» Articles » PMID: 25349675

Homotypic Clusters of Transcription Factor Binding Sites: A Model System for Understanding the Physical Mechanics of Gene Expression

Overview
Specialty Biotechnology
Date 2014 Oct 29
PMID 25349675
Citations 35
Authors
Affiliations
Soon will be listed here.
Abstract

The organization of binding sites in cis-regulatory elements (CREs) can influence gene expression through a combination of physical mechanisms, ranging from direct interactions between TF molecules to DNA looping and transient chromatin interactions. The study of simple and common building blocks in promoters and other CREs allows us to dissect how all of these mechanisms work together. Many adjacent TF binding sites for the same TF species form homotypic clusters, and these CRE architecture building blocks serve as a prime candidate for understanding interacting transcriptional mechanisms. Homotypic clusters are prevalent in both bacterial and eukaryotic genomes, and are present in both promoters as well as more distal enhancer/silencer elements. Here, we review previous theoretical and experimental studies that show how the complexity (number of binding sites) and spatial organization (distance between sites and overall distance from transcription start sites) of homotypic clusters influence gene expression. In particular, we describe how homotypic clusters modulate the temporal dynamics of TF binding, a mechanism that can affect gene expression, but which has not yet been sufficiently characterized. We propose further experiments on homotypic clusters that would be useful in developing mechanistic models of gene expression.

Citing Articles

Mechanisms of enhanced or impaired DNA target selectivity driven by protein dimerization.

Sang M, Johnson M bioRxiv. 2025; .

PMID: 40027831 PMC: 11870488. DOI: 10.1101/2025.02.18.638941.


From homogeneity to heterogeneity: Refining stochastic simulations of gene regulation.

Chae S, Shin S, Lee K, Lee S, Kim J Comput Struct Biotechnol J. 2025; 27:411-422.

PMID: 39906159 PMC: 11791169. DOI: 10.1016/j.csbj.2025.01.004.


Evolution and Comparative Genomics of the Transforming Growth Factor-β-Related Proteins in Nile Tilapia.

Khan M, Parveen S, Sultana M, Zhu P, Xu Y, Safdar A Mol Biotechnol. 2024; .

PMID: 39240458 DOI: 10.1007/s12033-024-01263-x.


Identification of functional enhancer variants associated with type I diabetes in CD4+ T cells.

Mishra A, Jajodia A, Weston E, Jayavelu N, Garcia M, Hossack D Front Immunol. 2024; 15:1387253.

PMID: 38947339 PMC: 11211866. DOI: 10.3389/fimmu.2024.1387253.


Less-is-more: selecting transcription factor binding regions informative for motif inference.

Xu J, Gao J, Ni P, Gerstein M Nucleic Acids Res. 2024; 52(4):e20.

PMID: 38214231 PMC: 10899791. DOI: 10.1093/nar/gkad1240.


References
1.
Ruusala T, Crothers D . Sliding and intermolecular transfer of the lac repressor: kinetic perturbation of a reaction intermediate by a distant DNA sequence. Proc Natl Acad Sci U S A. 1992; 89(11):4903-7. PMC: 49196. DOI: 10.1073/pnas.89.11.4903. View

2.
Ochoa-Espinosa A, Yucel G, Kaplan L, Pare A, Pura N, Oberstein A . The role of binding site cluster strength in Bicoid-dependent patterning in Drosophila. Proc Natl Acad Sci U S A. 2005; 102(14):4960-5. PMC: 555997. DOI: 10.1073/pnas.0500373102. View

3.
Cox 3rd R, Surette M, Elowitz M . Programming gene expression with combinatorial promoters. Mol Syst Biol. 2007; 3:145. PMC: 2132448. DOI: 10.1038/msb4100187. View

4.
Melnikov A, Murugan A, Zhang X, Tesileanu T, Wang L, Rogov P . Systematic dissection and optimization of inducible enhancers in human cells using a massively parallel reporter assay. Nat Biotechnol. 2012; 30(3):271-7. PMC: 3297981. DOI: 10.1038/nbt.2137. View

5.
Weindl J, Dawy Z, Hanus P, Zech J, Mueller J . Modeling promoter search by E. coli RNA polymerase: one-dimensional diffusion in a sequence-dependent energy landscape. J Theor Biol. 2009; 259(3):628-34. DOI: 10.1016/j.jtbi.2009.05.006. View