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Thermodynamics-based models of transcriptional regulation with gene sequence

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Abstract

Quantitative models of gene regulatory activity have the potential to improve our mechanistic understanding of transcriptional regulation. However, the few models available today have been based on simplistic assumptions about the sequences being modeled or heuristic approximations of the underlying regulatory mechanisms. In this work, we have developed a thermodynamics-based model to predict gene expression driven by any DNA sequence. The proposed model relies on a continuous time, differential equation description of transcriptional dynamics. The sequence features of the promoter are exploited to derive the binding affinity which is derived based on statistical molecular thermodynamics. Experimental results show that the proposed model can effectively identify the activity levels of transcription factors and the regulatory parameters. Comparing with the previous models, the proposed model can reveal more biological sense.

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Acknowledgments

The authors would like to thank the editor and the anonymous reviewers for their constructive comments that helped to improve the paper. This work was supported in part by China Postdoctoral Science Foundations (Grants No. 2014M562223 and No. 2015T80925), Shenzhen Basic Research Project (Grant No. JCYJ20140610151856729) and National Natural Science Foundations of China (Grants No. 61503368 and No. 61502473) and Natural Science Foundation of Guangdong Province (Grant No. 2014A030310154).

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Authors and Affiliations

  1. Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

    Shuqiang Wang, Yanyan Shen & Jinxing Hu

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  1. Shuqiang Wang
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  2. Yanyan Shen
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  3. Jinxing Hu
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Correspondence to Shuqiang Wang.

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Wang, S., Shen, Y. & Hu, J. Thermodynamics-based models of transcriptional regulation with gene sequence. Bioprocess Biosyst Eng 38, 2469–2476 (2015). https://doi.org/10.1007/s00449-015-1484-6

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  • DOI: https://doi.org/10.1007/s00449-015-1484-6

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