Abstract
The prediction of functional RNA structures has attracted increased interest, as it allows us to study the potential functional roles of many genes. RNA structure prediction methods, however, assume that there is a unique functional RNA structure and also do not predict functional features required for in vivo folding. In order to understand how functional RNA structures form in vivo, we require sophisticated experiments or reliable prediction methods. So far, there exist only a few, experimentally validated transient RNA structures. On the computational side, there exist several computer programs which aim to predict the co-transcriptional folding pathway in vivo, but these make a range of simplifying assumptions and do not capture all features known to influence RNA folding in vivo. We want to investigate if evolutionarily related RNA genes fold in a similar way in vivo. To this end, we have developed a new computational method, Transat, which detects conserved helices of high statistical significance. We introduce the method, present a comprehensive performance evaluation and show that Transat is able to predict the structural features of known reference structures including pseudo-knotted ones as well as those of known alternative structural configurations. Transat can also identify unstructured sub-sequences bound by other molecules and provides evidence for new helices which may define folding pathways, supporting the notion that homologous RNA sequence not only assume a similar reference RNA structure, but also fold similarly. Finally, we show that the structural features predicted by Transat differ from those assuming thermodynamic equilibrium. Unlike the existing methods for predicting folding pathways, our method works in a comparative way. This has the disadvantage of not being able to predict features as function of time, but has the considerable advantage of highlighting conserved features and of not requiring a detailed knowledge of the cellular environment.
Highlights
RNA molecules play diverse roles in many of the most basic cellular processes
The resulting folding pathway is known to depend on a variety of features such as the transcription speed, the concentration of various ions and the binding of proteins and other molecules. Not all of these influences can be adequately captured by the existing computational methods which try to replicate what happens in vivo
In order to investigate if functionally similar RNA sequences from different organisms fold in a similar way, we have developed a new computational method, called TRANSAT, which does not require the detailed computational modeling of the cellular environment
Summary
RNA molecules play diverse roles in many of the most basic cellular processes. In the translation process, for instance, the protein coding ‘message’ is encoded in a messenger RNA (mRNA) and transfer RNAs (tRNAs) and ribosomal RNAs (rRNAs) are involved in this catalytic process. For many classes of ncRNA molecules studied so far, RNA structure plays a crucial part in defining its functional role in the cell. For example, that tRNAs assume a distinct threedimensional conformation in order to function properly during translation and that the functional configuration of the ribosome complex relies both, on properly folded rRNAs as well as many proteins binding to the respective rRNAs. In contrast to proteins, we can typically learn a lot about an RNA’s functionality by studying only its secondary structure, i.e. the set of base-pairing nucleotide positions in the RNA sequence. We can typically learn a lot about an RNA’s functionality by studying only its secondary structure, i.e. the set of base-pairing nucleotide positions in the RNA sequence This is the case because most RNA sequences studied so far fold in a hierarchical manner, with the secondary structure emerging first and the tertiary contacts between secondary structure elements emerging later
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