MONSTER v1.1: a tool to extract and search for RNA non-branching structures

BMC Genomics

Research

Paola Paci¹  Giulio Iannello²  Giulia Fiscon³ 

[1] Institute for System Analysis and Computer Science "Antonio Ruberti" (IASI), National Research Council (CNR), Via dei Taurini 19, 00185, Rome, Italy;Institute for System Analysis and Computer Science "Antonio Ruberti" (IASI), National Research Council (CNR), Via dei Taurini 19, 00185, Rome, Italy;Centro integrato di ricerca, Università Campus Bio-medico di Roma, Via Alvaro del Portillo 21, 00128, Rome, Italy;Institute for System Analysis and Computer Science "Antonio Ruberti" (IASI), National Research Council (CNR), Via dei Taurini 19, 00185, Rome, Italy;Department of Computer, Control and Management Engineering (DIAG), Sapienza University, Via Ariosto 25, 00185, Rome, Italy;

关键词: RNA secondary structure;    RNA folding prediction;    Dynamic Programming Algorithm;    Structural Motifs;    Long Non-coding RNA;   

DOI  :  10.1186/1471-2164-16-S6-S1

来源: Springer

【 摘 要 】

BackgroundDetection of RNA structure similarities is still one of the major computational problems in the discovery of RNA functions. A case in point is the study of the new appreciated long non-coding RNAs (lncRNAs), emerging as new players involved in many cellular processes and molecular interactions. Among several mechanisms of action, some lncRNAs show specific substructures that are likely to be instrumental for their functioning. For instance, it has been reported in literature that some lncRNAs have a guiding or scaffolding role by binding chromatin-modifying protein complexes. Thus, a functionally characterized lncRNA (reference) can be used to infer the function of others that are functionally unknown (target), based on shared structural motifs.MethodsIn our previous work we presented a tool, MONSTER v1.0, able to identify structural motifs shared between two full-length RNAs. Our procedure is mainly composed of two ad-hoc developed algorithms: nbRSSP_extractor for characterizing the folding of an RNA sequence by means of a sequence-structure descriptor (i.e., an array of non-overlapping substructures located on the RNA sequence and coded by dot-bracket notation); and SSD_finder, to enable an effective search engine for groups of matches (i.e., chains) common to the reference and target RNA based on a dynamic programming approach with a new score function. Here, we present an updated version of the previous one (MONSTER v1.1) accounting for the peculiar feature of lncRNAs that are not expected to have a unique fold, but appear to fluctuate among a large number of equally-stable folds. In particular, we improved our SSD_finder algorithm in order to take into account all the alternative equally-stable structures.ResultsWe present an application of MONSTER v1.1 on lincRNAs, which are a specific class of lncRNAs located in genomic regions which do not overlap protein-coding genes. In particular, we provide reliable predictions of the shared chains between HOTAIR, ANRIL and COLDAIR. The latter are lincRNAs which interact with the same protein complexes of the Polycomb group and hence they are expected to share structural motifs.Software availability: the software package is provided as additional file 1 ("archive_updated.zip").

【 授权许可】

CC BY   
© Fiscon et al.; licensee BioMed Central Ltd. 2015