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Two main stream methods analysis and visual 3D genome architecture

期刊

SEMINARS IN CELL & DEVELOPMENTAL BIOLOGY
卷 90, 期 -, 页码 43-53

出版社

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.semcdb.2018.07.011

关键词

3D genome; Architecture; Hi-C; ChIA-PET; Chromosome

资金

  1. Zhongshan Distinguished Professor Grant
  2. National Nature Science Foundation of China [91230204, 81270099, 81320108001, 81270131, 81300010, 81700008]
  3. Shanghai Committee of Science and Technology [12JC1402200, 12431900207, 11410708600, 14431905100]
  4. Shanghai Institute of Clinical Bioinformatics, Ministry of Education [20130071110043]
  5. National Key Research and Development Program [2016YFC0902400, 2017YFSF090207]

向作者/读者索取更多资源

Multi-dimensions dynamics of the genome play important roles in the maintenance of cell function, regulation of transcriptional signals and occurrence of diseases. With rapid development of methodologies, the genome organization and structure are found as three-dimensional (3D) or with dynamic changes (4D), and regulated by a large number of factors. The present article aims to overview the 3C derivation method Hi-C and ChIA-PET assay technologies coupled with newdata analysis methods, capture the spatial interactions between different loci across the entire genome, reveal the regularity of the genome spatial structure. Its relationship with gene regulation is for better understanding of the spatial structure of the genome. From two mainstream methods of ChIA-PET and Hi-C, we obtain some special proteins mediated chromatin interaction and whole genome chromatin interaction, transform frequency relation to distance relation for further coordinates, and predict 3D architecture. ChIA-PET method more focuses on one protein binding effect of chromatin activities, while Hi-C method more comprehensive with challenges in data process. Data of chromatin interaction, thermogram, and chromatin spatial structure from integrated analyses of two methods indicates the further need of deep mining and exploration. (C) 2018 Elsevier Ltd. All rights reserved.

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