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bioRxiv · 10.1101/2020.10.13.338004

Connecting high-resolution 3D chromatin organization with epigenomics

Feng, F.·Yao, Y.·Wang, X. Q. D.·Zhang, X.·Liu, J.
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Abstract

The resolution of chromatin conformation capture technologies keeps increasing, and the recent nucleosome resolution chromatin contact maps allow us to explore how fine-scale 3D chromatin organization is related to epigenomic states in human cells. Using publicly available Micro-C datasets, we have developed a deep learning model, CAESAR, to learn a mapping function from epigenomic features to 3D chromatin organization. The model accurately predicts fine-scale structures, such as short-range chromatin loops and stripes, that Hi-C fails to detect. With existing epigenomic datasets from ENCODE and Roadmap Epigenomics Project, we successfully imputed high-resolution 3D chromatin contact maps for 91 human tissues and cell lines. In the imputed high-resolution contact maps, we identified the spatial interactions between genes and their experimentally validated regulatory elements, demonstrating CAESARs potential in coupling transcriptional regulation with 3D chromatin organization at high resolution.

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Feng, F., Yao, Y., Wang, X. Q. D., Zhang, X., Liu, J.. 2020-10-14. Connecting high-resolution 3D chromatin organization with epigenomics. https://doi.org/10.1101/2020.10.13.338004

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