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      Target prediction and validation of microRNAs expressed from FSHR and aromatase genes in human ovarian granulosa cells

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          Abstract

          MicroRNAs (miRNAs) are known post-transcriptional regulators of various biological processes including ovarian follicle development. We have previously identified miRNAs from human pre-ovulatory ovarian granulosa cells that are expressed from the intronic regions of two key genes in normal follicular development: FSH receptor ( FSHR) and CYP19A1, the latter encoding the aromatase enzyme. The present study aims to identify the target genes regulated by these miRNAs: hsa-miR-548ba and hsa-miR-7973, respectively. The miRNAs of interest were transfected into KGN cell line and the gene expression changes were analyzed by Affymetrix microarray. Potential miRNA-regulated genes were further filtered by bioinformatic target prediction algorithms and validated for direct miRNA:mRNA binding by luciferase reporter assay. LIFR, PTEN, NEO1 and SP110 were confirmed as targets for hsa-miR-548ba. Hsa-miR-7973 target genes ADAM19, PXDN and FMNL3 also passed all verification steps. Additionally, the expression pattern of the miRNAs was studied in human primary cumulus granulosa cell culture in relation to the expression of their host genes and FSH stimulation. Based on our findings we propose the involvement of hsa-miR-548ba in the regulation of follicle growth and activation via LIFR and PTEN. Hsa-miR-7973 may be implicated in the modulation of extracellular matrix and cell-cell interactions by regulating the expression of its identified targets.

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          Most cited references41

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          miRDB: an online resource for microRNA target prediction and functional annotations

          MicroRNAs (miRNAs) are small non-coding RNAs that are extensively involved in many physiological and disease processes. One major challenge in miRNA studies is the identification of genes regulated by miRNAs. To this end, we have developed an online resource, miRDB (http://mirdb.org), for miRNA target prediction and functional annotations. Here, we describe recently updated features of miRDB, including 2.1 million predicted gene targets regulated by 6709 miRNAs. In addition to presenting precompiled prediction data, a new feature is the web server interface that allows submission of user-provided sequences for miRNA target prediction. In this way, users have the flexibility to study any custom miRNAs or target genes of interest. Another major update of miRDB is related to functional miRNA annotations. Although thousands of miRNAs have been identified, many of the reported miRNAs are not likely to play active functional roles or may even have been falsely identified as miRNAs from high-throughput studies. To address this issue, we have performed combined computational analyses and literature mining, and identified 568 and 452 functional miRNAs in humans and mice, respectively. These miRNAs, as well as associated functional annotations, are presented in the FuncMir Collection in miRDB.
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            Switching from repression to activation: microRNAs can up-regulate translation.

            AU-rich elements (AREs) and microRNA target sites are conserved sequences in messenger RNA (mRNA) 3' untranslated regions (3'UTRs) that control gene expression posttranscriptionally. Upon cell cycle arrest, the ARE in tumor necrosis factor-alpha (TNFalpha) mRNA is transformed into a translation activation signal, recruiting Argonaute (AGO) and fragile X mental retardation-related protein 1 (FXR1), factors associated with micro-ribonucleoproteins (microRNPs). We show that human microRNA miR369-3 directs association of these proteins with the AREs to activate translation. Furthermore, we document that two well-studied microRNAs-Let-7 and the synthetic microRNA miRcxcr4-likewise induce translation up-regulation of target mRNAs on cell cycle arrest, yet they repress translation in proliferating cells. Thus, activation is a common function of microRNPs on cell cycle arrest. We propose that translation regulation by microRNPs oscillates between repression and activation during the cell cycle.
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              The mirtron pathway generates microRNA-class regulatory RNAs in Drosophila.

              The canonical microRNA (miRNA) pathway converts primary hairpin precursor transcripts into approximately 22 nucleotide regulatory RNAs via consecutive cleavages by two RNase III enzymes, Drosha and Dicer. In this study, we characterize Drosophila small RNAs that derive from short intronic hairpins termed "mirtrons." Their nuclear biogenesis appears to bypass Drosha cleavage, which is essential for miRNA biogenesis. Instead, mirtron hairpins are defined by the action of the splicing machinery and lariat-debranching enzyme, which yield pre-miRNA-like hairpins. The mirtron pathway merges with the canonical miRNA pathway during hairpin export by Exportin-5, and both types of hairpins are subsequently processed by Dicer-1/loqs. This generates small RNAs that can repress perfectly matched and seed-matched targets, and we provide evidence that they function, at least in part, via the RNA-induced silencing complex effector Ago1. These findings reveal that mirtrons are an alternate source of miRNA-type regulatory RNAs.
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                Author and article information

                Contributors
                agne.velthut@taltech.ee
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                10 February 2020
                10 February 2020
                2020
                : 10
                : 2300
                Affiliations
                [1 ]ISNI 0000000110107715, GRID grid.6988.f, Department of Chemistry and Biotechnology, , Tallinn University of Technology, ; Tallinn, Estonia
                [2 ]GRID grid.487355.8, Competence Centre on Health Technologies, ; Tartu, Estonia
                [3 ]ISNI 0000 0001 0943 7661, GRID grid.10939.32, Institute of Molecular and Cell Biology, University of Tartu, ; Tartu, Estonia
                [4 ]ISNI 0000 0001 0943 7661, GRID grid.10939.32, Proteomics Core Facility, Institute of Technology, University of Tartu, ; Tartu, Estonia
                [5 ]ISNI 0000 0001 0943 7661, GRID grid.10939.32, Institute of Clinical Medicine, Department of Obstetrics and Gynecology, University of Tartu, ; Tartu, Estonia
                [6 ]ISNI 0000 0001 0943 7661, GRID grid.10939.32, Institute of Biomedicine and Translational Medicine, Department of Biomedicine, University of Tartu, ; Tartu, Estonia
                [7 ]ISNI 0000 0004 0410 2071, GRID grid.7737.4, Department of Obstetrics and Gynecology, , University of Helsinki and Helsinki University Hospital, ; Helsinki, Finland
                Article
                59186
                10.1038/s41598-020-59186-x
                7010774
                32042028
                b695ac05-887e-4ec5-b9dc-f0d10ab0bd49
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 16 September 2019
                : 8 January 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100011264, FP7 People: Marie-Curie Actions;
                Award ID: EU324509
                Award ID: EU324509
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100003510, Haridus- ja Teadusministeerium;
                Award ID: IUT34-16
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100006598, Ettevõtluse Arendamise Sihtasutus;
                Award ID: EU48695
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100007601, Horizon 2020;
                Award ID: 692065
                Award Recipient :
                Funded by: MSCA-RISE-2015 program MOMENDO
                Award ID: 691058
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                Uncategorized
                mirnas,transcriptomics,ovary
                Uncategorized
                mirnas, transcriptomics, ovary

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