ABSTRACT
BACKGROUND: The function of many noncoding RNAs (ncRNAs) depend upon their secondary structures. Over the last decades, several methodologies have been developed to predict such structures or to use them to functionally annotate RNAs into RNA families. However, to fully perform this analysis, researchers should utilize multiple tools, which require the constant parsing and processing of several intermediate files. This makes the large-scale prediction and annotation of RNAs a daunting task even to researchers with good computational or bioinformatics skills. RESULTS: We present an automated pipeline named StructRNAfinder that predicts and annotates RNA families in transcript or genome sequences. This single tool not only displays the sequence/structural consensus alignments for each RNA family, according to Rfam database but also provides a taxonomic overview for each assigned functional RNA. Moreover, we implemented a user-friendly web service that allows researchers to upload their own nucleotide sequences in order to perform the whole analysis. Finally, we provided a stand-alone version of StructRNAfinder to be used in large-scale projects. The tool was developed under GNU General Public License (GPLv3) and is freely available at http://structrnafinder.integrativebioinformatics.me . CONCLUSIONS: The main advantage of StructRNAfinder relies on the large-scale processing and integrating the data obtained by each tool and database employed along the workflow, of which several files are generated and displayed in user-friendly reports, useful for downstream analyses and data exploration.
Subject(s)
Computational Biology/methods , Internet , RNA/genetics , Software , Automation , RNA/chemistry , RNA/classification , WorkflowABSTRACT
BACKGROUND: Trypanosomes mostly control gene expression by post-transcriptional events such as modulation of mRNA stability and translational efficiency. These mechanisms involve RNA-binding proteins (RBPs), which associate with transcripts to form messenger ribonucleoprotein (mRNP) complexes. RESULTS: In this study, we report the identification of mRNA targets for Trypanosoma cruzi U-rich RBP 1 (TcUBP1) and T. cruzi RBP 3 (TcRBP3), two phylogenetically conserved proteins among Kinetoplastids. Co-immunoprecipitated RBP-associated RNAs were extracted from mRNP complexes and binding of RBPs to several targets was confirmed by independent experimental assays. Analysis of target transcript sequences allowed the identification of different signature RNA motifs for each protein. Cis-elements for RBP binding have a stem-loop structure of 30-35 bases and are more frequently represented in the 3'-untranslated region (UTR) of mRNAs. Insertion of the correctly folded RNA elements to a non-specific mRNA rendered it into a target transcript, whereas substitution of the RNA elements abolished RBP interaction. In addition, RBPs competed for RNA-binding sites in accordance with the distribution of different and overlapping motifs in the 3'-UTRs of common mRNAs. CONCLUSION: Functionally related transcripts were preferentially associated with a given RBP; TcUBP1 targets were enriched in genes encoding proteins involved in metabolism, whereas ribosomal protein-encoding transcripts were the largest group within TcRBP3 targets. Together, these results suggest coordinated control of different mRNA subsets at the post-transcriptional level by specific RBPs.