Steven Busan

RNA motif discovery by SHAPE and mutational profiling (SHAPE-MaP)

Many biological processes are RNA-mediated, but higher-order structures for most RNAs are unknown, which makes it difficult to understand how RNA structure governs function. Here we describe selective 2′-hydroxyl acylation analyzed by primer extension and mutational profiling (SHAPE-MaP) that makes possible de novo and large-scale identification of RNA functional motifs. Sites of 2′-hydroxyl acylation by SHAPE are encoded as noncomplementary nucleotides during cDNA synthesis, as measured by massively parallel sequencing. SHAPE-MaP–guided modeling identified greater than 90% of accepted base pairs in complex RNAs of known structure, and we used it to define a new model for the HIV-1 RNA genome. The HIV-1 model contains all known structured motifs and previously unknown elements, including experimentally validated pseudoknots. SHAPE-MaP yields accurate and high-resolution secondary-structure models, enables analysis of low-abundance RNAs, disentangles sequence polymorphisms in single experiments and will ultimately democratize RNA-structure analysis.

Selective 2′-hydroxyl acylation analyzed by primer extension and mutational profiling (SHAPE-MaP) for direct, versatile and accurate RNA structure analysis

Selective 2′-hydroxyl acylation analyzed by primer extension (SHAPE) chemistries exploit small electrophilic reagents that react with 2′-hydroxyl groups to interrogate RNA structure at single-nucleotide resolution. Mutational profiling (MaP) identifies modified residues by using reverse transcriptase to misread a SHAPE-modified nucleotide and then counting the resulting mutations by massively parallel sequencing. The SHAPE-MaP approach measures the structure of large and transcriptome-wide systems as accurately as can be done for simple model RNAs. This protocol describes the experimental steps, implemented over 3 d, that are required to perform SHAPE probing and to construct multiplexed SHAPE-MaP libraries suitable for deep sequencing. Automated processing of MaP sequencing data is accomplished using two software packages. ShapeMapper converts raw sequencing files into mutational profiles, creates SHAPE reactivity plots and provides useful troubleshooting information. SuperFold uses these data to model RNA secondary structures, identify regions with well-defined structures and visualize probable and alternative helices, often in under 1 d. SHAPE-MaP can be used to make nucleotide-resolution biophysical measurements of individual RNA motifs, rare components of complex RNA ensembles and entire transcriptomes.

Single-molecule correlated chemical probing of RNA

Significance RNA molecules function as the central conduit of information transfer in biology. To do this, they encode information both in their sequences and in their higher-order structures. Understanding the higher-order structure of RNA remains challenging. In this work we devise a simple, experimentally concise, and accurate approach for examining higher-order RNA structure by converting widely used massively parallel sequencing into an easily implemented single-molecule experiment for detecting through-space interactions and multiple conformations. We then use this experiment to analyze higher-order RNA structure, detect biologically important hidden states, and refine accurate three-dimensional structure models. 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.

Accurate detection of chemical modifications in RNA by mutational profiling (MaP) with ShapeMapper 2

Mutational profiling (MaP) enables detection of sites of chemical modification in RNA as sequence changes during reverse transcription (RT), subsequently read out by massively parallel sequencing. We introduce ShapeMapper 2, which integrates careful handling of all classes of adduct-induced sequence changes, sequence variant correction, basecall quality filters, and quality-control warnings to now identify RNA adduct sites as accurately as achieved by careful manual analysis of electrophoresis data, the prior highest-accuracy standard. MaP and ShapeMapper 2 provide a robust, experimentally concise, and accurate approach for reading out nucleic acid chemical probing experiments.

SHAPE analysis of small RNAs and riboswitches.

We describe structural analysis of small RNAs by SHAPE chemical probing. RNAs are treated with 1-methyl-7-nitroisatoic anhydride, a reagent that detects local nucleotide flexibility; and N-methylisatoic anhydride and 1-methyl-6-nitroisatoic anhydride, reagents which together detect higher-order and noncanonical interactions. Chemical adducts are quantified as stops during reverse transcriptase-mediated primer extension. Probing information can be used to infer conformational changes and ligand binding and to develop highly accurate models of RNA secondary structures.

Visualization of RNA structure models within the Integrative Genomics Viewer

Analyses of the interrelationships between RNA structure and function are increasingly important components of genomic studies. The SHAPE-MaP strategy enables accurate RNA structure probing and realistic structure modeling of kilobase-length noncoding RNAs and mRNAs. Existing tools for visualizing RNA structure models are not suitable for efficient analysis of long, structurally heterogeneous RNAs. In addition, structure models are often advantageously interpreted in the context of other experimental data and gene annotation information, for which few tools currently exist. We have developed a module within the widely used and well supported open-source Integrative Genomics Viewer (IGV) that allows visualization of SHAPE and other chemical probing data, including raw reactivities, data-driven structural entropies, and data-constrained base-pair secondary structure models, in context with linear genomic data tracks. We illustrate the usefulness of visualizing RNA structure in the IGV by exploring structure models for a large viral RNA genome, comparing bacterial mRNA structure in cells with its structure under cell- and protein-free conditions, and comparing a noncoding RNA structure modeled using SHAPE data with a base-pairing model inferred through sequence covariation analysis.

The roles of five conserved lentiviral RNA structures in HIV-1 replication

The HIV-1 RNA genome contains complex structures with many structural elements playing regulatory roles during viral replication. A recent study has identified multiple RNA structures with unknown functions that are conserved among HIV-1 and two simian immunodeficiency viruses. To explore the roles of these conserved RNA structures, we introduced synonymous mutations into the HIV-1 genome to disrupt each structure. These mutants exhibited similar particle production, viral infectivity, and replication kinetics relative to the parent NL4-3 virus. However, when replicating in direct competition with the wild-type NL4-3 virus, mutations of RNA structures at inter-protein domain junctions can cause fitness defects. These findings reveal the ability of HIV-1 to tolerate changes in its sequences, even in apparently highly conserved structures, which permits high genetic diversity in HIV-1 population. Our results also suggest that some conserved RNA structures may function to fine-tune viral replication.