Analysis of differential genomic interactions between experimental conditions in capture Hi-C data: Sharing data between neighbouring restriction fragments

Author(s): Marco Geigges,Charlotte Soneson,Filippo M Rijli,Michael B Stadler

Affiliation(s): Friedrich Miescher Institute for Biomedical Research and SIB Swiss Institute of Bioinformatics, Basel, Switzerland



Capture Hi-C (CHi-C) is a sequencing-based method to study three-dimensional chromosomal interactions of pre-selected genomic regions like promoters with other genomic regions. For example, it is widely used to identify interactions of promoters with regulatory elements. Several bioinformatic tools are available and well-established for the quality control, the processing of sequencing reads and the identification of significant chromosomal interactions in CHi-C data. However, the detection of statistically significant differential interactions between conditions remains a challenge due to the sparsity of the data especially at long interaction distances. As the CHi-C signal is usually not restricted to a single restriction fragment but spread over surrounding fragments, it is a common approach to combine reads across several neighbouring restriction fragments to increase power for differential signal detection. Usually, the reads from a fixed number of neighbouring fragments around each interacting fragment are pooled for this purpose. However, this approach does not consider the signal strength over background at the surrounding fragments and may lead to redundant use of data or a suboptimal loss of resolution. To overcome this problem, we developed a new approach of aggregating CHi-C signal from neighbouring restriction fragments in a data-driven way. We focus on restriction fragments that contain a significant signal over background and use them to build a hierarchical tree of interacting fragments based on their genomic position. Differential interaction analysis is then performed on this tree-based representation of the data. This novel approach allows to reliably detect interaction differences between conditions when signal strength at individual restriction fragments might not be strong enough.