Clustering of RNA secondary structures with application to messenger RNAs.

There is growing evidence of translational gene regulation at the mRNA level, and of the important roles of RNA secondary structure in these regulatory processes. Because mRNAs likely exist in a population of structures, the popular free energy minimization approach may not be well suited to prediction of mRNA structures in studies of post-transcriptional regulation. Here, we describe an alternative procedure for the characterization of mRNA structures, in which structures sampled from the Boltzmann-weighted ensemble of RNA secondary structures are clustered. Based on a random sample of full-length human mRNAs, we find that the minimum free energy (MFE) structure often poorly represents the Boltzmann ensemble, that the ensemble often contains multiple structural clusters, and that the centroids of a small number of structural clusters more effectively characterize the ensemble. We show that cluster-level characteristics and statistics are statistically reproducible. In a comparison between mRNAs and structural RNAs, similarity is observed for the number of clusters and the energy gap between the MFE structure and the sampled ensemble. However, for structural RNAs, there are more high-frequency base-pairs in both the Boltzmann ensemble and the clusters, and the clusters are more compact. The clustering features have been incorporated into the Sfold software package for nucleic acid folding and design.