Revealing protein–lncRNA interaction

• Published in: Briefings in bioinformatics Vol. 17; no. 1; pp. 106 - 116
• Main Authors: Ferrè, Fabrizio, Colantoni, Alessio, Helmer-Citterich, Manuela
• Format: Journal Article
• Language: English
• Published: England Oxford Publishing Limited (England) 01.01.2016; Oxford University Press
• Subjects: Binding sites; Bioinformatics; Computational Biology - methods; Computer Simulation; Deregulation; High-Throughput Nucleotide Sequencing - statistics & numerical data; Humans; Models, Molecular; non-coding RNA; Nucleic Acid Conformation; pathological processes and conditions; prediction; Protein Conformation; Protein Interaction Maps - genetics; Proteins; Ribonucleic acid; RNA; RNA, Long Noncoding - chemistry; RNA, Long Noncoding - genetics; RNA, Long Noncoding - metabolism; RNA-binding proteins; RNA-Binding Proteins - chemistry; RNA-Binding Proteins - genetics; RNA-Binding Proteins - metabolism; RNA-protein interactions; SELEX Aptamer Technique - statistics & numerical data; co-immunoprecipitation; long non-coding RNAs; protein–RNA interactions; high-throughput sequencing
• ISSN: 1467-5463; 1477-4054; 1477-4054
• DOI: 10.1093/bib/bbv031

Long non-coding RNAs (lncRNAs) are associated to a plethora of cellular functions, most of which require the interaction with one or more RNA-binding proteins (RBPs); similarly, RBPs are often able to bind a large number of different RNAs. The currently available knowledge is already drawing an intricate network of interactions, whose deregulation is frequently associated to pathological states. Several different techniques were developed in the past years to obtain protein-RNA binding data in a high-throughput fashion. In parallel, in silico inference methods were developed for the accurate computational prediction of the interaction of RBP-lncRNA pairs. The field is growing rapidly, and it is foreseeable that in the near future, the protein-lncRNA interaction network will rise, offering essential clues for a better understanding of lncRNA cellular mechanisms and their disease-associated perturbations.