Predicting CTCF-mediated Chromatin Interactions by Integrating Genomic and Epigenomic Features

Overview

Journal Nat Commun

Specialty Biology

Date 2018 Oct 13

PMID 30310060

Citations 27

Authors

Yan Kai

Jaclyn Andricovich

Zhouhao Zeng

Jun Zhu

Alexandros Tzatsos

Weiqun Peng

Affiliations

Soon will be listed here.

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 find 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 demonstrate 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 are confirmed computationally and experimentally by Chromatin Conformation Capture (3C). Moreover, our approach identifies other 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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