Decrypting noncoding RNA interactions, structures, and functional networks

  1. George A. Calin4,5
  1. 1University of Hawaii Cancer Center, Cancer Biology Program, Honolulu, Hawaii 96813, USA;
  2. 2Department of Oncology-Pathology, Cellular and Molecular Tumor Pathology, Karolinska Institute, and Karolinska University Hospital, Stockholm, 17164 Sweden;
  3. 3Department of Chemistry, University of Washington, Seattle, Washington 98195-1700, USA;
  4. 4Department of Experimental Therapeutics, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030, USA;
  5. 5Center for RNA Interference and Non-Coding RNAs, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030, USA
  1. 6 These authors contributed equally to this work.

  • Corresponding authors: gcalin{at}mdanderson.org, varani{at}chem.washington.edu
  • Abstract

    The world of noncoding RNAs (ncRNAs) is composed of an enormous and growing number of transcripts, ranging in length from tens of bases to tens of kilobases, involved in all biological processes and altered in expression and/or function in many types of human disorders. The premise of this review is the concept that ncRNAs, like many large proteins, have a multidomain architecture that organizes them spatially and functionally. As ncRNAs are beginning to be imprecisely classified into functional families, we review here how their structural properties might inform their functions with focus on structural architecture–function relationships. We will describe the properties of “interactor elements” (IEs) involved in direct physical interaction with nucleic acids, proteins, or lipids and of “structural elements” (SEs) directing their wiring within the “ncRNA interactor networks” through the emergence of secondary and/or tertiary structures. We suggest that spectrums of “letters” (ncRNA elements) are assembled into “words” (ncRNA domains) that are further organized into “phrases” (complete ncRNA structures) with functional meaning (signaling output) through complex “sentences” (the ncRNA interactor networks). This semiotic analogy can guide the exploitation of ncRNAs as new therapeutic targets through the development of IE-blockers and/or SE-lockers that will change the interactor partners’ spectrum of proteins, RNAs, DNAs, or lipids and consequently influence disease phenotypes.

    This article, published in Genome Research, is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/.

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