Dataset Information

Identification of a thymus microRNA?mRNA regulatory network in Down syndrome.

ABSTRACT: The present bioinformatics analysis was performed using a multi?step approach to identify a microRNA (miR)?mRNA regulatory network in Down syndrome. miR (GSE69210) and mRNA (GSE70573) data was downloaded and collected from the thymic tissues of both Down syndrome and karyotypically normal subjects and placed in a public repository. Then, weighted gene co?expression network analysis (WGCNA) was performed to screen for miRs and mRNAs associated with Down syndrome. Subsequently, differentially expressed miRs (DEmiRs) and mRNAs/differentially expressed genes (DEGs) were identified following screening and mapping to RNA data. Bidirectional hierarchical clustering analysis was then performed to distinguish DEmiRs and DEGs between Down syndrome samples and normal control samples. DEmiR targets were retrieved using the miRanda database and mapped to the mRNA module screen by WGCNA. A gene co?expression network was constructed and subjected to functional enrichment analysis. During WGCNA, a total of 6 miR modules and 20 mRNA modules associated with Down syndrome were identified. Following mapping of these miRs and mRNAs to the miR and mRNA modules screened using WGNCA, a total of 12 DEmiRs and 237 DEGs were collected. Following comparison with DEmiR targets retrieved from the miRanda database, a total of 255 DEmiR?DEG pairs, including 6 DEmiRs and 106 DEGs were obtained. At expression correlation coefficient >0.9, a total of 231 gene pairs were selected. These gene pairs were enriched in response to stress and response to stimuli following functional annotation and module division. An integrated analysis of miR and mRNA expression in the thymus in Down syndrome is reported in the present study. miR?30c, miR?145, miR?183 and their targets may serve important roles in the pathogenesis and development of complications in Down syndrome. However, further experimental studies are required to verify these results.

SUBMITTER: Chai M

PROVIDER: S-EPMC6691205 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identification of a thymus microRNA‑mRNA regulatory network in Down syndrome.

Chai Miao M Su Liju L Hao Xiaolei X Zhang Meng M Zheng Lihui L Bi Jiabing J Han Xiao X Gao Chunbo C

Molecular medicine reports 20190627 3

The present bioinformatics analysis was performed using a multi‑step approach to identify a microRNA (miR)‑mRNA regulatory network in Down syndrome. miR (GSE69210) and mRNA (GSE70573) data was downloaded and collected from the thymic tissues of both Down syndrome and karyotypically normal subjects and placed in a public repository. Then, weighted gene co‑expression network analysis (WGCNA) was performed to screen for miRs and mRNAs associated with Down syndrome. Subsequently, differentially expr ...[more]

PMID: 31257513

Similar Datasets

Project description:BackgroundLung adenocarcinoma (LUAD) is a common lung cancer with a high mortality, for which microRNAs (miRNAs) play a vital role in its regulation. Multiple messenger RNAs (mRNAs) may be regulated by miRNAs, involved in LUAD tumorigenesis and progression. However, the miRNA-mRNA regulatory network involved in LUAD has not been fully elucidated.MethodsDifferentially expressed miRNAs and mRNA were derived from the Cancer Genome Atlas (TCGA) dataset in tissue samples and from our microarray data in plasma (GSE151963). Then, common differentially expressed (Co-DE) miRNAs were obtained through intersected analyses between the above two datasets. An overlap was applied to confirm the Co-DEmRNAs identified both in targeted mRNAs and DEmRNAs in TCGA. A miRNA-mRNA regulatory network was constructed using Cytoscape. The top five miRNA were identified as hub miRNA by degrees in the network. The functions and signaling pathways associated with the hub miRNA-targeted genes were revealed through Gene Ontology (GO) analysis and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. The key mRNAs in the protein-protein interaction (PPI) network were identified using the STRING database and CytoHubba. Survival analyses were performed using Gene Expression Profiling Interactive Analysis (GEPIA).ResultsThe miRNA-mRNA regulatory network consists of 19 Co-DEmiRNAs and 760 Co-DEmRNAs. The five miRNAs (miR-539-5p, miR-656-3p, miR-2110, let-7b-5p, and miR-92b-3p) in the network were identified as hub miRNAs by degrees (>100). The 677 Co-DEmRNAs were targeted mRNAs from the five hub miRNAs, showing the roles in the functional analyses of the GO analysis and KEGG pathways (inclusion criteria: 836 and 48, respectively). The PPI network and Cytoscape analyses revealed that the top ten key mRNAs were NOTCH1, MMP2, IGF1, KDR, SPP1, FLT1, HGF, TEK, ANGPT1, and PDGFB. SPP1 and HGF emerged as hub genes through survival analysis. A high SPP1 expression indicated a poor survival, whereas HGF positively associated with survival outcomes in LUAD.ConclusionThis study investigated a miRNA-mRNA regulatory network associated with LUAD, exploring the hub miRNAs and potential functions of mRNA in the network. These findings contribute to identify new prognostic markers and therapeutic targets for LUAD patients in clinical settings.

Project description:Ependymomas (EPNs) are one of the most common types of malignant neuroepithelial tumors. In an effort to identify potential biomarkers involved in the pathogenesis of EPN, the mRNA expression profiles of the GSE25604, GSE50161, GSE66354, GSE74195 and GSE86574 datasets, in addition to the microRNA (miRNA/miR) expression profiles of GSE42657 were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) between EPN and normal brain tissue samples were identified using the Limma package in R and GEO2R, respectively. Functional and pathway enrichment analyses were conducted using the Database for Annotation, Visualization and Integrated Discovery. A protein-protein interaction network was constructed using the Search Tool for Retrieval of Interacting Genes database, which was visualized using Cytoscape. The targeted genes of DEMs were predicted using miRWalk2.0 and a miRNA-mRNA regulatory network was constructed. Following analysis, a total of 948 DEGs and 129 DEMs were identified. Functional enrichment analysis revealed that 609 upregulated DEGs were significantly enriched in 'PI3K-Akt signaling pathway', while 339 downregulated DEGs were primarily involved in 'cell junction' and 'retrograde endocannabinoid signaling'. In addition, 6 hub genes [cyclin dependent kinase 1, CD44 molecule (Indian blood group) (CD44), proliferating cell nuclear antigen (PCNA), MYC, synaptotagmin 1 (SYT1) and kinesin family member 4A] and 6 crucial miRNAs [homo sapiens (hsa)-miR-34a-5p, hsa-miR-449a, hsa-miR-106a-5p, hsa-miR-124-3p, hsa-miR-128-3p and hsa-miR-330-3p] were identified as biomarkers and potential therapeutic targets for EPN. Furthermore, a microRNA-mRNA regulatory network was constructed to highlight the interactions between DEMs and their target DEGs; this included the hsa-miR-449a-SYT1, hsa-miR-34a-5p-SYT1, hsa-miR-330-3p-CD44 and hsa-miR-124-3p-PCNA pairs, whose expression levels were confirmed using reverse transcription-quantitative polymerase chain reaction. In conclusion, the present study may provide important data for the investigation of the molecular mechanisms of EPN pathogenesis.

Dataset Information

Identification of a thymus microRNA?mRNA regulatory network in Down syndrome.

Publications

Identification of a thymus microRNA‑mRNA regulatory network in Down syndrome.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets