Gene Ontology and KEGG Pathway Enrichment Analysis of a Drug Target-Based Classification System

Drug-target interaction (DTI) is a key aspect in pharmaceutical research. With the ever-increasing new drug data resources, computational approaches have emerged as powerful and labor-saving tools in predicting new DTIs. However, so far, most of these predictions have been based on structural similarities rather than biological relevance. In this study, we proposed for the first time a “GO and KEGG enrichment score” method to represent a certain category of drug molecules by further classification and interpretation of the DTI database. A benchmark dataset consisting of 2,015 drugs that are assigned to nine categories ((1) G protein-coupled receptors, (2) cytokine receptors, (3) nuclear receptors, (4) ion channels, (5) transporters, (6) enzymes, (7) protein kinases, (8) cellular antigens and (9) pathogens) was constructed by collecting data from KEGG. We analyzed each category and each drug for its contribution in GO terms and KEGG pathways using the popular feature selection “minimum redundancy maximum relevance (mRMR)” method, and key GO terms and KEGG pathways were extracted. Our analysis revealed the top enriched GO terms and KEGG pathways of each drug category, which were highly enriched in the literature and clinical trials. Our results provide for the first time the biological relevance among drugs, targets and biological functions, which serves as a new basis for future DTI predictions.     

miR-29a靶基因预测及其相关生物信息学分析

目的:通过对miR-29a进行靶基因预测及相关生物信息学分析,为miR-29a靶基因的实验验证提供数据支持,以期为深入研究miR-29a的生物学功能和调控机制提供理论指导。方法:利用PubMed检索miR-29a相关文章,通过miRBase在线工具分析miR-29a序列。应用TargetScan及miRNAda两种计算方法预测miR-29a靶基因并取其交集作为分析的基因集合,分别进行基因本体(gene ontology,GO)中的分子功能和生物学过程以及KEGG(Kyoto Encyclopedia of Genes and Genomes)生物通路富集分析。结果:(1)miR-29a序列在多物种间具有高度保守性。(2)两种方法预测miR-29a靶基因交集共191个。(3)miR-29a靶基因GO分子功能集中于转录因子活性、DNA结合和钙离子结合等(P0.05);miR-29a靶基因GO生物学过程集中于调控转录、细胞粘附、细胞增殖与凋亡等(P0.05);KEGG生物通路主要富集于PI3K-AKT信号通路、JAK-STAT信号通路、T细胞受体信号通路和胰岛素信号通路等信号转导通路,以及肺小细胞癌和子宫内膜癌等疾病通路(P0.05)。结论:miR-29a可能通过参与多个靶基因信号通路的调控,在机体的多种生理病理过程中发挥重要作用,是一个颇有研究价值的生物学靶标。     

Identification of MicroRNAs and Target Genes in the Fruit and Shoot Tip of Lycium chinense: A Traditional Chinese Medicinal Plant

Although Lycium chinense (goji berry) is an important traditional Chinese medicinal plant, little genome information is available for this plant, particularly at the small-RNA level. Recent findings indicate that the evolutionary role of miRNAs is very important for a better understanding of gene regulation in different plant species. To elucidate small RNAs and their potential target genes in fruit and shoot tissues, high-throughput RNA sequencing technology was used followed by qRT-PCR and RLM 5’-RACE experiments. A total of 60 conserved miRNAs belonging to 31 families and 30 putative novel miRNAs were identified. A total of 62 significantly differentially expressed miRNAs were identified, of which 15 (14 known and 1 novel) were shoot-specific, and 12 (7 known and 5 novel) were fruit-specific. Additionally, 28 differentially expressed miRNAs were recorded as up-regulated in fruit tissues. The predicted potential targets were involved in a wide range of metabolic and regulatory pathways. GO (Gene Ontology) enrichment analysis and the KEGG (Kyoto Encyclopedia of Genes and Genomes) database revealed that “metabolic pathways” is the most significant pathway with respect to the rich factor and gene numbers. Moreover, five miRNAs were related to fruit maturation, lycopene biosynthesis and signaling pathways, which might be important for the further study of fruit molecular biology. This study is the first, to detect known and novel miRNAs, and their potential targets, of L. chinense. The data and findings that are presented here might be a good source for the functional genomic study of medicinal plants and for understanding the links among diversified biological pathways.     

Genome-wide identification and characterization of perirenal adipose tissue microRNAs in rabbits fed a high-fat diet

MicroRNAs (miRNAs) are a class of endogenous single-stranded RNA molecules that play an important role in gene regulation in animals by pairing with target gene mRNA. Extensive evidence shows that miRNAs are key players in metabolic regulation and the development of obesity. However, the systemic understanding of miRNAs in the adipogenesis of obese rabbits need further investigation. Here, seven small RNA libraries from rabbits fed either a standard normal diet (SND; n=3) or high-fat diet (HFD; n=4) were constructed and sequenced. Differentially expressed (DE) miRNAs were identified using the edgeR data analysis package from R. Software miRanda and RNAhybrid were used to predict the target genes of miRNAs. To further explore the functions of DE miRNAs, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed. A total of 81449996 clean reads were obtained from the seven libraries, of which, 52 known DE miRNAs (24 up-regulated, 28 down-regulated) and 31 novel DE miRNAs (14 up-regulated, 17 down-regulated) were identified. GO enrichment analysis revealed that the DE miRNAs target genes were involved in intermediate filament cytoskeleton organization, intermediate filament-based process, and α-tubulin binding. DE miRNAs were involved in p53 signaling, linoleic acid metabolism, and other adipogenesis-related KEGG pathways. Our study further elucidates the possible functions of DE miRNAs in rabbit adipogenesis, contributing to the understanding of rabbit obesity.     

小儿脓毒症休克相关基因的筛选及网络构建

为探究脓毒症休克与SIRS的差异表达基因及网络的构建,筛选潜在的核心基因,从GEO数据库下载相关基因表达谱GSE26378,数据分为脓毒症休克与SIRS各29个样本,通过在线软件GCBI对其进行标准化及差异基因筛选;对差异基因进行GO分析;基于KEGG进行功能通路分析以及基因信号网络分析;差异基因共表达网络分析。结果表明:两组中总共有1 456个基因被识别为差异基因(P0.05),与SIRS组相比,脓毒症休克组中有条859条下调基因,597条上调基因。GO功能富集分析显示差异基因主要参与了细胞周期、细胞免疫、细胞代谢。KEGG功能通路分析显示差异基因主要参与了MAPK信号通路、P53信号通路、wnt信号通路、细胞凋亡信号通路,细胞周期受体信号通路等。共表达分析发现基因CCNB1、NUSAP1、OIP5、SHCBP1、ZWINT、TOP2A、DLGAP5等位于网络中央部位,而基因信号网络分析发现基因PLCB1、PIK3CA、STAT3、CAMK2D、PRKCB、CREB1位于网络核心。基因芯片分析有助于发现脓毒症休克与SIRS患儿外周血单核细胞在转录组学上的改变,而生物信息学网络分析有助于发现潜在的靶点。     

Identification of Key Genes and Pathways Involved in the Heterogeneity of Intrinsic Growth Ability Between Neurons After Spinal Cord Injury in Adult Zebrafish

In the adult central nervous system (CNS), axon regeneration is a major hurdle for functional recovery after trauma. The intrinsic growth potential of an injured axon varies widely between neurons. The underlying molecular mechanisms of such heterogeneity are largely unclear. In the present study, the adult zebrafish dataset GSE56842 were downloaded. Differentially expressed genes (DEGs) were sorted and deeply analyzed by bioinformatics methods. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs were performed with the DAVID. A DEGs-associated protein–protein interaction network was constructed from the STRING database and visualized with Cytoscape software. In total, 621 DEGs were identified. GO analysis showed that the biological processes of DEGs focused mainly on the Notch signaling pathway, cell differentiation and positive regulation of neuron differentiation. The molecular functions mainly included calcium-transporting ATPase activity and calcium ion binding and structural constituents of the cytoskeleton. The cellular components included the plasma membrane, spectrin, and cytoplasmic and membrane-bound vesicles. KEGG pathway analysis showed that these DEGs were mainly involved in the metabolic pathway and Notch signaling pathway, and subnetworks revealed that genes within modules were involved in the metabolic pathway, Wnt signaling pathway, and calcium signaling pathway. This study identified DEG candidate genes and pathways involved in the heterogeneity of the intrinsic growth ability between neurons after spinal cord injury in adult zebrafish, which could facilitate our understanding of the molecular mechanisms underlying axon regeneration, and these candidate genes and pathways could be therapeutic targets for the treatment of CNS injury.

     

GSEA-SNP identifies genes associated with Johne’s disease in cattle

SNP-based gene-set enrichment analysis from single nucleotide polymorphisms, or GSEA-SNP, is a tool to identify candidate genes based on enrichment analysis of sets of genes rather than single SNP associations. The objective of this study was to identify modest-effect genes associated with Mycobacterium avium subsp. paratuberculosis (Map) tissue infection or fecal shedding using GSEA-SNP applied to KEGG pathways or Gene Ontology (GO) gene sets. The Illumina Bovine SNP50 BeadChip was used to genotype 209 Holstein cows for the GSEA-SNP analyses. For each of 13,744 annotated genes genome-wide located within 50 kb of a Bovine SNP50 SNP, the single SNP with the highest Cochran-Armitage Max statistic was used as a proxy statistic for that gene’s strength of affiliation with Map. Gene-set enrichment was tested using a weighted Kolmogorov-Smirnov-like running sum statistic with data permutation to adjust for multiple testing. For tissue infection and fecal shedding, no gene sets in KEGG pathways or in GO sets for molecular function or cellular component were enriched for signal. The GO biological process gene set for positive regulation of cell motion (GO:0051272, q = 0.039, 5/11 genes contributing to the core enrichment) was enriched for Map tissue infection, while no GO biological process gene sets were enriched for fecal shedding. GSEA-SNP complements traditional SNP association approaches to identify genes of modest effects as well as genes with larger effects as demonstrated by the identification of one locus that we previously found to be associated with Map tissue infection using a SNP-by-SNP genome-wide association study.     

林麝及其近缘物种编码区微卫星分布规律及功能分析

麝科和鹿科动物均属于偶蹄反刍类动物,具有重要的经济价值。通过系统的微卫星序列 (Simple sequences repeats, SSRs) 从基因组水平揭示物种间的系统进化关系,探索微卫星序列的基因功能及其富集的信号通路,目前仍缺乏相关研究。随着林麝 (Moschus berezovskii)、原麝 (Moschus moschiferus)、小麂 (Muntiacus reevesi)、赤麂 (Muntiacus vaginalis) 和马鹿 (Cervus elaphus) 基因组测序的完成,本文利用生物信息学方法提取了这些动物蛋白质编码区 (coding sequences, CDS) 序列,统计和分析了其CDS区微卫星序列分布规律及其生物学功能,探索了含SSR 基因富集的信号通路及其与疾病的关联性。结果表明,林麝、原麝、小麂、赤麂和马鹿蛋白质编码区含SSR序列的基因所占比例分别为6.96% (1 696个)、7.18% (2 359个)、7.29% (3 005个)、7.36% (1 916个) 和7.48% (1 924个),并且这5种动物CDS区SSRs分布模式具有相似性,均是三倍体核苷酸 (即三核苷酸和六核苷酸) SSRs最多,分别为96.85%、94.87%、65.44%、64.23%和88.04%。GO功能富集表明,林麝与其他4种动物蛋白质编码区SSR序列在分子功能、细胞组成和生物学过程3个方面具有较多共同显著富集的功能,包括DNA结合、染色质和生长发育等。KEGG 通路分析表明,林麝及其他4种动物蛋白质编码区SSR序列具有7个共同显著富集的KEGG通路,包括遗传信息调控蛋白家族、转录因子、染色体及相关蛋白、剪接体、转录机制和Notch信号通路和成体糖尿病。通过对林麝编码区含SSR关键免疫基因及其相关联的KEGG通路进行分析,发现10个含SSR的关键免疫基因对应的KEGG通路与疾病密切相关。     

基于网络药理学的益母草治疗产后腹痛的潜在分子机制研究

本文通过网络药理学方法探讨益母草治疗产后腹痛的潜在分子机制。首先根据TCMSP数据库和文献挖掘益母草的活性成分,在TCMSP、Swiss Target Prediction、Similarity ensemble approach平台上检索活性成分靶点,在OMIM、GeneCards上检索产后腹痛靶点,得到益母草-产后腹痛交集靶点。利用STRING数据库构建蛋白互作(PPI)网络,接着利用Cytoscape软件对PPI网络进行拓扑分析,并对拓扑分析筛选出的核心靶点进行基因本体论(Gene Ontology,GO)分析和京都基因与基因组百科全书(Kyoto Encyclopedia of Genes and Genomes,KEGG)通路分析。最后利用免疫组化实验验证益母草对流产大鼠模型子宫组织中PGF2αR、MMP9、TIMP1、VEGFA、VEGFR2蛋白表达水平的影响。最终得到益母草活性成分10种,与产后腹痛相关靶点144个;通过PPI网络分析筛选出118个靶点,进一步拓扑分析后得到98个节点;然后对这98个节点进行GO和KEGG注释。GO分析得到1151个生物过程(BP)条目,97个细胞组成(CC)条目,122个分子功能(MF)条目;KEGG分析得到41条通路,主要涉及雌激素、PI3K-Akt、MAPK、HIF-1信号通路等。最后免疫组化实验证明益母草可显著抑制流产模型大鼠子宫组织中PGF2αR、MMP9蛋白上调和TIMP1、VEGFR2蛋白下调。本研究通过网络药理学和免疫组化实验验证,显示益母草治疗产后腹痛是多成分、多靶点、多途径相互作用的结果,为益母草的临床应用提供了一定的理论依据。     

GS2PATH: a web-based integrated analysis tool for finding functional relationships using gene ontology and biochemical pathway data

GS2PATH is a Web-based pipeline tool to permit functional enrichment of a given gene set from prior knowledge databases, including gene ontology (GO) database and biological pathway databases. The tool also provides an estimation of gene set enrichment, in GO terms, from the databases of the KEGG and BioCarta pathways, which may allow users to compute and compare functional over-representations. This is especially useful in the perspective of biological pathways such as metabolic, signal transduction, genetic information processing, environmental information processing, cellular process, disease, and drug development. It provides relevant images of biochemical pathways with highlighting of the gene set by customized colors, which can directly assist in the visualization of functional alteration.

Availability     

Prognostic value of metabolic genes in lung adenocarcinoma via integrative analyses

BackgroundLung adenocarcinoma (LUAD) is the most common malignant lung tumor. Metabolic pathway reprogramming is an important hallmark of physiologic changes in cancers. However, the mechanisms through which these metabolic genes and pathways function in LUAD as well as their prognostic values have not been fully established.MethodsFour publicly available datasets from GEO and TCGA were used to identify differentially expressed genes (DEGs) in LUAD, which were then subjected to GO and KEGG pathway enrichment analysis. Associations between metabolic gene expressions with overall survival, tumor stage, TP53 mutation status, and infiltrated immune cells were investigated. Protein-protein interactions were evaluated using GeneMANIA and Metascape.ResultsBy integrating four public datasets, 247 DEGs were identified in LUAD. These DEGs were significantly enriched in regulation of chromosome segregation, centromeric region, and histone kinase activity GO terms, as well as in cell cycle, p53 signaling pathway, metabolic pathways, and other KEGG pathways. Elevated expressions of ten metabolic genes in LUAD were significantly associated with poor survival outcomes. These metabolic genes were highly expressed in more advanced tumor stage and TP53 mutated patients. Moreover, expression levels were significantly correlated with tumor-infiltrating immune cells. PPI interaction analysis revealed that the top 20 genes interacting with each metabolic gene were significantly enriched in DNA replication, response to radiation, and central carbon metabolism in cancer.ConclusionThis study elucidates on molecular changes in metabolic genes in LUAD, which may inform the development of genetically oriented diagnostic approaches and effective treatment options.     

基于蛋白互作网络识别非小细胞肺癌相关基因功能模块

本研究对非小细胞肺癌(non-small cell lung carcinoma,NSCLC)基因表达数据进行差异表达分析,并与蛋白质相互作用网络(PPIN)数据进行整合,进一步利用Heinz搜索算法识别NSCLC相关的基因功能模块,并对模块中的基因进行功能(GO term)和通路(KEGG)富集分析,旨在探究肺癌发病分子机制。蛋白互作网络分析得到一个包含96个基因和117个相互作用的功能模块,以及8个对NSCLC的发生和发展起到关键作用候选基因标志物。富集分析结果表明,这些基因主要富集于基因转录催化及染色质调控等生物学过程,并在基础转录因子、黏着连接、细胞周期、Wnt信号通路及HTLV-Ⅰ感染等生物学通路中发挥重要作用。本研究对非小细胞肺癌相关的基因和生物学通路进行预测,可用于肺癌的早期诊断和早期治疗,以降低肺癌死亡率。     

单细胞测序分析人类胚胎干细胞神经分化的分子机制

目的 探讨人类胚胎干细胞(ESCs)分化为神经细胞的关键性靶基因及分子机制,为临床靶向治疗神经康复患者提供分子理论依据.方法 基于GEO数据平台芯片,采用单细胞测序方法(scRNA-seq),利用R语言从多分子维度(单细胞差异基因、蛋白互作网络和基因通路等)分析人类ESCs分化过程中的关键Marker基因并利用质控和数...     

High-dose dexamethasone injection disordered metabolism and multiple protein kinases expression in the mouse kidney

Glucocorticoids (GCs) have been widely used in clinical treatment as anti-inflammatory, anti-shock and immunosuppressive medicines. However, the effect of excessive GCs on immune response and metabolism of kidney remains unclear. Here, we profiled the gene expression of kidney from mice with high-dose dexamethasone (DEX) treatment. A total of 1193 differentially expressed genes (DEGs) were screened in DEX treatment group compared with the saline group, including 715 down- regulated and 478 up-regulated. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of these DEGs showed extracellular matrix (ECM)–receptor interaction, cell adhesion molecules signaling pathway were significantly enriched, and that the vast majority of DEGs were involved in monocarboxylic acid metabolism, leukocyte cell–cell adhesion and fatty acid metabolism. Gene set enrichment analysis (GSEA) revealed that DEGs were strongly associated with immune-response and cell adhesion gene sets, such as Fc γ R-mediated phagocytosis, leukocyte transendothelial migration, T-cell receptor signaling pathway, cell adhesion, ECM–receptor interaction and focal adhesion-associated pathways. KEGG pathway analysis of differentially expressed kinases (DEKs) showed T-cell receptor and forkhead box class O signaling pathway were enriched. Furthermore, we found multiple protein kinases expression were dysregulated greatly after dexamethasone treatment, including classical effector of GCs stimulation-serum and GC-regulated kinase. These protein kinases are involved in multiple signaling pathways in mice kidney, such as mitogen-activated protein kinase (MAPK) and phosphoinositide 3-kinase (PI3K)/Akt signaling pathway. We profiled the gene expression of the kidney from high-dose dexamethasone-treated mice and provided important information for further study the mechanism of side effects of GCs in clinical therapy.