Recent developments in whole-genome mapping approaches for the chromatin interactome (such as Hi-C) have offered new insights into 3D genome organization. However, our knowledge of the evolutionary patterns of 3D genome structures in mammalian species remains surprisingly limited. In particular, there are no existing phylogenetic-model based methods to analyze chromatin interactions as continuous features across different species. Here we develop a new probabilistic model, named phylogenetic hidden Markov random field (Phylo-HMRF), to identify evolutionary patterns of 3D genome structures based on multi-species Hi-C data by jointly utilizing spatial constraints among genomic loci and continuous-trait evolutionary models. The effectiveness of Phylo-HMRF is demonstrated in both simulation evaluation and application to real Hi-C data. We used Phylo-HMRF to uncover cross-species 3D genome patterns based on Hi-C data from the same cell type in four primate species (human, chimpanzee, bonobo, and gorilla). The identified evolutionary patterns of 3D genome organization correlate with features of genome structure and function, including long-range interactions, topologically-associating domains (TADs), and replication timing patterns. This work provides a new framework that utilizes general types of spatial constraints to identify evolutionary patterns of continuous genomic features and has the potential to reveal the evolutionary principles of 3D genome organization.
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