Dynamic-module redundancy confers robustness to the gene regulatory network involved in hair patterning of Arabidopsis epidermis

Redundancy among dynamic modules is emerging as a potentially generic trait in gene regulatory networks. Moreover, module redundancy could play an important role in network robustness to perturbations. We explored the effect of dynamic-module redundancy in the networks associated to hair patterning in Arabidopsis root and leaf epidermis. Recent studies have put forward several dynamic modules belonging to these networks. We defined these modules in a discrete dynamical framework that was previously reported. Then, we addressed whether these modules are sufficient or necessary for recovering epidermal cell types and patterning. After defining two quantitative estimates of the system's robustness, we also compared the robustness of each separate module with that of a network coupling all the leaf or root modules. We found that, considering certain assumptions, all the dynamic modules proposed so far are sufficient on their own for pattern formation, but reinforce each other during epidermal development. Furthermore, we found that networks of coupled modules are more robust to perturbations than single modules. These results suggest that dynamic-module redundancy might be an important trait in gene regulatory networks and point at central questions regarding network evolution, module coupling, pattern robustness and the evolution of development.     

Prognostic genes of hepatocellular carcinoma based on gene coexpression network analysis

Hepatocellular carcinoma (HCC) is the most common subtype in liver cancer whose prognosis is affected by malignant progression associated with complex gene interactions. However, there is currently no available biomarkers associated with HCC progression in clinical application. In our study, RNA sequencing expression data of 50 normal samples and 374 tumor samples was analyzed and 9225 differentially expressed genes were screened. Weighted gene coexpression network analysis was then conducted and the blue module we were interested was identified by calculating the correlations between 17 gene modules and clinical features. In the blue module, the calculation of topological overlap was applied to select the top 30 genes and these 30 genes were divided into the green group (11 genes) and the yellow group (19 genes) through searching whether these genes were validated by in vitro or in vivo experiments. The genes in the green group which had never been validated by any experiments were recognized as hub genes. These hub genes were subsequently validated by a new data set GSE76427 and KM Plotter Online Tool, and the results indicated that 10 genes (FBXO43, ARHGEF39, MXD3, VIPR1, DNASE1L3, PHLDA1, CSRNP1, ADR2B, C1RL, and CDC37L1) could act as prognosis and progression biomarkers of HCC. In summary, 10 genes who have never been mentioned in HCC were identified to be associated with malignant progression and prognosis of patients. These findings may contribute to the improvement of the therapeutic decision, risk stratification, and prognosis prediction for HCC patients.     

The evolutionary dynamics of evolvability in a gene network model

Evolvability, the ability of populations to adapt, has recently emerged as a major unifying concept in biology. Although the study of evolvability offers new insights into many important biological questions, the conceptual bases of evolvability, and the mechanisms of its evolution, remain controversial. We used simulated evolution of a model of gene network dynamics to test the contentious hypothesis that natural selection can favour high evolvability, in particular in sexual populations. Our results conclusively demonstrate that fluctuating natural selection can increase the capacity of model gene networks to adapt to new environments. Detailed studies of the evolutionary dynamics of these networks establish a broad range of validity for this result and quantify the evolutionary forces responsible for changes in evolvability. Analysis of the genotype–phenotype map of these networks also reveals mechanisms connecting evolvability, genetic architecture and robustness. Our results suggest that the evolution of evolvability can have a pervasive influence on many aspects of organisms.     

根据蛋白质互作网络预测乳腺癌相关蛋白质的细致功能

乳腺癌是最为常见的恶性肿瘤之一。已有的关于乳腺癌相关蛋白质的功能注释比较宽泛, 制约了乳腺癌的后续研究工作。对于已知部分功能的乳腺癌相关蛋白质, 提出了一种结合Gene Ontology功能先验知识和蛋白质互作的方法, 通过构建功能特异的局部相互作用网络来预测乳腺癌相关蛋白质的细致功能。结果显示该方法能够以很高的精确率为乳腺癌相关蛋白质预测更为精细的功能。预测的相关蛋白质的功能对于指导实验研究乳腺癌的分子机制具有重要的价值。     

一种基于时间自动机的基因网络逻辑模型

最近几年来国外基因组（基因网络）系统逻辑行为的研究新进展——基于有限状态自动机模型的方法,针对该方法的局限性,提出了一种基于时间自动机的基因网络模型,以描述网络行为的时间约束。     

Identification of hub genes in colorectal cancer based on weighted gene co-expression network analysis and clinical data from The Cancer Genome Atlas

Colorectal cancer (CRC) is one of the most common tumors worldwide and is associated with high mortality. Here we performed bioinformatics analysis, which we validated using immunohistochemistry in order to search for hub genes that might serve as biomarkers or therapeutic targets in CRC. Based on data from The Cancer Genome Atlas (TCGA), we identified 4832 genes differentially expressed between CRC and normal samples (1562 up-regulated and 3270 down-regulated in CRC). Gene ontology (GO) analysis showed that up-regulated genes were enriched mainly in organelle fission, cell cycle regulation, and DNA replication; down-regulated genes were enriched primarily in the regulation of ion transmembrane transport and ion homeostasis. Weighted gene co-expression network analysis (WGCNA) identified eight gene modules that were associated with clinical characteristics of CRC patients, including brown and blue modules that were associated with cancer onset. Analysis of the latter two hub modules revealed the following six hub genes: adhesion G protein-coupled receptor B3 (BAI3, also known as ADGRB3), cyclin F (CCNF), cytoskeleton-associated protein 2 like (CKAP2L), diaphanous-related formin 3 (DIAPH3), oxysterol binding protein-like 3 (OSBPL3), and RERG-like protein (RERGL). Expression levels of these hub genes were associated with prognosis, based on Kaplan–Meier survival analysis of data from the Gene Expression Profiling Interactive Analysis database. Immunohistochemistry of CRC tumor tissues confirmed that OSBPL3 is up-regulated in CRC. Our findings suggest that CCNF, DIAPH3, OSBPL3, and RERGL may be useful as therapeutic targets against CRC. BAI3 and CKAP2L may be novel biomarkers of the disease.     

基于对数线性模型的酵母基因转录调控模体分析

识别真核基因的转录因子结合位点(或称模体)是后基因组时代的一项主要工作,对共表达或共调控的基因同时进行分析可以提高模体识别的准确性.本文基于2×2列联表的对数线性模型,以模体出现的基因条数计数,对酵母核糖体蛋白(RP)基因普遍使用的转录调控模体进行分析,然后用U-检验进一步筛选出相对于背景序列来说过表达的模体.这些模体为酵母RP基因潜在的转录调控元件,与实验获得的转录因子结合位点的符合率达90%.本方法的优点在于用严格的统计标准在一组基因启动子中搜索普遍使用的模体,克服了以往分析中对模体使用普遍性的模糊判断.本文的方法也可以有效地搜索共表达基因族的组合调控模体对.研究中还发现一个现象:2×2列联表中反映属性相关程度的Pearson相关系数与对数线性模型的交互效应之间存在着明显的相关性.这一结果提示,可以用对数线性模型的交互效应来评价两属性的关联情况.     

基于PCR的基因差异表达分析技术

基因差异表达分析是研究许多生物学过程的分子基础的一条直接、有效的途径。自DDRT-PCR技术建立以来,一系列基于PCR的基因差异表达分析技术,如SAGE、SSH、RDA和DNA微阵列等相继发展起来,为分析和克隆差异表达的基因提供了更为快速、灵敏的工具。本对这几种方法进行了简要综述,比较了不同方法的优缺点,并展望了今后基因差异表达研究技术的发展方向。     

基于转录组和加权基因共表达网络的广叶绣球菌木质纤维素降解特性分析

【目的】分析广叶绣球菌（Sparassis latifolia）在不同木质纤维素诱导条件下基因表达差异,为广叶绣球菌木质纤维素降解关键基因和分子机制研究提供参考。【方法】以松木、杉木、甘蔗渣和天然堆积发酵后的杉木和发酵后的甘蔗渣为碳源,在液体培养条件下培养诱导广叶绣球菌,对其转录组进行测序研究,并对不同木质纤维素诱导样本进行加权基因共表达网络分析（weighted gene co-expression network analysis,WGCNA）。【结果】杉木培养与松木培养比较组差异表达基因最少（20个）,蔗渣培养与松木培养比较组差异表达基因最多（486个）。基因本体（gene ontology,GO）富集分析结果表明,差异表达基因主要涉及氧化还原酶活性、单加氧酶活性和铁离子结合活性等,京都基因和基因组百科全书（Kyoto encyclopedia of genes and genomes,KEGG）通路富集分析结果表明,差异表达基因主要涉及戊糖和葡萄糖醛酸转换、甲烷代谢和乙醛酸盐和二羧酸盐代谢等通路。发酵甘蔗渣为碳源培养时,纤维素和半纤维素降解相关的糖苷水解酶基因表达量总体上较高,而未发酵的松木、杉木和甘蔗渣为碳源培养时木质素降解或修饰相关的碳水化合物辅助酶基因表达量总体上较高。利用WGCNA共鉴定出10个共表达模块,其中green模块与未发酵蔗渣诱导显著正相关,blue模块与发酵甘蔗渣诱导显著正相关,magenta和turquoise模块与发酵杉木诱导显著正相关。GO富集分析结果表明,turquoise模块内基因显著富集到尿素跨膜转运子活性、甲基转移酶活性和单加酶活性等,blue模块基因显著富集到水解酶活性和β-甘露糖苷酶活性。KEGG通路富集分析结果表明,blue模块内基因显著富集的通路有半乳糖代谢、果糖和甘露糖代谢、苯丙氨酸代谢、精氨酸和脯氨酸代谢等。通过构建互作网络图挖掘到12个核心基因,其可能参与了基质降解及相关基因的表达调控。【结论】不同木质纤维素类型显著影响了广叶绣球菌木质纤维素降解基因的差异表达轮廓,这种差异反映了广叶绣球菌对不同木质纤维素特异的降解策略。     

Analysis of metabolic network based on conservation of molecular structure

Recent work has revealed much about chemical reactions inside hundreds of organisms as well as universal characteristics of metabolic networks, which shed light on the evolution of the networks. However, characteristics of individual metabolites have been neglected. For example, some carbohydrates have structures that are decomposed into small molecules by metabolic reactions, but coenzymes such as ATP are mostly preserved. Such differences in metabolite characteristics are important for understanding the universal characteristics of metabolic networks. To quantify the structure conservation of metabolites, we defined the "structure conservation index" (SCI) for each metabolite as the fraction of metabolite atoms restored to their original positions through metabolic reactions. As expected, coenzymes and coenzyme-like metabolites that have reaction loops in the network show a higher SCI. Using the index, we found that the sum of metabolic fluxes is negatively correlated with the structure preservation of metabolite. Also, we found that each reaction path around high SCI metabolites changes independently, while changes in reaction paths involving low SCI metabolites coincide through evolution processes. These correlations may provide a clue to universal properties of metabolic networks.     

Analysis on regulatory network linked to Hpa gene in invasion and metastasis of colon cancer

Our purpose was to discuss the biological function of Hpa gene and its regulatory network in invasion and metastasis of colon cancer. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes database were used to perform functional annotation and pathway analysis on Hpa gene. Gene Ontology analysis results showed that Hpa plays a significant role in cellular component, molecular function and biological process; and combined with Kyoto Encyclopedia of Genes and Genomes database, regulatory network of angiogenesis of colon cancer was drawn out. Through analysis of regulatory network linked to angiogenesis in invasion and metastasis of colon cancer, the study lays foundation for further prevention, diagnosis and treatment of colon cancer.     

基于网络特征的道路生态干扰——以澜沧江流域为例

道路网络对区域景观的生态格局和过程产生较大的影响,作为干扰因子,区域道路网络的特征和所产生的生态干扰水平存在一定的相关性.利用GIS和网络分析法,以澜沧江流域县域为基本单元,分析了研究区各县的道路网络特征指数,在揭示了区域道路网络不同特征之间的规律性的基础上,进一步对区域网络特点和生态干扰之间相关性进行了内在关系的探讨.结果表明,澜沧江流域道路网络结构的空间差异很大,流域内各县的道路网络节点数、连接线数目、α环度、β线点率、γ连接度指数等网络特征因子也存在较大差异;道路密度和道路总长度与区域海拔高度呈现较明显的负相关关系;道路密度和区域道路的廊道密度呈现正相关关系,和区域道路的α指数、β指数和γ指数关系可以用倒数模型来拟合.缓冲区分析表明,耕地比例和道路密度线性相关关系显著,而其他类型相关性较差,但区域综合的人工干扰指数(Hd)(1980,2000)和道路网络的特征指数相关显著,而且不同时期的区域景观的斑块密度、平均斑块面积和区域道路网络特征之间也存在较强的相关性,即网络扩展使得区域生态系统受干扰强度增加,破碎化严重,但较短时期内的生态系统变化和道路网络特征之间相关性不显著.     

Shape identification of electrocardiographic ST segment based on radial basis function neural network

The types of myocardial ischemia can be revealed by electrocardiographic (ECG) ST segment. Effective measurement and electrocardiographic analysis of ST as well as calculation of displacement and shape change of ST segment can help doctors diagnose coronary heart disease and myocardial ischemia, especially for asymptomatic myocardial ischemia. Therefore, it is a very important subject in clinical practice to measure and classify the ECG ST segment. In this paper, we introduce a computerized automatic identification method of the electrocardiographic ST segment shape with radial basis function neural network based on adaptive fuzzy system, which has a better effect than other methods. It helps to analyze the reason of the ST segment change and confirm the position of myocardial ischemia, and is useful for doctor diagnosis. Translated from Acta Biophysica Sinica, 2005, 21(6): 443–448 [译自: 生物物理学报]     

Shape identification of electrocardiographic ST segment based on radial basis function neural network

The types of myocardial ischemia can be revealed by electrocardiographic (ECG) ST segment.Effective measurement and electrocardiographic analysis of ST as well as calculation of displacement and shape change of ST segment can help doctors diagnose coronary heart disease and myocardial ischemia,especially for asymptomatic myocardial ischemia.Therefore,it is a very important subject in clinical practice to measure and classify the ECG ST segment.In this paper,we introduce a computerized automatic identification method of the electrocardiographic ST segment shape with radial basis function neural network based on adaptive fuzzy system,which has a better effect than other methods.It helps to analyze the reason of the ST segment change and confirm the position of myocardial ischemia,and is useful for doctor diagnosis.     

基于网络药理学的柿果药理功能定位及作用机制

基于网络药理学,通过国内外文献检索获取柿果中的化合物,采用Swiss target prediction数据库对化合物进行潜在靶点垂钓以探讨柿果的药理功能定位及作用机制。以Cytoscape软件构建化合物-靶点网络,靶点-疾病名称-疾病分类网络,同时对靶点进行蛋白相互作用(PPI)网络构建,采用DAVID数据库对靶点进行通路富集分析。本研究共收集到柿果中16个化合物,可作用于68个靶点,这些靶点主要作用于心血管疾病、神经精神性疾病等。PPI网络图包含84个节点,226条边,其中degree值排前10的关键蛋白分别为ERS1、PGS2、MMP2、TIMP1、MMP9、MMP1、AR、SLC6A3、PRKCB、CYP19A1。上述靶点可调节氮素代谢、血清素能突触以及TRP通道炎症介质的调节等信号通路。本研究为阐明柿果的药理功能定位及其作用机制研究提供了可靠的依据。     

基于生态网络的生态安全格局评价

生态网络可用于描述、评价生境破碎条件下景观空间组织方式与物种存续的关系.本文以青岛市为研究区域,基于最小成本路径方法模拟得到2005年林地、湿地生态网络,并基于廊道累计成本值对得到的生态网络进行分级.利用介数指数、相关长度-逐块筛选指数对生态网络中斑块与廊道等结构要素进行重要性区分,形成生态网络结构体系.并在评价2005—2013年新增建设用地对生态网络影响的基础上,提出应对建设用地变化的生态安全格局.结果表明: 在生态网络框架基础上,图形理论的相关评价方法能够量化评价识别生态用地的具体属性(如生态网络斑块的面积)和生态用地之间的功能联系;2005—2013年间,青岛市新增建设用地对湿地侵占面积较大,且没有考虑具体林地、湿地在整个地区生态系统连通性维护中的作用;基于生态网络的生态安全格局的划定可以优化地区生态基底,为生态保护与恢复提供更加精确的空间决策依据,同时为城市空间扩张提供科学合理的空间指引.     

Reduced point charge models of proteins: assessment based on molecular dynamics simulations

A reduced point charge distribution is used to model Ubiquitin and two complexes, Vps27 UIM-1–Ubiquitin and Barnase–Barstar. It is designed from local extrema in charge density distributions obtained from the Poisson equation applied to smoothed molecular electrostatic potentials. A variant distribution is built by locating point charges on atoms. Various charge fitting conditions are selected, i.e. from either electrostatic Amber99 (Assisted Model Building with Energy Refinement) Coulomb potential or forces, considering reference grid points located within various distances from the protein atoms, with or without separate treatment of main and side chain charges. The program GROMACS (Groningen Machine for Chemical Simulations) is used to generate Amber99SB molecular dynamics (MD) trajectories of the solvated proteins modelled using the various reduced point charge models (RPCMs) so obtained. Point charges that are not located on atoms are considered as virtual sites. Some RPCMs lead to stable MD trajectories. They, however, involve a partial loss in the protein secondary structure and lead to a less-structured solute solvation shell. The model built by fitting charges on Coulomb forces calculated at grid points ranging between 1.4 and 2.0 times the van der Waals radius of the atoms, with a separate treatment of main chain and side chain charges, appears to best approximate all-atom MD trajectories.