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      Identification of Transposable Elements Contributing to Tissue-Specific Expression of Long Non-Coding RNAs

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          Abstract

          It has been recently suggested that transposable elements (TEs) are re-used as functional elements of long non-coding RNAs (lncRNAs). This is supported by some examples such as the human endogenous retrovirus subfamily H (HERVH) elements contained within lncRNAs and expressed specifically in human embryonic stem cells (hESCs), as required to maintain hESC identity. There are at least two unanswered questions about all lncRNAs. How many TEs are re-used within lncRNAs? Are there any other TEs that affect tissue specificity of lncRNA expression? To answer these questions, we comprehensively identify TEs that are significantly related to tissue-specific expression levels of lncRNAs. We downloaded lncRNA expression data corresponding to normal human tissue from the Expression Atlas and transformed the data into tissue specificity estimates. Then, Fisher’s exact tests were performed to verify whether the presence or absence of TE-derived sequences influences the tissue specificity of lncRNA expression. Many TE–tissue pairs associated with tissue-specific expression of lncRNAs were detected, indicating that multiple TE families can be re-used as functional domains or regulatory sequences of lncRNAs. In particular, we found that the antisense promoter region of L1PA2, a LINE-1 subfamily, appears to act as a promoter for lncRNAs with placenta-specific expression.

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

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            A germline-specific class of small RNAs binds mammalian Piwi proteins.

            Small RNAs associate with Argonaute proteins and serve as sequence-specific guides to regulate messenger RNA stability, protein synthesis, chromatin organization and genome structure. In animals, Argonaute proteins segregate into two subfamilies. The Argonaute subfamily acts in RNA interference and in microRNA-mediated gene regulation using 21-22-nucleotide RNAs as guides. The Piwi subfamily is involved in germline-specific events such as germline stem cell maintenance and meiosis. However, neither the biochemical function of Piwi proteins nor the nature of their small RNA guides is known. Here we show that MIWI, a murine Piwi protein, binds a previously uncharacterized class of approximately 29-30-nucleotide RNAs that are highly abundant in testes. We have therefore named these Piwi-interacting RNAs (piRNAs). piRNAs show distinctive localization patterns in the genome, being predominantly grouped into 20-90-kilobase clusters, wherein long stretches of small RNAs are derived from only one strand. Similar piRNAs are also found in human and rat, with major clusters occurring in syntenic locations. Although their function must still be resolved, the abundance of piRNAs in germline cells and the male sterility of Miwi mutants suggest a role in gametogenesis.
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              Expression Atlas update—a database of gene and transcript expression from microarray- and sequencing-based functional genomics experiments

              Expression Atlas (http://www.ebi.ac.uk/gxa) is a value-added database providing information about gene, protein and splice variant expression in different cell types, organism parts, developmental stages, diseases and other biological and experimental conditions. The database consists of selected high-quality microarray and RNA-sequencing experiments from ArrayExpress that have been manually curated, annotated with Experimental Factor Ontology terms and processed using standardized microarray and RNA-sequencing analysis methods. The new version of Expression Atlas introduces the concept of ‘baseline’ expression, i.e. gene and splice variant abundance levels in healthy or untreated conditions, such as tissues or cell types. Differential gene expression data benefit from an in-depth curation of experimental intent, resulting in biologically meaningful ‘contrasts’, i.e. instances of differential pairwise comparisons between two sets of biological replicates. Other novel aspects of Expression Atlas are its strict quality control of raw experimental data, up-to-date RNA-sequencing analysis methods, expression data at the level of gene sets, as well as genes and a more powerful search interface designed to maximize the biological value provided to the user.
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                Author and article information

                Journal
                Genes (Basel)
                Genes (Basel)
                genes
                Genes
                MDPI
                2073-4425
                09 January 2018
                January 2018
                : 9
                : 1
                : 23
                Affiliations
                [1 ]Department of Electrical Engineering and Bioscience, Faculty of Science and Engineering, Waseda University, 55N-06-10, 3-4-1, Okubo Shinjuku-ku, Tokyo 169-8555, Japan; unzncsmtkfm@ 123456asagi.waseda.jp
                [2 ]Computational Bio Big-Data Open Innovation Laboratory (CBBD-OIL), National Institute of Advanced Industrial Science and Technology (AIST), 63-520, 3-4-1, Okubo Shinjuku-ku, Tokyo 169-8555, Japan
                [3 ]Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, 277-8562 Chiba, Japan; iwakiri@ 123456cb.k.u-tokyo.ac.jp
                [4 ]Artificial Intelligence Research Center (AIRC), National Institute of Advanced Industrial Science and Technology (AIST), 2-3-26, Aomi, Koto-ku, Tokyo 135-0064, Japan
                [5 ]Institute for Medical-oriented Structural Biology, Waseda University, 2-2, Wakamatsu-cho, Shinjuku-ku, Tokyo 162-8480, Japan
                [6 ]Graduate School of Medicine, Nippon Medical School, 1-1-5, Sendagi, Bunkyo-ku, Tokyo 113-8602, Japan
                Author notes
                [* ]Correspondence: mhamada@ 123456waseda.jp ; Tel.: +81-3-5286-3130
                Author information
                https://orcid.org/0000-0001-9466-1034
                Article
                genes-09-00023
                10.3390/genes9010023
                5793176
                29315213
                cfb553c3-d0d7-473c-ae74-09092db6162b
                © 2018 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 30 November 2017
                : 28 December 2017
                Categories
                Article

                long non-coding rna,transposable element,tissue-specific expression

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