Dataset Information

Comprehensive analysis of human microRNA target networks.

ABSTRACT:

Background

MicroRNAs (miRNAs) mediate posttranscriptional regulation of protein-coding genes by binding to the 3' untranslated region of target mRNAs, leading to translational inhibition, mRNA destabilization or degradation, depending on the degree of sequence complementarity. In general, a single miRNA concurrently downregulates hundreds of target mRNAs. Thus, miRNAs play a key role in fine-tuning of diverse cellular functions, such as development, differentiation, proliferation, apoptosis and metabolism. However, it remains to be fully elucidated whether a set of miRNA target genes regulated by an individual miRNA in the whole human microRNAome generally constitute the biological network of functionally-associated molecules or simply reflect a random set of functionally-independent genes.

Methods

The complete set of human miRNAs was downloaded from miRBase Release 16. We explored target genes of individual miRNA by using the Diana-microT 3.0 target prediction program, and selected the genes with the miTG score ? 20 as the set of highly reliable targets. Then, Entrez Gene IDs of miRNA target genes were uploaded onto KeyMolnet, a tool for analyzing molecular interactions on the comprehensive knowledgebase by the neighboring network-search algorithm. The generated network, compared side by side with human canonical networks of the KeyMolnet library, composed of 430 pathways, 885 diseases, and 208 pathological events, enabled us to identify the canonical network with the most significant relevance to the extracted network.

Results

Among 1,223 human miRNAs examined, Diana-microT 3.0 predicted reliable targets from 273 miRNAs. Among them, KeyMolnet successfully extracted molecular networks from 232 miRNAs. The most relevant pathway is transcriptional regulation by transcription factors RB/E2F, the disease is adult T cell lymphoma/leukemia, and the pathological event is cancer.

Conclusion

The predicted targets derived from approximately 20% of all human miRNAs constructed biologically meaningful molecular networks, supporting the view that a set of miRNA targets regulated by a single miRNA generally constitute the biological network of functionally-associated molecules in human cells.

SUBMITTER: Satoh J

PROVIDER: S-EPMC3130707 | biostudies-literature | 2011 Jun

REPOSITORIES: biostudies-literature

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Publications

Comprehensive analysis of human microRNA target networks.

Satoh Jun-Ichi J Tabunoki Hiroko H

BioData mining 20110617

<h4>Background</h4>MicroRNAs (miRNAs) mediate posttranscriptional regulation of protein-coding genes by binding to the 3' untranslated region of target mRNAs, leading to translational inhibition, mRNA destabilization or degradation, depending on the degree of sequence complementarity. In general, a single miRNA concurrently downregulates hundreds of target mRNAs. Thus, miRNAs play a key role in fine-tuning of diverse cellular functions, such as development, differentiation, proliferation, apopto ...[more]

PMID: 21682903

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Project description:BackgroundThe rate of ovarian cancer (OC) is one of the highest in women's reproductive systems. An improperly expressed microRNA (miRNA) has been discovered to have a vital role in the pathophysiology of OC. However, more research into OC's miRNA-message RNA (mRNA) gene interaction network is required.MethodsFirstly, the microarray data sets GSE25405 and GSE119055 from the GEO (Gene Expression Omnibus) database were downloaded and then analyzed with the GEO2R tool aiming at identifying DEMs (differential expressed miRNAs) between ovarian malignant tissue and ovarian normal tissue. The whole consistently changed miRNAs were then screened out to be candidate DEMs. For estimating underlying upstream transcription factors, FunRich was employed. miRNet was utilized to determine putative DEMs' downstream target genes. The R program was then used to do the GO annotation as well as the analysis of KEGG pathway enrichment for target genes. The PPI (protein-protein interaction), as well as the DEM-hub gene networks, were created by the Cytoscape software and STRING database. Finally, we chose the GSE74448 dataset to test the precision of hub gene expressions.ResultsWe have screened out six (five upregulated and one downregulated) DEMs. The majority of upregulated and downregulated DEMs are likely regulated by SP1 (specificity protein 1). SP4 (s protein 4), POU2F1 (POU class 2 homeobox 1), MEF2A (myocyte-specific enhancer factor 2A), ARID3A (AT-rich interaction domain 3A), and EGR1 (early growth response 1) can regulate upregulated and downregulated DEMs. We have found 807 target genes (656 upregulated and 151 downregulated DEM), being generally enriched in focal adhesion and proteoglycans in cancer, gastric cancer, hepatocellular carcinoma, as well as breast cancer. The majority of hub genes are projected to be controlled by hsa-miR-429, hsa-miR-140-5p, hsa-miR-199a-5p, and hsa-miR-199a-3p after the DEM-hub gene network was built. VEGFA (vascular endothelial growth factor A), EZH2 (enhancer of zeste 2 polycomb repressive complex 2 subunit), and HIF1A (hypoxia inducible factor 1 subunit alpha) expressions are consistent with the GSE74448 dataset in the first 18 hub genes.ConclusionWe have built an underlying miRNA-mRNA interacting network in OC, giving us unparalleled insight into the disease's diagnosis and treatment.

Project description:BackgroundHuman cytomegalovirus (HCMV) encodes microRNAs (miRNAs) that function as post-transcriptional regulators of gene expression during lytic infection in permissive cells. Some miRNAs have been shown to suppress virus replication, which could help HCMV to establish or maintain latent infection. However, HCMV miRNA expression has not been comprehensively examined and compared using cell culture systems representing permissive (lytic) and semi-permissive vs. non-permissive (latent-like) infection.MethodsViral miRNAs levels and expression kinetics during HCMV infection were determined by miRNA-specific stem-loop RT-PCR. HCMV infected THP-1 (non-permissive), differentiated THP-1 (d-THP-1, semi-permissive) and human embryo lung fibroblasts (HELs, fully-permissive) were examined. The impact of selected miRNAs on HCMV infection (gene expression, genome replication and virus release) was determined by Western blotting, RT-PCR, qPCR, and plaque assay.ResultsAbundant expression of 15 HCMV miRNAs was observed during lytic infection in HELs; highest peak inductions (11- to 1502-fold) occurred at 48 hpi. In d-THP-1s, fourteen mRNAs were detected with moderate induction (3- to 288-fold), but kinetics of expression was generally delayed for 24 h relative to HELs. In contrast, only three miRNAs were induced to low levels (3- to 4-fold) during quiescent infection in THP-1s. Interestingly, miR-UL70-3p was poorly induced in HEL (1.5-fold), moderately in THP-1s (4-fold), and strongly (58-fold) in d-THP-1s, suggesting a potentially specific role for miR-UL70-3p in THP-1s and d-THP-1s. MiR-US33, -UL22A and -UL70 were further evaluated for their impact on HCMV replication in HELs. Ectopic expression of miR-UL22A and miR-UL70 did not affect HCMV replication in HELs, whereas miR-US33 inhibited HCMV replication and reduced levels of HCMV US29 mRNA, confirming that US29 is a target of miR-US33.ConclusionsViral miRNA expression kinetics differs between permissive, semi-permissive and quiescent infections, and miR-US33 down-regulates HCMV replication. These results suggest that miR-US33 may function to impair entry into lytic replication and hence promote establishment of latency.

Dataset Information

Comprehensive analysis of human microRNA target networks.

Background

Methods

Results

Conclusion

Publications

Comprehensive analysis of human microRNA target networks.

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