Abstract
RNA structure heterogeneity is a major challenge when querying RNA structures with chemical probing. We introduce DRACO, an algorithm for the deconvolution of coexisting RNA conformations from mutational profiling experiments. Analysis of the SARS-CoV-2 genome using dimethyl sulfate mutational profiling with sequencing (DMS-MaPseq) and DRACO, identifies multiple regions that fold into two mutually exclusive conformations, including a conserved structural switch in the 3' untranslated region. This work may open the way to dissecting the heterogeneity of the RNA structurome.
Highlights
RNA structure heterogeneity is a major challenge when querying RNA structures with chemical probing
Even if powerful in principle, this method has two major limitations: (1) the maximum number of RNA conformations that can be searched for is user defined, to reduce the risk of overestimating the number of conformations; and (2) it can handle only experiments in which the sequencing reads cover the entire length of the target RNA
We introduce DRACO (v1.0), a method for the deconvolution of alternative RNA conformations from mutational profiling experiments, based on a combination of spectral clustering and fuzzy clustering (Supplementary Note 1)
Summary
RNA structure heterogeneity is a major challenge when querying RNA structures with chemical probing. Data-driven RNA structure prediction using these profiles produced secondary structure models nearly identical to the reference structures expected for the 10 °C and 37 °C conformations (positive predictive value, PPV, 1.00 and 0.91; sensitivity, 0.87 and 0.97, respectively; Fig. 2c). In each of the two experiments, analysis with DRACO unambiguously identified 22 windows, which accounted for ~15.5% of the SARS-CoV-2 genome, that folded consistently into two conformations (Supplementary Fig. 17a).
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