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

Nature Protocols volume 10, pages 1643–1669 (2015)Cite this article

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Abstract

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.

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Figure 1: SHAPE chemistry and useful SHAPE reagents.
Figure 2: Overview of SHAPE-MaP and ShapeMapper.
Figure 3: Overview of the SuperFold pipeline.
Figure 4: Overview of workflows useful for converting RNAs modified with SHAPE reagents into libraries compatible with massively parallel sequencing.
Figure 5: Representative library size distributions as a function of workflow.
Figure 6: Random primer design.
Figure 7: SHAPE-MaP reactivity profiles for the E. coli 16S rRNA.
Figure 8: Read-depth profiles.
Figure 9: Troubleshooting, showing example data from the E. coli 16S rRNA.
Figure 10: Nucleotide-resolution interrogation of RNA structure and ligand-induced conformational changes for the TPP riboswitch aptamer domain.
Figure 11: SuperFold analysis.
Figure 12: Secondary structure models for well-determined regions.
Figure 13: Representative SHAPE-MaP reactivity profile obtained using the randomer workflow.

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Acknowledgements

This work was supported by grants from the US National Institutes of Health (NIH) (AI068462) and the National Science Foundation (MCB-1121024) to K.M.W. M.J.S. is a Graduate Research Fellow of the National Science Foundation (DGE-1144081). G.M.R. and M.J.S. were supported in part by an NIH training grant in molecular and cellular biophysics (T32 GM08570). N.A.S. was a Lineberger Postdoctoral Fellow in the Basic Sciences and a Ruth L. Kirschstein NRSA Fellow (F32 GM010169). We are indebted to many members of the Weeks laboratory who provided continuous and thoughtful feedback on the strategies and algorithms described here.

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  1. Matthew J Smola, Greggory M Rice and Steven Busan: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Chemistry, University of North Carolina, Chapel Hill, North Carolina, USA

    Matthew J Smola, Greggory M Rice, Steven Busan, Nathan A Siegfried & Kevin M Weeks

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Contributions

N.A.S., S.B., G.M.R. and K.M.W. conceived and developed the original SHAPE-MaP strategy. M.J.S., S.B. and G.M.R. modified and updated the technology to its current state. All authors wrote and edited the manuscript.

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Correspondence to Kevin M Weeks.

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N.S., S.B. and K.M.W. are listed on a pending PCT patent application that covers concepts in this manuscript.

Integrated supplementary information

Supplementary Figure 1 Ambiguously aligned deletion detection algorithm.

Example shows the ambiguous deletion detection algorithm applied to a single short read. (a) Reference sequence and aligned read. (b) The deletion is “collapsed” and the surrounding sequence stored. (c) The deletion is repositioned upstream and downstream of its Bowtie2-reported location, up to as many nucleotides as it is long. (d) The repositioned deletions are “collapsed” and the surrounding sequences compared to the original surrounding sequence. In any reposition, the absence of mismatches with the original surrounding sequence indicates an alternate valid deletion placement.

Supplementary Figure 2 Ambiguously aligned deletion removal.

(a) SHAPE reactivities from a portion of the bacterial 16S rRNA, identified as stops to primer extension by reverse transcription, read out by capillary electrophoresis using fluorescently-label primers. (b) SHAPE-MaP reactivities from the same region of 16S rRNA, obtained using the reverse transcription read-through SHAPE-MaP strategy, including the ambiguous deletion removal algorithm. (c) Reactivities from the same experiment, but analysed omitting ambiguous deletion removal. The orange arrow highlights a nucleotide reactivity inconsistent with the capillary electrophoresis experiment.

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Supplementary Figures 1 and 2, Supplementary Methods 1 and 2 (PDF 587 kb)

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Smola, M., Rice, G., Busan, S. et al. Selective 2′-hydroxyl acylation analyzed by primer extension and mutational profiling (SHAPE-MaP) for direct, versatile and accurate RNA structure analysis. Nat Protoc 10, 1643–1669 (2015). https://doi.org/10.1038/nprot.2015.103

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