Non-coding RNA Expression Profiles Research Articles

The Novel Regulatory Role of lncRNA-miRNA-mRNA Axis in Amyotrophic Lateral Sclerosis: An Integrated Bioinformatics Analysis.

Amyotrophic lateral sclerosis (ALS) is an incurable neurodegenerative disease that primarily affects motor neurons, causing muscle atrophy, bulbar palsy, and pyramidal tract signs. However, the aetiology and pathogenesis of ALS have not been elucidated to date. In this study, a competitive endogenous RNA (ceRNA) network was constructed by analyzing the expression profiles of messenger RNAs (mRNAs) and long noncoding RNAs (lncRNAs) that were matched by 7 ALS samples and 4 control samples, and then a protein-protein interaction (PPI) network was constructed to identify the genes related to ALS. Gene Ontology (GO) was used to study the potential functions of differentially expressed mRNAs (DEmRNAs) in the ceRNA network. For the ALS and control groups, 247177 potential lncRNA-mRNA ceRNA relationship pairs were screened. Analysis of significant relationship pairs demonstrated that the PPI modules formed by the MALAT1-regulated SYNRG, ITSN2, PICALM, AP3B1, and AAK1 genes may play important roles in the pathogenesis of ALS, and these results may help to characterize the pathogenesis of ALS.

Microarray analysis of the time-dependent expression profiles of long non-coding RNAs in the progression of vein graft stenotic disease.

Long non-coding RNAs (lncRNAs) have been reported to be involved in various biological processes, including cell proliferation and apoptosis. However, the expression profiles of lncRNAs in patients with vein graft restenosis remain unknown. In the present study, the time-dependent expression profiles of genes in vein bypass grafting models were examined by microarray analysis. A total of 2,572 lncRNAs and 1,652 mRNAs were identified to be persistently significantly differentially expressed. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis was performed to investigate the functions of these lncRNAs. A total of 360 lncRNAs and 135 protein-coding genes were predicted to be involved in the vascular remodeling process. Co-expression network analysis revealed the association between 194 lncRNAs and seven associated protein-coding genes, including transforming growth factor-β1, Fes, Yes1 associated transcriptional regulator, sphingosine-1-phosphate receptor 1, Src, insulin receptor and melanoma cell adhesion molecule. Moreover, reverse transcription-quantitative PCR results supported those of the microarray data, and overexpression of AF062402, which regulates the transcription of Src, stimulated the proliferation of primary vascular smooth muscle cells. The findings of the present study may facilitate the development of novel therapeutic targets for vein graft restenosis and may help to improve the prognosis of patients following coronary artery bypass grafting.

Differentially Expressed Long Noncoding RNAs Involved in FUBP1 Promoting Hepatocellular Carcinoma Cells Proliferation.

Background Far upstream element-binding protein 1 (FUBP1) is reported to be involved in cancer development by regulating the transcription of c-myc gene through binding to far upstream element. Highly expressed FUBP1 was negatively correlated with survival rate of patients with hepatocellular carcinoma (HCC) and could promote the proliferation of HCC cells. However, the downstream mechanism of FUBP1 has not yet been clearly explained. This study is aimed at identifying the expression profiles of long noncoding RNA (lncRNA) in HCC cells in response to FUBP1 overexpression and at investigating the possible lncRNAs that participated in cell proliferation process regulated by FUBP1. Methods The overexpression of FUBP1 was mediated by lentiviral infection on 3 different types of HCC cell lines (MHCC97-H, MHCC97-L, and Huh-7). The expression of target genes was detected by quantitative reverse transcription-PCR (RT-PCR) and western blotting assays. Microarray and quantitative RT-PCR were applied to screen the differentially expressed lncRNAs in HCC cells after FUBP1 overexpression. The Cell Counting Kit-8 assay was used to confirm the growth vitality of HCC cells. Results The growth vitality of HCC cells was significantly increased after lentivirus infection. A total of 12 lncRNAs had the same expression trend in the 3 HCC cell lines in response to FUBP1 overexpression, including 3 upregulated lncRNAs and 9 downregulated lncRNAs. Coexpression analysis of dysregulated lncRNAs-mRNAs network showed that lnc-LYZ-2 was the lncRNA most relevant to FUBP1. Inhibition of lnc-LYZ-2 could significantly relieve the proproliferation effect of FUBP1 on HCC cells, suggesting that lnc-LYZ-2 was partially involved in proproliferation regulation of FUBP1. Conclusions Our results indicated that FUBP1 induced the abnormal expression of lncRNAs and the FUBP1-lncRNAs coexpression network in HCC cells, which could provide theoretical and experimental basis for FUBP1-lncRNAs network involved in HCC development.

Long Noncoding RNA Expression Profiles of Periodontal Ligament Stem Cells from the Periodontitis Microenvironment in Response to Static Mechanical Strain.

During the period of orthodontic tooth movement, periodontal ligament stem cells (PDLSCs) play an important role in transducing mechanical stimulation and tissue remodeling. However, our previous studies verified that the periodontitis microenvironment causes damage to the biological functions of PDLSCs and abnormal mechanical sensitivity. Long noncoding RNAs (lncRNAs) participate in the inflammatory pathogenesis and development of many diseases. Whether lncRNAs are abnormally expressed in PDLSCs obtained from periodontal tissues of periodontitis patients (PPDLSCs) and whether putative lncRNAs participate in the mechanotransductive process in PDLSCs remain poorly understood. First, we subjected PDLSCs obtained from healthy periodontal tissues (HPDLSCs) and PPDLSCs to static mechanical strain (SMS) with 12% elongation at 0.1 Hz frequency using an FX-4000T system and screened overall lncRNA profiles in both cell types by microarray. Among lncRNAs with a fold change (FC) > 20.0, 27 lncRNAs were upregulated in strained HPDLSCs, and 16 lncRNAs (9 upregulated and 7 downregulated) were detected in strained PPDLSCs. For mRNAs with FC > 20.0, we detected 25 upregulated mRNAs and one downregulated mRNA in strained HPDLSCs and 7 upregulated and 5 downregulated mRNAs in strained PPDLSCs. Further enrichment analysis showed that, unlike HPDLSCs with annotations principally involving transduction-associated signaling pathways, dysregulated mRNAs in PPDLSCs are mainly responsible for pathological conditions. Moreover, coexpressed lncRNA-mRNA networks confirmed the pathological state and exacerbated inflammatory conditions in strained PPDLSCs. Taken together, when compared with strained HPDLSCs, various lncRNAs and mRNAs were dysregulated in PPDLSCs under mechanical forces, implicating the response of lncRNAs in PPDLSCs to mechanical stress. Moreover, we provide potential lncRNA targets, which may contribute to future intervention strategies for orthodontic treatment in periodontitis patients.

Genome-wide analysis of long noncoding RNA expression profile in nasal mucosa with allergic rhinitis

BackgroundLong noncoding RNAs (lncRNAs) are involved in a variety of human immune diseases. However, the expression profile and precise function of lncRNAs in allergic rhinitis (AR) remain unknown. In the present study, genome-wide analysis of lncRNA expression was performed in the nasal mucosa tissue and mRNA regulatory relationship was examined among patients with or without AR.MethodsMicroarray assays were performed and the differential expressions of lncRNAs or mRNA were verified through RT-PCR. The lncRNA functions were annotated using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The potential regulatory relationships between lncRNAs and the co-expressed mRNAs were analyzed using Cytoscape software. The expressions of specific lncRNAs and mRNAs were examined using an in vitro cell model.ResultsA total of 57 lncRNAs and 127 mRNAs were dysregulated in the nasal mucosa tissue of patients with AR, compared to those of patients without AR (fold change > 2.0 and P < 0.05). GO and pathway analysis indicated that the lncRNA–co-expressed mRNAs were enriched in several biological processes and cellular signaling pathways related to AR, such as positive regulation of the integrin biosynthetic process, cell adhesion, and leukocyte transendothelial migration. Some lncRNAs regulated the co-expressed genes in a cis- and/or trans-regulatory manner. Furthermore, allergen exposure significantly increased the expression of lnc-CXCL12-4, CXCL12, and CXCR4 in BEAS-2B cells compared to untreated cells (P < 0.01).ConclusionThe results of the present study suggest that lncRNAs participate in the biological pathways related to AR. Leukocyte transepithelial migration may be a potential target for lncRNAs to regulate allergic inflammation and CXCL12/CXCR4 axis plays an important role in the inflammatory process of AR.

Long Non-coding RNA Expression Profile in A549 Cells Infected with Human Respiratory Syncytial Virus

Long Non-coding RNA Expression Profile in A549 Cells Infected with Human Respiratory Syncytial Virus

Construction of sepsis-associated competing endogenous RNA network based on Gene Expression Omnibus datasets and bioinformatic analysis

To analyze the sepsis related long non-coding RNA (lncRNA) and mRNA expression profiles based on Gene Expression Omnibus (GEO) datasets and bioinformatic analysis, and to analyze the sepsis-associated competing endogenous RNA (ceRNA) network based on microRNA (miRNA) database. The sepsis-related lncRNA dataset was downloaded from the GEO database, and the differential expression analysis was conducted by Bioconductor on the sepsis dataset to obtain differentially expressed lncRNA (DElncRNA) and differentially expressed mRNA (DEmRNA), and cluster heat map was drawn. miRNA combined with DElncRNA were predicted by miRcode. mRNA targeted by miRNA was simultaneously met by three databases: TargetScan, miRDB, and mirTarBase. The interaction relationship of lncRNA-miRNA-mRNA was obtained. The regulatory network visualization software CytoScape was used to draw ceRNA networks. DEmRNA in the ceRNA networks were imported into the Search Tool for the Retrieval of Interacting Genes Database (STRING) online database to draw the protein-protein interaction (PPI) map. The gene ontology (GO) function annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of DEmRNA were performed. Dataset GSE89376 and GSE145227 were found from GEO database. Difference analysis showed there were 14 DElncRNA and 359 DEmRNA in the elderly group of GSE89376; 8 DElncRNA and 153 DEmRNA in the adult group of GSE89376; 1 232 DElncRNA and 1 224 DEmRNA in the children group of GSE145227. Clustering heatmap showed that there were significant differences in the expression of lncRNA and mRNA between the sepsis group and the control group. The ceRNA networks were constructed with miRNA. Several DElncRNA and multiple DEmRNA participated in the ceRNA network of sepsis. The PPI diagram demonstrated that several genes encoding proteins interacted with each other and form a multi-node interaction network with multiple genes encoding proteins. Functional annotation and enrichment analysis demonstrated that there might be a crosstalk mechanism on functionally related genes such as nuclear receptor activity, ligand-activated transcription factor activity, and steroid hormone receptor activity, and played a role in the occurrence and development of diseases through forkhead box transcription factor O (FoxO) signaling pathway, Janus kinase/signal transducers and activators of transcription (JAK/STAT) signaling pathway, p53 signaling pathway, and phosphateidylinositol 3-kinase (PI3K)/Akt signaling pathway. Through sepsis-related lncRNA-miRNA-mRNA ceRNA network and combining with KEGG pathway analysis, there were several lncRNA and mRNA participating in the ceRNA network related sepsis, which played an important role in several signal pathways.

The identify role and molecular mechanism of the MALAT1/hsa-mir-20b-5p/TXNIP axis in liver inflammation caused by CHB in patients with chronic HBV infection complicated with NAFLD

Background/aimsTo identify the inflammatory damage caused by chronic hepatitis B (CHB) in patients of chronic hepatitis B virus (HBV) infection complicated with non-alcoholic fatty liver disease (NAFLD), then guiding clinicians to carry out antiviral treatment. MethodsAccording to the pathological features of liver biopsy, treatment-naïve obese patients of chronic HBV infection complicated with NAFLD who had elevated alanine transaminase (ALT) were divided into CHB group and NASH group. Transcriptome chips were used to analyze the expression profiles of long non-coding RNA (lncRNA) and mRNA in liver puncture tissues from the two groups. The chip data of CHB and NASH groups were analyzed for differential expression analysis, gene function analysis, signal pathway analysis, target gene prediction and competing endogenous RNAs (ceRNA) network analysis. ResultsBy comparing CHB group with NASH group, a total of 44 differentially expressed lncRNAs and 567 differentially expressed mRNAs were screened. GO analysis predicted that the differentially expressed mRNAs may affect monooxygenase activity and oxidoreductase activity. KEGG analysis predicted that the differentially expressed mRNAs may be related to signaling pathways involved in oxidative phosphorylation, phagosomes, and NAFLD. Differential analysis of lncRNA shown that the expression of metastasis associated in lung adenocarcinoma transcript 1 (MALAT1) in CHB group was significantly upregulated. Subsequently, through target gene prediction and ceRNA network analysis, we found thioredoxin interacting protein (TXNIP), which was significantly upregulated in the CHB group and had a ceRNA relationship with MALAT1. It is predicted that there may be a ceRNA regulation relationship of MALAT1/hsa-miR- 20b-5p/TXNIP. ConclusionThe MALAT1/hsa-miR-20b-5p/TXNIP axis may mediate CHB-induced inflammatory damage in chronic HBV infection complicated with NAFLD, and the mechanism may be related to the activation of NLRP3 inflammatory bodies and downstream inflammatory responses.

Genome-wide long noncoding RNA and mRNA expression profiles demonstrate associations between exposure to inorganic elements and the risk of developing hepatocellular carcinoma

BackgroundLong noncoding RNAs (lncRNAs) are closely associated with the development of hepatocellular carcinoma (HCC). The present study conducted a genome-wide microarray analysis and qPCR validation to obtain comprehensive insights into this issue.MethodsThirty male HCC patients with chronic HBV infection were included in the present study. Primary HCC tissue and normal tissue were collected. Double-stranded complementary DNA synthesized from 10 pairs of samples was labeled and hybridized to a microarray chip. Further analyses, such as hierarchical clustering, gene ontology (GO) and pathway analyses, were performed. In addition, qPCR validation was performed on tissue samples and additional serum samples.ResultsThe microarray analysis identified 946 upregulated and 571 downregulated lncRNAs and 1720 upregulated and 1106 downregulated mRNAs. Among these RNAs, ENST00000583827.1 (fold change: 21) and uc010isf.1 (fold change: 18) were the most over- and underexpressed lncRNAs in the HCC tissues, respectively. For the mRNAs, KIF20A (fold change: 26) and HEPACAM (fold change: 50) were the most over- and underexpressed in the HCC tissues, respectively. The GO analysis demonstrated that the most differentially expressed mRNAs were related to the response of metal ions. The pathway analysis also suggested that the most enriched pathway was mineral absorption.ConclusionsThe subsequent qPCR validation exhibited high consistency with the microarray analysis, except for three lncRNAs. The qPCR analysis also demonstrated that TCONS_00008984 had a 767-fold overexpression level in HCC tissues when compared with normal tissues, and this finding was confirmed in the serum samples; therefore, TCONS_00008984 has the potential to serve as a diagnostic marker or prognostic indicator. The GO and pathway analyses indicated that exposure to inorganic elements may be involved in HCC risk.

Comprehensive In Silico Analysis of a Novel Serum Exosome-Derived Competitive Endogenous RNA Network for Constructing a Prognostic Model for Glioblastoma.

PurposeGlioblastoma (GBM) is one of the most aggressive brain tumors with high mortality, and tumor-derived exosomes provide new insight into the mechanisms of GBM tumorigenesis, metastasis and therapeutic resistance. We aimed to establish an exosome-derived competitive endogenous RNA (ceRNA) network for constructing a prognostic model for GBM.MethodsWe obtained the expression profiles of long noncoding RNAs (lncRNAs), miRNAs, and mRNAs from the GEO and TCGA databases and identified differentially expressed RNAs in GBM to construct a ceRNA network. By performing lasso and multivariate Cox regression analyses, we identified optimal prognosis-related differentially expressed lncRNAs (DElncRNAs) and generated a risk score model termed the exosomal lncRNA (exo-lncRNA) signature. The exo-lncRNA signature was subsequently validated in the CGGA GBM cohort. Finally, a novel prognostic nomogram was constructed based on the exo-lncRNA signature and clinicopathological parameters and validated in the CGGA external cohort. Based on the ceRNA hypothesis, oncocers were identified based on highly positive correlations between lncRNAs and mRNAs mediated by the same miRNAs. Furthermore, regression analyses were performed to assess correlations between the expression abundances of lncRNAs in tumors and exosomes.ResultsA total of 45 DElncRNAs, six DEmiRNAs, and 38 DEmRNAs were identified, and an exosome-derived ceRNA network was built. Three optimal prognostic-related DElncRNAs, HOTAIR (HR=0.341, P<0.001), SOX21-AS1 (HR=0.30, P<0.001), and STEAP3-AS1 (HR=2.47, P<0.001), were included to construct the exo-lncRNA signature, which was further proven to be an independent prognostic factor. The novel prognostic nomogram was constructed based on the exo-lncRNA signature, patient age, pharmacotherapy, radiotherapy, IDH mutation status, and MGMT promoter status, with a concordance index of 0.878. ROC and calibration plots both suggested that the nomogram had beneficial discrimination and predictive abilities. A total of 11 pairs of prognostic oncocers were identified. Regression analysis suggested excellent consistency of the expression abundance of the three exosomal lncRNAs between exosomes and tumor tissues.ConclusionsExosomal lncRNAs may serve as promising prognostic predictors and therapeutic targets. The prognostic nomogram based on the exo-lncRNA signature might provide an intuitive method for individualized survival prediction and facilitate better treatment strategies.

Comprehensive Analysis of Survival-Related lncRNAs, miRNAs, and mRNAs Forming a Competing Endogenous RNA Network in Gastric Cancer.

To analyze and construct a survival-related endogenous RNA (ceRNA) network in gastric cancer (GC) with lymph node metastasis, we obtained expression profiles of long non-coding RNAs (lncRNAs), mRNAs, and microRNAs (miRNAs) in GC from The Cancer Genome Atlas database. The edgeR package was used to screen differentially expressed lncRNAs, mRNAs, and miRNAs between GC patients with lymphatic metastasis and those without lymphatic metastasis. Then, we used univariate Cox regression analysis to identify survival-related differentially expressed RNAs. In addition, we used multivariate Cox regression analysis to screen lncRNAs, miRNAs, and mRNAs for use in the prognostic prediction models. The results showed that 2,247 lncRNAs, 155 miRNAs, and 1,253 mRNAs were differentially expressed between the two patient groups. Using univariate Cox regression analysis, we found that 395 lncRNAs, eight miRNAs, and 180 mRNAs were significantly related to the survival time of GC patients. We next created a survival-related network consisting of 59 lncRNAs, seven miRNAs, and 36 mRNAs. In addition, we identified eight RNAs associated with prognosis by multivariate Cox regression analysis, comprising three lncRNAs (AC094104.2, AC010457.1, and AC091832.1), two miRNAs (miR-653-5p and miR-3923), and three mRNAs (C5orf46, EPHA8, and HPR); these were used to construct the prognostic prediction models, and their risk scores could be used to assess GC patients’ prognosis. In conclusion, this study provides new insights into ceRNA networks in GC and the screening of prognostic biomarkers for GC.

Altered non-coding RNA expression profile in F1 progeny 1\xa0year after parental irradiation is linked to adverse effects in zebrafish

Gamma radiation produces DNA instability and impaired phenotype. Previously, we observed negative effects on phenotype, DNA methylation, and gene expression profiles, in offspring of zebrafish exposed to gamma radiation during gametogenesis. We hypothesize that previously observed effects are accompanied with changes in the expression profile of non-coding RNAs, inherited by next generations. Non-coding RNA expression profile was analysed in F1 offspring (5.5 h post-fertilization) by high-throughput sequencing 1 year after parental irradiation (8.7 mGy/h, 5.2 Gy total dose). Using our previous F1-γ genome-wide gene expression data (GSE98539), hundreds of mRNAs were predicted as targets of differentially expressed (DE) miRNAs, involved in pathways such as insulin receptor, NFkB and PTEN signalling, linking to apoptosis and cancer. snRNAs belonging to the five major spliceosomal snRNAs were down-regulated in the F1-γ group, Indicating transcriptional and post-transcriptional alterations. In addition, DEpiRNA clusters were associated to 9 transposable elements (TEs) (LTR, LINE, and TIR) (p = 0.0024), probable as a response to the activation of these TEs. Moreover, the expression of the lincRNAs malat-1, and several others was altered in the offspring F1, in concordance with previously observed phenotypical alterations. In conclusion, our results demonstrate diverse gamma radiation-induced alterations in the ncRNA profiles of F1 offspring observable 1 year after parental irradiation.

LncRNAs Landscape in the patients of primary gout by microarray analysis.

To determine the expression profile and clinical significance of long non-coding RNAs (lncRNAs) in peripheral blood mononuclear cells (PBMCs) of patients with primary gout and healthy control subjects. Human lncRNA microarrays were used to identify the differentially expressed lncRNAs and mRNAs in primary gout patients (n = 6) and healthy control subjects (n = 6). Bioinformatics analyses were performed to predict the roles of differently expressed lncRNAs and mRNAs. Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to detect the expression levels of 8 lnRNAs in 64 primary gout patients and 32 healthy control subjects. Spearman’s correlation was used to analyze the correlation between these eight lncRNAs and the laboratory values of gout patients. A receiver operating characteristic (ROC) curve was constructed to evaluate the diagnostic value of the lncRNAs identified in gout. The microarray analysis identified 1479 differentially expressed lncRNAs (879 more highly expressed and 600 more lowly expressed), 862 differentially expressed mRNAs (390 more highly expressed and 472 more lowly expressed) in primary gout (fold change > 2, P < 0.05), respectively. The bioinformatic analysis indicated that the differentially expressed lncRNAs regulated the abnormally expressed mRNAs, which were involved in the pathogenesis of gout through several different pathways. The expression levels of TCONS_00004393 and ENST00000566457 were significantly increased in the acute gout flare group than those in the intercritical gout group or healthy subjects (P<0.01). Moreover, inflammation indicators were positive correlated with TCONS_00004393 and ENST00000566457 expression levels. The areas under the ROC curve of ENST00000566457 and NR-026756 were 0.868 and 0.948, respectively. Our results provide novel insight into the mechanisms of primary gout, and reveal that TCONS_00004393 and ENST00000566457 might be as candidate targets for the treatment of gout flare; ENST00000566457 and NR-026756 could effectively discriminate between the gout and the healthy control groups.

Expression profiles of long non-coding RNAs in the cartilage of patients with knee osteoarthritis and normal individuals.

Knee osteoarthritis is caused by a multifactorial imbalance in the synthesis and degradation of knee chondrocytes, subchondral bone and extracellular matrix. Abnormal expression of long non-coding RNAs (lncRNAs) affects the metabolism, synovitis, autophagy and apoptosis of chondrocytes, as well as the production of cartilage matrix. The aim of the present study was to identify novel targets for the treatment of osteoarthritis and to examine the pathogenesis of the disease. The lncRNA expression profiles of seven patients with knee osteoarthritis and six healthy controls were examined by RNA-sequencing. Differentially expressed lncRNAs were selected for bioinformatics analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Reverse transcription-quantitative PCR (RT-qPCR) was used to further investigate the differential expression of the lncRNAs. A total of 23,583 lncRNAs were identified in osteoarthritis cartilage, including 5,255 upregulated and 5,690 downregulated lncRNAs, compared with normal cartilage. Although there were more downregulated lncRNAs compared with upregulated lncRNAs, among the changed lncRNAs (fold-change >6), there were more upregulated lncRNAs compared with downregulated lncRNAs. Several lncRNAs exhibiting differences were identified as potential therapeutic targets in knee osteoarthritis. GO and KEGG pathway analyses were performed for the target genes of the differentially expressed lncRNAs. RT-qPCR validation was performed on three randomly selected upregulated and downregulated lncRNAs. The results of RT-qPCR were consistent with the findings obtained by RNA-sequencing analysis. The findings from the present study may contribute to the diagnosis of osteoarthritis and may predict the development of osteoarthritis. Furthermore, the differentially expressed lncRNAs may aid in the identification of novel candidate targets for the treatment of knee osteoarthritis.

Expression profiling and bioinformatics analysis of exosomal long noncoding RNAs in patients with myasthenia gravis by RNA sequencing.

BackgroundMyasthenia gravis (MG) is an autoimmune disease mediated by acetylcholine receptor antibodies. Exosomes were shown to be involved in the immune modulation and autoimmune diseases. However, the expression and function of exosomal long noncoding RNAs (lncRNAs) in MG are still unclear.MethodsWe conducted high‐throughput sequencing to detect the lncRNA profiles of serum exosomes in 6 MG patients (2 grade I, 2 grade IIa, and 2 grade IIb) and 6 healthy controls (HC). Then, differentially expressed (DE) lncRNAs with the greatest difference between the MG and HC groups were selected for further quantitative real‐time polymerase chain reaction (qRT‐PCR) validation in additional 30 MG patients and 10 HC. The DE lncRNAs were used to construct the coding/noncoding network and perform enrichment analysis.ResultsWe identified 378 significantly upregulated and 348 significantly downregulated lncRNAs in MG patients compared with HC. The top 5 lncRNAs (NR_104677.1, ENST00000583253.1, NR_046098.1, NR_022008.1, and ENST00000581362.1) were validated and shown to be significantly increased in the serum exosome of MG, and the expression level of NR_046098.1 significantly increased with the MG grading. Enrichment analysis showed that DE genes mainly participated in the basic biological regulation of MG and immune‐related pathways, such as autoimmune thyroid disease pathway and T‐cell receptor signaling pathway. A specific lncRNA‐miRNA‐mRNA regulatory network associated with the 5 lncRNAs, 14 MG‐related miRNAs and 30 mRNAs was constructed.ConclusionsWe conducted a comprehensive analysis of exosomal lncRNAs to reveal potential biomarkers for the MG diagnosis and severity assessment.

Differential Expression Profiles and Functional Analysis of Long Non-coding RNAs in Children With Dilated Cardiomyopathy.

Aim: To evaluate the expression profile of long non-coding RNAs (lncRNAs) in different left ventricular function of dilated cardiomyopathy (DCM) in children and explore their possible functions.Methods: The lncRNA microarray experiment was used to determine the differential expression profile of lncRNA in three children with DCM and three healthy volunteers. The functional analysis and the construction of the lncRNA-mRNA interaction network were carried out to study the biological functions. Quantitative real-time polymerase chain reaction (qRT-PCR) analysis was used to verify the microarray data.Results: There were 369 up-regulated lncRNAs identified in the DCM patients (fold change >2, P < 0.05), and 505 down-regulated lncRNAs. Based on target gene prediction and co-expression network construction, 9 differentially expressed lncRNAs were selected for the PCR to verify the accuracy of the microarray data, of which 5 were up-regulated and 4 were down-regulated, and finally proved that 7 of them were consistent with the trend of microarray data results. Four of these lncRNAs had significant differences between the patients with poor cardiac function and patients with improved left ventricle function.Conclusion: LncRNAs may play an important role in pediatric DCM and may provide a new perspective for the pathogenesis, diagnosis, and treatment of this disease.

Genome-Wide Integrated Analysis Revealed Functions of lncRNA-miRNA-mRNA Interaction in Growth of Intermuscular Bones in Megalobrama amblycephala.

Intermuscular bone (IB) occurs in the myosepta of teleosts. Its existence has an adverse influence on the edible and economic value of fish, especially for aquaculture species belonging to Cypriniformes. The growth mechanism of IBs is quite lacking. In this study, we firstly used single molecular real-time sequencing (SMRT) technology to improve the draft genome annotation and full characterization of the transcriptome for one typical aquaculture species, blunt snout bream (Megalobrama amblycephala). The long non-coding RNA (lncRNA), microRNA (miRNA), and messenger RNA (mRNA) expression profiles in two IB growth stages (1 and 3 years old) were compared through transcriptome and degradome analyses. A total of 126 miRNAs, 403 mRNAs, and 353 lncRNAs were found to be differentially expressed between the two stages. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that the significantly upregulated map2k6 and cytc in the MAPK/p53 signaling pathway and the significantly downregulated lama3 and thbs4b in the extracellular matrix (ECM)–receptor pathway may play a key regulatory role in IB growth. Bioinformatics analysis subsequently revealed 14 competing endogenous RNA (ceRNA) pairs related to the growth of IBs, consisting of 10 lncRNAs, 7 miRNAs, and 10 mRNAs. Of these, dre-miR-24b-3p and dre-miR-193b-3p are core regulatory factors interacting with four lncRNAs and three mRNAs, the interaction mechanism of which was also revealed by subsequent experiments at the cellular level. In conclusion, our data showed that IBs had higher activity of cell apoptosis and lower mineralization activity in IB_III compared to IB_I via interaction of MAPK/p53 and ECM–receptor signaling pathways. The downregulated zip1 interacted with miR-24a-3p and lnc017705, decreased osteoblast differentiation and Ca2+ deposition in the IB_III stage. Our identified functional mRNAs, lncRNAs, and miRNAs provide a data basis for in-depth elucidation of the growth mechanism of teleost IB.

An edge-based statistical analysis of long non-coding RNA expression profiles reveals a negative association between Parkinson\u2019s disease and colon cancer

BackgroundColon cancer (CC) is one of the most common malignant tumors, while Parkinson’s disease (PD) is the second most common neurodegenerative disorder. Recent accumulating evidence indicates that these two diseases are associated with each other. Also, from the perspective of long non-coding RNAs, some well-known genes such as H19 and PVT1 can link these two diseases together. Several studies have shown that patients with PD had a decreased risk of developing CC compared with patients without PD. However, controversies surround the relationship between PD and CC, and to date, no concordant conclusion has been drawn.MethodsIn this study, we aimed to assess the association between these two diseases based on lncRNA-to-lncRNA interactions. Motivated by the weighted gene co-expression network analysis method, a customized procedure was proposed and used to identify differentially correlated edges (DCEs) in the respective interaction networks for PD and CC and explore how these two diseases are linked.ResultsOf the two sets of DCEs for PD and CC, 16 pairs overlapped. Among them, 15 edges had opposite signs, with positive signs for CC indicating a gain of connectivity, whereas negative signs for PD indicating a loss of connectivity.ConclusionsBy using the lncRNA expression profiles, and a customized procedure, an answer to the question about how PD and CC are associated is provided.

Profiles of differentially expressed long noncoding RNAs and messenger RNAs in the myocardium of septic mice.

BackgroundSepsis is the primary cause of mortality in the intensive care unit (ICU), mainly due to sepsis-induced dysfunction of essential organs such as the heart and lungs. This study investigated the myocardium’s epigenetic characterization from septic mice to identify potential treatment targets for septic myocardial dysfunction.MethodsCecal ligation and puncture (CLP) was used to induce sepsis in male C57BL/6 mice. Hearts were collected 24 h after surgery to determine the expression profiles of long noncoding RNAs (lncRNAs) and messenger RNAs (mRNAs) by microarray. To validate the reliability of microarray results, we randomly chose six differentially expressed lncRNAs for qRT-PCR. Functional mapping of differentially expressed mRNAs was annotated with gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses; lncRNA-mRNA co-expression network was constructed to reveal connections between lncRNAs and mRNAs.ResultsMicroarray analysis indicated that 1,568 lncRNAs and 2,166 mRNAs were differentially expressed in the myocardium from septic mice, which was further confirmed by qRT-PCR. KEGG pathway analysis showed that numerous differentially expressed mRNAs were relevant to tumor necrosis factor (TNF) and phosphatidylinositol-3-kinase/protein kinase B (PI3K/Akt) signaling pathways. Moreover, according to the lncRNA-mRNA co-expression network constructed by the above six lncRNAs and their interacting mRNAs, the co-expression network profiles had 57 network nodes and 134 connections, including 76 positive interactions and 58 negative interactions.ConclusionsIn mouse hearts, sepsis resulted in differential expression of lncRNAs and mRNAs related to TNF and PI3K-Akt signaling pathways, suggesting that lncRNAs and their interacting mRNAs may participate in the pathogenesis of septic myocardial dysfunction by regulating TNF and PI3K-Akt signaling pathways.

Systematic analysis of purified astrocytes after SCI unveils Zeb2os function during astrogliosis

SUMMARYSpinal cord injury (SCI) is one of the most devastating neural injuries without effective therapeutic solutions. Astrocytes are the predominant component of the scar. Understanding the complex contributions of reactive astrocytes to SCI pathophysiologies is fundamentally important for developing therapeutic strategies. We have studied the molecular changes in the injury environment and the astrocyte-specific responses by astrocyte purification from injured spinal cords from acute to chronic stages. In addition to protein-coding genes, we have systematically analyzed the expression profiles of long non-coding RNAs (lncRNAs) (>200 bp), which are regulatory RNAs that play important roles in the CNS. We have identified a highly conserved lncRNA, Zeb2os, and demonstrated using functional assays that it plays an important role in reactive astrogliosis through the Zeb2os/Zeb2/Stat3 axis. These studies provide valuable insights into the molecular basis of reactive astrogliosis and fill the knowledge gap regarding the function(s) of lncRNAs in astrogliosis and SCI.