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Genome-wide probing of RNA structure reveals active unfolding of mRNA structures in vivo

Nature volume 505, pages 701–705 (2014)Cite this article

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Abstract

RNA has a dual role as an informational molecule and a direct effector of biological tasks. The latter function is enabled by RNA’s ability to adopt complex secondary and tertiary folds and thus has motivated extensive computational1,2 and experimental3,4,5,6,7,8 efforts for determining RNA structures. Existing approaches for evaluating RNA structure have been largely limited to in vitro systems, yet the thermodynamic forces which drive RNA folding in vitro may not be sufficient to predict stable RNA structures in vivo5. Indeed, the presence of RNA-binding proteins and ATP-dependent helicases can influence which structures are present inside cells. Here we present an approach for globally monitoring RNA structure in native conditions in vivo with single-nucleotide precision. This method is based on in vivo modification with dimethyl sulphate (DMS), which reacts with unpaired adenine and cytosine residues9, followed by deep sequencing to monitor modifications. Our data from yeast and mammalian cells are in excellent agreement with known messenger RNA structures and with the high-resolution crystal structure of the Saccharomyces cerevisiae ribosome10. Comparison between in vivo and in vitro data reveals that in rapidly dividing cells there are vastly fewer structured mRNA regions in vivo than in vitro. Even thermostable RNA structures are often denatured in cells, highlighting the importance of cellular processes in regulating RNA structure. Indeed, analysis of mRNA structure under ATP-depleted conditions in yeast shows that energy-dependent processes strongly contribute to the predominantly unfolded state of mRNAs inside cells. Our studies broadly enable the functional analysis of physiological RNA structures and reveal that, in contrast to the Anfinsen view of protein folding whereby the structure formed is the most thermodynamically favourable, thermodynamics have an incomplete role in determining mRNA structure in vivo.

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Figure 1: Using dimethyl sulphate for RNA structure probing by deep sequencing.
Figure 2: Comparison of DMS-seq data to known RNA structures.
Figure 3: Identification of structured mRNA regions reveals far less structure in vivo than in vitro.
Figure 4: Factors affecting the difference between mRNA structure in vivo and in vitro.

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Gene Expression Omnibus

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All data are deposited in Gene Expression Omnibus (accession number GSE45803).

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Acknowledgements

We thank R. Andino, M. Bassik, J. Doudna, J. Dunn, T. Faust, N. Stern-Ginossar, C. Gross, C. Guthrie, N. Ingolia, C. Jan, M. Kampmann, D. Koller, G.W. Li, S. Mortimer, E. Oh, C. Pop and members of the Weissman laboratory for discussions; J. Stewart-Ornstein and O. Brandman for plasmids; C. Chu, N. Ingolia and J. Lund for sequencing help. This research was supported by the Center for RNA Systems Biology (J.S.W.), the Howard Hughes Medical Institute (J.S.W.), and the National Science Foundation (M.Z.).

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Authors and Affiliations

  1. Department of Cellular and Molecular Pharmacology, California Institute of Quantitative Biology, Center for RNA Systems Biology, Howard Hughes Medical Institute, University of California, San Francisco, 94158, California, USA

    Silvi Rouskin, Meghan Zubradt & Jonathan S. Weissman

  2. Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, 02139, Massachusetts, USA

    Stefan Washietl & Manolis Kellis

  3. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, 02139, Massachusetts, USA

    Stefan Washietl & Manolis Kellis

  4. The Broad Institute, Cambridge, 02139, Massachusetts, USA

    Stefan Washietl & Manolis Kellis

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  1. Silvi Rouskin
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Contributions

S.R., M.Z. and J.S.W. designed the experiments. S.R. and M.Z. performed the experiments, and S.R. analysed the data. S.W. and M.K. completed the phylogenetic analysis. S.R., M.Z. and J.S.W. drafted and revised the manuscript.

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Correspondence to Jonathan S. Weissman.

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Extended data figures and tables

Extended Data Figure 1 Ribosomal RNA analysis.

a, Histogram of raw counts distribution for denatured and structured 18S rRNA. Log2 (raw counts) for A bases plotted for in vivo and denatured samples. b, ROC curve on the DMS signal for A and C bases from the 25S rRNA in denatured, in vitro, intact ribosomes, and in vivo samples. True positives are defined as bases that are both unpaired and solvent-accessible, and true negatives are defined as bases that are paired. c, DMS signal on all of the 18S rRNA A bases plotted from least to most reactive in the denatured or in vivo samples. The A bases that are false negatives relative to the crystal structure are coloured as black dots on both the denatured and in vivo samples.

Extended Data Figure 2 mRNA structure analysis with different window sizes.

a, b, Scatter plots of Gini index versus r values in replicate samples and for in vivo or in vitro samples relative to denatured sample for mRNA regions with an average of at least 15 counts per position, spanning the sequence of 25 A/C nucleotides (5,000 randomly selected regions are shown) (a) or 100A/C nucleotides (b). Shown are regions spanning validated secondary structures (red dots) and regions from the 18S rRNA (green dots).

Extended Data Figure 3 Agreement of DMS-seq with validated structures in mammalian K562 cells.

Raw DMS counts were normalized to the most reactive nucleotide in the given region. A and C bases were normalized separately. a, The DMS signal is colour coded proportional to intensity and plotted onto the secondary structure model of MSRB1 selenocysteine insertion element, nucleotide 1 corresponds to nucleotide 966 of the transcript. b, TPRC iron recognition element, nucleotide 1 corresponds to nucleotide 3901 of the transcript. c, XBP1 conserved non canonical intron recognized by Ire1, nucleotide 1 corresponds to nucleotide 520 of the transcript.

Extended Data Figure 4 Global mRNA analysis of human foreskin fibroblast cells.

Scatter plots of Gini index versus r values for in vivo or in vitro samples relative to denatured sample for mRNA regions spanning the sequence of 50 A/C nucleotides.

Extended Data Figure 5 Functional verification of novel 5′ UTR structures in vivo.

a, Putative 5′ UTR stems were manipulated in the context of a Venus reporter in vivo. b, PMA1 5′ UTR structure was mutated and compensated twice with Venus reporter, differing in number and character of bases mutated. Mutation location shown in red on schematic. Reported P values relative to wild-type Venus levels, calculated by two-sided t-test (*P < 0.01, **P < 0.001, ***P < 0.0001). For all graphs, Venus signal normalized to cell size before calculating fold change and data presented is from two biological and two technical replicates. Error bars represent s.e.m. c, Secondary structure of functional PMA1 5′ UTR stem, with compensatory mutations (arrows) found in Saccharomyces paradoxus, Saccharomyces mikatae, Saccharomyces kudriavzevii and Saccharomyces bayanus. Raw DMS signal shown below (position 1 = chromosome VII:482745). d, SFT2 5′ UTR structure was mutated and compensated three times in Venus reporter system, differing in number, character and location of bases mutated. Mutation location shown in red on schematic. Stem stability as predicated by mfold. Reported P values relative to wild-type Venus levels, also by two-sided t-test (*P < 0.01, **P < 0.001, ***P < 0.0001). Error bars represent standard deviation. e, Secondary structure of functional SFT2 5′ UTR stem. Position 1 = chromosome II:24023.

Extended Data Figure 6 Functional verification of novel PRC1 3′ UTR structure in vivo.

a, Putative 3′ UTR stems were manipulated in the context of a Venus reporter in vivo, followed by Venus quantification with flow cytometry. b, PRC1 3′ UTR structure was mutated and compensated in Venus reporter system. For all data, reported P values relative to wild-type Venus levels, calculated by two-sided t-test (*P < 0.01, **P < 0.001, ***P < 0.0001). Venus signal was normalized to cell size with fold change reported relative to Venus levels seen with the wild-type stem. All results shown are derived from four measurements: two biological and two technical replicates. Error bars show standard deviation. c, Secondary structure of functional PRC1 3′ UTR stem, shown with raw DMS signal for in vivo and denatured samples. Position 1 = chromosome XIII:863554. d, Weakly structured 3′ UTRs in vivo were tested for function as in b, but reveal little effect when mutated and no evidence for compensation.

Extended Data Figure 7 Global analysis of mRNA structure.

a, In vitro DMS-seq on RNA refolded in different Mg+2 concentrations. b, Metagene plot of the average DMS signal (normalized to denatured control) over 5′ UTR, coding, and 3′ UTR regions. c, Scatter plot of Gini index (calculated over the first 100 A/C bases) of in vivo messages (relative to denatured) versus translation efficiency.

Extended Data Figure 8 In vivo structures forming in ATP depleted conditions.

a, b, Raw DMS counts were normalized to the most reactive nucleotide in a given region. a, The DMS signal is colour coded proportional to intensity and plotted onto the mfold predicted secondary structure model of CBF5, nucleotide 1 corresponds to chromosome XII position 506479. b, TCP1, nucleotide 1 corresponds to chromosome IV position 887991.

Extended Data Figure 9 Analysis of mRNA structure at 10 °C.

a, Histogram of Gini index difference (calculated over 100A or Cs) between 10 °C and wild-type (30 °C) samples. b, Scatter plot of the Gini index differences in ATP depleted or 10 °C yeast relative to wild-type yeast calculated over 50 As or Cs.

Extended Data Table 1 Sequences of functional structure mutations
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Rouskin, S., Zubradt, M., Washietl, S. et al. Genome-wide probing of RNA structure reveals active unfolding of mRNA structures in vivo. Nature 505, 701–705 (2014). https://doi.org/10.1038/nature12894

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