Dissecting the Human MicroRNA Regulatory Networks via Phylogenetic Decomposition
Date Issued
2014
Date
2014
Author(s)
Ho, Andy
Abstract
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.
Subjects
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
Type
thesis
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