Statistical confidence estimation for Hi-C data reveals regulatory chromatin contacts

Abstract

Our current understanding of how DNA is packed in the nucleus is most accurate at the fine scale of individual nucleosomes and at the large scale of chromosome territories. However, accurate modeling of DNA architecture at the intermediate scale of~50 kb-10 Mb is crucial for identifying functional interactions among regulatory elements and their target promoters. We describe a method, Fit-Hi-C, that assigns statistical confidence estimates to mid-range intra-chromosomal contacts by jointly modeling the random polymer looping effect and previously observed technical biases in Hi-C data sets. We demonstrate that our proposed approach computes accurate empirical null models of contact probability without any distribution assumption, corrects for binning artifacts, and provides improved statistical power relative to a previously described method. High-confidence contacts identified by Fit-Hi-C preferentially link expressed gene promoters to active enhancers identified by chromatin signatures in human embryonic stem cells (ESCs), capture 77% of RNA polymerase II-mediated enhancer-promoter interactions identified using ChIA-PET in mouse ESCs, and confirm previously validated, cell line-specific interactions in mouse cortex cells. We observe that insulators and heterochromatin regions are hubs for high-confidence contacts, while promoters and strong enhancers are involved in fewer contacts. We also observe that binding peaks of master pluripotency factors such as NANOG and POU5F1 are highly enriched in high-confidence contacts for human ESCs. Furthermore, we show that pairs of loci linked by high-confidence contacts exhibit similar replication timing in human and mouse ESCs and preferentially lie within the boundaries of topological domains for human and mouse cell lines.

GITAR: an Open Source Tool for Analysis and Visualization of Hi-C Data

“…However, besides correcting biases and generating contact maps, most of them do not provide the entire pipeline to pre-process the raw data (downloadable files) or to compute topological domain coordinates. To call significant chromosome contacts CHiCAGO [18], Fit-Hi-C [19] and HMRFBayesHiC [20] are available, while chromoR and diffHiC [21] can be used to compare spatial interactions between cell lines. For topological domain analysis, HiCseg [22], HubPredictor [23] and TADtree [24] serve to calculate the domain coordinates.…”

Parallel Exploration of the Nuclear Chromosome Conformation with NuChart-II

“…The HiTC package proposes a list of options to define the appropriate data visualization, such as contrast, color or counts trimming. Fit-Hi-C [13] assigns statistical confidence estimates to mid-range, intra-chromosomal contacts by jointly modelling the random polymer looping effect and previously observed technical biases in Hi-C data sets.…”

Mapping of long-range chromatin interactions by proximity ligation-assisted ChIP-seq

“…PLAC-seq covered more regulatory elements, such as promoters and distal DNase I hypersensitive sites (DHSs), than ChIA-PET (Supplementary information, Figure S1J). As a reference, we performed in situ Hi-C with the mouse ES cell line and collected nearly 1.2 billion paired-end sequencing reads, from which we identified 68 781 long-range chromatin interactions (FDR < 0.01) using FitHiC [13]. Compared with chromatin interactions identified by in situ Hi-C, PLAC-seq is 8 times more sensitive than ChIA-PET and also more accurate ( Figure 1F).…”

“…Additionally, the PLAC-seq experiments generated longrange chromatin contacts that were highly reproducible between biological replicates (Pearson correlation > 0.90; Supplementary information, Figure S1E). To identify long-range chromatin interactions, we used 'FitHiC' [13] to analyze the combined datasets from two biological replicates (Supplementary information, Data S1). A total of 72 074, 273 145, and 155 545 chromatin loops (FDR < 0.01) were identified from the Pol II, H3K4me3, and H3K27ac PLAC-seq experiments, respectively.…”