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Semi-nonparametric modeling of topological domain formation from epigenetic data.
Algorithms for Molecular Biology ( IF 1 ) Pub Date : 2019-03-05 , DOI: 10.1186/s13015-019-0142-y
Emre Sefer 1 , Carl Kingsford 2
Affiliation  

BACKGROUND Hi-C experiments capturing the 3D genome architecture have led to the discovery of topologically-associated domains (TADs) that form an important part of the 3D genome organization and appear to play a role in gene regulation and other functions. Several histone modifications have been independently associated with TAD formation, but their combinatorial effects on domain formation remain poorly understood at a global scale. RESULTS We propose a convex semi-nonparametric approach called nTDP based on Bernstein polynomials to explore the joint effects of histone markers on TAD formation as well as predict TADs solely from the histone data. We find a small subset of modifications to be predictive of TADs across species. By inferring TADs using our trained model, we are able to predict TADs across different species and cell types, without the use of Hi-C data, suggesting their effect is conserved. This work provides the first comprehensive joint model of the effect of histone markers on domain formation. CONCLUSIONS Our approach, nTDP, can form the basis of a unified, explanatory model of the relationship between epigenetic marks and topological domain structures. It can be used to predict domain boundaries for cell types, species, and conditions for which no Hi-C data is available. The model may also be of use for improving Hi-C-based domain finders.

中文翻译:

基于表观遗传数据的拓扑域形成的半非参数建模。

背景 捕捉 3D 基因组结构的 Hi-C 实验导致发现拓扑相关域 (TAD),它构成 3D 基因组组织的重要组成部分,似乎在基因调控和其他功能中发挥作用。一些组蛋白修饰与 TAD 形成独立相关,但它们对结构域形成的组合影响在全球范围内仍然知之甚少。结果 我们提出了一种基于 Bernstein 多项式的称为 nTDP 的凸半非参数方法,以探索组蛋白标记对 TAD 形成的联合影响,并仅根据组蛋白数据预测 TAD。我们发现一小部分修饰可以预测跨物种的 TAD。通过使用我们训练有素的模型推断 TAD,我们能够预测不同物种和细胞类型的 TAD,不使用 Hi-C 数据,表明它们的效果是保守的。这项工作提供了第一个关于组蛋白标记对域形成影响的综合联合模型。结论 我们的方法 nTDP 可以形成表观遗传标记和拓扑域结构之间关系的统一解释模型的基础。它可用于预测没有可用 Hi-C 数据的细胞类型、物种和条件的域边界。该模型还可用于改进基于 Hi-C 的域查找器。表观遗传标记与拓扑域结构之间关系的解释模型。它可用于预测没有可用 Hi-C 数据的细胞类型、物种和条件的域边界。该模型还可用于改进基于 Hi-C 的域查找器。表观遗传标记与拓扑域结构之间关系的解释模型。它可用于预测没有可用 Hi-C 数据的细胞类型、物种和条件的域边界。该模型还可用于改进基于 Hi-C 的域查找器。
更新日期:2019-11-01
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