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Quantitative analysis of RNA-protein interactions on a massively parallel array reveals biophysical and evolutionary landscapes

Nature Biotechnology volume 32, pages 562568 (2014) | Download Citation

Abstract

RNA-protein interactions drive fundamental biological processes and are targets for molecular engineering, yet quantitative and comprehensive understanding of the sequence determinants of affinity remains limited. Here we repurpose a high-throughput sequencing instrument to quantitatively measure binding and dissociation of a fluorescently labeled protein to >107 RNA targets generated on a flow cell surface by in situ transcription and intermolecular tethering of RNA to DNA. Studying the MS2 coat protein, we decompose the binding energy contributions from primary and secondary RNA structure, and observe that differences in affinity are often driven by sequence-specific changes in both association and dissociation rates. By analyzing the biophysical constraints and modeling mutational paths describing the molecular evolution of MS2 from low- to high-affinity hairpins, we quantify widespread molecular epistasis and a long-hypothesized, structure-dependent preference for G:U base pairs over C:A intermediates in evolutionary trajectories. Our results suggest that quantitative analysis of RNA on a massively parallel array (RNA-MaP) provides generalizable insight into the biophysical basis and evolutionary consequences of sequence-function relationships.

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Acknowledgements

This work was supported by National Institutes of Health (NIH) NIH R01-HG004361 (to H.Y.C.); H.Y.C. is an Early Career Scientist of the Howard Hughes Medical Institute. J.D.B. and L.M.C. acknowledge support from the National Science Foundation Graduate Research Fellowships. J.D.B. also acknowledges support from NIH training grant T32HG000044. L.M.C. acknowledges support from NIH training grant T32GM067586. J.D.B. and L.M.C. each acknowledge support of a National Science Foundation graduate research fellowship. M.P.S. and C.L.A. acknowledge the NIH and the National Human Genome Research Institute (NHGRI) for funding through 5U54HG00455805. We thank D. Herschlag for feedback and advice throughout the methods development, and G. Sherlock and D. Herschlag for critical readings of earlier versions of this manuscript. We thank R. Landick for discussions regarding the design of our synthetic DNA library and K. Bajaj for discussions regarding quantification of cluster fluorescence. We also thank O.D. Phanstiel, M. Sikora and O. Cornejo for discussions on the modeling and evolutionary analyses.

Author information

Author notes

    • Jason D Buenrostro
    •  & Carlos L Araya

    These authors contributed equally to this work.

Affiliations

  1. Department of Genetics, Stanford University School of Medicine, Stanford, California, USA.

    • Jason D Buenrostro
    • , Carlos L Araya
    • , Lauren M Chircus
    • , Curtis J Layton
    • , Michael P Snyder
    •  & William J Greenleaf
  2. Program in Epithelial Biology and the Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, California, USA.

    • Jason D Buenrostro
    •  & Howard Y Chang
  3. Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, California, USA.

    • Lauren M Chircus

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Contributions

W.J.G., J.D.B. and C.J.L. conceived of the method. J.D.B. developed the RNA display protocol. J.D.B. and L.M.C. designed and performed on-chip assays. L.M.C. designed and performed the protein purification and in vitro binding assays. J.D.B. wrote the image analysis algorithm with input from W.J.G. and C.J.L. C.L.A. developed and implemented the structural (epistatic), functional (modeling, kinetic) and evolutionary analyses. All authors interpreted the data and wrote the manuscript. W.J.G. supervised all aspects of this work.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to William J Greenleaf.

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary Figures 1–13 and Supplementary Discussion

Excel files

  1. 1.

    Supplementary Table 1

    Oligonucleotide sequences used in this study.

  2. 2.

    Supplementary Table 2

    Measured binding energies and quality metrics for 129,248 MS2 RNA hairpin sequences. Note: Position indexes in -15,+3 indexing whereby. "NA:NA" indicates the consensus sequence (with zero mutations).

  3. 3.

    Supplementary Table 3

    Measured dissociation and inferred association rates for 3,029 MS2 RNA hairpin sequences. Note: Position indexes in -15,+3 indexing whereby. "NA:NA" indicates the consensus sequence (with zero mutations).

  4. 4.

    Supplementary Table 4

    Summary of evolutionary path probabilities and constraint in 1,997 tesseracts. Note: Position indexes in -15,+3 indexing whereby. "NA:NA" indicates the consensus sequence (with zero mutations).

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  1. 1.

    Supplementary Data

    Image analysis software.

Videos

  1. 1.

    Equilibrium binding and dissociation rate measurements on a sequenced flow cell

    A small region of the flow cell is shown as fluorescently tagged MS2 coat protein is bound at increasing concentrations to the RNA clusters and is then removed from solution to determine dissociation constants. In the first frame, the fluorescence signal from a complementary oligonucleotide annealed to all RNAs is shown. A single cluster is circled (blue), and quantified fluorescence is shown in the inset. Subsequent frames show the quantified fluorescence signal at increasing concentrations of labeled MS2 coat protein. At the end of the binding experiment, the fit for that individual cluster is shown in the inset. The following frames show dissociation of labeled MS2, measured by replacing labeled with unlabeled MS2 in solution, and observing the decay of fluorescence over time. The inset dissociation curve depicts data from all clusters that share the sequence with the circled cluster (-5C variant).

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DOI

https://doi.org/10.1038/nbt.2880

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