Visualizing the genome in high resolution challenges our textbook understanding

Abstract

The relationship between the 4D folding of the genome and its function is an outstanding question in biology. A range of methods that probe the folding of the genome in space and time with unprecedented resolution have been developed. These methods, including chromosome conformation capture and high-resolution light and electron microscopy, are shedding new light on genome architecture and function. Here, we review the emerging picture of genome organization revealed by super-resolution and live-cell imaging. We compare and contrast population-based chromosome conformation capture approaches and imaging-based approaches and highlight future challenges.

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Fig. 1: Artist’s rendering of the different levels of genome organization and the methodologies that have identified each organizational unit.
Fig. 2: Super-resolution imaging of histone and DNA organization.
Fig. 3: Artist’s rendering of the methods for visualizing specific genomic sites.

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Acknowledgements

This work was supported by the University of Pennsylvania Epigenetics Pilot Award (to M.L.), the Center for Engineering and Mechanobiology (CEMB), an NSF Science and Technology Center Pilot Award under grant agreement CMMI 15-48571 (to M.L.), a Linda Pechenik Montague Investigator Award (to M.L.), the European Union’s Horizon 2020 Research and Innovation Programme (CellViewer No 686637 to M.L. and M.P.C.), Ministerio de Ciencia e Innovación, grant BFU2017-86760-P (AEI/FEDER, UE), and an AGAUR grant from Secretaria d’Universitats i Recerca del Departament d’Empresa i Coneixement de la Generalitat de Catalunya (2017 SGR 689 to M.P.C.). We acknowledge the support of the Spanish Ministry of Science and Innovation to the EMBL partnership, the Centro de Excelencia Severo Ochoa and the CERCA Programme / Generalitat de Catalunya.

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Correspondence to Melike Lakadamyali.

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Lakadamyali, M., Cosma, M.P. Visualizing the genome in high resolution challenges our textbook understanding. Nat Methods (2020). https://doi.org/10.1038/s41592-020-0758-3

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