Reconstruction of 3D Genome Architecture from Chromatin Conformation Capture Data

描述（由申请人提供）：人们普遍认为，真核染色质的三维（3D）结构在核和细胞功能中起着关键作用。的确， 这种关系构成了刚刚出版的（09/06/12）来自ENCODE协会的自然论文集的关键“线索”之一。然而，直到几年前，即使是在中等分辨率下观察/推断3D结构也是有问题的，部分原因是基因组高度浓缩。最近发明的分子技术正在改变这种情况。特别是，新的基因组规模的测定，如染色质构象捕获（CCC）的发展，使染色质“接触”的启发。这些技术已经以前所未有的分辨率提供了对染色质组织的深入了解，并允许探索这种组织对各种生物学的下游影响。值得注意的是，基因调控和癌症驱动基因融合被认为受到3D组织的强烈影响。因此，获得基因组结构的高分辨率3D重建是一个令人信服的生物学探索。然而，CCC数据的大多数分析都集中在一维（1D）接触水平上，对评估3D重建的准确性和再现性以及部署此类结构以分析随后的生物过程的努力明显较少。该提案中要解决的首要假设是，染色质接触数据可以可靠地用于确定基因组的3D结构，并评估下游与生物功能的关系。为了验证这一假设，我们将开发新的，并完善现有的，重建算法，并将进行系统的性能和操作特性的评估。唯一的基因组规模的算法开发采用约束优化，由于高维数，计算负担沉重，并可能陷入局部最优。因此，我们将研究替代算法。我们的初步工作表明，在合理的扰动下的数据和约束输入的再现性是定性差。我们会设计出 来量化3D协议。虽然扰动下的重现性可以使用计算和统计工具进行评估，但评估准确性需要使用有针对性的验证性测定，正如我们的湿实验室合作者所部署的那样。此外，我们将应用我们的3D重建纲要来探索一系列与功能元件邻近性相关的生物学问题。

DESCRIPTION (provided by applicant): It is widely recognized that the three dimensional (3D) architecture of eukaryotic chromatin plays critical roles in nuclear and cellular function. Indeed, such relationships constitute one of the key "threads" of the just published (09/06/12) suite of Nature papers from the ENCODE consortium. However, until a few years ago, observing / inferring, 3D structure at even modest resolutions was problematic, in part because genomes are highly condensed. Recently devised molecular techniques are changing this situation. In particular, the development of novel genome-scale assays, such as chromatin conformation capture (CCC), has enabled elicitation of chromatin "contacts". These techniques have already provided insight into chromatin organization at unprecedented resolutions, and permitted exploration of the downstream influence of such organization on a variety of biological. Notably, gene regulation and cancer-driving gene fusions are believed to be strongly influenced by 3D organization. Accordingly, obtaining high resolution 3D reconstructions of genome architecture is a compelling biological quest. However, most analysis of CCC data has focused on the one dimensional (1D) contact level, with appreciably less effort directed toward evaluating accuracy and reproducibility of 3D reconstructions, and deploying such structures to analyze consequent biological processes. The overarching hypothesis to be addressed in this proposal is that chromatin contact data can be reliably used to determine 3D structures of genomes and to assess downstream relationships with biological function. To test this hypothesis we will develop new, and refine existing, reconstruction algorithms, and will undertake a systematic evaluation of their performance and operating characteristics. The only genome-scale algorithms developed employ constrained optimization which, on account of high-dimensionality, is computationally burdensome and can be trapped in local optima. Accordingly, we will investigate alternate algorithms. Our preliminary work indicates that reproducibility under plausible perturbations to data and constraint inputs is qualitatively poor. We will devise metrics to quantify 3D agreement. While reproducibility under perturbations can be assessed using computational and statistical tools, appraising accuracy requires using targeted confirmatory assays, as will be deployed by our wet-lab collaborators. Further, we will apply our compendium of 3D reconstructions to explore a series of biologic questions relating to proximities of functional elements.