Person:

Huang, Jialiang

Genome-wide mapping of three dimensional chromatin organization is an important yet technically challenging task. To aid experimental effort and to understand the determinants of long-range chromatin interactions, we have developed a computational model integrating Hi-C and histone mark ChIP-seq data to predict two important features of chromatin organization: chromatin interaction hubs and topologically associated domain (TAD) boundaries. Our model accurately and robustly predicts these features across datasets and cell types. Cell-type specific histone mark information is required for prediction of chromatin interaction hubs but not for TAD boundaries. Our predictions provide a useful guide for the exploration of chromatin organization. Electronic supplementary material The online version of this article (doi:10.1186/s13059-015-0740-z) contains supplementary material, which is available to authorized users.

Chromatin-state analysis is widely applied in the studies of development and diseases. However, existing methods operate at a single length scale, and therefore cannot distinguish large domains from isolated elements of the same type. To overcome this limitation, we present a hierarchical hidden Markov model, diHMM, to systematically annotate chromatin states at multiple length scales. We apply diHMM to analyse a public ChIP-seq data set. diHMM not only accurately captures nucleosome-level information, but identifies domain-level states that vary in nucleosome-level state composition, spatial distribution and functionality. The domain-level states recapitulate known patterns such as super-enhancers, bivalent promoters and Polycomb repressed regions, and identify additional patterns whose biological functions are not yet characterized. By integrating chromatin-state information with gene expression and Hi-C data, we identify context-dependent functions of nucleosome-level states. Thus, diHMM provides a powerful tool for investigating the role of higher-order chromatin structure in gene regulation.