2型糖尿病早期大鼠外周神经节基因表达谱分析

糖尿病神经病变(Diabetic neuropathy,DN)是糖尿病在神经系统发生的多种并发病变的总称。文章旨在筛选2型糖尿病早期大鼠外周神经节差异表达的基因。采用Illumina大鼠基因表达芯片,比较糖尿病模型与非糖尿病大鼠外周神经节基因表达谱差异。结果表明,全基因组12 604个已知基因中,158个基因差异表达。糖尿病组与非糖尿病组相比,87个基因表达上调,71个表达下调。对差异表达的基因进行GO分析,发现上调基因所参与的最显著(P<0.001)的几个生物学过程都与神经细胞骨架及运动功能有关;下调基因所参与的最显著的生物学过程主要与"对病毒/生物刺激/其它生物的反应"有关。KEGG(Kyoto encyclopedia of genes and genomes)分析显示,差异表达的基因所参与的最显著(P<0.001)的生物学通路为代谢通路。结果表明:高血糖可导致糖尿病大鼠外周神经节代谢紊乱;高血糖可能通过免疫炎症反应、改变神经细胞骨架及运动功能相关的基因的表达,继而损害外周神经节的结构和功能。     

新基因BM390716、BI274487和AA963863与大鼠再生肝8种细胞的细胞外基质代谢

为了解新基因BM390716、BI274487、AA963863在细胞外基质代谢中的作用及其与大鼠肝再生的相关性,文章用Percoll密度梯度离心结合免疫磁珠分选分离大鼠再生肝的8种细胞,用Rat Genome 230 2.0芯片检测它们的基因表达变化,用Microsoft Excel、BLAST等软件分析基因的共表达关系、序列同源性及参与的代谢活动。结果表明,BM390716与pparα同源和共表达,BI274487与timp2同源和共表达,AA963863与csgalnact1同源和共表达。根据上述基因的同源性和共表达推测,新基因BM390716、BI274487和AA963863参与大鼠再生肝8种细胞的细胞外基质代谢。     

胚胎神经管缺陷大鼠模型差异基因的表达

通过构建妊娠合并糖尿病诱发先天性神经管缺陷的SD大鼠模型, 与胚胎不伴有先天性神经管缺陷组大鼠和正常对照组大鼠胚胎进行研究, 提取卵黄囊细胞的mRNA, cDNA 基因芯片技术对表达差异基因进行检测, 应用特异性抗磷酸化抗体进行免疫共沉淀及Western blotting, 对卵黄囊细胞MAP Kinase信号途径蛋白激酶活性进行分析。在神经管缺陷大鼠胚胎卵黄囊细胞和对照组1 200个基因中, 共筛选出表达差异基因79个, 其中42个基因表达上调、37个基因表达下调。同时发现神经管缺陷胚胎卵黄囊细胞出现细胞凋亡特征性的DNA ladder(梯状电泳), 凋亡相关基因 caspase-3、Bax 高表达, 凋亡抑制基因 AKT活性明显受抑; 与正常对照组相比ERK1/2蛋白激酶活性显著下降、JNK1/2活性明显升高。因此, 认为妊娠合并糖尿病诱发胚胎先天性神经管缺陷的发生存在多种差异基因表达, 以及MAP Kinase、凋亡信号传导机制的共同作用。     

一种从多表达谱数据挖掘基因共表达团的新方法

随着近年来高通量基因表达谱数据的涌现,集成多个不同实验条件的表达谱数据,并挖掘在多数据源都保守的基因共表达团,成为预测基因功能或者调控关系的方法之一．但是,常用的方法通常仅简单地集成不同表达谱数据并推导保守基因共表达团,这样可能会导致结果中出现并非真正在多数据源保守的共表达团．提出一种结合最小哈希与局部敏感哈希的新方法,可以高效地寻找在多表达谱数据源中真正保守的基因共表达团．结果分析证明,相比过去的方法,现提出的方法可以获得更加功能相关和调控相关的基因共表达团．     

利用生物信息学研究肥胖与2型糖尿病患者肝组织基因表达变化

目的:利用芯片数据分析工具对GEO基因芯片数据进行数据挖掘,系统分析肥胖与2型糖尿病患者肝组织相关基因表达的变化,探讨肥胖与2型糖尿病的联系及糖尿病早期预防和诊断的新靶点。方法:首先在公共芯片数据库中选择肥胖与2型糖尿病相关芯片数据(GSE15653),利用R等芯片数据分析工具分析肥胖与2型糖尿病患者肝组织基因的表达变化,并预测相关差异表达基因在血中蛋白表达。结果:肥胖患者与正常人肝组织比较发现412个差异表达基因,其中上调表达基因212个,下调表达基因200个,2型糖尿病患者中控制良好者与正常人肝组织比较发现486个差异表达基因,其中上调表达基因253个,下调表达基因233个,而2型糖尿病患者中控制不良者与正常人肝组织比较发现1051个差异表达基因,其中上调表达基因560个,下调表达基因491个;2型糖尿病控制良好者与肥胖患者肝组织有263个相同的表达变化基因,而2型糖尿病控制不良者与肥胖患者肝组织有131个相同的表达变化基因;结合蛋白质组学结果分析肥胖与2型糖尿病相关的差异表达基因中有30个蛋白表达产物是分泌型蛋白。结论:肥胖及2型糖尿病患者肝组织与正常肝组织比较基因表达均发生明显变化,其基因表达变化数目随疾病的严重性增加而增多,而且2型糖尿病的控制情况与肝组织基因表达变化有密切关系。肥胖与2型糖尿病相关的差异表达基因中表达分泌型蛋白的可进一步用于研发监测疾病发生发展的候选靶分子。     

糖尿病性高血压大鼠肾损害相关基因cDNA片段的克隆与初步鉴定

为筛选大鼠糖尿病性高血压病所致的肾损害相关基因,自发性高血压大鼠以STZ 50 mg/kg一次性尾静脉注射,建立糖尿病性高血压大鼠模型,4周后该模型大鼠尿蛋白持续阳性,电镜观察到肾小球基质增生、足突融合或扁平.应用荧光标记的差异显示反转录聚合酶链反应(DDRT-PCR)及RNA印迹技术,比较两种模型大鼠肾皮质的基因表达差异,并进行差异条带的cDNA序列生物信息学分析.其中4个差异条带与Genbank数据库比较,2个为未知基因,2个为已知基因,即成淀粉样糖蛋白（amyloidogenic glycoprotein,AGG）、CDK109,两者可能与糖尿病性高血压肾损害的发生相关,对它们的进一步研究将为肾损害发病机理的发现提供思路.     

调控通路内基因表达的相关性分析

本研究从基因表达调控通路的角度分析了基因功能与基因表达之间的关系,利用7套酿酒酵母基因芯片表达谱数据和通路数据库（KEGG和CYGD）所提供的信息,应用我们研制的Genehub软件分析研究了同一基因表达调控通路内的基因在mRNA表达水平上的相关性,共涉及16条通路,495个基因。通过Pearson相关系数和Spearman相关系数两种相似性测度的分析,我们发现有94%（15条）的基因表达调控通路内的基因在大于等于4套的表达谱数据中是共表达的,以上结果从基因表达调控通路的角度,证实了基因功能与基因表达之间存在着一定的相关性。     

基于SNP共表达网络肝癌分子分型及预后分析

基于SNP突变数据与mRNA表达谱关联分析,构建一种肝癌分子分型方法并对比不同分型预后的差异,并对不同分型肝癌的发生发展机制进一步研究。首先通过TCGA数据库收集359例肝细胞癌患者的SNP突变数据和mRNA表达数据,采用Wilcoxon秩和检验,筛选突变后差异表达基因,并通过生物信息学工具String和Cytoscape构建差异表达基因的蛋白互作网络,筛选连接度最高的10个Hub基因。利用Consensus Cluster Plus软件包,基于Hub基因mRNA表达水平构建NMF分子分型模型,再结合生存数据评估各分型患者的预后。最后利用加权基因共表达网络分析(WGCNA),识别与肝癌分子分型相关的模块,并针对关键模块的基因进行通路富集,从而对不同分型肝癌的基因表达谱进行比较。结果：NMF模型将肝癌分为高危、低危2个分型,其中CDKN2A和FOXO1基因对分型贡献度高。生存分析显示低危组患者的生存情况显著优于高危组,高危组富集多个与肿瘤细胞侵蚀、转移、复发过程相关的信号通路,低危组则与细胞周期和胰液分泌相关。本研究在无先验性信息的前提下,基于突变后显著差异表达的Hub基因表达水平构建的...     

基于集成的共表达网络分析方法研究3种癌症的肿瘤相关模块

在肿瘤/癌旁基因表达数据中,差异表达 (DE,differential expression) 代表各种生物条件下基因表达水平的变化,而差异共表达 (DC,differential co-expression) 代表基因对之间相关系数的变化。单独的DC和DE研究方法已经被广泛应用于人类疾病研究中。但是,目前仍然缺乏有效整合DC和DE的分析方法。文中提出一个新颖的分析框架DC&DEmodule,该框架可以基于共表达模块整合DC和DE的特征,并同时整合多个肿瘤/癌旁表达谱的信息,用以识别与疾病相关的基因共表达模块,包括激活模块 (肿瘤样本中上调且共表达增强) 和失能模块 (肿瘤样本中下调且失去共表达)。将该框架用于分析肝癌、胃癌和结直肠癌各两组微阵列数据,分别得到肝癌、胃癌和结直肠癌的2、5和2个激活模块以及5、5和1个失能模块。富集分析表明与同类方法相比,文中的方法在检测已知的肿瘤相关通路和发现新通路方面均具有更高的灵敏度。然后,进一步从这3种癌症的激活模块中鉴定出17、69和11个模块关键基因,其中包含53个已报道的预后生物标志物以及3个分别与3种癌症存活率显著相关的新预后标志物。基于关键基因训练了3种癌症的随机森林模型,用于区分TCGA(The Cancer Genome Atlas) 和GEO (Gene Expression Omnibus)数据库中的肿瘤和癌旁样本,结果显示其分类的平均准确性达到了93%。三种癌症的比较为不同癌症的共有和组织特异性机制提供了新的见解。一系列评估表明,DC&DEmodule框架能够整合公共数据库中快速积累的表达谱,发现更多疾病中功能失调的生物过程。     

宫颈癌差异表达基因筛选及功能分析

目的:筛选参与宫颈癌发生、发展的关键基因,为临床诊疗提供新的靶点。方法:在NCBI-GEO数据库中筛选多组宫颈癌基因表达检测数据集,利用GEO2R分析工具筛选各组数据集的差异表达基因;应用R分析筛选不同数据集之间共有的差异表达基因;利用DAVID在线分析对差异表达基因进行功能聚类和通路分析;利用STRING分析差异表达基因编码蛋白之间的相互作用关系。结果:共选择6组表达数据集,筛选得到59个差异表达基因(宫颈癌组织vs正常组织),表达差异至少达2倍,其中包含50个表达上调基因及9个表达下调基因。这些差异表达基因参与细胞周期、DNA复制、细胞分裂等生物进程。蛋白互作分析表明,这些差异表达基因多数存在相互作用。结论:利用生物信息学方法对不同来源的基因检测数据进行整合分析,有助于更准确的筛选对宫颈癌发生、发展过程具有重要作用的关键基因,本文筛选的宫颈癌差异基因为进一步研究宫颈癌发生、发展的分子机制及临床诊疗提供思路。     

埃及伊蚊不同组织的基因共表达模式分析

【目的】利用权重基因共表达网络分析(weighted gene co-expression network analysis,WGCNA)探索埃及伊蚊Aedes aegypti不同组织基因共表达模式。【方法】从NCBI SRA数据库中选择埃及伊蚊不同组织的转录组数据中具代表性的9种组织(雌雄成蚊的触角和脑,雌蚊的喙、下颚须和卵巢,雄成蚊的前足、中足、后足和腹部末端)的双端测序数据;经过缺失值移除以及方差计算后,筛选出方差最大的5 000个基因,利用R软件中WGCNA包建立埃及伊蚊成蚊不同组织的基因共表达网络并划分模块;然后利用clusterProfiler包对组织特异性模块内的基因进行GO(Gene Ontology)和KEGG(Kyoto Encyclopediaof Genes and Genomes)富集分析,并用Cytoscape软件中的CytoHubba插件筛选共表达模块内的hub基因。【结果】从埃及伊蚊成蚊不同组织中共鉴定出11个基因共表达模块,在雌蚊触角、喙、卵巢、下颚须以及雄蚊脑、腹部末端组织中各鉴定出1个特异性表达模块,雄蚊前足、中足和后足组织中无特异性表达模块。6个组织特异性表达模块内基因功能注释到组织生物学功能;其中,雌蚊触角特异性green模块内基因具有气味结合和嗅觉受体活性等功能;雌蚊喙特异性purple模块内基因具有丝氨酸型肽链内切酶活性和丝氨酸水解酶活性等功能;雄蚊脑特异性blue模块内基因在生物学过程调节、信号转导和神经系统过程等生物学过程中发挥主要作用。利用CytoHubba进一步鉴定出所选组织特异性共表达模块中具有高连通性的hub基因,包括AAEL010426, AAEL002896, AAEL002600, AAEL000961, AAEL007784和AAEL006429。【结论】本研究依据埃及伊蚊不同组织转录组数据,利用WGCNA方法发现了许多重要的基因共表达模块。本研究的结果为蚊虫基因共表达模式分析提供新思路和方法基础,对探究蚊虫不同组织特有的基因资源信息以及功能基因生物信息学研究有参考价值。     

Co-expression analysis provides important module and pathways of human dilated cardiomyopathy

Dilated cardiomyopathy (DCM) is a heart disease that injured greatly to the people wordwide. Systemic co-expression analysis for this cancer is still limited, although massive clinic experiments and gene profiling analyses had been well performed previously. Here, using the public RNA-Seq data “GSE116250” and gene annotation of Ensembl database, we built the co-expression modules for DCM by Weighted Gene Co-Expression Network Analysis, and investigated the function enrichment and protein-protein interaction (PPI) network of co-expression genes of each module by Database for Annotation, Visualization, and Integrated Discovery and Search Tool for the Retrieval of Interacting Genes/Proteins database, respectively. First, 5,000 genes in the 37 samples were screened and 11 co-expression modules were conducted. The number of genes for each module ranged from 77 to 936, with a mean of 455. Second, interaction relationships of hub-genes between pairwise modules showed great differences, suggesting relatively high-scale independence of the modules. Third, functional enrichments of the co-expression modules exhibited great differences. We found that genes in module 3 were significantly enriched in the pathways of focal adhesion and ubiquitin-mediated proteolysis. This module was inferred as the key module involved in DCM. In addition, PPI analysis revealed that the genes HSP90AA1, CTNNB1, MAPK1, GART, and PPP2CA owned the largest number of adjacency genes, unveiling that they may function importantly during the occurrence of DCM. Focal adhesion and ubiquitin-mediated proteolysis play important roles in human DCM.     

Identification of biomarkers correlated with hypertrophic cardiomyopathy with co-expression analysis

Hypertrophic cardiomyopathy (HCM) is reported to be the most common genetic heart disease. To identify key module and candidate biomarkers correlated with clinical prognosis of patients with HCM, we carried out this study with co-expression analysis. To construct a co-expression network of hub genes correlated with HCM, the Weighted Gene Co-expression Network Analysis (WGCNA) was performed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed by Database for Annotation, Visualization and Integrated Discovery (DAVID). The protein-protein interaction network analysis of central genes was performed to recognize the interactions of central genes. Gene set enrichment analyses were carried out to discover the possible mechanisms involved in the pathways promoted by hub genes. To validate the hub genes, quantitative real-time polymerase chain reaction (RT-PCR) was performed. Based on the results of topological overlap measure based clustering, 2,351 differentially expressed genes (DEGs) were identified. Those genes were included in six different modules. Of these modules, the yellow and the blue modules showed a pivotal correlation with HCM. DEGs were enriched in immune system procedure associated GO terms and KEGG pathways. We identified nine hub genes (TYROBP, STAT3, CSF1R, ITGAM, SYK, ITGB2, LILRB2, LYN, and HCK) affected the immune system significantly. Among the genes we validated with RT-PCR, TYROBP, CSF1R, and SYK showed significant increasing expression levels in model HCM rats. In conclusion, we identified two modules and nine hub genes, which were prominently associated with HCM. We found that immune system may play a crucial role in the HCM. Accordingly, those genes and pathways might become therapeutic targets with clinical usefulness in the future.     

Analysis of gene co-expression networks and function modules at different developmental stages of chicken breast muscle

The development of poultry muscle fibers after hatching is closely related to meat quality and production efficiency. It is necessary to identify functional modules (groups of functionally related genes) related to muscle development at different developmental stages, and to investigate their relationships based on the weighted gene co-expression network analysis (WGCNA) methods. Accordingly, we investigated the co-expression associations between genes related to chicken breast muscle at four different developmental stages (between 2 and 14 weeks of age), and systematically analyzed the network topology in Jinmao Hua chicken. As a result, 2341 differentially expressed genes were identified and subjected to co-expression analysis. Four modules were identified to be related to a particular growth stage for the development of breast muscle. A series of genes with the highest connectivity were identified in the pink (2 weeks), yellow (6 weeks), green (10 weeks) and black modules (14 weeks), respectively, and visualized by Cytoscape. These hub genes (FGF, MAPKAPK5, NRG1, SCD, ACSL1, PPAR etc.) were mainly enriched in 15 pathways, such as MAPK signaling pathway, NRG/ErbB signaling pathway, and insulin signaling pathway. They shared biological functions related to development of breast muscle and adipogenesis. This is the first study of gene network with different stages of muscle development in Jinmao Hua chicken to observe co-expression patterns. It may contribute to the underlied molecular mechanisms of chicken breast muscle development.     

Deciphering Ascorbic Acid Regulatory Pathways in Ripening Tomato Fruit Using a Weighted Gene Correlation Network Analysis Approach

Genotype is generally determined by the co-expression of diverse genes and multiple regulatory pathways in plants. Gene co-expression analysis combining with physiological trait data provides very important information about the gene function and regulatory mechanism. L-Ascorbic acid （AsA）, which is an essential nutrient component for human health and plant metabolism, plays key roles in diverse biological processes such as cell cycle, cell expansion, stress resistance, hormone synthesis, and signaling. Here, we applied a weighted gene correlation network analysis approach based on gene expression values and AsA content data in ripening tomato （Solanum lycopersicum L.） fruit with different AsA content levels, which leads to identification of AsA relevant modules and vital genes in AsA regulatory pathways. Twenty- four modules were compartmentalized according to gene expression profiling. Among these modules, one negatively related module containing genes involved in redox processes and one positively related module enriched with genes involved in AsA biosynthetic and recycling pathways were further analyzed. The present work herein indicates that redox pathways as well as hormone-signal pathways are closely correlated with AsA accumulation in ripening tomato fruit, and allowed us to prioritize candidate genes for follow-up studies to dissect this interplay at the biochemical and molecular level.     

活血化瘀方对糖尿病模型大鼠糖脂代谢、血管内皮生长因子和血管紧张素II1型受体表达的影响

目的:探讨活血化瘀方对糖尿病模型大鼠糖脂代谢、血管内皮生长因子(VEGF)和血管紧张素Ⅱ1型受体(AT1R)表达的影响。方法:选取健康雄性SD大鼠50只,适应性喂养7 d后以随机数字表法分成对照组10只、模型组13只、中药组14只、西药组13只。其中模型组与对照组予以纯净水灌胃,中药组予以活血化瘀通络中药配方颗粒灌胃,西药组则予以厄贝沙坦灌胃,1次/d,连续灌胃16周。分别比较各组大鼠的糖脂代谢指标水平及24 h尿蛋白定量、糖化血红蛋白、血清肌酐水平,并检测肾组织VEGF和AT1R表达情况。结果:模型组、中药组、西药组大鼠空腹血糖(FBG)、总胆固醇(TC)、甘油三酯(TG)、高密度脂蛋白胆固醇(HDL-C)、低密度脂蛋白胆固醇(LDL-C)水平均高于对照组,中药组、西药组大鼠LDL-C水平低于模型组,中药组大鼠FBG水平低于模型组与西药组(P0.05)。模型组、中药组、西药组大鼠24 h尿蛋白定量与糖化血红蛋白均高于对照组,中药组、西药组大鼠24 h尿蛋白定量低于模型组(P0.05)。模型组、中药组、西药组大鼠VEGF、AT1R水平均高于对照组,中药组、西药组大鼠VEGF、AT1R水平低于模型组,中药组大鼠AT1R水平低于西药组(P0.05)。结论:活血化瘀方可有效改善糖尿病大鼠糖脂代谢状态,通过抑制VEGF与AT1R的表达水平,延缓糖尿病的发生与发展。     

Integrating genetic and network analysis to characterize genes related to mouse weight

Systems biology approaches that are based on the genetics of gene expression have been fruitful in identifying genetic regulatory loci related to complex traits. We use microarray and genetic marker data from an F2 mouse intercross to examine the large-scale organization of the gene co-expression network in liver, and annotate several gene modules in terms of 22 physiological traits. We identify chromosomal loci (referred to as module quantitative trait loci, mQTL) that perturb the modules and describe a novel approach that integrates network properties with genetic marker information to model gene/trait relationships. Specifically, using the mQTL and the intramodular connectivity of a body weight–related module, we describe which factors determine the relationship between gene expression profiles and weight. Our approach results in the identification of genetic targets that influence gene modules (pathways) that are related to the clinical phenotypes of interest.