GOntact: using chromatin contacts to infer Gene Ontology enrichments for cis-regulatory elements

Abstract

While the genomic positions and the patterns of activity of enhancer elements can now be efficiently determined, predicting their target genes remains a difficult task. Although chromatin conformation capture data has revealed numerous long-range regulatory interactions between genes and enhancers, enhancer target genes are still traditionally inferred based on genomic proximity. This approach is at the basis of GREAT, a widely used tool for analyzing the functional significance of sets of cis-regulatory elements. Here, we propose a new tool, named GOntact, which infers regulatory relationships using promoter-capture Hi-C (PCHi-C) data and uses these predictions to derive Gene Ontology enrichments for sets of cis-regulatory elements. We apply GOntact on enhancer and PCHi-C data from human and mouse and show that it generates functional annotations that are coherent with the patterns of activity of enhancers. We find that there is substantial overlap between functional predictions obtained with GREAT and GOntact but that each method can yield unique testable hypotheses, reflecting the underlying differences in target gene assignment. With the increasing availability of high-resolution chromatin contact data, we believe that GOntact can provide better-informed functional predictions for cis-regulatory elements.