Thermodynamics-based modeling reveals regulatory effects of indirect transcription factor-DNA binding in Drosophila

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Sequence-to-expression relationship is one of the major research topics in the field of regulatory genomics. Prediction of epigenomic states such as DNA accessibility or transcription factor(TF)-DNA binding has been studied extensively, but predicting a gene's expression in different cell types based on its regulatory enhancer sequences remains largely unsolved. Here, we present a thermodynamics-based sequence-to-expression model that combines DNA accessibility, TF concentrations and enhancer sequence information to classify enhancers into their spatio-temporal activity classes in Drosophila mesoderm.