Inference of multi-enhancer interactions in T lymphocytes using Hi-Cociety

Abstracts Three-dimensional (3D) enhancer communities are key regulators of gene expression, shaping cell fate decisions and contributing to disease pathogenesis. Assays such as H3K27ac HiChIP have been used to map enhancer–enhancer interactions and define enhancer communities; however, their reliance on antibody-based enrichment restricts scalability and cross-cell-type applicability. In contrast, Hi-C provides an unbiased, genome-wide view of chromatin architecture but lacks direct annotation of regulatory elements, limiting its utility for enhancer-focused analyses. To bridge this gap, we introduce Hi-Cociety—a graph-based computational framework and accompanying R package that infers 3D enhancer communities directly from Hi-C data, without relying on histone modification or chromatin accessibility measurements. Hi-Cociety constructs a network of significant interactions and applies clustering algorithms to define chromatin interaction modules. Applying Hi-Cociety to Hi-C measurements in T lymphocytes, we identified highly connected modules enriched for active transcription, chromatin accessibility, and histone acetylation. Notably, modules identified in T cells pinpoint critical genes central to T cell biology. Hi-Cociety also detects cell-type-specific differences in chromatin organization, highlighting dynamic regulatory rewiring across T cell states. Our findings underscore the importance of network properties— connectivity, transitivity, and centrality—in shaping gene regulation through 3D genome organization. Hi-Cociety provides a scalable and versatile tool for mapping enhancer communities at scale, advancing our understanding of immune cell identity and the regulatory logic encoded in 3D chromatin structure. Competing Interest Statement The authors have declared no competing interest.