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Identification of chromatin loops from Hi-C interaction matrices by CTCF-CTCF topology classification

View ORCID ProfileSilvia Galan, View ORCID ProfileFrançois Serra, View ORCID ProfileMarc A. Marti-Renom
doi: https://doi.org/10.1101/2020.07.21.214585
Silvia Galan
1CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Baldiri i Reixac 4, 08028 Barcelona, Spain
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François Serra
1CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Baldiri i Reixac 4, 08028 Barcelona, Spain
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  • For correspondence: martirenom@cnag.crg.eu francois.serra@bsc.es
Marc A. Marti-Renom
1CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Baldiri i Reixac 4, 08028 Barcelona, Spain
2Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Dr. Aiguader 88, 08003 Barcelona, Spain
3Universitat Pompeu Fabra (UPF), 08002 Barcelona, Spain
4ICREA, Pg. Lluís Companys 23, 08010 Barcelona, Spain
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  • For correspondence: martirenom@cnag.crg.eu francois.serra@bsc.es
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ABSTRACT

Genome-wide profiling of long-range interactions has revealed that the CCCTC-Binding factor (CTCF) often anchors chromatin loops and is enriched at boundaries of the so-called Topologically Associating Domains, which suggests that CTCF is essential in the 3D organization of chromatin. However, the systematic topological classification of pairwise CTCF-CTCF interactions has not been yet explored.

Here, we developed a computational pipeline able to classify all CTCF-CTCF pairs according to their chromatin interactions from Hi-C experiments. The interaction profiles of all CTCF-CTCF pairs were further structurally clustered using self-organizing feature maps and their functionality characterized by their epigenetic states. The resulting clusters were then input to a convolutional neural network aiming at the de novo detecting chromatin loops from Hi-C interaction matrices.

Our new method, called LOOPbit, is able to automatically detect significant interactions with a higher proportion of enhancer-promoter loops compared to any other callers. Our highly specific loop caller adds a new layer of detail to the link between chromatin structure and function.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted February 15, 2021.
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Identification of chromatin loops from Hi-C interaction matrices by CTCF-CTCF topology classification
Silvia Galan, François Serra, Marc A. Marti-Renom
bioRxiv 2020.07.21.214585; doi: https://doi.org/10.1101/2020.07.21.214585
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Identification of chromatin loops from Hi-C interaction matrices by CTCF-CTCF topology classification
Silvia Galan, François Serra, Marc A. Marti-Renom
bioRxiv 2020.07.21.214585; doi: https://doi.org/10.1101/2020.07.21.214585

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