To construct a ceRNA regulatory network as prognostic biomarkers for bladder cancer

Emerging evidence demonstrates that competing endogenous RNA (ceRNA) hypothesis has played a role in molecular biological mechanisms of cancer occurrence and development. But the effect of ceRNA network in bladder cancer (BC), especially lncRNA‐miRNA‐mRNA regulatory network of BC, was not completely expounded. By means of The Cancer Genome Atlas (TCGA) database, we compared the expression of RNA sequencing (RNA‐Seq) data between 19 normal bladder tissue and 414 primary bladder tumours. Then, weighted gene co‐expression network analysis (WGCNA) was conducted to analyse the correlation between two sets of genes with traits. Interactions between miRNAs, lncRNAs and target mRNAs were predicted by MiRcode, miRDB, starBase, miRTarBase and TargetScan. Next, by univariate Cox regression and LASSO regression analysis, the 86 mRNAs obtained by prediction were used to construct a prognostic model which contained 4 mRNAs (ACTC1 + FAM129A + OSBPL10 + EPHA2). Then, by the 4 mRNAs in the prognostic model, a ceRNA regulatory network with 48 lncRNAs, 14 miRNAs and 4 mRNAs was constructed. To sum up, the ceRNA network can further explore gene regulation and predict the prognosis of BC patients.     

结节性甲状腺肿circRNA-miRNA-mRNA调控网络的构建

基于生物信息分析筛选结节性甲状腺肿中差异表达的环状RNA(circRNA),并揭示circRNA-miRNA-mRNA调控网络在结节性甲状腺肿中的作用。从GEO数据库中检索结节性甲状腺肿组织基因芯片数据,利用R软件筛选出差异表达的circRNA。联合多个生物信息数据库预测差异表达circRNA下游的miRNA及mRNA, 并对靶mRNA进行GO及KEGG富集分析。利用STRING在线数据库及Cytoscape软件筛选核心基因。确定了2个circRNA,42个miRNA及546个mRNA。GO及KEGG富集分析表明靶mRNA主要涉及细胞生长及基因表达调控过程。基于Cytoscape软件筛选出了14个核心基因(SP1、IGF1R、RPS6KB1、SMAD2、SMAD3、SMAD4、VEGFA、CCND1、CDK2、HSPA4、HIF1A、CREB1,NR3C1和STAT5A)。最终基于2个circRNA、11个miRNA和14个核心mRNA构建了circRNA-miRNA-mRNA调控网络。结节性甲状腺肿组织中异常表达的circRNA及相关的circRNA-miRNA-mRNA调控网络可能成为结节性甲状腺肿诊断与治疗的新靶点。     

Sweating the small stuff: microRNA discovery in plants

The class of small RNAs known as microRNAs (miRNAs) has a demonstrated role in the negative regulation of gene expression in both plants and animals. These small molecules have been shown to play a critical role in a wide range of developmental and physiological pathways. Although hundreds of different miRNAs have now been identified using cloning and computational approaches, characterization of their targets and biological roles has been more limited. New sequencing technologies promise to accelerate the sequencing of small RNAs and additional genetic and genomic strategies are being applied to assess their regulatory function on RNA targets. These technologies will enable the identification of large numbers of small RNAs from diverse species, and comparative genomics approaches based on these data are likely to identify additional miRNAs. Combined with bioinformatics and experimental approaches to separate miRNAs from short-interfering RNAs (siRNAs), the pace of miRNA discovery is likely to accelerate, leading to an improved understanding of miRNA function and biological significance.     

RNA Expression Profiling of Human iPSC-Derived Cardiomyocytes in a Cardiac Hypertrophy Model

Cardiac hypertrophy is an independent risk factor for cardiovascular disease and heart failure. There is increasing evidence that microRNAs (miRNAs) play an important role in the regulation of messenger RNA (mRNA) and the pathogenesis of various cardiovascular diseases. However, the ability to comprehensively study cardiac hypertrophy on a gene regulatory level is impacted by the limited availability of human cardiomyocytes. Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) offer the opportunity for disease modeling. Here we utilize a previously established in vitro model of cardiac hypertrophy to interrogate the regulatory mechanism associated with the cardiac disease process. We perform miRNA sequencing and mRNA expression analysis on endothelin 1 (ET-1) stimulated hiPSC-CMs to describe associated RNA expression profiles. MicroRNA sequencing revealed over 250 known and 34 predicted novel miRNAs to be differentially expressed between ET-1 stimulated and unstimulated control hiPSC-CMs. Messenger RNA expression analysis identified 731 probe sets with significant differential expression. Computational target prediction on significant differentially expressed miRNAs and mRNAs identified nearly 2000 target pairs. A principal component analysis approach comparing the in vitro data with human myocardial biopsies detected overlapping expression changes between the in vitro samples and myocardial biopsies with Left Ventricular Hypertrophy. These results provide further insights into the complex RNA regulatory mechanism associated with cardiac hypertrophy.