Unveiling transcription factor regulation and differential co-expression genes in Duchenne muscular dystrophy

Construction of a TFs-miRNA-mRNA network related to idiopathic pulmonary fibrosis

Background

The transcription factors (TFs)-microRNA (miRNA)-messenger RNA (mRNA) network plays an important role in a variety of diseases. However, the relationship between the TFs-miRNA-mRNA network and idiopathic pulmonary fibrosis (IPF) remains unclear.

Methods

The GSE110147 and GSE53845 datasets from the Gene Expression Omnibus (GEO) database were used to process differentially expressed genes (DEGs) analysis, gene set enrichment analysis (GSEA), weighted gene co-expression network analysis (WGCNA), as well as Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. The GSE13316 dataset was used to perform differentially expressed miRNAs (DEMs) analysis and TFs prediction. Finally, a TFs-miRNA-mRNA network related to IPF was constructed, and its function was evaluated by Gene Ontology (GO) and KEGG analyses. Also, 19 TFs in the network were verified by quantitative real time polymerase chain reaction (qRT-PCR).

Results

Through our analysis, 53 DEMs and 2,630 DEGs were screened. The GSEA results suggested these genes were mainly related to protein digestion and absorption. The WGCNA results showed that these DEGs were divided into eight modules, and the GO and KEGG analyses results of blue module genes showed that these 86 blue module genes were mainly enriched in cilium assembly and cilium organization. Moreover, a TFs-miRNA-mRNA network comprising 25 TFs, 11 miRNAs, and 60 mRNAs was constructed. Ultimately, the functional enrichment analysis showed that the TFs-miRNA-mRNA network was mainly related to the cell cycle and the phosphatidylinositol 3 kinase-protein kinase B (PI3K-Akt) signaling pathway. Furthermore, experimental verification of the TFs showed that ARNTL, TRIM28, EZH2, BCOR, and ASXL1 were sufficiently up-regulated in the transforming growth factor (TGF)-β1 treatment groups, while BCL6, BHLHE40, FOXA1, and EGR1 were significantly down-regulated.

Conclusions

The novel TFs-miRNA-mRNA network that we constructed could provide new insights into the underlying molecular mechanisms of IPF. ARNTL, TRIM28, EZH2, BCOR, ASXL1, BCL6, BHLHE40, FOXA1, and EGR1 may play important roles in IPF and become effective biomarkers for diagnosis and treatment.

Analysis of Differentially Expressed Long Non-coding RNAs and the Associated TF-mRNA Network in Tongue Squamous Cell Carcinoma

Accumulating evidence indicates that long non-coding RNAs (lncRNAs) play crucial roles in tongue squamous cell carcinoma (TSCC) tumorigenesis. However, the comprehensive regulation of lncRNAs-transcription factors (TFs)-messenger RNAs (mRNAs) in TSCC remains largely unknown. The purpose of this study was to identify aberrantly expressed lncRNAs and the associated TF-mRNA network in TSCC. To explore lncRNA and mRNA expression profiles and their biological functions in TSCC, we surveyed the lncRNA and mRNA expression profiles of TSCC and adjacent tissues using next-generation RNA sequencing in six patients. Thousands of significantly differentially expressed lncRNAs (DELs) and mRNAs (DEGs) were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to demonstrate the principal functions of the significantly dysregulated lncRNAs and genes. A total of 40 DELs were screened between TSCC and adjacent non-cancerous tissues. Results obtained from GEPIA and StarBase confirmed the expression levels of nine pivotal DELs obtained in our study. Three of the nine deregulated DELs were identified to have a significant impact on the overall survival of TSCC patients, which were evaluated with GEPIA and StarBase. LncMAP was used to predict the lncRNA-TF-mRNA triplets in TSCC. Furthermore, based on these results, we established lncRNA-TF-mRNA coexpression networks for the up- and downregulated lncRNAs using Cytoscape. We also found that among the nine pivotal lncRNAs, there is limited research on the abnormally expressed lncRNAs, including RP11-54H7.4, CTD-2545M3.8, RP11-760H22.2, RP4-791M13.3, and LINC01405, in TSCC pathogenesis. This is the first study to show that RP11-54H7.4, LINC00152, and LINC01405 can be acted as a prognostic target for TSCC. Our findings provide a novel perspective and lay the foundation for future research on the potential roles of lncRNAs, TFs, and mRNAs in TSCC. Verification of the potential lncRNA-TF-mRNA regulatory networks will provide a more comprehensive understanding of the pathogenesis of TSCC.

Microarray Analysis For Expression Profiles of lncRNAs and circRNAs in Rat Liver after Brain-Dead Donor Liver Transplantation

The mechanisms underlying severe liver injury after brain-dead (BD) donor liver transplantation (BDDLT) remain unclear. In this study, we aimed to explore the roles of lncRNAs and circRNAs in liver injury after BDDLT. Rat liver injury was detected in the sham, BD, control, and BDDLT groups. We examined the expression profiles of lncRNAs and circRNAs in the livers of the BDDLT and control group using microarray analysis. The main functions of the differentially expressed genes were analyzed by gene ontology (GO) and KEGG pathway enrichment analysis. In addition, we used bioinformatic analyses to construct related expression networks. Liver injury was aggravated in the BD and BDDLT groups. We found various mRNAs, lncRNAs, and circRNAs that were differentially expressed in the BDDLT group compared with those in the control group. Coding-noncoding gene co-expression (CNC) network analysis showed that expression of the lncRNA LOC102553657 was associated with that of the apoptosis-related genes including HMOX1 and ATF3. Furthermore, competing endogenous RNAs (ceRNAs) network analysis revealed that the lncRNA LOC103692832 and rno_circRNA_007609 were ceRNAs of rno-miR-135a-5p targeting Atf3, Per2, and Mras. These results suggest that lncRNAs and circRNAs play important roles in the pathogenesis and development of liver injury during BDDLT.

Comprehensive analysis of differentially expressed profiles of lncRNAs and circRNAs with associated co-expression and ceRNA networks in bladder carcinoma

Accumulating evidences indicate that long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs) play important roles in tumorigenesis. However, the mechanisms remain largely unknown. To explore lncRNAs and circRNAs expression profiling and their biological functions in bladder cancer, we surveyed the lncRNA/circRNA and mRNA expression profiles of bladder cancer and para-cancer tissues using microarray for four patients. Thousands of significantly changed lncRNAs and mRNAs as well as hundreds of circRNAs were identified. Five dysregulated lncRNAs and four mRNAs were confirmed by quantitative real-time PCR in 30 pairs of samples. GO and KEGG pathway enrichment analyses were executed to determine the principal functions of the significantly deregulated genes. Further more, we constructed correlated expression networks including coding-noncoding co-expression (CNC), competing endogenous RNAs (ceRNA), cis regulation, lncRNAs-transcription factor (TF)-mRNA with bioinformatics methods. Co-expression analysis showed lncRNA APLP2 expression is correlated with apoptosis-related genes, including PTEN and TP53INP1. CeRNA network inferred that lncRNA H19 and circRNA MYLK could bind competitively with miRNA-29a-3p increasing target gene DNMT3B, VEGFA and ITGB1 expressions. Moreover, the nearby genes pattern displayed that overexpressing ADAM2 and C8orf4 are cis-regulated by lncRNA RP11-359E19.2, involving in progression of bladder cancer. In addition, lncRNAs-TF-mRNA diagram indicated that lncRNA BC041488 could trans-regulate CDK1 mRNA expression through SRF transcription factor. Taken together, these results suggested lncRNAs and circRNAs could implicate in the pathogenesis and development of bladder cancer. Our findings provide a novel perspective on lncRNAs and circRNAs and lay the foundation for future research of potential roles of lncRNAs and circRNAs in bladder carcinoma.

Peroxisome Proliferator-activated Receptor γ Coactivator-1 α Isoforms Selectively Regulate Multiple Splicing Events on Target Genes

Endurance and resistance exercise training induces specific and profound changes in the skeletal muscle transcriptome. Peroxisome proliferator-activated receptor γ coactivator-1 α (PGC-1α) coactivators are not only among the genes differentially induced by distinct training methods, but they also participate in the ensuing signaling cascades that allow skeletal muscle to adapt to each type of exercise. Although endurance training preferentially induces PGC-1α1 expression, resistance exercise activates the expression of PGC-1α2, -α3, and -α4. These three alternative PGC-1α isoforms lack the arginine/serine-rich (RS) and RNA recognition motifs characteristic of PGC-1α1. Discrete functions for PGC-1α1 and -α4 have been described, but the biological role of PGC-1α2 and -α3 remains elusive. Here we show that different PGC-1α variants can affect target gene splicing through diverse mechanisms, including alternative promoter usage. By analyzing the exon structure of the target transcripts for each PGC-1α isoform, we were able to identify a large number of previously unknown PGC-1α2 and -α3 target genes and pathways in skeletal muscle. In particular, PGC-1α2 seems to mediate a decrease in the levels of cholesterol synthesis genes. Our results suggest that the conservation of the N-terminal activation and repression domains (and not the RS/RNA recognition motif) is what determines the gene programs and splicing options modulated by each PGC-1α isoform. By using skeletal muscle-specific transgenic mice for PGC-1α1 and -α4, we could validate, in vivo, splicing events observed in in vitro studies. These results show that alternative PGC-1α variants can affect target gene expression both quantitatively and qualitatively and identify novel biological pathways under the control of this system of coactivators.