NucleoMap: A computational tool for identifying nucleosomes in ultra-high resolution contact maps.
NucleoMap: A computational tool for identifying nucleosomes in ultra-high resolution contact maps.
复制标题
NucleoMap：在超高分辨率接触图中识别核小体的计算工具。
DOI：
10.1371/journal.pcbi.1010265
复制
发表时间：
2022-07
影响因子：
4.3
通讯作者：
中科院分区：
文献类型：
--
作者：
尽管定位不良的核小体在真核基因组中普遍存在，但它们难以用现有的核小体鉴定方法鉴定。最近可用的增强型高通量染色质构象捕获技术，如Micro-C，DNase Hi-C和Hi-CO表征核小体水平的染色质接近性，同时探测单核小体的位置和核小体对之间的间距，使核小体分析定位不良的区域成为可能。在这里，我们开发了一种新的计算方法，NucleoMap，从超高分辨率染色质接触图中识别核小体定位。通过整合核小体读段密度、接触距离和结合偏好，NucleoMap精确定位原核和真核基因组中的核小体，并在精确度和召回率方面优于现有的核小体识别方法。我们严格表征真核生物中单核小体的空间组织与其相应的组蛋白修饰、蛋白结合活性和高阶染色质功能之间的全基因组关联。我们还发现了人类胚胎干细胞中两个四核小体折叠结构的证据，并分析了它们与多个结构和功能区域的关联。基于所识别的核小体，构建了核小体接触图，该接触图反映了核小体间的距离，并保留了原始接触图中的接触距离轮廓。核小体是染色质的保守结构单元，其排列规律和定位水平与转录活性密切相关，但由于定位不佳，其在真核生物基因组中的分布尚未得到全面研究。最近可用的高通量增强的染色质构象捕获技术，如Micro-C，DNase Hi-C和Hi-CO提供核小体水平染色质接近度的信息，包括单核小体的位置和核小体对之间的间距，使得能够识别定位不良区域中的核小体。在这里，我们提出了NucleoMap，一种从超高分辨率染色质接触图中识别核小体的方法。在本文中，我们概述了NucleoMap的工作流程和功能。我们在多个数据集中使用流行的基线方法对NucleoMap进行基准测试。接下来，我们严格表征真核生物中单核小体的空间组织与其相应的组蛋白修饰、蛋白质结合活性和高阶染色质功能之间的全基因组关联。基于已鉴定的核小体，我们还构建了更精确和更可解释的核小体接触图，该图保留了核小体间的距离。
Although poorly positioned nucleosomes are ubiquitous in the eukaryotic genome, they are difficult to identify with existing nucleosome identification methods. Recently available enhanced high-throughput chromatin conformation capture techniques such as Micro-C, DNase Hi-C, and Hi-CO characterize nucleosome-level chromatin proximity, probing the positions of mono-nucleosomes and the spacing between nucleosome pairs at the same time, enabling nucleosome profiling in poorly positioned regions. Here we develop a novel computational approach, NucleoMap, to identify nucleosome positioning from ultra-high resolution chromatin contact maps. By integrating nucleosome read density, contact distances, and binding preferences, NucleoMap precisely locates nucleosomes in both prokaryotic and eukaryotic genomes and outperforms existing nucleosome identification methods in both precision and recall. We rigorously characterize genome-wide association in eukaryotes between the spatial organization of mono-nucleosomes and their corresponding histone modifications, protein binding activities, and higher-order chromatin functions. We also find evidence of two tetra-nucleosome folding structures in human embryonic stem cells and analyze their association with multiple structural and functional regions. Based on the identified nucleosomes, nucleosome contact maps are constructed, reflecting the inter-nucleosome distances and preserving the contact distance profiles in original contact maps. Nucleosomes are the conservative building blocks of the chromatin, and their array regularity and positioning level correlate with transcription activity, but their underlying distributions in eukaryote genomes have not been comprehensively studied due to the poorly positioned ones. Recently available high-throughput enhanced chromatin conformation capture techniques such as Micro-C, DNase Hi-C, and Hi-CO provide information of nucleosome-level chromatin proximity, including the positions of mononucleosomes and the spacing between nucleosome pairs, enabling identifying nucleosomes in poorly positioned regions. Here, we present NucleoMap, a nucleosome identification approach from ultra-high resolution chromatin contact maps. In this paper, we provide an overview of NucleoMap’s workflow and capabilities. We benchmark NucleoMap with popular baseline methods in multiple datasets. Next, we rigorously characterize genome-wide association between the spatial organization of mono-nucleosomes and their corresponding histone modifications, protein binding activities, and higher-order chromatin functions in eukaryotes. Based on the identified nucleosomes, we also construct more precise and more interpretable nucleosome contact maps, which preserve the inter-nucleosome distances.
登录
查看更多内容
影响因子：
30.8
作者：
He, Housheng Hansen;Meyer, Clifford A.;Shin, Hyunjin;Bailey, Shannon T.;Wei, Gang;Wang, Qianben;Zhang, Yong;Xu, Kexin;Ni, Min;Lupien, Mathieu;Mieczkowski, Piotr;Lieb, Jason D.;Zhao, Keji;Brown, Myles;Liu, X. Shirley
通讯作者：
Liu, X. Shirley
影响因子：
48
作者：
Langmead, Ben;Salzberg, Steven L.
通讯作者：
Salzberg, Steven L.
影响因子：
64.8
作者：
Brogaard, Kristin;Xi, Liqun;Wang, Ji-Ping;Widom, Jonathan
通讯作者：
Widom, Jonathan
DOI：
10.1093/bioinformatics/bts206
发表时间：
2012-06-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Polishko A;Ponts N;Le Roch KG;Lonardi S
通讯作者：
Lonardi S
影响因子：
48
作者：
Hsieh, Tsung-Han S.;Fudenberg, Geoffrey;Rando, Oliver J.
通讯作者：
Rando, Oliver J.