Comparison of the Hi-C, GAM and SPRITE methods using polymer models of chromatin.
Journal
Nature methods
ISSN: 1548-7105
Titre abrégé: Nat Methods
Pays: United States
ID NLM: 101215604
Informations de publication
Date de publication:
05 2021
05 2021
Historique:
received:
29
05
2020
accepted:
31
03
2021
entrez:
8
5
2021
pubmed:
9
5
2021
medline:
28
7
2021
Statut:
ppublish
Résumé
Hi-C, split-pool recognition of interactions by tag extension (SPRITE) and genome architecture mapping (GAM) are powerful technologies utilized to probe chromatin interactions genome wide, but how faithfully they capture three-dimensional (3D) contacts and how they perform relative to each other is unclear, as no benchmark exists. Here, we compare these methods in silico in a simplified, yet controlled, framework against known 3D structures of polymer models of murine and human loci, which can recapitulate Hi-C, GAM and SPRITE experiments and multiplexed fluorescence in situ hybridization (FISH) single-molecule conformations. We find that in silico Hi-C, GAM and SPRITE bulk data are faithful to the reference 3D structures whereas single-cell data reflect strong variability among single molecules. The minimal number of cells required in replicate experiments to return statistically similar contacts is different across the technologies, being lowest in SPRITE and highest in GAM under the same conditions. Noise-to-signal levels follow an inverse power law with detection efficiency and grow with genomic distance differently among the three methods, being lowest in GAM for genomic separations >1 Mb.
Identifiants
pubmed: 33963348
doi: 10.1038/s41592-021-01135-1
pii: 10.1038/s41592-021-01135-1
pmc: PMC8416658
doi:
Substances chimiques
Chromatin
0
Polymers
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
482-490Subventions
Organisme : NIDDK NIH HHS
ID : U54 DK107977
Pays : United States
Organisme : NHGRI NIH HHS
ID : UM1 HG011585
Pays : United States
Commentaires et corrections
Type : CommentIn
Type : ErratumIn
Références
Kempfer, R. & Pombo, A. Methods for mapping 3D chromosome architecture. Nat. Rev. Genet. 21, 207–226 (2019).
pubmed: 31848476
doi: 10.1038/s41576-019-0195-2
Lieberman-Aiden, E. et al. Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science 326, 289–293 (2009).
pubmed: 19815776
pmcid: 2858594
doi: 10.1126/science.1181369
Fullwood, M. J. et al. An oestrogen-receptor-α-bound human chromatin interactome. Nature 462, 58–64 (2009).
pubmed: 19890323
pmcid: 2774924
doi: 10.1038/nature08497
Rao, S. S. P. et al. A 3D map of the human genome at kilobase resolution reveals principles of chromatin looping. Cell 159, 1665–1680 (2014).
pubmed: 25497547
pmcid: 5635824
doi: 10.1016/j.cell.2014.11.021
Mumbach, M. R. et al. HiChIP: efficient and sensitive analysis of protein-directed genome architecture. Nat. Methods 13, 919–922 (2016).
pubmed: 27643841
pmcid: 5501173
doi: 10.1038/nmeth.3999
Oudelaar, A. M. et al. Single-allele chromatin interactions identify regulatory hubs in dynamic compartmentalized domains. Nat. Genet. 50, 1744–1751 (2018).
pubmed: 30374068
pmcid: 6265079
doi: 10.1038/s41588-018-0253-2
Hsieh, T. H. S. et al. Mapping nucleosome resolution chromosome folding in yeast by micro-C. Cell 162, 108–119 (2015).
pubmed: 26119342
pmcid: 4509605
doi: 10.1016/j.cell.2015.05.048
Krietenstein, N. et al. Ultrastructural details of mammalian chromosome architecture. Mol. Cell 78, 554–565 (2020).
pubmed: 32213324
pmcid: 7222625
doi: 10.1016/j.molcel.2020.03.003
Beagrie, R. A. et al. Complex multi-enhancer contacts captured by genome architecture mapping. Nature 543, 519–524 (2017).
pubmed: 28273065
pmcid: 5366070
doi: 10.1038/nature21411
Quinodoz, S. A. et al. Higher-order inter-chromosomal hubs shape 3D genome organization in the nucleus. Cell 174, 744–757 (2018).
pubmed: 29887377
pmcid: 6548320
doi: 10.1016/j.cell.2018.05.024
Bickmore, W. A. The spatial organization of the human genome. Annu. Rev. Genomics Hum. Genet. 14, 67–84 (2013).
pubmed: 23875797
doi: 10.1146/annurev-genom-091212-153515
Dekker, J. & Misteli, T. Long-range chromatin interactions. Cold Spring Harb. Perspect. Biol. 7, a019356 (2015).
pubmed: 26430217
pmcid: 4588061
doi: 10.1101/cshperspect.a019356
Pombo, A. & Dillon, N. Three-dimensional genome architecture: players and mechanisms. Nat. Rev. Mol. Cell Biol. 16, 245–257 (2015).
pubmed: 25757416
doi: 10.1038/nrm3965
Dekker, J. & Mirny, L. The 3D genome as moderator of chromosomal communication. Cell 164, 1110–1121 (2016).
pubmed: 26967279
pmcid: 4788811
doi: 10.1016/j.cell.2016.02.007
Dixon, J. R., Gorkin, D. U. & Ren, B. Chromatin domains: the unit of chromosome organization. Mol. Cell 62, 668–680 (2016).
pubmed: 27259200
pmcid: 5371509
doi: 10.1016/j.molcel.2016.05.018
Spielmann, M., Lupiáñez, D. G. & Mundlos, S. Structural variation in the 3D genome. Nat. Rev. Genet. 19, 453–467 (2018).
pubmed: 29692413
doi: 10.1038/s41576-018-0007-0
Finn, E. H. & Misteli, T. Molecular basis and biological function of variability in spatial genome organization. Science 365, eaaw9498 (2019).
pubmed: 31488662
pmcid: 7421438
doi: 10.1126/science.aaw9498
Nora, E. P. et al. Spatial partitioning of the regulatory landscape of the X-inactivation centre. Nature 485, 381–385 (2012).
pubmed: 22495304
pmcid: 3555144
doi: 10.1038/nature11049
Dixon, J. R. et al. Topological domains in mammalian genomes identified by analysis of chromatin interactions. Nature 485, 376–380 (2012).
pubmed: 22495300
pmcid: 3356448
doi: 10.1038/nature11082
Fraser, J. et al. Hierarchical folding and reorganization of chromosomes are linked to transcriptional changes in cellular differentiation. Mol. Syst. Biol. 11, 852 (2015).
pubmed: 26700852
pmcid: 4704492
doi: 10.15252/msb.20156492
Cattoni, D. I. et al. Single-cell absolute contact probability detection reveals chromosomes are organized by multiple low-frequency yet specific interactions. Nat. Commun. 8, 1753 (2017)..
Bintu, B. et al. Super-resolution chromatin tracing reveals domains and cooperative interactions in single cells. Science 362, eaau1783 (2018).
pubmed: 30361340
pmcid: 6535145
doi: 10.1126/science.aau1783
Cardozo Gizzi, A. M. et al. Microscopy-based chromosome conformation capture enables simultaneous visualization of genome organization and transcription in intact organisms. Mol. Cell 74, 212–222 (2019).
pubmed: 30795893
doi: 10.1016/j.molcel.2019.01.011
Finn, E. H. et al. Extensive heterogeneity and intrinsic variation in spatial genome organization. Cell 176, 1502–1515 (2019).
pubmed: 30799036
pmcid: 6408223
doi: 10.1016/j.cell.2019.01.020
Chiariello, A. M., Annunziatella, C., Bianco, S., Esposito, A. & Nicodemi, M. Polymer physics of chromosome large-scale 3D organisation. Sci. Rep. 6, 29775 (2016).
pubmed: 27405443
pmcid: 4942835
doi: 10.1038/srep29775
Bianco, S. et al. Modeling single-molecule conformations of the HoxD region in mouse embryonic stem and cortical neuronal cells. Cell Rep. 28, 1574–1583 (2019).
pubmed: 31390570
doi: 10.1016/j.celrep.2019.07.013
Bianco, S. et al. Polymer physics predicts the effects of structural variants on chromatin architecture. Nat. Genet. 50, 662–667 (2018).
pubmed: 29662163
doi: 10.1038/s41588-018-0098-8
Conte, M. et al. Polymer physics indicates chromatin folding variability across single-cells results from state degeneracy in phase separation. Nat. Commun. 11, 3289 (2020).
pubmed: 32620890
pmcid: 7335158
doi: 10.1038/s41467-020-17141-4
Lupiáñez, D. G. et al. Disruptions of topological chromatin domains cause pathogenic rewiring of gene–enhancer interactions. Cell 161, 1012–1025 (2015).
pubmed: 25959774
pmcid: 4791538
doi: 10.1016/j.cell.2015.04.004
Andrey, G. et al. A switch between topological domains underlies HoxD genes collinearity in mouse limbs. Science 340, 1234167 (2013).
Noordermeer, D. et al. The dynamic architecture of Hox gene clusters. Science 334, 222–225 (2011).
pubmed: 21998387
doi: 10.1126/science.1207194
Li, Q. et al. The three-dimensional genome organization of Drosophila melanogaster through data integration. Genome Biol. 18, 145 (2017).
pubmed: 28760140
pmcid: 5576134
doi: 10.1186/s13059-017-1264-5
Serra, F. et al. Automatic analysis and 3D-modelling of Hi-C data using TADbit reveals structural features of the fly chromatin colors. PLoS Comput. Biol. 13, e1005665 (2017).
pubmed: 28723903
pmcid: 5540598
doi: 10.1371/journal.pcbi.1005665
Nir, G. et al. Walking along chromosomes with super-resolution imaging, contact maps, and integrative modeling. PLoS Genet. 14, e1007872 (2018).
pubmed: 30586358
pmcid: 6324821
doi: 10.1371/journal.pgen.1007872
Lin, D., Bonora, G., Yardimci, G. G. & Noble, W. S. Computational methods for analyzing and modeling genome structure and organization. Wiley Interdiscip. Rev. Syst. Biol. Med. 11, e1435 (2018).
pubmed: 30022617
pmcid: 6294685
Tjong, H. et al. Population-based 3D genome structure analysis reveals driving forces in spatial genome organization. Proc. Natl Acad. Sci. USA 113, E1663–E1672 (2016).
pubmed: 26951677
pmcid: 4812752
doi: 10.1073/pnas.1512577113
Bohn, M. & Heermann, D. W. Diffusion-driven looping provides a consistent provides a consistent framework for chromatin organization. PLoS ONE 5, e12218 (2010).
pubmed: 20811620
pmcid: 2928267
doi: 10.1371/journal.pone.0012218
Barbieri, M. et al. Complexity of chromatin folding is captured by the strings and binders switch model. Proc. Natl Acad. Sci. USA 109, 16173–16178 (2012).
pubmed: 22988072
pmcid: 3479593
doi: 10.1073/pnas.1204799109
Brackley, C. A., Taylor, S., Papantonis, A., Cook, P. R. & Marenduzzo, D. Nonspecific bridging-induced attraction drives clustering of DNA-binding proteins and genome organization. Proc. Natl Acad. Sci. USA 110, E3605–E3611 (2013).
pubmed: 24003126
pmcid: 3780866
doi: 10.1073/pnas.1302950110
Jost, D., Carrivain, P., Cavalli, G. & Vaillant, C. Modeling epigenome folding: formation and dynamics of topologically associated chromatin domains. Nucleic Acids Res. 42, 9553–9561 (2014).
pubmed: 25092923
pmcid: 4150797
doi: 10.1093/nar/gku698
Sanborn, A. L. et al. Chromatin extrusion explains key features of loop and domain formation in wild-type and engineered genomes. Proc. Natl Acad. Sci. USA 112, E6456–E6465 (2015).
pubmed: 26499245
pmcid: 4664323
doi: 10.1073/pnas.1518552112
Fudenberg, G. et al. Formation of chromosomal domains by loop extrusion. Cell Rep. 15, 2038–2049 (2016).
pubmed: 27210764
pmcid: 4889513
doi: 10.1016/j.celrep.2016.04.085
Di Pierro, M., Zhang, B., Aiden, E. L., Wolynes, P. G. & Onuchic, J. N. Transferable model for chromosome architecture. Proc. Natl Acad. Sci. USA 113, 12168–12173 (2016).
pubmed: 27688758
pmcid: 5087044
doi: 10.1073/pnas.1613607113
Buckle, A., Brackley, C. A., Boyle, S., Marenduzzo, D. & Gilbert, N. Polymer simulations of heteromorphic chromatin predict the 3D folding of complex genomic loci. Mol. Cell 72, 786–797 (2018).
pubmed: 30344096
pmcid: 6242782
doi: 10.1016/j.molcel.2018.09.016
Fiorillo, L. et al. A modern challenge of polymer physics: novel ways to study, interpret, and reconstruct chromatin structure. Wiley Interdiscip. Rev. Comput. Mol. Sci. 10, e1454 (2019).
Shi, G., Liu, L., Hyeon, C. & Thirumalai, D. Interphase human chromosome exhibits out of equilibrium glassy dynamics. Nat. Commun. 9, 3161 (2018)..
Nicodemi, M. & Prisco, A. Thermodynamic pathways to genome spatial organization in the cell nucleus. Biophys. J. 96, 2168–2177 (2009).
pubmed: 19289043
pmcid: 2717292
doi: 10.1016/j.bpj.2008.12.3919
Fiorillo, L. et al. Inference of chromosome 3D structures from GAM data by a physics computational approach. Methods 181–182, 70–79 (2020).
pubmed: 31604121
doi: 10.1016/j.ymeth.2019.09.018
Barbieri, M. et al. Active and poised promoter states drive folding of the extended HoxB locus in mouse embryonic stem cells. Nat. Struct. Mol. Biol. 24, 515–524 (2017).
pubmed: 28436944
doi: 10.1038/nsmb.3402
Kragesteen, B. K. et al. Dynamic 3D chromatin architecture contributes to enhancer specificity and limb morphogenesis. Nat. Genet. 50, 1463–1473 (2018).
pubmed: 30262816
doi: 10.1038/s41588-018-0221-x
Yang, T. et al. HiCRep: assessing the reproducibility of Hi-C data using a stratum-adjusted correlation coefficient. Genome Res. 27, 1939–1949 (2017).
pubmed: 28855260
pmcid: 5668950
doi: 10.1101/gr.220640.117
Dekker, J. et al. The 4D nucleome project. Nature 549, 219–226 (2017).
pubmed: 28905911
pmcid: 5617335
doi: 10.1038/nature23884
Rao, S. S. P. et al. Cohesin loss eliminates all loop domains. Cell 171, 305–320 (2017).
pubmed: 28985562
pmcid: 5846482
doi: 10.1016/j.cell.2017.09.026
Stevens, T. J. et al. 3D structures of individual mammalian genomes studied by single-cell Hi-C. Nature 544, 59–64 (2017).
pubmed: 28289288
pmcid: 5385134
doi: 10.1038/nature21429
Nagano, T. et al. Single-cell Hi-C reveals cell-to-cell variability in chromosome structure. Nature 502, 59–64 (2013).
doi: 10.1038/nature12593
pubmed: 24067610
Nagano, T. et al. Cell-cycle dynamics of chromosomal organization at single-cell resolution. Nature 547, 61–67 (2017).
pubmed: 28682332
pmcid: 5567812
doi: 10.1038/nature23001
Flyamer, I. M. et al. Single-nucleus Hi-C reveals unique chromatin reorganization at oocyte-to-zygote transition. Nature 544, 110–114 (2017).
pubmed: 28355183
pmcid: 5639698
doi: 10.1038/nature21711
Ramani, V. et al. Massively multiplex single-cell Hi-C. Nat. Methods 14, 263–266 (2017).
pubmed: 28135255
pmcid: 5330809
doi: 10.1038/nmeth.4155
Lando, D., Stevens, T. J., Basu, S. & Laue, E. D. Calculation of 3D genome structures for comparison of chromosome conformation capture experiments with microscopy: an evaluation of single-cell Hi-C protocols. Nucleus 9, 190–201 (2018).
pubmed: 29431585
pmcid: 5883084
doi: 10.1080/19491034.2018.1438799
Díaz, N. et al. Chromatin conformation analysis of primary patient tissue using a low input Hi-C method. Nat. Commun. 9, 4938 (2018)..
Plimpton, S. Fast parallel algorithms for short-range molecular dynamics. J. Comput. Phys. 117, 1–19 (1995).
doi: 10.1006/jcph.1995.1039
Kremer, K. & Grest, G. S. Dynamics of entangled linear polymer melts: a molecular-dynamics simulation. J. Chem. Phys. 92, 5057–5086 (1990).
doi: 10.1063/1.458541
Gribnau, J., Hochedlinger, K., Hata, K., Li, E. & Jaenisch, R. Asynchronous replication timing of imprinted loci is independent of DNA methylation, but consistent with differential subnuclear localization. Genes Dev. 17, 759–773 (2003).
pubmed: 12651894
pmcid: 196021
doi: 10.1101/gad.1059603
Rosa, A. & Everaers, R. Structure and dynamics of interphase chromosomes. PLoS Comput. Biol. 4, e1000153 (2008).
pubmed: 18725929
pmcid: 2515109
doi: 10.1371/journal.pcbi.1000153
Bystricky, K., Heun, P., Gehlen, L., Langowski, J. & Gasser, S. M. Long-range compaction and flexibility of interphase chromatin in budding yeast analyzed by high-resolution imaging techniques. Proc. Natl Acad. Sci. USA 101, 16495–16500 (2004).
pubmed: 15545610
pmcid: 534505
doi: 10.1073/pnas.0402766101
Gavrilov, A., Razin, S. V. & Cavalli, G. In vivo formaldehyde cross-linking: it is time for black box analysis. Brief. Funct. Genomics 14, 163–165 (2015).
pubmed: 25241225
doi: 10.1093/bfgp/elu037
Ester, M., Kriegel, H.-P., Sander, J. & Xu, X. A density-based algorithm for discovering clusters in large spatial databases with noise. In Proc. 2nd International Conference on Knowledge Discovery and Data Mining (eds Simoudis, E. et al.) 226–231 (AAAI Press, 1996).
Tahara, M. et al. Cell diameter measurements obtained with a handheld cell counter could be used as a surrogate marker of G2/M arrest and apoptosis in colon cancer cell lines exposed to SN-38. Biochem. Biophys. Res. Commun. 434, 753–759 (2013).
pubmed: 23583407
doi: 10.1016/j.bbrc.2013.03.128
Yang, F. et al. Dielectrophoretic separation of colorectal cancer cells. Biomicrofluidics 4, 13204 (2010).
pubmed: 20644667
doi: 10.1063/1.3279786