指導教授：阮雪芬臺灣大學：生醫電子與資訊學研究所何亮融Ho, AndyAndyHo2014-11-262018-07-052014-11-262018-07-052014http://ntur.lib.ntu.edu.tw//handle/246246/261862為有效描述分子生物系統中巨量的相互作用資訊，網路模型是普遍被使用的抽象化工具之一。常見的蛋白質間的交互作用和微型核醣核酸與基因間的調控關係均可透過網路模型的建立，並藉由數學上的拓樸概念與圖形理論進行分析，讓我們能以更宏觀與系統的角度理解生物系統的運作。然而，目前典型的網路分析受限於拓樸空間上的二維結構，致無法加入時間與空間層面的觀察與分析。本研究試圖提出新的分析框架，將固有的方法進行擴展，以應用於微型核醣核酸調控網路的整合分析。本研究藉由分析人類基因體與其他物種的同源基因，將演化年齡參數結合於每個蛋白質與微型核醣核酸，並以此引入時序維度對網路模型進行分解。除了整體網路分析，本研究也挑出粒線體相關調控網路作為小尺度個案研究。在微型核醣核酸調控網路的分析中，我們發現古老的基因會被較多種類的微型核醣核酸調控，而年輕的微型核醣核酸則能調控較多的基因。此外，由調控偏好可以發現微型核醣核酸會傾向調控年齡相近的基因。我們也發現年輕微型核醣核酸更喜愛調控蛋白質網路中樞紐位置的基因。而在粒線體相關的網路分析中，微型核醣核酸的調控偏好與整體網路中偏好調控年齡相近基因的結果大致相同。由功能性分析則可以發現人類粒線體功能大多由最古老的基因參與，僅有細胞凋亡相關功能會由較年輕的基因扮演重要角色。結合上述，不同年齡的基因與微型核醣核酸在網路中的確會扮演不同的角色，而利用此年齡分類策略，確實能增進對網路拓樸特性的了解。Owing to the clear fact that most biological characteristics arise from complex interactions between numerous constituents, more and more researche works apply the network model to generate the information of these complicated relationships such as protein interactions and miRNA regulations. Providing a framework for better understanding the cell machinery, network analysis can successfully reveal an insight to the functional organization in a system biology point of view. However, limited to its two-dimensional structure, typical network analysis may results in the lack of observation from temporal level. In this study, we adopted a phylogenetic strategy to divide human genes and miRNAs into age groups and thus decompose the miRNA regulatory network from an evolutionary perspective to answer if miRNAs of different ages would play different roles in the networks. We also extracted the mitochondria-related networks as a case study. For human miRNA regulatory network, we first found that ancient genes were regulated by more types of miRNAs. In contrast, young miRNAs could target more types of genes. Second, the regulatory preference between miRNA and genes indicated that miRNAs tended to regulate genes of similar age. The analysis also showed that genes targeted by young miRNAs were more likely to be hub in PPI networks. For mitochondria-related network, the regulatory preference pattern was roughly the same as the pattern in global miRNA regulatory network. Most of the functions in human mitochondria were contributed by proteins in G1 (eukaryote-conserved) and G2 (metazoan-conserved). Only the functions associated with cell death were occupied by proteins in G3 (vertebrate-conserved). Based on all the findings, it is clear that the proposed phylogenetic strategy, which utilized an additional age dimension for decomposition, had successfully enhanced the understanding of the topological organization of networks.口試委員會審定書 ……………………………………………………………………i 致謝 …………………………………………………………………………………….ii 摘要 ……………………………………………………………………………………iii ABSTRACT ………………………………………………………………………….iv CONTENTS ……………………………………………………………………………vi LIST OF FIGURES …………………………………………………………………….ix LIST OF TABLES ……………………………………………………………………xi Chapter 1 Introduction ……………………………………………………………1 1.1 Network models ……………………………………………………………...1 1.2 Protein-protein Interaction (PPI) network …………………………………... 2 1.3 MicroRNA regulatory network ………………………………………………4 1.4 Mitochondria …………………………………………………………………5 1.5 Dissecting the human protein-protein interaction network via phylogenetic decomposition ………………………………………………………………...6 1.5.1 Overview of Phylo-decomposition of human PPI network …………..6 1.5.2 Age-dependent core-periphery structure and network centralities …...6 1.5.3 Ubiquitous yet combinatorial scale-free and hierarchy network properties ……………………………………………………………..8 1.5.4 Age homophily in PPI network ………………………………………9 1.5.5 Age-dependent functional landscape ………………………………..10 1.6 Specific aims ………………………………………………………………..11 Chapter 2 Materials and Methods ………………………………………………13 2.1 Phylogenetic decomposition of networks …………………………………...13 2.1.1 Phylogenetic decomposition of human genome …………………….13 2.1.2 Construction of PPI network ………………………………………..14 2.1.3 Phylogenetic decomposition of human miRNAs …………………...16 2.1.4 Construction of bipartite miRNA regulatory network ………………16 2.2 Analysis of networks ………………………………………………………17 2.2.1 Interaction density and standard score ……………………………...17 2.2.2 Gene essentiality ……………………………………………………18 2.2.3 Normalization for distribution of network features across groups ….19 2.2.4 Generation of housekeeping genes ………………………………….19 2.2.5 Regulatory density and standard score ……………………………...20 2.2.6 Standard score of features for miRNA target genes ………………...21 2.2.7 Extraction of mitochondria-related networks ……………………..21 2.2.8 Age profile of mitochondrial pathway ……………………………...22 Chapter 3 Results and Discussion ……….……….……….……….…………….23 3.1 miRNA regulatory network ………..………..………..………..……………23 3.1.1 Age-dependent spectrum of miRNA regulatory network …………..23 3.1.2 Age homophily in miRNA regulatory network ………..……………24 3.1.3 Correlation between miRNA and their targets in PPI network ……..25 3.2 Mitochondria-related networks …..………..………..………..……………..26 3.2.1 Age homophily in mitochondria-related miRNA regulatory network ……………………………………………………………...26 3.2.2 Age-dependent functional enrichment in mitochondria …………….26 Chapter 4 Conclusions …………………………………………………………...28 Figures ………………………………………………………………………………...29 Tables ………………………………………………………………………………….44 REFERENCES ……………………………………………………………………….454467379 bytesapplication/pdf論文公開時間：2015/08/16論文使用權限：同意有償授權(權利金給回饋學校)蛋白質交互作用網路微型核醣核酸微型核醣核酸調控網路基因親緣分解粒線體thesishttp://ntur.lib.ntu.edu.tw/bitstream/246246/261862/1/ntu-103-R01945020-1.pdf