The statistical-mechanics of chromosome conformation capture

Abstract

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.

Potential roles for interactions between the mitochondrial and nuclear DNA throughout the cell cycle of Schizosaccharomyces pombe

“…This supports our earlier observations where mt-nDNA interactions were captured in S. cerevisiae , with their numbers and positions being dependent upon carbon source and metabolism (Rodley et al, 2012, 2009). GCC is probabilistic and does not enable us to estimate the numbers of cells within the population in which the interactions are occurring, either singly or in combination (O’Sullivan et al, 2013), however these results support earlier observations that there is continual transfer of specific mitochondrial DNA regions to the nucleus and this transfer varies according to the cell’s energy state and cell cycle phase (Ricchetti et al, 2004, 1999; Thorsness and Fox, 1993, 1990). Moreover, the specificity of cell cycle phase mt-nDNA interactions suggests a regulatory role for these connections in cell function and growth.…”

Three-dimensional genome architecture: players and mechanisms

“…Ligation events generated between sequences located close to specific contacts and baseline ligation levels arising from random contacts between chromatin 105 will add to the background noise. Ligation-based methods are also affected by inherent biases in restriction enzyme cutting efficiency, ligation frequency and the fact that the contacts detected represent the average of the chromatin states of the individual cells in a population at the moment of crosslinking 111 .…”

Topology, structures, and energy landscapes of human chromosomes

“…They can also be used as constraints to derive a unique chromosome structure using algorithms resembling NMR protein structure determination (15,16). Because the experimental contact frequencies are ensemble averages from a population of cells that potentially vary in chromosome conformation (17)(18)(19)(20), the explicit form of this mapping to specific spatial distances is not known and may not be unique. In this study, we propose a method that confronts the issue of the averaging involved and directly reproduces the observed contact frequencies using an ensemble of chromosome conformations.…”