A generalizable Hi-C foundation model for chromatin architecture, single-cell and multiomics analysis across species.

Authors

Xiao Wang, Yuanyuan Zhang, Suhita Ray, Anupama Jha, Tangqi Fang, Shengqi Hang, Sergei Doulatov, William S Noble, Sheng Wang

Published in

Nature methods. Jun 15, 2026. Epub Jun 15, 2026.

Abstract

Nuclear DNA is organized into a three-dimensional (3D) structure that impacts critical cellular processes. However, the integrative analysis of 3D structure (measured by high-throughput chromosome conformation capture (Hi-C)) and associated epigenomic regulation (for example, assay for transposase-accessible chromatin using sequencing (ATAC-seq) and chromatin immunoprecipitation followed by sequencing (ChIP-seq)) remains challenging due to the differences in data format, resolution and analytical pipelines. Here we propose HiCFoundation, a foundation model trained on massive Hi-C data for integrative analysis linking chromatin structure to downstream regulatory function. The model achieves state-of-the-art performance and generalizability across species on various 3D genome analysis, including reproducibility analysis, resolution enhancement and loop detection. Additionally, HiCFoundation can predict various epigenomic activities from Hi-C to reveal how 3D structure links to regulatory function. Finally, HiCFoundation can easily adapt to single-cell Hi-C data. HiCFoundation thus offers a general, interpretable framework for studying the 3D genome and its functional roles across cell types and species.

PMID:
42298067
Bibliographic data and abstract were imported from PubMed on 16 Jun 2026.

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