An integrative method to decode regulatory logics in gene transcription

Bin Yan, Daogang Guan, Chao Wang, Junwen Wang, Bing He, Jing Qin, Kenneth R. Boheler, Aiping Lu (), Ge Zhang () and Hailong Zhu ()
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Bin Yan: University of Hong Kong
Daogang Guan: Hong Kong Baptist University
Chao Wang: Hong Kong Baptist University
Junwen Wang: Arizona State University
Bing He: Hong Kong Baptist University
Jing Qin: The Chinese University of Hong Kong
Kenneth R. Boheler: University of Hong Kong
Aiping Lu: Hong Kong Baptist University
Ge Zhang: Hong Kong Baptist University
Hailong Zhu: Hong Kong Baptist University

Nature Communications, 2017, vol. 8, issue 1, 1-12

Abstract: Abstract Modeling of transcriptional regulatory networks (TRNs) has been increasingly used to dissect the nature of gene regulation. Inference of regulatory relationships among transcription factors (TFs) and genes, especially among multiple TFs, is still challenging. In this study, we introduced an integrative method, LogicTRN, to decode TF–TF interactions that form TF logics in regulating target genes. By combining cis-regulatory logics and transcriptional kinetics into one single model framework, LogicTRN can naturally integrate dynamic gene expression data and TF-DNA-binding signals in order to identify the TF logics and to reconstruct the underlying TRNs. We evaluated the newly developed methodology using simulation, comparison and application studies, and the results not only show their consistence with existing knowledge, but also demonstrate its ability to accurately reconstruct TRNs in biological complex systems.

Date: 2017
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DOI: 10.1038/s41467-017-01193-0

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