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Predicting DNA hybridization kinetics from sequence

Nature Chemistry volume 10, pages 91–98 (2018)Cite this article

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Abstract

Hybridization is a key molecular process in biology and biotechnology, but so far there is no predictive model for accurately determining hybridization rate constants based on sequence information. Here, we report a weighted neighbour voting (WNV) prediction algorithm, in which the hybridization rate constant of an unknown sequence is predicted based on similarity reactions with known rate constants. To construct this algorithm we first performed 210 fluorescence kinetics experiments to observe the hybridization kinetics of 100 different DNA target and probe pairs (36 nt sub-sequences of the CYCS and VEGF genes) at temperatures ranging from 28 to 55 °C. Automated feature selection and weighting optimization resulted in a final six-feature WNV model, which can predict hybridization rate constants of new sequences to within a factor of 3 with ∼91% accuracy, based on leave-one-out cross-validation. Accurate prediction of hybridization kinetics allows the design of efficient probe sequences for genomics research.

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Figure 1: Experimental characterization of hybridization kinetics.
Figure 2: Hybridization model and rate constant parameterization.
Figure 3: Summary of observed hybridization kinetics.
Figure 4: Rate constant prediction using the WNV model.
Figure 5: Prediction accuracy of the WNV model using different numbers of features.
Figure 6: Comparison of probes predicted to possess median versus fast hybridization kinetics for enrichment from human genomic DNA.

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Acknowledgements

The authors thank S.X. Chen for assistance with NGS sequence alignment. This work was funded by National Institutes of Health grant R01HG008752 to D.Y.Z.

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Author notes

  1. Jinny X. Zhang and John Z. Fang: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Bioengineering, Rice University, Houston, 77030, Texas, USA

    Jinny X. Zhang, John Z. Fang, Wei Duan, Lucia R. Wu, Angela W. Zhang & David Yu Zhang

  2. Systems, Synthetic, and Physical Biology, Rice University, Houston, 77030, Texas, USA

    Jinny X. Zhang & David Yu Zhang

  3. Microsoft Research, Cambridge, CB1 2FB, UK

    Neil Dalchau, Boyan Yordanov, Rasmus Petersen & Andrew Phillips

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  1. Jinny X. Zhang
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Contributions

J.X.Z., L.R.W. and D.Y.Z. conceived the project. J.X.Z. and A.W.Z. performed the experiments. N.D. and A.P. performed hybridization reaction model fitting and selection. J.X.Z., J.Z.F., B.Y. and R.P. performed feature construction. W.D. and D.Y.Z. performed WNV model construction and optimization. N.D., B.Y. and R.P. performed MLR model construction and optimization. D.Y.Z. wrote the manuscript with input from all authors.

Corresponding author

Correspondence to David Yu Zhang.

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Competing interests

There is a patent pending on the X-probes used in this work, and a patent pending on the WNV model of hybridization rate constant prediction.

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Zhang, J., Fang, J., Duan, W. et al. Predicting DNA hybridization kinetics from sequence. Nature Chem 10, 91–98 (2018). https://doi.org/10.1038/nchem.2877

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