A Systematic Ensemble Approach to Thermodynamic Modeling of Gene Expression from Sequence Data. Author Md Samee, Bomyi Lim, Núria Samper, Hang Lu, Christine Rushlow, Gerardo Jiménez, Stanislav Shvartsman, Saurabh Sinha Publication Year 2015 Type Journal Article Abstract To understand the relationship between an enhancer DNA sequence and quantitative gene expression, thermodynamics-driven mathematical models of transcription are often employed. These "sequence-to-expression" models can describe an incomplete or even incorrect set of regulatory relationships if the parameter space is not searched systematically. Here, we focus on an enhancer of the Drosophila gene ind and demonstrate how a systematic search of parameter space can reveal a more comprehensive picture of a gene's regulatory mechanisms, resolve outstanding ambiguities, and suggest testable hypotheses. We describe an approach that generates an ensemble of ind models; all of these models are technically acceptable solutions to the sequence-to-expression problem in light of wild-type data, and some represent mechanistically distinct hypotheses about the regulation of ind. This ensemble can be restricted to biologically plausible models using requirements gleaned from in vivo perturbation experiments. Biologically plausible models make unique predictions about how specific ind enhancer sequences affect ind expression; we validate these predictions in vivo through site mutagenesis in transgenic Drosophila embryos. Journal Cell Syst Volume 1 Issue 6 Pages 396-407 Date Published 2015 Dec 23 ISSN Number 2405-4712 DOI 10.1016/j.cels.2015.12.002 Alternate Journal Cell Syst PMCID PMC5094195 PMID 27136354 PubMedPubMed CentralGoogle ScholarBibTeXEndNote X3 XML