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Comparison of the Hi-C, GAM and SPRITE methods using polymer models of chromatin

Abstract

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.

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Fig. 1: In silico Hi-C, SPRITE and GAM average contact maps match experimental data.
Fig. 2: Model 3D structures are a bona fide representation of chromatin conformations in single cells.
Fig. 3: Bulk Hi-C, SPRITE and GAM data are faithful overall to average 3D distances.
Fig. 4: Stochasticity of single-cell contact maps reflects the intrinsic variability of single-molecule 3D conformations.
Fig. 5: The number of cells required for replicate reproducibility differs among Hi-C, SPRITE and GAM.
Fig. 6: Noise-to-signal levels vary differently with genomic distance in Hi-C, SPRITE and GAM.

Data availability

Published Hi-C, SPRITE, GAM and microscopy data used for analysis are available at the referenced papers. The new GAM data from the F123 cell line are available on the 4D Nucleome data portal under accession no. 4DNFIFBSQ1EO.

Code availability

The codes used in our work are based on standard, publicly available software packages, as detailed in Methods. Molecular dynamics simulations use LAMMPS, v.30july2016. Analyses and plots were produced with the Anaconda package v.4.7.12. HiCRep correlations were computed with R v.3.5.1. 3D structure visualizations were produced with POV-Ray, v.3.7. The algorithms for simulation of Hi-C, SPRITE, GAM and SLICE in silico use standard routines, such as DBSCAN, and are described in full detail in Methods. The Hi-C, SPRITE and GAM algorithms are available at https://github.com/fmusella/In-silico_Hi-C_GAM_SPRITE.

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Acknowledgements

We received no specific funding for this work. M.N. acknowledges support from CINECA ISCRA (nos. HP10CYFPS5 and HP10CRTY8P), Einstein BIH Fellowship Award (nos. EVF-BIH-2016 and 2019), Regione Campania SATIN Project 2018–2020 and computer resources from INFN, CINECA, ENEA CRESCO/ENEAGRID and Scope/ReCAS/Ibisco at the University of Naples. A. Pombo thanks the Helmholtz Association (Germany) for support. M.N. and A. Pombo acknowledge support from the National Institutes of Health Common Fund 4D Nucleome Program (grant nos. 1U54DK107977-01 and 1UM1HG011585-01) and the EU H2020 Marie Curie ITN (no. 813282). I.I.-A. acknowledges support from the Federation of European Biochemical Societies (FEBS Long-Term Fellowship). A.M.C. and S.B. acknowledge support from CINECA ISCRA (grant no. HP10CCZ4KN).

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M.N. designed the project with input from A. Pombo and A. Prisco. L.F., F.M. and M.C. developed the modeling. L.F. and F.M. ran computer simulations and performed data analyses with help from M.C., A.M.C., S.B., A.E. and A.A. R.K., A.K. and I.I.-A. produced and normalized the GAM dataset. M.N., L.F., F.M., A. Pombo and A. Prisco wrote the manuscript, with input from all the authors.

Corresponding author

Correspondence to Mario Nicodemi.

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Competing interests

A. Pombo and M.N. hold a patent on ‘Genome Architecture Mapping’: Pombo, A., Edwards, P. A. W., Nicodemi, M., Beagrie, R. A. & Scialdone, A. Patent no. PCT/EP2015/079413 (2015).

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Peer review information Nature Methods thanks Zhijun Duan and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Lei Tang was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

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Fiorillo, L., Musella, F., Conte, M. et al. Comparison of the Hi-C, GAM and SPRITE methods using polymer models of chromatin. Nat Methods 18, 482–490 (2021). https://doi.org/10.1038/s41592-021-01135-1

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