plan to integrate the information of the existing public biological database by a semi-automatic process. The metabolic network of rice genome was constructed. A new metabolic network vacancy filling method based on INTERGROWTH theory (DEF),) is developed. Then, the network is revised and evaluated by the methods of system biology and experiment, including the calculation of the intracellular valence state of compounds, the balance of the reaction equation, the prediction of the reversibility of the reaction, and the searching and filling of the vacancy. This paper attempts to construct the first high quality genome scale metabolic network of rice at present data level. On this basis, the integrated protein interaction network, transcriptional regulatory network experimental verification data and prediction data, completed the preliminary construction of the multi-level regulatory network of rice. In order to annotate the constructed genome scale multilevel regulatory network into suborganelles, we have also developed a new integration algorithm, (PSI)., which can be used to predict the subcellular localization of plant proteins. Based on the prediction results of PSI, we annotated the multi-level biological regulatory network of rice genome into 10 suborganelles. Finally, the development of (RiceNetDB) and 3D display tool of multi-level biological regulation network is completed. It is expected that this study can provide a reference for the study of the mechanism of rice biomolecular regulation. It is helpful to study the relationship between genotypes and phenotypes of rice.
【学位授予单位】：浙江大学
【学位级别】：博士
【学位授予年份】：2016
【分类号】：Q943.2;Q811.4
【参考文献】
相关期刊论文 前1条
1 Evangelia I. Petsalaki;Pantelis G. Bagos;Zoi I. Litou;Stavros J. Hamodrakas;;PredSL: A Tool for the N-terminal Sequence-based Prediction of Protein Subcellular Localization[J];Genomics Proteomics & Bioinformatics;2006年01期
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