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

In SHAPE-MaP, reverse transcriptase–induced mutations at SHAPE-modified RNA nucleotides are detected by high-throughput sequencing. ShapeMapper converts sequence data to mutational profiles (MaPs), which can be used by SuperFold for RNA structure modeling. Selective 2′-hydroxyl acylation analyzed by...

Full description

Saved in:
Bibliographic Details
Published inNature protocols Vol. 10; no. 11; pp. 1643 - 1669
Main Authors Smola, Matthew J, Rice, Greggory M, Busan, Steven, Siegfried, Nathan A, Weeks, Kevin M
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 01.11.2015
Nature Publishing Group
Subjects
Online AccessGet full text
ISSN1754-2189
1750-2799
1750-2799
DOI10.1038/nprot.2015.103

Cover

More Information
Summary:In SHAPE-MaP, reverse transcriptase–induced mutations at SHAPE-modified RNA nucleotides are detected by high-throughput sequencing. ShapeMapper converts sequence data to mutational profiles (MaPs), which can be used by SuperFold for RNA structure modeling. 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.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
contributed equally
ISSN:1754-2189
1750-2799
1750-2799
DOI:10.1038/nprot.2015.103