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The statistical-mechanics of chromosome conformation capture

Since Jacob and Monod’s characterization of the role of DNA elements in gene control, it has been recognized that the linear organization of genome structure is important for the regulation of gene transcription and hence the manifestation of phenotypes. Similarly, it has long been hypothesized that...

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Detalles Bibliográficos
Autores principales: O'Sullivan, Justin M, Hendy, Michael D, Pichugina, Tatyana, Wake, Graeme C, Langowski, Jörg
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Landes Bioscience 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3899129/
https://www.ncbi.nlm.nih.gov/pubmed/24051548
http://dx.doi.org/10.4161/nucl.26513
Descripción
Sumario:Since Jacob and Monod’s characterization of the role of DNA elements in gene control, it has been recognized that the linear organization of genome structure is important for the regulation of gene transcription and hence the manifestation of phenotypes. Similarly, it has long been hypothesized that the spatial organization (in three dimensions evolving through time), as part of the epigenome, makes a significant contribution to the genotype-phenotype transition. Proximity ligation assays commonly known as chromosome conformation capture (3C) and 3C based methodologies (e.g., GCC, HiC, and ChIA-Pet) are increasingly being incorporated into empirical studies to investigate the role that three-dimensional genome structure plays in the regulation of phenotype. The apparent simplicity of these methodologies—crosslink chromatin, digest, dilute, ligate, detect interactions—belies the complexity of the data and the considerations that should be taken into account to ensure the generation and accurate interpretation of reliable data. Here we discuss the probabilistic nature of these methodologies and how this contributes to their endogenous limitations.