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HiC-3DViewer: a new tool to visualize Hi-C data in 3D space |
Mohamed Nadhir Djekidel1, Mengjie Wang2, Michael Q. Zhang3,1( ), Juntao Gao1( ) |
1. MOE Key Laboratory of Bioinformatics; Bioinformatics Division and Center for Synthetic & Systems Biology, TNLIST; Department of Automation, Tsinghua University, Beijing 100084, China 2. School of Pharmaceutical Sciences, Tsinghua University, Beijing 100084, China 3. Department of Biological Sciences, Center for Systems Biology, The University of Texas at Dallas, Richardson, TX 75080-3021, USA |
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Abstract Background: Although significant progress has been made to map chromatin structure at unprecedented resolution and scales, we are short of tools that enable the intuitive visualization and navigation along the three-dimensional (3D) structure of chromatins. The available tools people have so far are generally script-based or present basic features that do not easily enable the integration of genomic data along with 3D chromatin structure, hence, many scientists find themselves in the obligation to hack tools designed for other purposes such as tools for protein structure study. Methods: We present HiC-3DViewer, a new browser-based interactive tool designed to provide an intuitive environment for investigators to facilitate the 3D exploratory analysis of Hi-C data along with many useful annotation functionalities. Among the key features of HiC-3DViewer relevant to chromatin conformation studies, the most important one is the 1D-to-2D-to-3D mapping, to highlight genomic regions of interest interactively. This feature enables investigators to explore their data at different levels/angels. Additionally, investigators can superpose different genomic signals (such as ChIP-Seq, SNP) on the top of the 3D structure. Results: As a proof of principle we applied HiC-3DViewer to investigate the quality of Hi-C data and to show the spatial binding of GATA1 and GATA2 along the genome. Conclusions: As a user-friendly tool, HiC-3DViewer enables the visualization of inter/intra-chromatin interactions and gives users the flexibility to customize the look-and-feel of the 3D structure with a simple click. HiC-3DViewer is implemented in Javascript and Python, and is freely available at: http://bioinfo.au.tsinghua.edu.cn/member/nadhir/HiC3DViewer/. Supplementary information (User Manual, demo data) is also available at this website.
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| Author Summary Recently, many tools have developed to analyze and visualize chromatin conformation data. However, we are short of tools that enable the interactive visualization of the 3D chromatin structure. Here, we introduce HiC3D-Viewer, a new browser-based interactive visualization tool designed to provide an intuitive environment that facilitates the 3D exploratory analysis of Hi-C data. Among the key features of HiC-3DViewer is the 1D-to-2D-to-3D interactive highlight of genomic regions, display of inter- and intra-chromatin interactions and 3D model predictions, in addition to the flexibility to customize the displayed models, which make very valuable for the chromatin structure community. |
| Keywords
Hi-C
3D genome visualization
chromatin structure prediction
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Corresponding Author(s):
Michael Q. Zhang,Juntao Gao
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Online First Date: 30 December 2016
Issue Date: 07 June 2017
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| 1 |
E. Lieberman-Aiden, , N. L. van Berkum, , L. Williams, , M. Imakaev, , T. Ragoczy, , A. Telling, , I. Amit, , B. R. Lajoie, , P. J. Sabo, , M. O. Dorschner, , et al. (2009) Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science, 326, 289–293
https://doi.org/10.1126/science.1181369
pmid: 19815776
|
| 2 |
G. Li, , X. Ruan, , R. K. Auerbach, , K. S. Sandhu, , M. Zheng, , P. Wang, , H. M. Poh, , Y. Goh, , J. Lim, , J. Zhang, , et al. (2012) Extensive promoter-centered chromatin interactions provide a topological basis for transcription regulation. Cell, 148, 84–98
https://doi.org/10.1016/j.cell.2011.12.014
pmid: 22265404
|
| 3 |
A. Sanyal, , B. R. Lajoie, , G. Jain, and J. Dekker, (2012) The long-range interaction landscape of gene promoters. Nature, 489, 109–113
https://doi.org/10.1038/nature11279
pmid: 22955621
|
| 4 |
A. Göndör, and R. Ohlsson, (2009) Chromosome crosstalk in three dimensions. Nature, 461, 212–217
https://doi.org/10.1038/nature08453
pmid: 19741702
|
| 5 |
N. Varoquaux, , F. Ay, , W. S. Noble, and J.-P. Vert, (2014) A statistical approach for inferring the 3D structure of the genome. Bioinformatics, 30, i26–i33
https://doi.org/10.1093/bioinformatics/btu268
pmid: 24931992
|
| 6 |
D. Baù, , A. Sanyal, , B. R. Lajoie, , E. Capriotti, , M. Byron, , J. B. Lawrence, , J. Dekker, and M. A. Marti-Renom, (2011) The three-dimensional folding of the α-globin gene domain reveals formation of chromatin globules. Nat. Struct. Mol. Biol., 18, 107–114
https://doi.org/10.1038/nsmb.1936
pmid: 21131981
|
| 7 |
S. Wang, , J. Xu, and J. Zeng, (2015) Inferential modeling of 3D chromatin structure. Nucleic Acids Res., 43, e54
https://doi.org/10.1093/nar/gkv100
pmid: 25690896
|
| 8 |
S. Thongjuea, , R. Stadhouders, , F. G. Grosveld, , E. Soler, and B. Lenhard, (2013) r3Cseq: an R/Bioconductor package for the discovery of long-range genomic interactions from chromosome conformation capture and next-generation sequencing data. Nucleic Acids Res., 41, e132
https://doi.org/10.1093/nar/gkt373
pmid: 23671339
|
| 9 |
D. H. Phanstiel, , A. P. Boyle, , C. L. Araya, and M. P. Snyder, (2014) Sushi.R: flexible, quantitative and integrative genomic visualizations for publication-quality multi-panel figures. Bioinformatics, 30, 2808–2810
https://doi.org/10.1093/bioinformatics/btu379
pmid: 24903420
|
| 10 |
LLC Schrödinger, (2010) The PyMOL Molecular Graphics System, Versio1 1.3r1.
|
| 11 |
J. Nowotny, , A. Wells, , L. Xu, , R. Cao, , T. Trieu, , C. He, , J Cheng, . (2016) GMOL: an interactive tool for 3D genome structure visualization. Sci. Rep. 6, 20802
|
| 12 |
T. M. Asbury, , M. Mitman, , J. Tang, and W. J. Zheng, (2010) Genome3D: a viewer-model framework for integrating and visualizing multi-scale epigenomic information within a three-dimensional genome. BMC Bioinformatics, 11, 444
https://doi.org/10.1186/1471-2105-11-444
pmid: 20813045
|
| 13 |
C. Peng, , L.-Y. Fu, , P.-F. Dong, , Z.-L. Deng, , J.-X. Li, , X. T. Wang, and H. Y. Zhang, (2013) The sequencing bias relaxed characteristics of Hi-C derived data and implications for chromatin 3D modeling. Nucleic Acids Res., 41, e183
https://doi.org/10.1093/nar/gkt745
pmid: 23965308
|
| 14 |
L. Teng, , B. He, , J. Wang, and K. Tan, (2015) 4DGenome: a comprehensive database of chromatin interactions. Bioinformatics, 31, 2560–2564
https://doi.org/10.1093/bioinformatics/btv158
pmid: 25788621
|
| 15 |
J. Dirksen, (2013) Learning Three.js: The JavaScript 3D Library for WebGL. Birmingham: Packt Publishing
|
| 16 |
M. Grinberg, (2014) Flask Web Development. Sebastopol: O’Reilly Media
|
| 17 |
Z. Duan, , M. Andronescu, , K. Schutz, , S. McIlwain, , Y. J. Kim, , C. Lee, , J. Shendure, , S. Fields, , C. A. Blau, and W. S. Noble, (2010) A three-dimensional model of the yeast genome. Nature, 465, 363–367
https://doi.org/10.1038/nature08973
pmid: 20436457
|
| 18 |
T. Sexton, , E. Yaffe, , E. Kenigsberg, , F. Bantignies, , B. Leblanc, , M. Hoichman, , H. Parrinello, , A. Tanay, and G. Cavalli, (2012) Three-dimensional folding and functional organization principles of the Drosophila genome. Cell, 148, 458–472
https://doi.org/10.1016/j.cell.2012.01.010
pmid: 22265598
|
| 19 |
S. S. Rao, , M. H. Huntley, , N. C. Durand, , E. K. Stamenova, , I. D. Bochkov, , J. T. Robinson, , A. L. Sanborn, , I. Machol, , A. D. Omer, , E. S. Lander, , et al. (2014) A 3D map of the human genome at kilobase resolution reveals principles of chromatin looping. Cell, 159, 1665–1680
https://doi.org/10.1016/j.cell.2014.11.021
pmid: 25497547
|
| 20 |
J. R. Dixon, , S. Selvaraj, , F. Yue, , A. Kim, , Y. Li, , Y. Shen, , M. Hu, , J. S. Liu, and B. Ren, (2012) Topological domains in mammalian genomes identified by analysis of chromatin interactions. Nature, 485, 376–380
https://doi.org/10.1038/nature11082
pmid: 22495300
|
| 21 |
F. Ay, , E. M. Bunnik, , N. Varoquaux, , S. M. Bol, , J. Prudhomme, , J. P. Vert, , W. S. Noble, and K. G. Le Roch, (2014) Three-dimensional modeling of the P. falciparum genome during the erythrocytic cycle reveals a strong connection between genome architecture and gene expression. Genome Res., 24, 974–988
https://doi.org/10.1101/gr.169417.113
pmid: 24671853
|
| 22 |
X. Lan, , H. Witt, , K. Katsumura, , Z. Ye, , Q. Wang, , E. H. Bresnick, , P. J. Farnham, and V. X. Jin, (2012) Integration of Hi-C and ChIP-seq data reveals distinct types of chromatin linkages. Nucleic Acids Res., 40, 7690–7704
https://doi.org/10.1093/nar/gks501
pmid: 22675074
|
| 23 |
M. Hu, , K. Deng, , S. Selvaraj, , Z. Qin, , B. Ren, and J. S. Liu, (2012) HiCNorm: removing biases in Hi-C data via Poisson regression. Bioinformatics, 28, 3131–3133
https://doi.org/10.1093/bioinformatics/bts570
pmid: 23023982
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