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      The Dynamics of microRNA Transcriptome in Bovine Corpus Luteum during Its Formation, Function, and Regression

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          Abstract

          The formation, function, and subsequent regression of the ovarian corpus luteum (CL) are dynamic processes that enable ovary cyclical activity. Studies in whole ovary tissue have found microRNAs (miRNAs) to by critical for ovary function. However, relatively little is known about the role of miRNAs in the bovine CL. Utilizing small RNA next-generation sequencing we profiled miRNA transcriptome in bovine CL during the entire physiological estrous cycle, by sampling the CL on days: d 1–2, d 3–4, and d 5–7 (early CL, eCL), d 8–12 (mid CL, mCL), d 13–16 (late CL, lCL), and d > 18 (regressed CL, rCL). We characterized patterns of miRNAs abundance and identified 42 miRNAs that were consistent significantly different expressed (DE) in the eCL relative to their expression at each of the analyzed stages (mCL, lCL, and rCL). Out of these, bta-miR-210-3p, −2898, −96, −7-5p, −183-5p, −182, and −202 showed drastic up-regulation with a fold-change of ≥2.0 and adjusted P < 0.01 in the eCL, while bta-miR-146a was downregulated at lCL and rCL vs. the eCL. Another 24, 11, and 21 miRNAs were significantly DE only between individual comparisons, eCL vs. the mCL, lCL, and rCL, respectively. Irrespective of cycle stage two miRNAs, bta-miR-21-5p and bta-miR-143 were identified as the most abundant miRNAs species and show opposing expression abundance. Whilst bta-miR-21-5p peaked in number of reads in the eCL and was significantly downregulated in the mCL and lCL, bta-miR-143 reached its peak in the rCL and is significantly downregulated in the eCL. MiRNAs with significant DE in at least one cycle stage (CL class) were further grouped into eight distinct clusters by the self-organizing tree algorithm (SOTA). Half of the clusters contain miRNAs with low-expression, whilst the other half contain miRNAs with high-expression levels during eCL. Prediction analysis for significantly DE miRNAs resulted in target genes involved with CL formation, functionalization and CL regression. This study is the most comprehensive profiling of miRNA transcriptome in bovine CL covering the entire estrous cycle and provides a compact database for further functional validation and biomarker identification relevant for CL viability and fertility.

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          miRTarBase 2016: updates to the experimentally validated miRNA-target interactions database

          MicroRNAs (miRNAs) are small non-coding RNAs of approximately 22 nucleotides, which negatively regulate the gene expression at the post-transcriptional level. This study describes an update of the miRTarBase (http://miRTarBase.mbc.nctu.edu.tw/) that provides information about experimentally validated miRNA-target interactions (MTIs). The latest update of the miRTarBase expanded it to identify systematically Argonaute-miRNA-RNA interactions from 138 crosslinking and immunoprecipitation sequencing (CLIP-seq) data sets that were generated by 21 independent studies. The database contains 4966 articles, 7439 strongly validated MTIs (using reporter assays or western blots) and 348 007 MTIs from CLIP-seq. The number of MTIs in the miRTarBase has increased around 7-fold since the 2014 miRTarBase update. The miRNA and gene expression profiles from The Cancer Genome Atlas (TCGA) are integrated to provide an effective overview of this exponential growth in the miRNA experimental data. These improvements make the miRTarBase one of the more comprehensively annotated, experimentally validated miRNA-target interactions databases and motivate additional miRNA research efforts.
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            Cell-type-specific signatures of microRNAs on target mRNA expression.

            Although it is known that the human genome contains hundreds of microRNA (miRNA) genes and that each miRNA can regulate a large number of mRNA targets, the overall effect of miRNAs on mRNA tissue profiles has not been systematically elucidated. Here, we show that predicted human mRNA targets of several highly tissue-specific miRNAs are typically expressed in the same tissue as the miRNA but at significantly lower levels than in tissues where the miRNA is not present. Conversely, highly expressed genes are often enriched in mRNAs that do not have the recognition motifs for the miRNAs expressed in these tissues. Together, our data support the hypothesis that miRNA expression broadly contributes to tissue specificity of mRNA expression in many human tissues. Based on these insights, we apply a computational tool to directly correlate 3' UTR motifs with changes in mRNA levels upon miRNA overexpression or knockdown. We show that this tool can identify functionally important 3' UTR motifs without cross-species comparison.
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              The membrane-anchored MMP inhibitor RECK is a key regulator of extracellular matrix integrity and angiogenesis.

              Matrix metalloproteinases (MMPs) are essential for proper extracellular matrix remodeling. We previously found that a membrane-anchored glycoprotein, RECK, negatively regulates MMP-9 and inhibits tumor invasion and metastasis. Here we show that RECK regulates two other MMPs, MMP-2 and MT1-MMP, known to be involved in cancer progression, that mice lacking a functional RECK gene die around E10.5 with defects in collagen fibrils, the basal lamina, and vascular development, and that this phenotype is partially suppressed by MMP-2 null mutation. Also, vascular sprouting is dramatically suppressed in tumors derived from RECK-expressing fibrosarcoma cells grown in nude mice. These results support a role for RECK in the regulation of MMP-2 in vivo and implicate RECK downregulation in tumor angiogenesis.
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                Author and article information

                Contributors
                Journal
                Front Genet
                Front Genet
                Front. Genet.
                Frontiers in Genetics
                Frontiers Media S.A.
                1664-8021
                15 December 2017
                2017
                : 8
                : 213
                Affiliations
                [1] 1Department of Animal Husbandry and Biotechnology, Faculty of Agriculture and Veterinary, University of Pristina , Pristina, Albania
                [2] 2Department of Animal Physiology & Immunology, Weihenstephan, Technical University of Munich , Munich, Germany
                [3] 3Department of Environmental Systems Science, ETH Zürich , Zurich, Switzerland
                [4] 4Dr. von Hauner Children's Hospital, Ludwig Maximillian Universität , München, Germany
                [5] 5Department of Physiology, TUM School of Life Sciences Weihenstephan, Technical University of Munich , Freising, Germany
                [6] 6Eurofins Medigenomix Forensik GmbH , Ebersberg, Germany
                [7] 7Department of Health Science and Technology, ETH Zürich , Zurich, Switzerland
                Author notes

                Edited by: Emanuele Buratti, International Centre for Genetic Engineering and Biotechnology, Italy

                Reviewed by: Maurizio Romano, University of Trieste, Italy; Mauricio Fernando Budini, Universidad de Chile, Chile

                *Correspondence: Bajram Berisha bajram.berisha@ 123456uni-pr.edu

                This article was submitted to RNA, a section of the journal Frontiers in Genetics

                Article
                10.3389/fgene.2017.00213
                5736867
                29326752
                96769d48-1535-4918-8448-ef6b5c87aa43
                Copyright © 2017 Gecaj, Schanzenbach, Kirchner, Pfaffl, Riedmaier, Tweedie-Cullen and Berisha.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 27 September 2017
                : 30 November 2017
                Page count
                Figures: 4, Tables: 3, Equations: 0, References: 96, Pages: 16, Words: 12387
                Funding
                Funded by: Deutsche Forschungsgemeinschaft 10.13039/501100001659
                Award ID: DFG BE 3189/2-2
                Funded by: Ministry of Education, Science and Technology, Pristina, Kosovo
                Award ID: FPVSh-2-4051-2
                Categories
                Genetics
                Original Research

                Genetics
                microrna,small rna seq,bovine,corpus luteum,estrous cycle,sota
                Genetics
                microrna, small rna seq, bovine, corpus luteum, estrous cycle, sota

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