Decrypting noncoding RNA interactions, structures, and functional networks

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.

Figure 1.

Examples of interactor elements (IEs) and structural elements (SEs) in ncRNAs. (A) The IEs from the miR-15a/miR-16 cluster target the proapoptotic oncogene BCL2. When this miRNA cluster is down-regulated in human cancer cells, the BCL2 protein is overexpressed and can be targeted by the antiapoptotic small molecule venetoclax (Croce and Reed 2016). (B) The processing of another member of the miR-16 family, miR-195, is regulated by a direct interaction with the ultraconserved ncRNA uc.283. When this lncRNA is overexpressed in human cancer due to promoter hypomethylation, this interaction prevents DROSHA cropping of the mir-195 primary transcript, leading to down-regulation of the mature miR-195, a new mechanism of tumor-suppressor microRNA inactivation (Liz et al. 2014). (C) LINC01139 (LINK-A) is the first lncRNA known to interact with lipids, specifically with PIP₃, facilitating AKT activation and consequent resistance to AKT inhibitors (Lin et al. 2017). (PH-domain) Pleckstrin homology domain. (D) CCAT2 harbors a conserved SE, within which a SNP alters the secondary structure of the lncRNA so that the CCAT2 alleles bind to the CFIm splicing complex with distinct affinities. The cancer risk G allele induces the oncogenic GAC glutaminase-C isoform that causes colorectal cancer progression (Redis et al. 2016).

Figure 2.

The analogy between the natural language grammar and the ncRNA structure grammar. (A) The elements of the ncRNA language grammar. A schematic view of IEs, SEs, structural domains of a ncRNA, and the noncoding RNA interactor network (NIN) composed by the ncRNA, interactor RNAs (such as miRNAs), interactor proteins (such as P1), interactor DNA elements, and interactor lipids (such as PIP₃). Each ncRNA can contain multiple structural domains (here we show three for simplicity): one or multiple IEs and/or one or multiple SEs. These elements can be targeted by IE-blockers (IEBs), which release a specific interactor molecule (either DNAs, RNAs, proteins or lipids), and SE-lockers (SELs), which lock the lncRNA structure in a specific conformation favoring specific interactions with multiple molecules. A new type of therapy based on the correction of various interconnected genetic alterations that occur in the complex NINs by targeting the IEs can be envisaged, because these are docking sites for multiple types of molecules (DNA, RNA, proteins, and lipids) and/or the SEs, that directly affects the conformation of a lncRNA and indirectly the functional interactions with interactor molecules. (B) A comparison between the natural language and ncRNA language grammars. The various elements of the ncRNA language grammar are assembled under a “merge” (combine) function: The IEs and SEs from a lncRNA are combined during evolution by multiple rounds of merge (here, steps 1–6). (S) Subject; (NP) noun phrase; (VP) verb phrase; (V) verb.