Extracting physical characteristics of higher-order chromatin structures from 3D image data.
Extracting physical characteristics of higher-order chromatin structures from 3D image data.
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DOI：
10.1016/j.csbj.2022.06.018
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发表时间：
2022
影响因子：
6
通讯作者：
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文献类型：
--
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高阶染色质结构对基因调控和细胞身份确定具有功能性影响。使用基于高通量测序（HTS）的方法如Hi-C，可以在细胞群体水平上鉴定活性或非活性区室以及开放或闭合拓扑相关结构域（ODN）结构。最近开发的高分辨率三维（3D）分子成像技术，如3D电子显微镜与原位杂交（3D-EMSIH）和3D结构照明显微镜（3D-SIM），使直接检测的物理表示的染色质结构在一个单一的细胞。然而，三维图像数据的计算分析与可解释性和可解释性的染色质结构的功能特征仍然是具有挑战性的。我们开发了从染色质结构图像中提取物理特征（EPICS），这是一种基于机器学习的计算方法，用于处理高分辨率染色质3D图像数据。使用3D-EMISH或3D-SIM技术产生的图像上的EPICS，我们生成了更直接的高阶染色质结构的3D表示，确定了主要的染色质结构域，并确定了每个结构域的开放或关闭状态。我们从模型中确定了几个高贡献的特征作为定义开放或封闭染色质结构域的主要物理特征，证明了EPICS的可解释性和可解释性。EPICS可应用于空间基因组学研究中其他高分辨率三维分子成像数据的分析。EPICS的R和Python代码可以在https://github.com/zang-lab/epics上找到。
Higher-order chromatin structures have functional impacts on gene regulation and cell identity determination. Using high-throughput sequencing (HTS)-based methods like Hi-C, active or inactive compartments and open or closed topologically associating domain (TAD) structures can be identified on a cell population level. Recently developed high-resolution three-dimensional (3D) molecular imaging techniques such as 3D electron microscopy with in situ hybridization (3D-EMSIH) and 3D structured illumination microscopy (3D-SIM) enable direct detection of physical representations of chromatin structures in a single cell. However, computational analysis of 3D image data with explainability and interpretability on functional characteristics of chromatin structures is still challenging. We developed Extracting Physical-Characteristics from Images of Chromatin Structures (EPICS), a machine-learning based computational method for processing high-resolution chromatin 3D image data. Using EPICS on images produced by 3D-EMISH or 3D-SIM techniques, we generated more direct 3D representations of higher-order chromatin structures, identified major chromatin domains, and determined the open or closed status of each domain. We identified several high-contributing features from the model as the major physical characteristics that define the open or closed chromatin domains, demonstrating the explainability and interpretability of EPICS. EPICS can be applied to the analysis of other high-resolution 3D molecular imaging data for spatial genomics studies. The R and Python codes of EPICS are available at https://github.com/zang-lab/epics.
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影响因子：
64.8
作者：
Harris CR;Millman KJ;van der Walt SJ;Gommers R;Virtanen P;Cournapeau D;Wieser E;Taylor J;Berg S;Smith NJ;Kern R;Picus M;Hoyer S;van Kerkwijk MH;Brett M;Haldane A;Del Río JF;Wiebe M;Peterson P;Gérard-Marchant P;Sheppard K;Reddy T;Weckesser W;Abbasi H;Gohlke C;Oliphant TE
通讯作者：
Oliphant TE
影响因子：
30.8
作者：
Akdemir, Kadir C.;Le, Victoria T.;Zhang, Cheng-Zhong
通讯作者：
Zhang, Cheng-Zhong
DOI：
10.1073/pnas.1613607113
发表时间：
2016-10-25
影响因子：
11.1
作者：
Di Pierro, Michele;Zhang, Bin;Onuchic, Jose N.
通讯作者：
Onuchic, Jose N.
影响因子：
64.8
作者：
通讯作者：
--
DOI：
10.1126/science.aau1783
发表时间：
2018-10-26
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Bintu B;Mateo LJ;Su JH;Sinnott-Armstrong NA;Parker M;Kinrot S;Yamaya K;Boettiger AN;Zhuang X
通讯作者：
Zhuang X