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      Long non-coding RNAs harboring miRNA seed regions are enriched in prostate cancer exosomes

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          Abstract

          Long non-coding RNAs (lncRNAs) form the largest transcript class in the human transcriptome. These lncRNA are expressed not only in the cells, but they are also present in the cell-derived extracellular vesicles such as exosomes. The function of these lncRNAs in cancer biology is not entirely clear, but they appear to be modulators of gene expression. In this study, we characterize the expression of lncRNAs in several prostate cancer exosomes and their parental cell lines. We show that certain lncRNAs are enriched in cancer exosomes with the overall expression signatures varying across cell lines. These exosomal lncRNAs are themselves enriched for miRNA seeds with a preference for let-7 family members as well as miR-17, miR-18a, miR-20a, miR-93 and miR-106b. The enrichment of miRNA seed regions in exosomal lncRNAs is matched with a concomitant high expression of the same miRNA. In addition, the exosomal lncRNAs also showed an over representation of RNA binding protein binding motifs. The two most common motifs belonged to ELAVL1 and RBMX. Given the enrichment of miRNA and RBP sites on exosomal lncRNAs, their interplay may suggest a possible function in prostate cancer carcinogenesis.

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          The transcriptional landscape of the mammalian genome.

          This study describes comprehensive polling of transcription start and termination sites and analysis of previously unidentified full-length complementary DNAs derived from the mouse genome. We identify the 5' and 3' boundaries of 181,047 transcripts with extensive variation in transcripts arising from alternative promoter usage, splicing, and polyadenylation. There are 16,247 new mouse protein-coding transcripts, including 5154 encoding previously unidentified proteins. Genomic mapping of the transcriptome reveals transcriptional forests, with overlapping transcription on both strands, separated by deserts in which few transcripts are observed. The data provide a comprehensive platform for the comparative analysis of mammalian transcriptional regulation in differentiation and development.
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            Analysis of microarray data using Z score transformation.

            High-throughput cDNA microarray technology allows for the simultaneous analysis of gene expression levels for thousands of genes and as such, rapid, relatively simple methods are needed to store, analyze, and cross-compare basic microarray data. The application of a classical method of data normalization, Z score transformation, provides a way of standardizing data across a wide range of experiments and allows the comparison of microarray data independent of the original hybridization intensities. Data normalized by Z score transformation can be used directly in the calculation of significant changes in gene expression between different samples and conditions. We used Z scores to compare several different methods for predicting significant changes in gene expression including fold changes, Z ratios, Z and t statistical tests. We conclude that the Z score transformation normalization method accompanied by either Z ratios or Z tests for significance estimates offers a useful method for the basic analysis of microarray data. The results provided by these methods can be as rigorous and are no more arbitrary than other test methods, and, in addition, they have the advantage that they can be easily adapted to standard spreadsheet programs.
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              Endogenous miRNA sponge lincRNA-RoR regulates Oct4, Nanog, and Sox2 in human embryonic stem cell self-renewal.

              The embryonic stem cell (ESC) transcriptional and epigenetic networks are controlled by a multilayer regulatory circuitry, including core transcription factors (TFs), posttranscriptional modifier microRNAs (miRNAs), and some other regulators. However, the role of large intergenic noncoding RNAs (lincRNAs) in this regulatory circuitry and their underlying mechanism remains undefined. Here, we demonstrate that a lincRNA, linc-RoR, may function as a key competing endogenous RNA to link the network of miRNAs and core TFs, e.g., Oct4, Sox2, and Nanog. We show that linc-RoR shares miRNA-response elements with these core TFs and that linc-RoR prevents these core TFs from miRNA-mediated suppression in self-renewing human ESC. We suggest that linc-RoR forms a feedback loop with core TFs and miRNAs to regulate ESC maintenance and differentiation. These results may provide insights into the functional interactions of the components of genetic networks during development and may lead to new therapies for many diseases. Copyright © 2013 Elsevier Inc. All rights reserved.
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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                22 April 2016
                2016
                : 6
                : 24922
                Affiliations
                [1 ]Centre for Human Centred Technology Design, University of Technology , Sydney
                [2 ]Centre for Health Technologies, Faculty of Engineering and Information Technology, University of Technology , Sydney
                [3 ]School of Life Sciences, Faculty of Science, University of Technology , Sydney
                [4 ]Centre for Quantum Computation and Intelligent Systems, University of Technology , Sydney
                [5 ]The Sydney Head and Neck Cancer Institute, Sydney Cancer Centre, Royal Prince Alfred Hospital , Australia
                Author notes
                Article
                srep24922
                10.1038/srep24922
                4840345
                27102850
                4c5f639a-a18c-4121-aacb-6e3d9caad50c
                Copyright © 2016, Macmillan Publishers Limited

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 30 May 2015
                : 21 March 2016
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