Construction and dissection of the ceRNA‑ceRNA network reveals critical modules in depression

Ling, Yan; Zhang, Jingchao; Yuan, Zheng Wei

doi:10.3892/mmr.2019.10009

Cited by 8 publications

(7 citation statements)

References 41 publications

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“…Growing evidence indicates that the ceRNA regulation mechanism plays a role in disease progression and drug efficiency [137][138][139][140]. We checked if any of the DE lncRNAs in the infected cells were exerting such effects to ensure a particular miRNA does not downregulate a gene.…”

Section: Discussionmentioning

confidence: 99%

Perversely Expressed Long Noncoding Rnas Can Alter Host Response and Viral Proliferation in SARS-CoV-2 Infection

2020

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Background: Regulatory roles of long noncoding RNAs (lncRNAs) during viral infection has become more evident in last decade, but are yet to be explored for SARS-CoV-2. Materials & methods: We analyzed RNA-seq dataset of SARS-CoV-2 infected lung epithelial cells to identify differentially expressed genes. Results: Our analyses uncover 21 differentially expressed lncRNAs broadly involved in cell survival and regulation of gene expression. These lncRNAs can directly interact with six differentially expressed protein-coding genes, and ten host genes that interact with SARS-CoV-2 proteins. Also, they can block the suppressive effect of nine microRNAs induced in viral infections. Conclusion: Our investigation determines that deregulated lncRNAs in SARS-CoV-2 infection are involved in viral proliferation, cellular survival, and immune response, ultimately determining disease outcome.

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Section: Discussionmentioning

confidence: 99%

Perversely Expressed Long Noncoding Rnas Can Alter Host Response and Viral Proliferation in SARS-CoV-2 Infection

2020

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“…Over the last few years, numerous studies have validated the ceRNA theory. It is well known that disruption of the balance of ceRNA cross-talk is associated with various developmental processes and pathological conditions, including tumorigenesis, neurodegenerative diseases (e.g., Alzheimer’s disease (AD)) 23 , and mental disorders (e.g., SCZ and depression) 24 , 25 .…”

Section: Introductionmentioning

confidence: 99%

Bioinformatics analysis of long non-coding RNA-associated competing endogenous RNA network in schizophrenia

Sabaie

Moghaddam

et al. 2021

Sci Rep

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Schizophrenia (SCZ) is a serious psychiatric condition with a 1% lifetime risk. SCZ is one of the top ten global causes of disabilities. Despite numerous attempts to understand the function of genetic factors in SCZ development, genetic components in SCZ pathophysiology remain unknown. The competing endogenous RNA (ceRNA) network has been demonstrated to be involved in the development of many kinds of diseases. The ceRNA hypothesis states that cross-talks between coding and non-coding RNAs, including long non-coding RNAs (lncRNAs), via miRNA complementary sequences known as miRNA response elements, creates a large regulatory network across the transcriptome. In the present study, we developed a lncRNA-related ceRNA network to elucidate molecular regulatory mechanisms involved in SCZ. Microarray datasets associated with brain regions (GSE53987) and lymphoblasts (LBs) derived from peripheral blood (sample set B from GSE73129) of SCZ patients and control subjects containing information about both mRNAs and lncRNAs were downloaded from the Gene Expression Omnibus database. The GSE53987 comprised 48 brain samples taken from SCZ patients (15 HPC: hippocampus, 15 BA46: Brodmann area 46, 18 STR: striatum) and 55 brain samples taken from control subjects (18 HPC, 19 BA46, 18 STR). The sample set B of GSE73129 comprised 30 LB samples (15 patients with SCZ and 15 controls). Differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs) were identified using the limma package of the R software. Using DIANA-LncBase, Human MicroRNA Disease Database (HMDD), and miRTarBase, the lncRNA- associated ceRNA network was generated. Pathway enrichment of DEmRNAs was performed using the Enrichr tool. We developed a protein–protein interaction network of DEmRNAs and identified the top five hub genes by the use of STRING and Cytoscape, respectively. Eventually, the hub genes, DElncRNAs, and predictive miRNAs were chosen to reconstruct the subceRNA networks. Our bioinformatics analysis showed that twelve key DEmRNAs, including BDNF, VEGFA, FGF2, FOS, CD44, SOX2, NRAS, SPARC, ZFP36, FGG, ELAVL1, and STARD13, participate in the ceRNA network in SCZ. We also identified DLX6-AS1, NEAT1, MINCR, LINC01094, DLGAP1-AS1, BABAM2-AS1, PAX8-AS1, ZFHX4-AS1, XIST, and MALAT1 as key DElncRNAs regulating the genes mentioned above. Furthermore, expression of 15 DEmRNAs (e.g., ADM and HLA-DRB1) and one DElncRNA (XIST) were changed in both the brain and LB, suggesting that they could be regarded as candidates for future biomarker studies. The study indicated that ceRNAs could be research candidates for investigating SCZ molecular pathways.

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“…A number of studies have demonstrated the activity of ceRNA regulatory loops and the related networks in several pathological conditions and developmental processes, e.g., tumorigenesis, neurodegenerative diseases 38 , and mental disorders 39 , 40 . There may be various ceRNAs, including mRNAs, pseudogenes, circRNAs, and lncRNAs, in a network 31 .…”

Section: Discussionmentioning

confidence: 99%

Long non-coding RNA-associated competing endogenous RNA axes in the olfactory epithelium in schizophrenia: a bioinformatics analysis

Sabaie

Moghaddam

et al. 2021

Sci Rep

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The etiology of schizophrenia (SCZ), as a serious mental illness, is unknown. The significance of genetics in SCZ pathophysiology is yet unknown, and newly identified mechanisms involved in the regulation of gene transcription may be helpful in determining how these changes affect SCZ development and progression. In the current work, we used a bioinformatics approach to describe the role of long non-coding RNA (lncRNA)-associated competing endogenous RNAs (ceRNAs) in the olfactory epithelium (OE) samples in order to better understand the molecular regulatory processes implicated in SCZ disorders in living individuals. The Gene Expression Omnibus database was used to obtain the OE microarray dataset (GSE73129) from SCZ sufferers and control subjects, which contained information about both lncRNAs and mRNAs. The limma package of R software was used to identify the differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs). RNA interaction pairs were discovered using the Human MicroRNA Disease Database, DIANA-LncBase, and miRTarBase databases. In this study, the Pearson correlation coefficient was utilized to find positive correlations between DEmRNAs and DElncRNAs in the ceRNA network. Eventually, lncRNA-associated ceRNA axes were developed based on co-expression relations and DElncRNA-miRNA-DEmRNA interactions. This work found six potential DElncRNA-miRNA-DEmRNA loops in SCZ pathogenesis, including, SNTG2-AS1/hsa-miR-7-5p/SLC7A5, FLG-AS1/hsa-miR-34a-5p/FOSL1, LINC00960/hsa-miR-34a-5p/FOSL1, AQP4-AS1/hsa-miR-335-5p/FMN2, SOX2-OT/hsa-miR-24-3p/NOS3, and CASC2/hsa-miR-24-3p/NOS3. According to the findings, ceRNAs in OE might be promising research targets for studying SCZ molecular mechanisms. This could be a great opportunity to examine different aspects of neurodevelopment that may have been hampered early in SCZ patients.

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Construction and dissection of the ceRNA‑ceRNA network reveals critical modules in depression

Cited by 8 publications

References 41 publications

Perversely Expressed Long Noncoding Rnas Can Alter Host Response and Viral Proliferation in SARS-CoV-2 Infection

Perversely Expressed Long Noncoding Rnas Can Alter Host Response and Viral Proliferation in SARS-CoV-2 Infection

Bioinformatics analysis of long non-coding RNA-associated competing endogenous RNA network in schizophrenia

Long non-coding RNA-associated competing endogenous RNA axes in the olfactory epithelium in schizophrenia: a bioinformatics analysis

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