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Nucleic acids are particularly amenable to structural characterization using chemical and enzymatic probes. Each individual structure mapping experiment reveals specific information about the structure and/or dynamics of the nucleic acid. Currently, there is no simple approach for making these data publically available in a standardized format. We therefore developed a standard for reporting the results of single nucleotide resolution nucleic acid structure mapping experiments, or SNRNASMs. We propose a schema for sharing nucleic acid chemical probing data that uses generic public servers for storing, retrieving, and searching the data. We have also developed a consistent nomenclature (ontology) within the Ontology of Biomedical Investigations (OBI), which provides unique identifiers (termed persistent URLs, or PURLs) for classifying the data. Links to standardized data sets shared using our proposed format along with a tutorial and links to templates can be found at http://snrnasm.bio.unc.edu.

BayesFold is a Web application that folds an alignment of closely related sequences and evaluates hypotheses about their shared structure. It uses Bayes’s Theorem to combine information from several sources, including chemical mapping (if available), thermodynamic folding, and observed sequence variations. Its method provides a rational basis for integrating results, even when these methods conflict. On a gapped alignment of 86 tRNAPhe sequences each 77 bases long, BayesFold takes 31 sec to perform the calculations; the best structure contained 95% of the base pairs in the true structure, and the true structure was ranked second. Notably, similar results come from random samples of only 10 sequences from the alignment (running time 3 sec), suggesting that remarkably few sequences are required for good results. In contrast, folding single sequences with BayesFold produced structures 9.6 bp different, or with the Vienna package, 13.4 bp different, from the true structure . Similar results were obtained for other families of tRNAs. We especially recommend BayesFold for alignments of 3–50 closely related sequences, such as the sequence families frequently found in SELEX. In addition to providing a convenient way to explore the effects of each of the criteria on the plausibility of different structures, BayesFold also makes it easy to produce publication-quality secondary-structure graphics. The Web interface, available at http://bayes.colorado.edu/fold/, includes the flexibility to thread any of the sequences (or the consensus sequence) through any of the structures, including the one judged most probable.