Dynamic Network Analysis of the 4D Nucleome
Dynamic Network Analysis of the 4D Nucleome
复制标题
4D 核组的动态网络分析
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
I. Rajapakse
中科院分区：
文献类型：
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作者：
Sijia Liu;Pin;A. Hero;I. Rajapakse
动机对于许多生物系统来说，必须同时捕获功能，结构和动力学，以形成对潜在现象的全面理解。3D基因组空间结构和转录活性之间的动态相互作用产生了基因组签名，我们称之为细胞核的四维组织，或4D核组（4DN）。4DN的研究需要评估全基因组结构和基因表达，以及开发新的数据分析方法。结果我们提出了一种动态多层网络方法来研究4D Nucleome中形式和功能的协同进化。我们将动态生物系统建模为具有节点动态的时间网络，其中网络拓扑结构由染色体构象（Hi-C）捕获，节点的功能由RNA测序（RNA-seq）测量。基于网络的方法，如冯诺依曼图熵，网络中心性，和多层网络理论，揭示了动态基因组的普遍模式。我们的模型集成了基因组结构和基因表达的知识，沿着与时间的演变，并导致在系统范围内的基因组行为的描述。我们通过一个关于MYOD 1介导的人成纤维细胞重编程为肌源性谱系的真实的生物数据集来说明我们的模型的益处。我们表明，我们的方法能够更好地预测形式-功能关系，并加深我们对细胞重编程期间细胞动力学如何变化的理解。可用性：该软件可根据要求提供。联系indikar@umich.edu补充信息见补充材料。
Motivation For many biological systems, it is essential to capture simultaneously the function, structure, and dynamics in order to form a comprehensive understanding of underlying phenomena. The dynamical interaction between 3D genome spatial structure and transcriptional activity creates a genomic signature that we refer to as the four-dimensional organization of the nucleus, or 4D Nucleome (4DN). The study of 4DN requires assessment of genome-wide structure and gene expression as well as development of new approaches for data analysis. Results We propose a dynamic multilayer network approach to study the co-evolution of form and function in the 4D Nucleome. We model the dynamic biological system as a temporal network with node dynamics, where the network topology is captured by chromosome conformation (Hi-C), and the function of a node is measured by RNA sequencing (RNA-seq). Network-based approaches such as von Neumann graph entropy, network centrality, and multilayer network theory are applied to reveal universal patterns of the dynamic genome. Our model integrates knowledge of genome structure and gene expression along with temporal evolution and leads to a description of genome behavior on a system wide level. We illustrate the benefits of our model via a real biological dataset on MYOD1-mediated reprogramming of human fibroblasts into the myogenic lineage. We show that our methods enable better predictions on form-function relationships and refine our understanding on how cell dynamics change during cellular reprogramming. Availability: The software is available upon request. Contact indikar@umich.edu Supplementary information See Supplementary Material.
影响因子：
2.4
作者：
Battiston, Federico;Nicosia, Vincenzo;Latora, Vito
通讯作者：
Latora, Vito