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The statistical-mechanics of chromosome conformation capture

机译：染色体构象捕获的统计机制

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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 ChlA-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.
机译：自从Jacob和Monod表征了DNA元素在基因控制中的作用以来，人们已经认识到基因组结构的线性组织对于调节基因转录以及表型的表现很重要。同样，长期以来，人们一直认为，作为表观基因组的一部分的空间组织（在三个维度上随着时间的推移而变化）对基因型-表型的转变做出了重要贡献。通常称为基于染色体构象捕获（3C）和基于3C的方法（例如GCC，HiC和ChlA-Pet）的接近连接测定法正越来越多地被纳入经验研究，以研究三维基因组结构在调控基因组中所起的作用表型。这些方法的简单性-交联染色质，消化，稀释，连接，检测相互作用-掩盖了数据的复杂性以及为确保可靠数据的生成和准确解释而应考虑的因素。在这里，我们讨论了这些方法的概率性质，以及这如何导致其内生性局限性。

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