Quantitative prediction of enhancer-promoter interactions

Abstract Recent experimental and computational efforts provided large datasets describing 3-dimensional organization of mouse and human genomes and showed interconnection between expression profile, epigenetic status and spatial interactions of loci. These interconnections were utilized to infer spatial organization of chromatin, including enhancer-promoter contacts, from 1-dimensional epigenetic marks. Here we showed that predictive power of some of these algorithms is overestimated due to peculiar properties of biological data. We proposed an alternative approach, which gives high-quality predictions of chromatin interactions using only information about gene expression and CTCF-binding. Using multiple metrics, we confirmed that our algorithm could efficiently predict 3-dimensional architecture of normal and rearranged genomes.