Incorporating Nucleosomes into Thermodynamic Models of Transcription Regulation

Abstract

Transcriptional control is central to many cellular processes, and, consequently, much effort has been devoted to understanding its underlying mechanisms. The organization of nucleosomes along promoter regions is important for this process, since most transcription factors cannot bind nucleosomal sequences and thus compete with nucleosomes for DNA access. This competition is governed by the relative concentrations of nucleosomes and transcription factors and by their respective sequence binding preferences. However, despite its importance, a mechanistic understanding of the quantitative effects that the competition between nucleosomes and factors has on transcription is still missing. Here we use a thermodynamic framework based on fundamental principles of statistical mechanics to explore theoretically the effect that different nucleosome organizations along promoters have on the activation dynamics of promoters in response to varying concentrations of the regulating factors. We show that even simple landscapes of nucleosome organization reproduce experimental results regarding the effect of nucleosomes as general repressors and as generators of obligate binding cooperativity between factors. Our modeling framework also allows us to characterize the effects that various sequence elements of promoters have on the induction threshold and on the shape of the promoter activation curves. Finally, we show that using only sequence preferences for nucleosomes and transcription factors, our model can also predict expression behavior of real promoter sequences, thereby underscoring the importance of the interplay between nucleosomes and factors in determining expression kinetics.[Supplemental material is available online at www.genome.org. The computational model described in this paper is available at

DNase-seq predicts regions of rotational nucleosome stability across diverse human cell types

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Hybrid Incompatibility Arises in a Sequence-Based Bioenergetic Model of Transcription Factor Binding

“…Information-based bioenergetic models of other motifs have been studied in the context of the evolution of gene expression per se. These include cases where multiple independent TF's regulate expression at a single locus (Stewart and Plotkin 2014;Ezer et al 2014), where single TF's have multiple binding sites in a single promoter region (He et al 2012), and where a TF may be inhibited by nucleosomes at the binding site (Raveh-Sadka et al 2009). …”

Compensation for differences in gene copy number among yeast ribosomal proteins is encoded within their promoters

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