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Hi-C-constrained physical models of human chromosomes recover functionally-related properties of genome organization

Marco Di Stefano, Jonas Paulsen, Tonje G. Lien, Eivind Hovig & Cristian Micheletti

Scientific Reports 6, Article number: 35985 (2016)


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Biological physics Computational biophysics

Received: 06 June 2016 Accepted: 30 September 2016 Published online: 27 October 2016


Abstract

Combining genome-wide structural models with phenomenological data is at the forefront of efforts to understand the organizational principles regulating the human genome. Here, we use chromosome-chromosome contact data as knowledge-based constraints for large-scale three-dimensional models of the human diploid genome. The resulting models remain minimally entangled and acquire several functional features that are observed in vivo and that were never used as input for the model. We find, for instance, that gene-rich, active regions are drawn towards the nuclear center, while gene poor and lamina associated domains are pushed to the periphery. These and other properties persist upon adding local contact constraints, suggesting their compatibility with non-local constraints for the genome organization. The results show that suitable combinations of data analysis and physical modelling can expose the unexpectedly rich functionally-related properties implicit in chromosome-chromosome contact data. Specific directions are suggested for further developments based on combining experimental data analysis and genomic structural modelling.

Additional Information

How to cite this article: Di Stefano, M. et al. Hi-C-constrained physical models of human chromosomes recover functionally-related properties of genome organization. Sci. Rep. 6, 35985; doi: 10.1038/srep35985 (2016).

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Acknowledgements

We are grateful to Marc A. Marti-Renom, Davide Baù, and Angelo Rosa for useful discussions. This work was supported by The Norwegian Cancer Society [grant 71220-PR-2006-0433]; the Research Council of Norway; and the Italian Ministry of Education [grant PRIN 2010HXAW77].

Author information

Author notes

Marco Di Stefano & Jonas Paulsen

These authors contributed equally to this work.

Affiliations

SISSA, International School for Advanced Studies, Trieste, I-34136, Italy

Marco Di Stefano & Cristian Micheletti

Institute of Basic Medical Sciences, University of Oslo, Oslo, 0317, Norway

Jonas Paulsen

University of Oslo, Department of Mathematics, Oslo, 0316, Norway

Tonje G. Lien

Institute for Cancer Research, Oslo University Hospital, Department of Tumor Biology, Oslo, 0310, Norway

Eivind Hovig

University of Oslo, Department of Informatics, Oslo, 0316, Norway

Eivind Hovig

Institute of Cancer Genetics and Informatics, Oslo, 0310, Norway

Eivind Hovig

Contributions

M.D.S., J.P., E.H. and C.M. conceived and designed the experiments; J.P. and T.G.L. performed statistical analyses; M.D.S. performed the molecular dynamics simulations; M.D.S. and J.P. analysed the data and implemented the analysis tools; M.D.S., J.P., E.H. and C.M. wrote the paper.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Marco Di Stefano.