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Genome-wide measurement of RNA secondary structure in yeast

Nature volume 467, pages 103–107 (2010)Cite this article

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Abstract

The structures of RNA molecules are often important for their function and regulation1,2,3,4,5,6, yet there are no experimental techniques for genome-scale measurement of RNA structure. Here we describe a novel strategy termed parallel analysis of RNA structure (PARS), which is based on deep sequencing fragments of RNAs that were treated with structure-specific enzymes, thus providing simultaneous in vitro profiling of the secondary structure of thousands of RNA species at single nucleotide resolution. We apply PARS to profile the secondary structure of the messenger RNAs (mRNAs) of the budding yeast Saccharomyces cerevisiae and obtain structural profiles for over 3,000 distinct transcripts. Analysis of these profiles reveals several RNA structural properties of yeast transcripts, including the existence of more secondary structure over coding regions compared with untranslated regions, a three-nucleotide periodicity of secondary structure across coding regions and an anti-correlation between the efficiency with which an mRNA is translated and the structure over its translation start site. PARS is readily applicable to other organisms and to profiling RNA structure in diverse conditions, thus enabling studies of the dynamics of secondary structure at a genomic scale.

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Figure 1: Measuring structural properties of RNA by deep sequencing.
Figure 2: PARS correctly recapitulates results of RNA footprinting and known structures.
Figure 3: Functional units of the transcript are demarcated by distinct properties of RNA structure.
Figure 4: Structure around start codons correlates with low translational efficiency.

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Primary accessions

Gene Expression Omnibus

Data deposits

Sequencing data are deposited in the Gene Expression Omnibus under accession number GSE22393.

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Acknowledgements

We thank D. Herschlag’s group, A. Adler, A. Fire, M. Kay, the Life Technologies SOLiD team, M. Rabani, G. Sherlock and A. Weinberger for assistance and critiques. This work was supported by a National Institutes of Health grant (RO1HG004361). Y.W. is funded by the Agency of Science, Technology and Research of Singapore. H.Y.C. is an Early Career Scientist of the Howard Hughes Medical Institute. E.S. is the incumbent of the Soretta and Henry Shapiro career development chair.

Author information

Author notes

  1. Michael Kertesz

    Present address: Present address: Department of Bioengineering, Stanford University and Howard Hughes Medical Institute, Stanford, California 94305, USA.,

  2. Michael Kertesz and Yue Wan: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, 76100, Israel

    Michael Kertesz, Elad Mazor & Eran Segal

  2. Howard Hughes Medical Institute, Program in Epithelial Biology, Stanford University School of Medicine, Stanford, 94305, California, USA

    Yue Wan & Howard Y. Chang

  3. The Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, 02142, Massachusetts, USA

    John L. Rinn

  4. Life Technologies, Foster City, 94404, California, USA

    Robert C. Nutter

  5. Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, 76100, Israel

    Eran Segal

Authors
  1. Michael Kertesz
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Contributions

M.K., J.L.R., H.Y.C. and E.S. conceived the project; Y.W. and H.Y.C. developed the protocol and designed the experiments; Y.W. performed all experiments; M.K., E.M. and E.S. planned and conducted the data analysis; J.L.R. and R.C.N. helped with sequencing; M.K., Y.W., E.M., H.Y.C. and E.S. wrote the paper with contributions from all authors.

Corresponding authors

Correspondence to Howard Y. Chang or Eran Segal.

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Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Information

This file contains Supplementary Methods and Data, a Supplementary Note, additional references, Supplementary Figures 1-16 with legends and Supplementary Tables 1, 2 and 4 (see separate files for Supplementary Tables 3 and 5). (PDF 1680 kb)

Supplementary Table 3

This table lists all genes whose average nucleotide coverage is above 1.0 (Methods). Columns show, for each gene, the annotated transcript length, the total number of sequences mapping to that transcript, the computed load and the type of transcript: mRNA, rRNA, snoRNA, tRNA, snRNA or ncRNA. (XLS 322 kb)

Supplementary Table 5

This file contains sub-tables which list the Wilcoxon rank sum test p-value for each GO term when genes were sorted based on their average PARS score in each region of the transcript (5’ UTR, CDS, 3’ UTR). For each group, the FDR correction p-value threshold is indicated, and GO categories having a p-value below this threshold are marked in green. (XLS 44 kb)

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Kertesz, M., Wan, Y., Mazor, E. et al. Genome-wide measurement of RNA secondary structure in yeast. Nature 467, 103–107 (2010). https://doi.org/10.1038/nature09322

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