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Multiple platform assessment and isomir analysis of the EGF dependent microRNA-ome by microarray and deep sequencing analysis [small RNA-seq]

ABSTRACT: We have used an integrative high content analysis approach to identify the specific miRNAs implicated in EGF signaling in HeLa cells as potential mediators of cancer mediated functions. We have used microarray and deep-sequencing technologies in order to obtain a global view of the EGF miRNA transcriptome with a robust experimental cross-validation. By applying a procedure based on Rankprod tests, we have delimited a solid set of EGF-regulated miRNAs. After validating regulated miRNAs by RT-qPCR, we have derived protein networks and biological functions from the predicted targets of the regulated miRNAs to gain insight into the potential role of miRNAs in EGF-treated cells. In addition, we have analyzed sequence heterogeneity due to editing relative to the reference sequence (isomirs) among regulated miRNAs.

ORGANISM(S): Homo sapiens

PROVIDER: GSE41359 | GEO | 2013/06/11

SECONDARY ACCESSION(S): PRJNA176714

REPOSITORIES: GEO

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Project description:MicroRNAs (miRNAs) are single-stranded non-coding RNAs that negatively regulate target gene expression through mRNA cleavage or translational repression. There is mounting evidence that they play critical roles in heart disease. The expression of known miRNAs in the heart has been studied at length by microarray and quantitative PCR but it is becoming evident that microRNA isoforms (isomiRs) are potentially physiologically important. It is well known that left ventricular (patho)physiology is influenced by transmural heterogeneity of cardiomyocyte phenotype, and this likely reflects underlying heterogeneity of gene expression. Given the significant role of miRNAs in regulating gene expression, knowledge of how the miRNA profile varies across the ventricular wall will be crucial to better understand the mechanisms governing transmural physiological heterogeneity. To determinine miRNA/isomiR expression profiles in the rat heart we investigated tissue from different locations across the left ventricular wall using deep sequencing. We detected significant quantities of 145 known rat miRNAs and 68 potential novel orthologs of known miRNAs, in mature, mature* and isomiR formation. Many isomiRs were detected at a higher frequency than their canonical sequence in miRBase and have different predicted targets. The most common miR-133a isomiR was more effective at targeting a construct containing a sequence from the gelsolin gene than was canonical miR-133a, as determined by dual-fluorescence assay. We identified a novel rat miR-1 homolog from a second miR-1 gene; and a novel rat miRNA similar to miR-676. We also cloned and sequenced the rat miR-486 gene which is not in miRBase (v18). Signalling pathways predicted to be targeted by the most highly detected miRNAs include Ubiquitin-mediated Proteolysis, Mitogen-Activated Protein Kinase, Regulation of Actin Cytoskeleton, Wnt signalling, Calcium Signalling, Gap junctions and Arrhythmogenic Right Ventricular Cardiomyopathy. Most miRNAs are not expressed in a gradient across the ventricular wall, with exceptions including miR-10b, miR-21, miR-99b and miR-486.

Project description:miRNAs are small noncoding RNA molecules that play an important role in post-transcriptional regulation of gene expression. Length and/or sequence variants of the same miRNA are termed isomiRs. While most isomiRs are functionally redundant compared to their canonical counterparts, so-called 5âisomiRs exhibit a shifted 5â end and therefore a shifted seed sequence resulting in a different target spectrum. However, not much is known about the functional relevance of these isoforms. Analysis of miRNA-seq data from breast cancer cell lines identified six pairs of highly expressed miRNAs and associated 5âisomiRs. Among them, hsa-miR-140-3p was of particular interest because its 5âisomiR showed higher expression compared to the canonical miRNA annotated in miRbase. This miRNA has previously been shown to control stemness of breast cancer cells. MiRNAseq data of breast cancer patients (TCGA dataset) showed that both the canonical hsa-miR-140-3p and its 5âisomiR-140-3p were highly expressed in patients compared to normal breast tissue. In the current work, we present the functional characterization of 5âisomiR-140-3p and the cellular phenotypes associated with its overexpression in MCF10A and MDA-MB-231 cell lines in comparison to the canonical hsa-miR-140-3p. Contrary to the effect of the canonical hsa miR 140-3p, overexpression of the 5âisomiR-140-3p led to a decrease in cell viability. The latter observation was supported by cell cycle analysis, where the 5âisomiR-140-3p but not the hsa-miR-140-3p caused cell cycle arrest in G0/G1-phase. Additionally, 5âismoiR-140-3p overexpression was found to cause a decrease in cell migration in MCF10A cells. We identified three novel direct target genes of the 5â isomiR-140-3p; COL4A1, ITGA6 and MARCKSL1. Finally, we have shown that knocking down these genes partially phenocopied the effects of the 5âisomiR-140-4p overexpression, where COL4A1 and ITGA6 knockdown led to reduced cell viability and cell cycle arrest, while MARCKSL1 knockdown resulted in a decrease in the migratory potential of cells. In summary, this work presents evidence that there is a functional synergy between the canonical hsa-miR-140-3p and the newly identified 5âisomiR-140-3p in suppressing growth and progression of breast cancer by simultaneously targeting genes related to differentiation, proliferation, and migration. With this array, we aimed to address the question which genes are regulated by either of the two forms of the miRNA. Samples were measured in one biological replicate of cells transfected with mimic-ctrl1 and mimic-ctrl2 (Dharmacon) as control samples and two biological replicates of cells transfected with hsa-miR-140-3p and 5'isomiR-140-3p (Exiqon) in 30nM concentration using Lipofectamin 2000 as transfection reagent.

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Multiple platform assessment and isomir analysis of the EGF dependent microRNA-ome by microarray and deep sequencing analysis [small RNA-seq]

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