Single-molecule correlated chemical probing of RNA

Abstract

Complex higher-order RNA structures play critical roles in all facets of gene expression; however, the through-space interaction networks that define tertiary structures and govern sampling of multiple conformations are poorly understood. Here we describe single-molecule RNA structure analysis in which multiple sites of chemical modification are identified in single RNA strands by massively parallel sequencing and then analyzed for correlated and clustered interactions. The strategy thus identifies RNA interaction groups by mutational profiling (RING-MaP) and makes possible two expansive applications. First, we identify through-space interactions, create 3D models for RNAs spanning 80-265 nucleotides, and characterize broad classes of intramolecular interactions that stabilize RNA. Second, we distinguish distinct conformations in solution ensembles and reveal previously undetected hidden states and large-scale structural reconfigurations that occur in unfolded RNAs relative to native states. RING-MaP single-molecule nucleic acid structure interrogation enables concise and facile analysis of the global architectures and multiple conformations that govern function in RNA.

Keywords: dimethyl sulfate; motif discovery; spectral clustering; structure refinement.

Fig. 1.

Single-molecule RNA structure analysis by massively parallel sequencing. (A) RNA molecules experience local structural variations and “breathing” in which nucleotides become reactive to a chemical probe in a correlated way. Statistical association analysis is used to detect and quantify the strengths of these interdependencies. (B) RNA molecules can adopt multiple conformations in solution. Spectral clustering analysis, based on similarity of nucleotide reactivity patterns, can be used to separate data on individual RNA strands into different conformations.

Fig. 2.

Efficient DMS adduct formation at the base-pairing faces of adenosine and cytosine. (A) Reaction of nucleotides with 170 mM DMS in 300 mM cacodylate (pH 7) monitored by gel electrophoresis. (B) Time course of DMS reaction with adenosine and cytosine. Unconstrained nucleotides react to form methyl adducts with ∼12% efficiency in 6 min (arrow).

Fig. 3.

RING analysis of RNA structure. (A) Number of mutations per transcript detected by reverse transcription with (red) and without (black) DMS modification. (B) DMS modification-induced mutation frequencies as a function of nucleotide position. Data from DMS-treated samples are shown in red and no-reagent controls are black. (C) RINGs for the TPP riboswitch, P546 domain, and RNase P RNAs showing strong (green) and moderate (yellow) correlations. Correlations occur between positions that are reactive in the native structure (filled red circles) or become reactive during “breathing” motions (open circles). Correlation coefficients of 0.025 and 0.035 correspond to median 2.5- and 2.8-fold increases, respectively, in the probability of mutation at one nucleotide owing to mutation of a second nucleotide. Secondary structures are drawn to approximate relative helical orientations in 3D space, based on known structures (–9).

Fig. 4.

RINGs report the tertiary structure of the P546 domain and mutation-induced structural changes. Strong and medium internucleotide correlations are shown with green and yellow lines, respectively. (A) RINGs in the P546 domain folded in the presence of Mg²⁺. (B) RINGs in the P546 domain in the absence of Mg²⁺. RINGs in the (C) P6a and (D) J5 hinge mutants. For clarity, A is reproduced from to Fig. 3C.

Fig. 5.

RINGs and clustering analysis of the TPP riboswitch in the presence and absence of TPP ligand. RING analysis in the presence of (A) saturating ligand and (B) absence of ligand. Strong and moderate internucleotide associations are shown with green and yellow lines, respectively. Nucleotides that are less or more structured in the minor, less populated cluster are emphasized with open and closed spheres, respectively. Spectral clustering analysis in the (C) presence of saturating ligand and (D) absence of ligand. There are two clusters in each state. In the presence of saturating ligand, the major cluster (red) corresponds to the fully folded riboswitch. In the absence of ligand, the major cluster (red) reflects an unstructured state with few internucleotide interactions. The minor cluster (blue) in the saturating ligand sample is less structured than the major cluster and is similar to the no-ligand structure (gray). The minor cluster (blue) in the no-ligand sample is more highly structured than the major cluster specifically in the region of the thiamine binding pocket (blue closed circles).

Fig. 6.

Through-space RNA structural relationships revealed by RINGs. (A) Direct, through-helix, and global internucleotide interactions are illustrated on both secondary structures (Upper) and 3D models (–9) (Lower). (B) Three-dimensional models determined for each RNA using RING interdependencies as constraints. The P values report the significance of each model (18); the secondary structure was input during refinement.