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bioRxiv · 10.1101/215871

Predicting CTCF-mediated chromatin interactions by integrating genomic and epigenomic features

Kai, Y.·Andricovich, J.·Zeng, Z.·Zhu, J.·Tzatsos, A.·Peng, W.
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Abstract

The CCCTC-binding zinc finger protein (CTCF)-mediated network of long-range chromatin interactions is important for genome organization and function. Although this network has been considered largely invariant, we found that it exhibits extensive cell-type-specific interactions that contribute to cell identity. Here we present Lollipop--a machine-learning framework--which predicts CTCF-mediated long-range interactions using genomic and epigenomic features. Using ChIA-PET data as benchmark, we demonstrated that Lollipop accurately predicts CTCF-mediated chromatin interactions both within and across cell-types, and outperforms other methods based only on CTCF motif orientation. Predictions were confirmed computationally and experimentally by Chromatin Conformation Capture (3C). Moreover, our approach reveals novel determinants of CTCF-mediated chromatin wiring, such as gene expression within the loops. Our study contributes to a better understanding about the underlying principles of CTCF-mediated chromatin interactions and their impact on gene expression.

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Kai, Y., Andricovich, J., Zeng, Z., Zhu, J., Tzatsos, A., Peng, W.. 2017-12-01. Predicting CTCF-mediated chromatin interactions by integrating genomic and epigenomic features. https://doi.org/10.1101/215871

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