Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/100914
Title: TherMos : estimating protein-DNA binding energies from in vivo binding profiles
Authors: Sun, Wenjie
Hu, Xiaoming
Choo, Siew Hua
Drechsel, Daniela
Guillemot, Franc
Jauch, Ralf
Prabhakar, Shyam
Lim, Michael H. K.
Ng, Calista K. L.
Castro, Diogo S.
Kolatkar, Prasanna R.
Keywords: DRNTU::Science::Biological sciences::Genetics
Issue Date: 2013
Source: Sun, W., Hu, X., Lim, M. H. K., Ng, C. K. L., Choo, S. H., Castro, D. S., et al. (2013). TherMos: Estimating protein-DNA binding energies from in vivo binding profiles. Nucleic Acids Research, 41(11), 5555-5568.
Series/Report no.: Nucleic acids research
Abstract: Accurately characterizing transcription factor (TF)-DNA affinity is a central goal of regulatory genomics. Although thermodynamics provides the most natural language for describing the continuous range of TF-DNA affinity, traditional motif discovery algorithms focus instead on classification paradigms that aim to discriminate ‘bound’ and ‘unbound’ sequences. Moreover, these algorithms do not directly model the distribution of tags in ChIP-seq data. Here, we present a new algorithm named Thermodynamic Modeling of ChIP-seq (TherMos), which directly estimates a position-specific binding energy matrix (PSEM) from ChIP-seq/exo tag profiles. In cross-validation tests on seven genome-wide TF-DNA binding profiles, one of which we generated via ChIP-seq on a complex developing tissue, TherMos predicted quantitative TF-DNA binding with greater accuracy than five well-known algorithms. We experimentally validated TherMos binding energy models for Klf4 and Esrrb, using a novel protocol to measure PSEMs in vitro. Strikingly, our measurements revealed strong non-additivity at multiple positions within the two PSEMs. Among the algorithms tested, only TherMos was able to model the entire binding energy landscape of Klf4 and Esrrb. Our study reveals new insights into the energetics of TF-DNA binding in vivo and provides an accurate first-principles approach to binding energy inference from ChIP-seq and ChIP-exo data.
URI: https://hdl.handle.net/10356/100914
http://hdl.handle.net/10220/18607
DOI: 10.1093/nar/gkt250
Rights: © 2013 The Author(s) Oxford University Press. This paper was published in Nucleic Acids Research and is made available as an electronic reprint (preprint) with permission of The Author(s). The paper can be found at the following official DOI: [http://dx.doi.org/10.1093/nar/gkt250 ].  One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SBS Journal Articles

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