Integrated analysis of transcriptome profiling of lncRNAs and mRNAs in livers of type 2 diabetes mellitus.

Lan X ，Han J ，Wang B ，Sun M ... -  《-》

Identification of potential biomarkers and pathways associated with carotid atherosclerotic plaques in type 2 diabetes mellitus: A transcriptomics study.

Type 2 diabetes mellitus (T2DM) affects the formation of carotid atherosclerotic plaques (CAPs) and patients are prone to plaque instability. It is crucial to clarify transcriptomics profiles and identify biomarkers related to the progression of T2DM complicated by CAPs. Ten human CAP samples were obtained, and whole transcriptome sequencing (RNA-seq) was performed. Samples were divided into two groups: diabetes mellitus (DM) versus non-DM groups and unstable versus stable groups. The Limma package in R was used to identify lncRNAs, circRNAs, and mRNAs. Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, protein-protein interaction (PPI) network creation, and module generation were performed for differentially expressed mRNAs. Cytoscape was used to create a transcription factor (TF)-mRNA regulatory network, lncRNA/circRNA-mRNA co-expression network, and a competitive endogenous RNA (ceRNA) network. The GSE118481 dataset and RT-qPCR were used to verify potential mRNAs.The regulatory network was constructed based on the verified core genes and the relationships were extracted from the above network. In total, 180 differentially expressed lncRNAs, 343 circRNAs, and 1092 mRNAs were identified in the DM versus non-DM group; 240 differentially expressed lncRNAs, 390 circRNAs, and 677 mRNAs were identified in the unstable versus stable group. Five circRNAs, 14 lncRNAs, and 171 mRNAs that were common among all four groups changed in the same direction. GO/KEGG functional enrichment analysis showed that 171 mRNAs were mainly related to biological processes, such as immune responses, inflammatory responses, and cell adhesion. Five circRNAs, 14 lncRNAs, 46 miRNAs, and 54 mRNAs in the ceRNA network formed a regulatory relationship. C22orf34-hsa-miR-6785-5p-RAB37, hsacirc_013887-hsa-miR-6785-5p/hsa-miR-4763-5p/hsa-miR-30b-3p-RAB37, MIR4435-1HG-hsa-miR-30b-3p-RAB37, and GAS5-hsa-miR-30b-3p-RAB37 may be potential RNA regulatory pathways. Seven upregulated mRNAs were verified using the GSE118481 dataset and RT-qPCR. The regulatory network included seven mRNAs, five circRNAs, six lncRNAs, and 14 TFs. We propose five circRNAs (hsacirc_028744, hsacirc_037219, hsacirc_006308, hsacirc_013887, and hsacirc_045622), six lncRNAs (EPB41L4A-AS1, LINC00969, GAS5, MIR4435-1HG, MIR503HG, and SNHG16), and seven mRNAs (RAB37, CCR7, CD3D, TRAT1, VWF, ICAM2, and TMEM244) as potential biomarkers related to the progression of T2DM complicated with CAP. The constructed ceRNA network has important implications for potential RNA regulatory pathways.

Yu T ，Xu B ，Bao M ，Gao Y ，Zhang Q ，Zhang X ，Liu R ... -  《Frontiers in Endocrinology》

Integrated analysis of long noncoding RNA-associated competing endogenous RNA network in periodontitis.

Long noncoding RNAs (lncRNAs) play critical and complex roles in regulating various biological processes of periodontitis. This bioinformatic study aims to construct a putative competing endogenous RNA (ceRNA) network by integrating lncRNA, miRNA and mRNA expression, based on high-throughput RNA sequencing and microarray data about periodontitis. Data from 1 miRNA and 3 mRNA expression profiles were obtained to construct the lncRNA-associated ceRNA network. Gene Ontology enrichment analysis and pathway analysis were performed using the Gene Ontology website and Kyoto Encyclopedia of Genes and Genomes. A protein-protein interaction network was constructed based on the Search Tool for the retrieval of Interacting Genes/Proteins. Transcription factors (TFs) of differentially expressed genes were identified based on TRANSFAC database and then a regulatory network was constructed. Through constructing the dysregulated ceRNA network, 6 genes (HSPA4L, PANK3, YOD1, CTNNBIP1, EVI2B, ITGAL) and 3 miRNAs (miR-125a-3p, miR-200a, miR-142-3p) were detected. Three lncRNAs (MALAT1, TUG1, FGD5-AS1) were found to target both miR-125a-3p and miR-142-3p in this ceRNA network. Protein-protein interaction network analysis identified several hub genes, including VCAM1, ITGA4, UBC, LYN and SSX2IP. Three pathways (cytokine-cytokine receptor, cell adhesion molecules, chemokine signaling pathway) were identified to be overlapping results with the previous bioinformatics studies in periodontitis. Moreover, 2 TFs including FOS and EGR were identified to be involved in the regulatory network of the differentially expressed genes-TFs in periodontitis. These findings suggest that 6 mRNAs (HSPA4L, PANK3, YOD1, CTNNBIP1, EVI2B, ITGAL), 3 miRNAs (hsa-miR-125a-3p, hsa-miR-200a, hsa-miR-142-3p) and 3 lncRNAs (MALAT1, TUG1, FGD5-AS1) might be involved in the lncRNA-associated ceRNA network of periodontitis. This study sought to illuminate further the genetic and epigenetic mechanisms of periodontitis through constructing an lncRNA-associated ceRNA network.

Li S ，Liu X ，Li H ，Pan H ，Acharya A ，Deng Y ，Yu Y ，Haak R ，Schmidt J ，Schmalz G ，Ziebolz D ... -  《-》

Identification of Functional Genes in Pterygium Based on Bioinformatics Analysis.

The competing endogenous RNA (ceRNA) network regulatory has been investigated in the occurrence and development of many diseases. This research aimed at identifying the key RNAs of ceRNA network in pterygium and exploring the underlying molecular mechanism. Differentially expressed long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and mRNAs were obtained from the Gene Expression Omnibus (GEO) database and analyzed with the R programming language. LncRNA and miRNA expressions were extracted and pooled by the GEO database and compared with those in published literature. The lncRNA-miRNA-mRNA network was constructed of selected lncRNAs, miRNAs, and mRNAs. Metascape was used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses on mRNAs of the ceRNA network and to perform Protein-Protein Interaction (PPI) Network analysis on the String website to find candidate hub genes. The Comparative Toxicogenomic Database (CTD) was used to find hub genes closely related to pterygium. The differential expressions of hub genes were verified using the reverse transcription-real-time fluorescent quantitative PCR (RT-qPCR). There were 8 lncRNAs, 12 miRNAs, and 94 mRNAs filtered to construct the primary ceRNA network. A key lncRNA LIN00472 ranking the top 1 node degree was selected to reconstruct the LIN00472 network. The GO and KEGG pathway enrichment showed the mRNAs in ceRNA networks mainly involved in homophilic cell adhesion via plasma membrane adhesion molecules, developmental growth, regulation of neuron projection development, cell maturation, synapse assembly, central nervous system neuron differentiation, and PID FOXM1 PATHWAY. According to the Protein-Protein Interaction Network (PPI) analysis on mRNAs in LINC00472 network, 10 candidate hub genes were identified according to node degree ranking. Using the CTD database, we identified 8 hub genes closely related to pterygium; RT-qPCR verified 6 of them were highly expressed in pterygium. Our research found LINC00472 might regulate 8 hub miRNAs (miR-29b-3p, miR-183-5p, miR-138-5p, miR-211-5p, miR-221-3p, miR-218-5p, miR-642a-5p, miR-5000-3p) and 6 hub genes (CDH2, MYC, CCNB1, RELN, ERBB4, RB1) in the ceRNA network through mainly PID FOXM1 PATHWAY and play an important role in the development of pterygium.

Xu Y ，Qiao C ，He S ，Lu C ，Dong S ，Wu X ，Yan M ，Zheng F ... -  《-》

Non-coding RNA Identification in Osteonecrosis of the Femoral Head Using Competitive Endogenous RNA Network Analysis.

To investigate the regulatory network of long non-coding RNA (lncRNA) as competing endogenous RNAs (ceRNAs) in osteonecrosis of the femoral head (ONFH). The gene expression profile GSE74089 of ONFH and microRNA (miRNA) expression profile of GSE89587 were obtained from the Gene Expression Omnibus (GEO) database. The GSE74089 contained four ONFH samples and four controls. The GSE89587 included 10 ONFH samples and 10 control samples. The differentially expressed lncRNAs (DE-lncRNAs) and DE-mRNAs between ONFH group and control group were identified from GSE74089 using the limma package based on criteria of adjusted P value <0.05 and |log fold change (FC)| ≥2. The DEmiRNAs between ONFH group and control group were screened from GSE89587 on the basis of adjusted P value <0.05. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway for DE-mRNAs were analyzed using DAVID 6.7 and GSEA 3.0, respectively. Coexpressed lncRNA-mRNA pairs were identified by corr.test method in R based on the criteria of adjusted P value <0.01 and |r| ≥ 0.9. A ceRNA network was constructed and visualized using cytoscape 3.7.0 by integrating the DE-lncRNA, DE-miRNA, and DEmRNA data. The key mRNAs and lncRNAs in the ceRNA network were further validated in an independent dataset of GSE123568. Based on our analysis, a total of 28 DE-lncRNAs, 1403 DE-mRNAs, and 134 DE-miRNAs were identified, respectively. The DE-mRNAs were significantly enriched in the function of "skeletal system development," "collagen fibril organization," "blood vessel development," and "regulation of nervous system development." Besides, 72 KEGG pathways, including eight active pathways and 64 suppressed pathways were identified, including which immune pathway was the most significantly activated one and which ribosome-related function was the most suppressed. A co-expression network including 161 DE-mRNAs and 16 DE-lncRNAs was built. Highly connected nodes were identified among lncRNAs such as H19, C20orf203, LINC00355, SFTA3, CRNDE, CASC2, LINC00494, C9orf163, C10orf91, and LINC00301. The ceRNA network indicated that lncRNA H19 functioned as a ceRNA of hsa-miR-519b-3p and hsa-miR-296-5p in ANKH and ECHDC1 regulation; lncRNA C9orf163 functioned as a ceRNA of hsa-miR-424-5p in CCNT1 regulation. The expression trends of ANKH, CCNT1, and C9orf163 were successfully validated in independent dataset of GSE123568. The ceRNAs of lncRNA H19- hsa-miR-519b-3p/hsa-miR-296-5p-ANKH and lncRNA c9orf163- hsa-miR-424-5p-CCNT1 might play important roles in ONFH development. Our research provided an understanding of the important role of lncRNA-related ceRNAs in ONFH.

Han N ，Li Z 《-》