HiChIP: efficient and sensitive analysis of protein-directed genome architecture
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Abstract
Genome conformation is central to gene control but challenging to interrogate. Here we present HiChIP, a protein-centric chromatin conformation method. HiChIP improves the yield of conformation-informative reads by over 10-fold and lowers the input requirement over 100-fold relative to that of ChIA-PET. HiChIP of cohesin reveals multiscale genome architecture with greater signal-to-background ratios than those of in situ Hi-C.
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Enhancer function requires physical contacts between enhancers and promoters in three dimensions.
“The activity of enhancers depends on three-dimensional enhancer-promoter interactions (8)”
From Brain cell type–specific enhancer–promoter interactome maps and disease <b>-</b> risk association (2019) · cites this paper as [8]
The Main Text reports that certain Oct4–Smc1a chromatin loops are associated with active enhancers and promoters. It does not establish that enhancer activity depends on, or requires, those physical interactions. (LLM, conf=0.84)
Experimental — accuracy not yet measuredIn each cell type, a single promoter can connect to multiple enhancers.
“We identified putative active promoters and enhancers in each cell type and found a one-to many relationship between promoters and enhancers (8).”
From Brain cell type–specific enhancer–promoter interactome maps and disease <b>-</b> risk association (2019) · cites this paper as [8]
The Main Text (page not provided) associates some HiChIP loops with active enhancers and promoters, but does not report how many enhancers connect to a promoter in each cell type. Searches for a one-to-many promoter–enhancer relationship and for multiple enhancers per promoter found no passage addressing that relationship. (LLM, conf=0.73)
Experimental — accuracy not yet measuredAcute depletion of CTCF in mouse embryonic stem cells causes loss of chromatin loops between CTCF-bound sites genome-wide.
“CTCF is absolutely and dose-dependently required for looping between CTCF target sites and insulation of topologically associating domains (TADs).”
From Targeted Degradation of CTCF Decouples Local Insulation of Chromosome Domains from Genomic Compartmentalization (2017) · cites this paper as Mumbach et al., 2016
At stringent boundary thresholds, 62% of called boundaries matched previously identified loop anchors within ±1 20-kb bin.
“This comparison revealed that at high threshold values, corresponding to stricter boundary selection, up to 62% of detected boundaries co-aligned with the previously detected loop anchors within +-1 20kb bin precision.”
From Targeted Degradation of CTCF Decouples Local Insulation of Chromosome Domains from Genomic Compartmentalization (2017) · cites this paper as Mumbach et al., 2016
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Cites
Model-based Analysis of ChIP-Seq (MACS)
Zhang, Y., Liu, T., Meyer, C. A., Eeckhoute, J., Johnson, D. S., Bernstein, B. E., Nusbaum, C., Myers, R. M., Brown, M., Li, W., et al. (2008) · Genome Biology · doi:10.1186/gb-2008-9-9-r137 · Cited by 18,386 · see citing works
A 3D Map of the Human Genome at Kilobase Resolution Reveals Principles of Chromatin Looping
Rao, S. S. P., Huntley, M. H., Durand, N. C., Stamenova, E. K., Bochkov, I. D., Robinson, J. T., Sanborn, A. L., Machol, I., Omer, A. D., Lander, E. S., et al. (2014) · Cell · doi:10.1016/j.cell.2014.11.021 · Cited by 9,212 · see citing works
Comprehensive Mapping of Long-Range Interactions Reveals Folding Principles of the Human Genome
Lieberman-Aiden, E., van Berkum, N. L., Williams, L., Imakaev, M., Ragoczy, T., Telling, A., Amit, I., Lajoie, B. R., Sabo, P. J., Dorschner, M. O., et al. (2009) · Science · doi:10.1126/science.1181369 · Cited by 8,898 · see citing works
Topological domains in mammalian genomes identified by analysis of chromatin interactions
Dixon, J. R., Selvaraj, S., Yue, F., Kim, A., Li, Y., Shen, Y., Hu, M., Liu, J. S., & Ren, B. (2012) · Nature · doi:10.1038/nature11082 · Cited by 6,829 · see citing works
Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y., & Greenleaf, W. J. (2013) · Nature Methods · doi:10.1038/nmeth.2688 · Cited by 6,422 · see citing works
Self-citationJuicer Provides a One-Click System for Analyzing Loop-Resolution Hi-C Experiments
Durand, N. C., Shamim, M. S., Machol, I., Rao, S. S. P., Huntley, M. H., Lander, E. S., & Aiden, E. L. (2016) · Cell Systems · doi:10.1016/j.cels.2016.07.002 · Cited by 3,724 · see citing works
Spatial partitioning of the regulatory landscape of the X-inactivation centre
Nora, E. P., Lajoie, B. R., Schulz, E. G., Giorgetti, L., Okamoto, I., Servant, N., Piolot, T., van Berkum, N. L., Meisig, J., Sedat, J., et al. (2012) · Nature · doi:10.1038/nature11049 · Cited by 2,895 · see citing works
HiC-Pro: an optimized and flexible pipeline for Hi-C data processing.
Servant, N., Varoquaux, N., Lajoie, B. R., Viara, E., Chen, C.-J., Vert, J.-P., Heard, E., Dekker, J., & Barillot, E. (2015) · Genome Biology · doi:10.1186/s13059-015-0831-x · Cited by 2,565 · see citing works
Juicebox Provides a Visualization System for Hi-C Contact Maps with Unlimited Zoom
Durand, N. C., Robinson, J., Shamim, M. S., Machol, I., Mesirov, J. P., Lander, E. S., & Aiden, E. L. (2016) · Cell Systems · doi:10.1016/j.cels.2015.07.012 · Cited by 2,335 · see citing works
Mediator and cohesin connect gene expression and chromatin architecture
Kagey, M. H., Newman, J. J., Bilodeau, S., Zhan, Y., Orlando, D. A., van Berkum, N. L., Ebmeier, C. C., Goossens, J., Rahl, P. B., Levine, S. S., et al. (2010) · Nature · doi:10.1038/nature09380 · Cited by 1,939 · see citing works
An oestrogen-receptor-α-bound human chromatin interactome
Fullwood, M. J., Liu, M. H., Pan, Y. F., Liu, J., Han, X., Mohamed, Y. B., Orlov, Y. L., Velkov, S., Ho, A., Poh, H. M., et al. (2009) · Nature · doi:10.1038/nature08497 · Cited by 1,728 · see citing works
A high-resolution map of the three-dimensional chromatin interactome in human cells
Jin, F., Li, Y., Dixon, J. R., Selvaraj, S., Ye, Z., Lee, A. Y., Yen, C.-A., Schmitt, A. D., Espinoza, C. A., & Ren, B. (2013) · Nature · doi:10.1038/nature12644 · Cited by 1,208 · see citing works
CTCF-Mediated Human 3D Genome Architecture Reveals Chromatin Topology for Transcription
Tang, Z., Luo, O. J., Li, X., Zheng, M., Zhu, J. J., Szalaj, P., Trzaskoma, P., Magalska, A., Wlodarczyk, J., Ruszczycki, B., et al. (2015) · Cell · doi:10.1016/j.cell.2015.11.024 · Cited by 982 · see citing works
Organization of the mitotic chromosome
Naumova, N., Imakaev, M., Fudenberg, G., Zhan, Y., Lajoie, B. R., Mirny, L. A., & Dekker, J. (2013) · Science · doi:10.1126/science.1236083 · Cited by 976 · see citing works
Control of cell identity genes occurs in insulated neighborhoods in mammalian chromosomes
Dowen, J. M., Fan, Z. P., Hnisz, D., Ren, G., Abraham, B. J., Zhang, L. N., Weintraub, A. S., Schuijers, J., Lee, T. I., Zhao, K., et al. (2014) · Cell · doi:10.1016/j.cell.2014.09.030 · Cited by 884 · see citing works
ChIPmentation: fast, robust, low-input ChIP-seq for histones and transcription factors
Schmidl, C., Rendeiro, A. F., Sheffield, N. C., & Bock, C. (2015) · Nature Methods · doi:10.1038/nmeth.3542 · Cited by 509 · see citing works
Statistical confidence estimation for Hi-C data reveals regulatory chromatin contactsPreprint
Ay, F., Bailey, T. L., & Noble, W. S. (2014) · Genome Research · doi:10.1101/gr.160374.113 · Cited by 479 · see citing works
Hughes, J. R., Roberts, N., McGowan, S., Hay, D., Giannoulatou, E., Lynch, M., De Gobbi, M., Taylor, S., Gibbons, R., & Higgs, D. R. (2014) · Nature Genetics · doi:10.1038/ng.2871 · Cited by 461 · see citing works
Systematic discovery and characterization of regulatory motifs in ENCODE TF binding experiments
Kheradpour, P., & Kellis, M. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt1249 · Cited by 460 · see citing works
Structural organization of the inactive X chromosome in the mouse
Giorgetti, L., Lajoie, B. R., Carter, A. C., Attia, M., Zhan, Y., Xu, J., Chen, C. J., Kaplan, N., Chang, H. Y., Heard, É., et al. (2016) · Nature · doi:10.1038/nature18589 · Cited by 410 · see citing works
Self-citation3D Chromosome Regulatory Landscape of Human Pluripotent Cells
Ji, X., Dadon, D. B., Powell, B. E., Fan, Z. P., Borges-Rivera, D., Shachar, S., Weintraub, A. S., Hnisz, D., Pegoraro, G., Lee, T. I., et al. (2016) · Cell Stem Cell · doi:10.1016/j.stem.2015.11.007 · Cited by 400 · see citing works
Genome-wide map of regulatory interactions in the human genome
Heidari, N., Phanstiel, D. H., He, C., Grubert, F., Jahanbani, F., Kasowski, M., Zhang, M. Q., & Snyder, M. P. (2014) · Genome Research · doi:10.1101/gr.176586.114 · Cited by 278 · see citing works
Multiplexed analysis of chromosome conformation at vastly improved sensitivity
Davies, J. O. J., Telenius, J. M., McGowan, S. J., Roberts, N. A., Taylor, S., Higgs, D. R., & Hughes, J. R. (2016) · Nature Methods · doi:10.1038/nmeth.3664 · Cited by 268 · see citing works
Long-Range Chromatin Interactions
Dekker, J., & Misteli, T. (2015) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a019356 · Cited by 255 · see citing works
Comparison of Hi-C results using in-solution versus in-nucleus ligation
Nagano, T., Várnai, C., Schoenfelder, S., Javierre, B.-M., Wingett, S. W., & Fraser, P. (2015) · Genome Biology · doi:10.1186/s13059-015-0753-7 · Cited by 166 · see citing works
Mango: a bias-correcting ChIA-PET analysis pipeline
Phanstiel, D. H., Boyle, A. P., Heidari, N., & Snyder, M. P. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv336 · Cited by 113 · see citing works
Kolovos, P., van de Werken, H. J. G., Kepper, N., Zuin, J., Brouwer, R. W. W., Kockx, C. E. M., Wendt, K. S., van IJcken, W. F. J., Grosveld, F. G., & Knoch, T. (2014) · Epigenetics & Chromatin · doi:10.1186/1756-8935-7-10 · Cited by 88 · see citing works
Foxd3: A Repressor, an Activator, or Both?
Sweet, D. J. (2016) · Cell stem cell · doi:10.1016/j.stem.2015.12.009 · Cited by 58 · see citing works
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Activity-by-contact model of enhancer–promoter regulation from thousands of CRISPR perturbations
Fulco, C. P., Nasser, J., Jones, T. R., Munson, G., Bergman, D. T., Subramanian, V., Grossman, S. R., Anyoha, R., Doughty, B. R., Patwardhan, T. A., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0538-0 · Cited by 1,111 · see citing works
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Nott, A., Holtman, I. R., Coufal, N. G., Schlachetzki, J. C. M., Yu, M., Hu, R., Han, C. Z., Pena, M., Xiao, J., Wu, Y., et al. (2019) · Science · doi:10.1126/science.aay0793 · Cited by 823 · see citing works
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Yang, T., Zhang, F., Yardımcı, G. G., Song, F., Hardison, R. C., Noble, W. S., Yue, F., & Li, Q. (2017) · Genome Research · doi:10.1101/gr.220640.117 · Cited by 533 · see citing works
Mumbach, M. R., Satpathy, A. T., Boyle, E. A., Dai, C., Gowen, B. G., Cho, S. W., Nguyen, M. L., Rubin, A. J., Granja, J. M., Kazane, K. R., et al. (2017) · Nature Genetics · doi:10.1038/ng.3963 · Cited by 490 · see citing works
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Corces, M. R., Shcherbina, A., Kundu, S., Gloudemans, M. J., Frésard, L., Granja, J. M., Louie, B. H., Eulalio, T., Shams, S., Bagdatli, S. T., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-00721-x · Cited by 358 · see citing works
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- Authors
- Mumbach, M. R., Rubin, A. J., Flynn, R. A., Dai, C., Khavari, P. A., Greenleaf, W. J., & Chang, H. Y.
- Affiliations
- Stanford Medicine (US)
- Corresponding author
- Chang, Howard Y
- ORCID
- Venue
- Nature Methods
- Published
- 2016-09-19
- Volume
- 13
- Issue
- 11
- Pages
- 919-922
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- PMC
- PMC5501173
- OpenAlex
- W2523285811
- Cited by
- 1,139
- References
- 28
- Citations by year
- 2026: 77 · 2025: 102 · 2024: 148 · 2023: 153 · 2022: 134 · 2021: 165 · 2020: 143 · 2019: 107 · 2018: 76 · 2017: 27 · 2016: 4 · 2014: 1 · 2013: 1
- FWCI
- 37.03
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- cc-by-nc-nd
- www.springer.com/tdm (tdm)
- Locations
- Nature Methods (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (1s10od018220-01, NIH P50, HG007735)
- National Human Genome Research Institute (HG007735, P50HG007735, T32HG000044)
- National Cancer Institute (F30CA189514, P30CA124435)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomic variations and chromosomal abnormalities
- Keywords
- HiChIP, 3D genome organization, chromosome conformation capture, tagmentation, cohesin, signal-to-background ratio
- MeSH terms
- Cohesins, Animals, B-Lymphocytes, Cell Line, Cell Nucleus, Chromatin, Chromosomal Proteins, Non-Histone, Chromosome Mapping, DNA, Humans, Sensitivity and Specificity, Reproducibility of Results, Cell Cycle Proteins, Genomics, Chromatin Immunoprecipitation, Mice, Embryonic Stem Cells
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