T-ChroNet: Time-aware chromatin network reconstruction to detect dynamic regulatory programs in longitudinal epigenetic dataset.

Abstract

Networks are widely applied to investigate relationships among individual components of complex biological systems. Recent application of biological networks, such as gene co-expression networks and gene regulatory networks, has been instrumental to define principles of transcriptional modulation in development and disease. However, computational methods that can embed the activity of cis-regulatory elements (CRE) into a network are still limited. Capturing temporal CRE activity within a network could help reveal regulatory programs involved in cell fate commitment and disease development. To address this, we present T-ChroNet (Time-aware Chromatin Network), a network-based method that models CRE as nodes and their temporal co-accessibility as edges. Through the detection of CRE sharing similar accessibility patterns over time, T-ChroNet allows the inference of putative upstream regulators and downstream biological pathways. We applied T-ChroNet to temporally-resolved CRE datasets, from both human and mouse, including chromatin accessibility (ATAC-seq) and histone post-translational modifications (H3K27ac ChIP-seq). T-ChroNet successfully recovered known regulators and enriched pathways for both modalities and species, while also uncovering novel putative factors and mechanisms regulating cell identity, organ development and disease progression.