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.     

应用GSEA和WGCNA方法分析细菌性败血症宿主关键差异基因及意义

【目的】采用生物信息学方法分析公共数据库来源的细菌性败血症患者全血转录组学表达谱,探讨细菌败血症相关的宿主关键差异基因及意义。【方法】基于GEO数据库中GSE80496和GSE72829全血转录组基因数据集,采用GEO2R、基因集富集分析(GSEA)联用加权基因共表达网络分析(WGCNA)筛选细菌性败血症患者相比健康人群显著改变的差异基因,通过R软件对交集基因进行GO功能分析和KEGG富集分析。同时,通过String 11.0和Cytoscape分析枢纽基因,验证枢纽基因在数据集GSE72809(Health组52例,Definedsepsis组52例)全血标本中的表达情况,并探讨婴儿性别、月(胎)龄、出生体重、是否接触抗生素等因素与靶基因表达谱间的关系。【结果】分析GSE80496和GSE72829数据集分别筛选得到932个基因和319个基因,联合WGCNA枢纽模块交集得到与细菌性败血症发病相关的10个枢纽基因(MMP9、ITGAM、CSTD、GAPDH、PGLYRP1、FOLR3、OSCAR、TLR5、IL1RN和TIMP1);GSEA分析获得关键通路(氨基酸糖类-核糖代谢、PPAR信号通路、聚糖生物合成通路、自噬调控通路、补体、凝血因子级联反应、尼古丁和烟酰胺代谢、不饱和脂肪酸生物合成和阿尔兹海默症通路)及生物学过程(类固醇激素分泌、腺苷酸环化酶的激活、细胞外基质降解和金属离子运输)。【结论】本项研究通过GEO2R、GSEA联用WGCNA分析,筛选出与细菌性败血症发病相关的2个枢纽模块、10个枢纽基因以及一些关键信号通路和生物学过程,可为后续深入研究细菌性败血症致病机制奠定理论依据。     

权重基因共表达网络分析在生物医学中的应用

高通量生物监测方法可以同时检测同一样本的上千个参数,其在生物医学中的应用越来越广泛,但如何系统地分析并从高通量数据中挖掘有用信息,仍是一项重要的课题。网络生物学的出现使人们对复杂生物系统有了更深刻的理解,组织/细胞功能执行具有模块化特点。目前,相关网络(Correlation network)被越来越多地应用于生物信息学,权重基因共表达网络分析(Weighted gene co-expression network analysis,WGCNA)是描述样品基因表达相关模式的一种系统生物学工具。在此,对WGCNA在疾病分型及预后、发病机制和其他相关领域研究进展作一个较为系统的综述。首先,对WGCNA的原理、分析流程和优势缺点进行总结。其次,介绍如何用WGCNA研究疾病、正常组织、药物、进化和基因组注释。最后,结合新高通量技术展望WGCNA应用新空间。以期科研工作者能够对WGCNA的应用有所了解。     

Integration of miRNA weighted gene co-expression network and miRNA-mRNA co-expression analyses reveals potential regulatory functions of miRNAs in calf rumen development

This study aimed to explore the roles of microRNAs (miRNAs) in calf rumen development during early life. Rumen tissues were collected from 16 calves (8 at pre-weaning and 8 at post-weaning) for miRNA-sequencing, differential expression (DE), miRNA weighted gene co-expression network (WGCNA) and miRNA-mRNA co-expression analyses. 295 miRNAs were identified. Bta-miR-143, miR-26a, miR-145 and miR-27b were the most abundantly expressed. 122 miRNAs were significantly DE between the pre- and post-weaning periods and the most up- and down-regulated miRNAs were bta-miR-29b and bta-miR-493, respectively. Enrichment analyses of the target genes of DE miRNAs revealed important roles for miRNA in rumen developmental processes, immune system development, protein digestion and processes related to the extracellular matrix. WGCNA indicated that bta-miR-145 and bta-miR-199a-3p are important hub miRNAs in the regulation of these processes. Therefore, bta-miR-143, miR-29b, miR-145, miR-493, miR-26a and miR-199 family members might be key regulators of calf rumen development during early life.     

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。     

Identification of key lncRNAs in the carcinogenesis and progression of colon adenocarcinoma by co-expression network analysis

Colon adenocarcinoma (COAD) is one of the most common cancers, and its carcinogenesis and progression is influenced by multiple long non-coding RNAs (lncRNA), especially through the miRNA sponge effect. In this study, more than 4000 lncRNAs were re-annotated from the microarray datasets through probe sequence mapping to obtain reliable lncRNA expression profiles. As a systems biology method for describing the correlation patterns among genes across microarray samples, weighted gene co-expression network analysis was conducted to identify lncRNA modules associated with the five stepwise stages from normal colonic samples to COAD (n = 94). In the most relevant module (R² = −0.78, P = 4E-20), four hub lncRNAs were identified (CTD-2396E7.11, PCGF5, RP11-33O4.1, and RP11-164P12.5). Then, these four hub lncRNAs were validated using two other independent datasets including GSE20916 (n = 145) and GSE39582 (n = 552). The results indicated that all hub lncRNAs were significantly negatively correlated with the three-stage colonic carcinogenesis, as well as TNM stages in COAD (one-way analysis of variance P < 0.05). Kaplan-Meier survival curve showed that patients with higher expression of each hub lncRNA had a significantly higher overall survival rate and lower relapse risk (log-rank P < 0.05). In conclusion, through co-expression analysis, we identified and validated four key lncRNAs in association with the carcinogenesis and progression of COAD, and these lncRNAs might have important clinical implications for improving the risk stratification, therapeutic decision and prognosis prediction in COAD patients.     

The Arabidopsis co-expression tool (ACT): a WWW-based tool and database for microarray-based gene expression analysis

We present a new WWW-based tool for plant gene analysis, the Arabidopsis Co-Expression Tool (ACT), based on a large Arabidopsis thaliana microarray data set obtained from the Nottingham Arabidopsis Stock Centre. The co-expression analysis tool allows users to identify genes whose expression patterns are correlated across selected experiments or the complete data set. Results are accompanied by estimates of the statistical significance of the correlation relationships, expressed as probability (P) and expectation (E) values. Additionally, highly ranked genes on a correlation list can be examined using the novel clique finder tool to determine the sets of genes most likely to be regulated in a similar manner. In combination, these tools offer three levels of analysis: creation of correlation lists of co-expressed genes, refinement of these lists using two-dimensional scatter plots, and dissection into cliques of co-regulated genes. We illustrate the applications of the software by analysing genes encoding functionally related proteins, as well as pathways involved in plant responses to environmental stimuli. These analyses demonstrate novel biological relationships underlying the observed gene co-expression patterns. To demonstrate the ability of the software to develop testable hypotheses on gene function within a defined biological process we have used the example of cell wall biosynthesis genes. The resource is freely available at http://www.arabidopsis.leeds.ac.uk/ACT/     

Gene co-expression network analysis for identifying genetic markers in Parkinson's disease - a three-way comparative approach

Parkinson's disease (PD) is a neurodegenerative disorder involving progressive deterioration of dopaminergic neurons. Although few genetic markers for familial PD are known, the etiology of sporadic PD remains poorly understood. Microarray data was analysed for induced pluripotent stem cells (iPSCs) derived from PD patients and mature neuronal cells (mDA) differentiated from these iPSCs. Combining expression and semantic similarity, a highly-correlated PD interactome was constructed that included interactions of established Parkinson's disease marker genes. A novel three-way comparative approach was employed, delineating topologically and functionally important genes. These genes showed involvement in pathways like Parkin-ubiquitin proteosomal system (UPS), immune associated biological processes and apoptosis. Of interest are three genes, eEF1A1, CASK, and PSMD6 that are linked to PARK2 activity in the cell and thereby form attractive candidate genes for understanding PD. Network biology approach delineated in this study can be applied to other neurodegenerative disorders for identification of important genetic regulators.     

Long-term observation of a pollination network: fluctuation in species and interactions, relative invariance of network structure and implications for estimates of specialization

We analysed the dynamics of a plant-pollinator interaction network of a scrub community surveyed over four consecutive years. Species composition within the annual networks showed high temporal variation. Temporal dynamics were also evident in the topology of the network, as interactions among plants and pollinators did not remain constant through time. This change involved both the number and the identity of interacting partners. Strikingly, few species and interactions were consistently present in all four annual plant-pollinator networks (53% of the plant species, 21% of the pollinator species and 4.9% of the interactions). The high turnover in species-to-species interactions was mainly the effect of species turnover (c. 70% in pairwise comparisons among years), and less the effect of species flexibility to interact with new partners (c. 30%). We conclude that specialization in plant-pollinator interactions might be highly overestimated when measured over short periods of time. This is because many plant or pollinator species appear as specialists in 1 year, but tend to be generalists or to interact with different partner species when observed in other years. The high temporal plasticity in species composition and interaction identity coupled with the low variation in network structure properties (e.g. degree centralization, connectance, nestedness, average distance and network diameter) imply (i) that tight and specialized coevolution might not be as important as previously suggested and (ii) that plant-pollinator interaction networks might be less prone to detrimental effects of disturbance than previously thought. We suggest that this may be due to the opportunistic nature of plant and animal species regarding the available partner resources they depend upon at any particular time.     

杭州湾北岸大型围隔海域人工生态系统的能量流动和网络分析

根据2006年在杭州湾北岸大型围隔海域进行的生态调查数据,利用EwE软件构建围隔海域人工生态系统的能量流动模型.模型由13个功能组构成,分别是肉食性鱼类、底栖捕食鱼类、浮游动物性鱼类、草食性鱼类、蟹类、虾类、软体动物、底栖动物、肉食性浮游动物、植食性浮游动物、大型藻类、浮游植物和有机碎屑,每一组都代表在生态系统中具有相似地位的有机体,基本覆盖了该人工生态系统能量流动的主要过程.能量流动分析表明,围隔海域人工生态系统中能量流动主要以碎屑食物链途径为主,其中植食性浮游动物在能量从低级向高层次转换中起关键作用.人工生态系统的营养级范围为1.00～3.90级,系统的能量流动主要有6级,来自初级生产者的能流效率为9.4%,来自碎屑的转换效率为9.8%,平均能量转换效率为9.6%.经生态网络分析,直接来源于碎屑的比例占总流量的57%,而直接来源于初级生产者的比例为43%,生态系统特征参数:总初级生产计算量/总呼吸量(TPP/TR)、系统物质和能量循环率(FCI)和系统聚合度(A)值分别为2.672、0.25、0.315,表明围隔海域人工生态系统目前正处于发育时期.该研究为首次利用Ecopath模型分析大型围隔海域人工生态系统的结构和能量流动,旨在为富营养化近岸海域的生态修复提供理论依据.     

Analysis of genetic diversity of domestic water buffaloes and anoas based on variations in the mitochondrial gene for cytochrome b

There are two major groups of domestic water buffaloes in East and Southeast Asia: swamp buffaloes and river buffaloes. Genetic diversity among swamp and river buffaloes was studied by DNA sequence analysis of the mitochondrial gene for cytochrome b. The results showed that each of the two groups has mitochondrial DNA (mtDNA) with a specific cytochrome b haplotype. The pairwise nucleotide sequence divergence was calculated to be 2·67% between swamp and river buffaloes, suggesting that they might have diverged from the ancestral populations of Asiatic domestic water buffaloes, approximately 1 million years ago. In addition, the sequences of the same gene from three subspecies of anoa (lowland, mountain and quarles anoa) were determined and compared with that of a domestic water buffalo. The sequence divergence was 1·2% for mountain anoa vs quarles anoa, 3·6% for mountain anoa vs lowland anoa and 3·3% for quarles anoa vs lowland anoa. Moreover, the sequence divergence between water buffaloes and anoas was found to be approximately 3·33%. Our results provide molecular evidence to support the taxonomic classification, namely, that Asiatic buffaloes may be classified into four lineages, swamp buffalo, river buffalo, lowland anoa and mountain plus quarles anoa. However, the sequence divergence values among these four groups were lower than the sequence divergence values found in the genus and subgenus levels within the subfamily Bovinae. In particular, in contrast to some proposed taxonomic classifications, our results indicated that mtDNA in the water buffaloes and anoas did not diverge at the genus level.     

Comparison of an exact and a simulation method for calculating gene extinction probabilities in pedigrees

A comparison is made between a much used simulation method, commonly called gene dropping, and the exact computational technique of peeling. These methods are illustrated using the problem of finding the distribution of the number of distinct ancestral genes surviving at an autosomal locus. Each method is used on several real zoo pedigrees, of varying size and complexity, and the results are compared. Gene dropping is found to be a good approximation to peeling, but for all but the most complex pedigrees surveyed, peeling is preferable. The relationship between heterozygosity and allelic variability is investigated.     

The biomarkers of fetal growth in intrauterine growth retardation and large for gestational age cases: from adipocytokines to a metabolomic all-in-one tool

Adipose tissue is no longer considered as inert; the literature describes the role it plays in the production of many substances, such as adiponectin, visfatin, ghrelin, S100B, apelin, TNF, IL-6 and leptin. These molecules have specific roles in humans and their potential as biomarkers useful for identifying alterations related to intrauterine growth retardation and large for gestational age neonates is emerging. Infants born in such conditions have undergone metabolic changes, such as fetal hypo- or hyperinsulinemia, which may lead to development of dysmetabolic syndrome and other chronic diseases in adulthood. In this review, these biomarkers are analyzed specifically and it is discussed how metabolomics may be an advantageous tool for detection, discrimination and prediction of metabolic alterations and diseases. Thus, a holistic approach, such as metabolomics, could help the prevention and early diagnosis of metabolic syndrome.