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      Evaluation of circulating miRNAs during late pregnancy in the mare

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          Abstract

          MicroRNAs (miRNAs) are small, non-coding RNAs which are produced throughout the body. Individual tissues tend to have a specific expression profile and excrete many of these miRNAs into circulation. These circulating miRNAs may be diagnostically valuable biomarkers for assessing the presence of disease while minimizing invasive testing. In women, numerous circulating miRNAs have been identified which change significantly during pregnancy-related complications (e.g. chorioamnionitis, eclampsia, recurrent pregnancy loss); however, no prior work has been done in this area in the horse. To identify pregnancy-specific miRNAs, we collected serial whole blood samples in pregnant mares at 8, 9, 10 m of gestation and post-partum, as well as from non-pregnant (diestrous) mares. In total, we evaluated a panel of 178 miRNAs using qPCR, eventually identifying five miRNAs of interest. One miRNA (miR-374b) was differentially regulated through late gestation and four miRNAs (miR-454, miR-133b, miR-486-5p and miR-204b) were differentially regulated between the pregnant and non-pregnant samples. We were able to identify putative targets for the differentially regulated miRNAs using two separate target prediction programs, miRDB and Ingenuity Pathway Analysis. The targets for the miRNAs differentially regulated during pregnancy were predicted to be involved in signaling pathways such as the STAT3 pathway and PI3/AKT signaling pathway, as well as more endocrine-based pathways, including the GnRH, prolactin and insulin signaling pathways. In summary, this study provides novel information about the changes occurring in circulating miRNAs during normal pregnancy, as well as attempting to predict the biological effects induced by these miRNAs.

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          Most cited references35

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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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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              Analysis of microRNA turnover in mammalian cells following Dicer1 ablation

              Although microRNAs (miRNAs) are key regulators of gene expression, little is known of their overall persistence in the cell following processing. Characterization of such persistence is key to the full appreciation of their regulatory roles. Accordingly, we measured miRNA decay rates in mouse embryonic fibroblasts following loss of Dicer1 enzymatic activity. The results confirm the inherent stability of miRNAs, the intracellular levels of which were mostly affected by cell division. Using the decay rates of a panel of six miRNAs representative of the global trend of miRNA decay, we establish a mathematical model of miRNA turnover and determine an average miRNA half-life of 119 h (i.e. ∼5 days). In addition, we demonstrate that select miRNAs turnover more rapidly than others. This study constitutes, to our knowledge, the first in-depth characterization of miRNA decay in mammalian cells. Our findings indicate that miRNAs are up to 10× more stable than messenger RNA and support the existence of novel mechanism(s) controlling selective miRNA cellular concentration and function.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                7 April 2017
                2017
                : 12
                : 4
                : e0175045
                Affiliations
                [1 ]Department of Veterinary Science, University of Kentucky, Lexington, KY, United States of America
                [2 ]Department of Animal Sciences, Colorado State University, Fort Collins, CO, United States of America
                [3 ]Department of Veterinary Clinical Medicine, College of Veterinary Medicine, University of Illinois, Urbana, IL, United States of America
                University of Florida, UNITED STATES
                Author notes

                Competing Interests: One of our funding sources was a commercial source: the Kentucky Thoroughbred Association/Kentucky Thoroughbred Breeders and Owners. Although this is a commercial association, there are no ties to them through employment, consultancy, patents, products in development or marketed products. This group is comprised of local horse owners and breeders who are interested in learning more about the biology of pregnancy in the hopes of eventually reducing the incidence of late-term abortions in their own stock. Funding from this source does not alter our adherence to PLOS ONE policies on sharing data and materials.

                • Conceptualization: SCL BAB.

                • Formal analysis: SCL BAB.

                • Funding acquisition: MHTT ELS BAB.

                • Investigation: SCL.

                • Methodology: SCL BAB KES JEB.

                • Project administration: SCL BAB JEB.

                • Resources: BAB JEB IFC.

                • Supervision: BAB.

                • Validation: SCL BAB.

                • Visualization: SCL.

                • Writing – original draft: SCL.

                • Writing – review & editing: SCL KES JEB IFC MHTT ELS BAB.

                Author information
                http://orcid.org/0000-0001-5193-6675
                http://orcid.org/0000-0002-0502-0276
                Article
                PONE-D-16-49121
                10.1371/journal.pone.0175045
                5384662
                28388652
                980ab4d7-fad0-47e7-9adf-1f3490eb4853
                © 2017 Loux et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 13 December 2016
                : 20 March 2017
                Page count
                Figures: 2, Tables: 2, Pages: 12
                Funding
                This work was funded by the Kentucky Thoroughbred Association/Kentucky Thoroughbred Breeders and Owners ( http://www.kentuckybred.org), the Albert Clay Endowment and the Paul Mellon post-doctoral fellowship, and the Geoffrey Hughes doctoral fellowship. Due to their relatively small size, not all funding sources have a website or grant numbers. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and life sciences
                Genetics
                Gene expression
                Gene regulation
                MicroRNAs
                Biology and life sciences
                Biochemistry
                Nucleic acids
                RNA
                Non-coding RNA
                MicroRNAs
                Medicine and Health Sciences
                Endocrinology
                Endocrine Physiology
                Insulin Signaling
                Biology and Life Sciences
                Physiology
                Endocrine Physiology
                Insulin Signaling
                Medicine and Health Sciences
                Physiology
                Endocrine Physiology
                Insulin Signaling
                Medicine and Health Sciences
                Women's Health
                Maternal Health
                Pregnancy
                Medicine and Health Sciences
                Women's Health
                Obstetrics and Gynecology
                Pregnancy
                Biology and life sciences
                Cell biology
                Signal transduction
                Cell signaling
                STAT signaling
                Biology and life sciences
                Cell biology
                Signal transduction
                Cell signaling
                PPAR signaling
                Biology and Life Sciences
                Cell Biology
                Signal Transduction
                Cell Signaling
                G-Protein Signaling
                Computer and Information Sciences
                Network Analysis
                Signaling Networks
                Biology and Life Sciences
                Cell Biology
                Signal Transduction
                Cell Signaling
                Signaling Cascades
                Protein Kinase Signaling Cascade
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

                Uncategorized
                Uncategorized

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