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Identification of Risk Pathways and Functional Modules for Coronary Artery Disease Based on Genome-wide SNP Data

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Genomics, Proteomics & Bioinformatics 2016年第6期14卷 349-356页

作者： Xiang Zhao Yi-Zhao Luan Xiaoyu Zuo Ye-Da Chen Jiheng Qin Lv Jin Yiqing Tan Meihua Lin Naizun Zhang Yan Liang Shao-Qi Rao Institute for Medical Systems Biology and Department of Medical Statistics and Epidemiology School of Public HealthGuangdong Medical CollegeDongguan 523808China School of Life Sciences Sun Yat-sen UniversityGuangzhou 510080China Department of Medical Statistics and Epidemiology School of Public HealthSun Yat-sen UniversityGuangzhou 510080China Maoming People's Hospital Maoming 525000China

Coronary artery disease （CAD） is a complex human disease, involving multiple genes and their nonlinear interactions, which often act in a modular fashion. Genome-wide single nucleotide polymorphism （SNP） profiling provides an effective technique to unravel these underlying genetic interplays or their functional involvements for CAD. This study aimed to identify the susceptible pathways and modules for CAD based on SNP omics. First, the Wellcome Trust Case Control Consortium （WTCCC） SNP datasets of CAD and control samples were used to assess the joint effect of multiple genetic variants at the pathway level, using logistic kernel machine regression model. Then, an expanded genetic network was constructed by integrating statistical gene-gene interactions involved in these susceptible pathways with their protein protein interaction （PPI） knowledge. Finally, risk functional modules were identified by decomposition of the network. Of 276 KEGG pathways analyzed, 6 pathways were found to have a significant effect on CAD. Other than glycerolipid metabolism, glycosaminoglycan biosynthesis, and cardiac muscle contraction pathways, three pathways related to other diseases were also revealed, including Alzheimer＇s disease, non-alcoholic fatty liver disease, and Huntington＇s disease. A genetic epistatic network of 95 genes was further constructed using the abovementioned integrative approach. Of 10 functional modules derived from the network, 6 have been annotated to phospholipase C activity and cell adhesion molecule binding, which also have known functional involvement in Alzheimer＇s disease. These findings indicate an overlap of the underlying molecular mechanisms between CAD and Alzheimer＇s disease, thus providing new insights into the molecular basis for CAD and its molecular relationships with other diseases.

关键词： Coronary artery disease Genome-wide SNP profiling Risk pathway Functional module genetic network

维普期刊数据库

From genes to networks: The genetic control of leaf development

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Journal of Integrative Plant Biology 2021年第7期63卷 1181-1196页

作者： Hongfeng Wang Fanjiang Kong Chuanen Zhou The Key Laboratory of Plant Development and Environmental Adaptation Biology Ministry of EducationSchool of Life SciencesShandong UniversityQingdao 266101China Innovative Center of Molecular genetics and Evolution School of Life SciencesGuangzhou UniversityGuangzhou 510006China

Substantial diversity exists for both the size andshape of the leaf,the main photosynthetic organofflowering plants.The two major forms of leaf aresimple leaves,in which the leaf blade is undivided,and compound leaves,which comprise severalleaflets.Leaves form at the shoot apical meristemfrom a group of undifferentiated cells,whichfirstestablish polarity,then grow and differentiate.Each of these processes is controlled by a com-bination of transcriptional regulators,microRNAsand phytohormones.The present review docu-ments recent advances in our understanding ofhow these various factors modulate the develop-ment of both simple leaves(focusing mainly on themodel plantArabidopsis thaliana)and compoundleaves(focusing mainly on the model legumespeciesMedicago truncatula).

关键词： compound leaves genetic network leaf develop-ment leaf polarity simple leaves

维普期刊数据库

genetic and logic networks with the signal-inhibitor-activator structure are dynamically robust

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Progress in Natural Science:Materials International 2006年第12期16卷 1329-1336页

作者： LI Fangting** and TAN Ning(School of Physics and Centre for Theoretical Biology, Peking University, Beijing 100871, China) School of Physics and Centre for Theoretical Biology Peking University Beijing 100871 China

The proteins, DNA and RNA interaction networks govern various biological functions in living cells, these networks should be dynamically robust in the intracellular and environmental fluctuations. Here, we use Boolean network to study the robust structure of both genetic and logic networks. First, SOS network in bacteria E. coli, which regulates cell survival and repair after DNA damage, is shown to be dynamically robust. Comparing with cell cycle network in budding yeast and flagella network in E. coli, we find the signal-inhibitor-activator (SIA) structure in transcription regulatory networks. Second, under the dynamical rule that inhibition is much stronger than activation, we have searched 3-node non-self-loop logical networks that are dynamically robust, and that if the attractive basin of a final attractor is as large as seven, and the final attractor has only one active node, then the active node acts as inhibitor, and the SIA and signal-inhibitor (SI) structures are fundamental architectures of robust networks. SIA and SI networks with dynamic robustness against environment uncertainties may be selected and maintained over the course of evolution, rather than blind trial-error testing and being an accidental consequence of particular evolutionary history. SIA network can perform a more complex process than SI network, and SIA might be used to design robust artificial genetic network. Our results provide dynamical support for why the inhibitors and SIA/SI structures are frequently employed in cellular regulatory networks.

关键词： genetic network signal-inhibitor-activator (SIA) structure Boolean network model dynamical robust.

Generic properties of random gene regulatory networks

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Frontiers of Electrical and Electronic Engineering in China 2013年第4期8卷 253-260页

作者： Zhiyuan Li Simone Bianco Zhaoyang Zhang Chao Tang Center for Quantitative Biology School of Physics and Peking-Tsinghua Center for Life Sciences Peking University Beijing 100871 China Department of Bioengineering and Therapeutic Sciences University of California San Francisco CA 94158 USA Department of Physics Beijing Normal University Beijing 100875 China

Modeling gene regulatory networks （GRNs） is an important topic in systems biology. Although there has been much work focusing on various specific systems, the generic behavior of GRNs with continuous variables is still elusive. In particular, it is not clear typically how attractors partition among the three types of orbits： steady state, periodic and chaotic, and how the dynamical properties change with network＇s topological characteristics. In this work, we first investigated these questions in random GRNs with different network sizes, connectivity, fraction of inhibitory links and transcription regulation rules. Then we searched for the core motifs that govern the dynamic behavior of large GRNs. We show that the stability of a random GRN is typically governed by a few embedding motifs of small sizes, and therefore can in general be understood in the context of these short motifs. Our results provide insights for the study and design of genetic networks.

关键词： genetic network dynamic attractors complex systems

Asymptotic Stability of Stochastic genetic networks with Disturbance Attenuation

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Asymptotic Stability of Stochastic Genetic Networks with Dis...

Global Relative Input-Output Sensitivities of the Feed-Forward Loops in genetic networks

第三十届中国控制会议

作者： LI Hongjie College of Mathematics and Information and Engineering,Jiaxing University,Zhejiang,314001,P.R.China

Gene regulation is an intrinsically noise process,which is subject to intracellular and extracellular noise perturbations and environment fluctuations,moreover time delays play an important role in dynamics of genetic networks owing to slow biochemical reactions of transcription,translation and translocation.Basing on the above analysis,this paper presents a stochastic nonlinear model for genetic regulatory networks with SUM regulatory functions,sufficient conditions of the stochastic asymptotic stability with disturbance attenuation are derived in terms of LMIs,which are easy to be verified via the LMI toolbox.To show the effectiveness of the obtained results.Illustrative examples are also given at last.

关键词： genetic network Stochastic asymptotic stability Stochastic perturbation Time-varying

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Global Relative Input-Output Sensitivities of the Feed-Forwa...