Genome-wide profiling of in vivo RNA structure at single-nucleotide resolution using structure-seq

Abstract

Structure-seq is a high-throughput and quantitative method that provides genome-wide information on RNA structure at single-nucleotide resolution. Structure-seq can be performed both in vivo and in vitro to study RNA structure-function relationships, RNA regulation of gene expression and RNA processing. Structure-seq can be carried out by an experienced molecular biologist with a basic understanding of bioinformatics. Structure-seq begins with chemical RNA structure probing under single-hit kinetics conditions. Certain chemical modifications, e.g., methylation of the Watson-Crick face of unpaired adenine and cytosine residues by dimethyl sulfate, result in a stop in reverse transcription. Modified RNA is then subjected to reverse transcription using random hexamer primers, which minimizes 3′ end bias; reverse transcription proceeds until it is blocked by a chemically modified residue. Resultant cDNAs are amplified by adapter-based PCR and subjected to high-throughput sequencing, subsequently allowing retrieval of the structural information on a genome-wide scale. In contrast to classical methods that provide information only on individual transcripts, a single structure-seq experiment provides information on tens of thousands of RNA structures in 1 month. Although the procedure described here is for Arabidopsis thaliana seedlings in vivo, structure-seq is widely applicable, thereby opening new avenues to explore RNA structure–function relationships in living organisms.

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Figure 1: Structure-seq pipeline.
Figure 2: Key sequences and steps involved in constructing and sequencing structure-seq libraries.
Figure 3: Derivation of DMS reactivities from RTSC files.
Figure 4: Example of an in vivo DMS treatment time course.
Figure 5: Typical results of a DTT quench control (control 1).
Figure 6: Typical results of an RNA dope-in control (control 2).

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Acknowledgements

This protocol was developed under support from the Human Frontier Science Program (HFSP) grant RGP0002/2009-C, the Penn State Eberly College of Science and a Penn State Huck Huck Innovative & Transformational Seed (HITS) grant to P.C.B. and S.M.A., with additional support from NSF-IOS-1339282. We thank Y. Zhang for statistical advice; F. Pugh, Y. Li, A. Chan and K. Yen for help with Illumina sequencing; M. Axtell for helpful discussions; and P. Raghavan for access to the CyberSTAR server funded by the National Science Foundation through grant OCI-0821527. We thank L. Ritchey and Z. Su for helpful comments on the manuscript.

Author information

All authors developed the protocol, designed and interpreted the experiments and wrote the paper; Y.D. and C.K.K. performed the experiments; and Y.D., C.K.K. and Y.T. analyzed the data.

Correspondence to Yiliang Ding or Philip C Bevilacqua or Sarah M Assmann.

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The authors declare no competing financial interests.

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Ding, Y., Kwok, C., Tang, Y. et al. Genome-wide profiling of in vivo RNA structure at single-nucleotide resolution using structure-seq. Nat Protoc 10, 1050–1066 (2015). https://doi.org/10.1038/nprot.2015.064

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