General transfer matrix formalism to calculate DNA–protein–drug binding in gene regulation: application to O R operator of phage λ

Teif, Vladimir B.

doi:10.1093/nar/gkm268

Cited by 44 publications

(74 citation statements)

References 73 publications

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“…The program takes as input the DNA sequence, concentrations, and sequence-specific binding constants for transcription factors, as well as cell type-specific nucleosome coverage, and computes binding maps (binding probability distributions) for a given set of proteins to a defined DNA region as introduced elsewhere (Teif 2007(Teif , 2010. Average CTCF binding profiles were calculated by summing up binding maps for all individual genomic regions (FMR, LMR, UMR regions in the case of Figure 3C, and regions around CTCF binding sites in the case of Figure 6, B and D).…”

Section: Calculation Of Experimental Aggregate Profilesmentioning

confidence: 99%

Nucleosome repositioning links DNA (de)methylation and differential CTCF binding during stem cell development

et al. 2014

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During differentiation of embryonic stem cells, chromatin reorganizes to establish cell type-specific expression programs. Here, we have dissected the linkages between DNA methylation (5mC), hydroxymethylation (5hmC), nucleosome repositioning, and binding of the transcription factor CTCF during this process. By integrating MNase-seq and ChIP-seq experiments in mouse embryonic stem cells (ESC) and their differentiated counterparts with biophysical modeling, we found that the interplay between these factors depends on their genomic context. The mostly unmethylated CpG islands have reduced nucleosome occupancy and are enriched in cell type-independent binding sites for CTCF. The few remaining methylated CpG dinucleotides are preferentially associated with nucleosomes. In contrast, outside of CpG islands most CpGs are methylated, and the average methylation density oscillates so that it is highest in the linker region between nucleosomes. Outside CpG islands, binding of TET1, an enzyme that converts 5mC to 5hmC, is associated with labile, MNase-sensitive nucleosomes. Such nucleosomes are poised for eviction in ESCs and become stably bound in differentiated cells where the TET1 and 5hmC levels go down. This process regulates a class of CTCF binding sites outside CpG islands that are occupied by CTCF in ESCs but lose the protein during differentiation. We rationalize this cell type-dependent targeting of CTCF with a quantitative biophysical model of competitive binding with the histone octamer, depending on the TET1, 5hmC, and 5mC state.

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Section: Calculation Of Experimental Aggregate Profilesmentioning

confidence: 99%

Nucleosome repositioning links DNA (de)methylation and differential CTCF binding during stem cell development

et al. 2014

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“…In particular, gene regulation in chromatin is frequently tuned by changing DNA accessibility for transcription factors through partial unwrapping of the nucleosome [49,[97][98][99][100][101][102][103][104][105][106]. Matrix formulations of the lattice models for protein multimer assembly on the DNA allow considering the nucleosome as a par ticular case of a protein multimer [107], which can partially dissociate when some of the histone dimers leave the octamer [27].…”

Section: Nucleosome Unwrappingmentioning

confidence: 99%

Nucleosomes in gene regulation: Theoretical approaches

et al. 2012

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This work reviews current theoretical approaches of biophysics and bioinformatics for the descrip tion of nucleosome arrangements in chromatin and transcription factor binding to nucleosomal organized DNA. The role of nucleosomes in gene regulation is discussed from the molecular mechanistic and biologi cal points of view. In addition to classical problems in this field, actual questions of epigenetic regulation are discussed. The authors selected for discussion what seem to be the most interesting concepts and hypotheses. Mathematical approaches are described in a simplified language to attract attention to the most important directions of this field.

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“…Yet, few current models of TF binding take competition with nucleosomes and other TFs into account, and few current models of nucleosome binding take competition with TFs into account. Current models that do consider nucleosomes and TFs together suffer from various drawbacks, such as being restricted to small genomic regions or coarse resolution (Teif 2007), or a lack of genome-wide improvement of positioning as a result of this incorporation (AV Morozov, K Fortney, DA Gaykalova, VM Studitsky, J Widom, ED Siggia, http://arxiv.org/abs/ 0805.4017). Although a few models of TF binding consider a small number of TFs at once at single-nucleotide resolution (Sinha 2006;Segal et al 2008), these do not consider nucleosomes.…”

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An ensemble model of competitive multi-factor binding of the genome

Wasson¹,

Hartemink²

2009

Genome Res.

101

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Hundreds of different factors adorn the eukaryotic genome, binding to it in large number. These DNA binding factors (DBFs) include nucleosomes, transcription factors (TFs), and other proteins and protein complexes, such as the origin recognition complex (ORC). DBFs compete with one another for binding along the genome, yet many current models of genome binding do not consider different types of DBFs together simultaneously. Additionally, binding is a stochastic process that results in a continuum of binding probabilities at any position along the genome, but many current models tend to consider positions as being either binding sites or not. Here, we present a model that allows a multitude of DBFs, each at different concentrations, to compete with one another for binding sites along the genome. The result is an ''occupancy profile,'' a probabilistic description of the DNA occupancy of each factor at each position. We implement our model efficiently as the software package COMPETE. We demonstrate genome-wide and at specific loci how modeling nucleosome binding alters TF binding, and vice versa, and illustrate how factor concentration influences binding occupancy. Binding cooperativity between nearby TFs arises implicitly via mutual competition with nucleosomes. Our method applies not only to TFs, but also recapitulates known occupancy profiles of a well-studied replication origin with and without ORC binding. Importantly, the sequence preferences our model takes as input are derived from in vitro experiments. This ensures that the calculated occupancy profiles are the result of the forces of competition represented explicitly in our model and the inherent sequence affinities of the constituent DBFs.[Supplemental material is available online at http://www.genome.org. The COMPETE software is available at http:// www.cs.duke.edu/;amink/software/compete/.]Hundreds of different factors adorn the eukaryotic genome, binding to it in large number. These DNA binding factors (DBFs) are quite diverse. For example, nucleosomes occupy 75%-90% of the genome (Van Holde 1989), and DNA and RNA polymerases traverse large swaths of it at a time. In contrast, transcription factors and other specialized proteins and protein complexes-like the origin recognition complex (ORC)-bind to very specific regions of the genome, often only at specific times or under specific conditions. Key cellular processes involving the genomeincluding replication, transcription, and chromatin packagingare regulated by the spatio-temporal interactions of these various DBFs with DNA and with each other. Consequently, it is critical that we understand how these factors interact as they bind to the genome.In particular, DBFs bind to the genome in competition with one another, jockeying for position along the DNA. As one example, to fit into the nucleus, DNA is highly compacted into chromatin in a hierarchy of levels. The lowest level is the formation of nucleosomes, where ;150 base pairs of DNA are coiled around a histone octomer. Since transcription factors (...

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General transfer matrix formalism to calculate DNA–protein–drug binding in gene regulation: application to O R operator of phage λ

Cited by 44 publications

References 73 publications

Nucleosome repositioning links DNA (de)methylation and differential CTCF binding during stem cell development

Nucleosome repositioning links DNA (de)methylation and differential CTCF binding during stem cell development

Nucleosomes in gene regulation: Theoretical approaches

An ensemble model of competitive multi-factor binding of the genome

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