HiC-DC+ enables systematic 3D interaction calls and differential analysis for Hi-C and HiChIP

Şahin, Merve; Wong, Wai Lin; Zhan, Yingqian A.; Deynze, Kinsey Van; Koche, Richard P.; Leslie, Christina

doi:10.1038/s41467-021-23749-x

Cited by 28 publications

(32 citation statements)

References 35 publications

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“…Specifically, a permutation test was used to compare the number of co‐expressed (> 1 TPM in a specific cell type) enhancer‐promoter pairs versus that of background sets generated by sampling from all tag clusters. Differential interactions between enhancer‐promoter pairs identified by ABC scores were investigated using R library HiCDCPlus v0.99.12 (Sahin et al , 2021) using default parameters at 10 kb resolution. The degree of coordinated differential promoter interaction and differential expression was quantified through the application of RRHO2 v1.0 (Cahill et al , 2018) to gene lists ranked by DESeq2 test statistics; for promoters involved in multiple ABC E‐P pairs, the mean test statistic was used for ranking.…”

Section: Methodsmentioning

confidence: 99%

Nucleome programming is required for the foundation of totipotency in mammalian germline development

Nagano

Yokobayashi

et al. 2022

The EMBO Journal

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Germ cells are unique in engendering totipotency, yet the mechanisms underlying this capacity remain elusive. Here, we perform comprehensive and in-depth nucleome analysis of mouse germcell development in vitro, encompassing pluripotent precursors, primordial germ cells (PGCs) before and after epigenetic reprogramming, and spermatogonia/spermatogonial stem cells (SSCs). Although epigenetic reprogramming, including genome-wide DNA de-methylation, creates broadly open chromatin with abundant enhancer-like signatures, the augmented chromatin insulation safeguards transcriptional fidelity. These insulatory constraints are then erased en masse for spermatogonial development. Notably, despite distinguishing epigenetic programming, including global DNA re-methylation, the PGCs-to-spermatogonia/SSCs development entails further euchromatization. This accompanies substantial erasure of lamina-associated domains, generating spermatogonia/SSCs with a minimal peripheral attachment of chromatin except for pericentromeres-an architecture conserved in primates. Accordingly, faulty nucleome maturation, including persistent insulation and improper euchromatization, leads to impaired spermatogenic potential. Given that PGCs after epigenetic reprogramming serve as oogenic progenitors as well, our findings elucidate a principle for the nucleome programming that creates gametogenic progenitors in both sexes, defining a basis for nuclear totipotency.

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Section: Methodsmentioning

confidence: 99%

Nucleome programming is required for the foundation of totipotency in mammalian germline development

Nagano

Yokobayashi

et al. 2022

The EMBO Journal

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“…In order to evaluate the performance of MaxHiC, we performed a comprehensive benchmarking between MaxHiC and Hi-C significant interactions callers (SIC) including GOTHiC, Fit-Hi-C, Fit-Hi-C2, HiCDC+ [ 14 ], and CHiCAGO (for capture Hi-C only). We also compared the performance of MaxHiC with Hi-C loop callers including HiCCUPS [ 5 ], Peakachu [ 7 ], and Mustache [ 8 ].…”

Section: Resultsmentioning

confidence: 99%

MaxHiC: A robust background correction model to identify biologically relevant chromatin interactions in Hi-C and capture Hi-C experiments

et al. 2022

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Hi-C is a genome-wide chromosome conformation capture technology that detects interactions between pairs of genomic regions and exploits higher order chromatin structures. Conceptually Hi-C data counts interaction frequencies between every position in the genome and every other position. Biologically functional interactions are expected to occur more frequently than transient background and artefactual interactions. To identify biologically relevant interactions, several background models that take biases such as distance, GC content and mappability into account have been proposed. Here we introduce MaxHiC, a background correction tool that deals with these complex biases and robustly identifies statistically significant interactions in both Hi-C and capture Hi-C experiments. MaxHiC uses a negative binomial distribution model and a maximum likelihood technique to correct biases in both Hi-C and capture Hi-C libraries. We systematically benchmark MaxHiC against major Hi-C background correction tools including Hi-C significant interaction callers (SIC) and Hi-C loop callers using published Hi-C, capture Hi-C, and Micro-C datasets. Our results demonstrate that 1) Interacting regions identified by MaxHiC have significantly greater levels of overlap with known regulatory features (e.g. active chromatin histone marks, CTCF binding sites, DNase sensitivity) and also disease-associated genome-wide association SNPs than those identified by currently existing models, 2) the pairs of interacting regions are more likely to be linked by eQTL pairs and 3) more likely to link known regulatory features including known functional enhancer-promoter pairs validated by CRISPRi than any of the existing methods. We also demonstrate that interactions between different genomic region types have distinct distance distributions only revealed by MaxHiC. MaxHiC is publicly available as a python package for the analysis of Hi-C, capture Hi-C and Micro-C data.

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“…Raw and ICE-normalized contact matrices were prepared with HiC-Pro (Servant et al, 2015). ICE-normalized and condition-merged HiC-Pro matrices were converted to Juicer .hic files for resolutions 10 Kb and 100 Kb using a wrapper for the Juicer tools Pre command in the HiC-DC+ Bioconductor package (Durand et al, 2016; Sahin et al, 2021).…”

Section: Star Methodsmentioning

confidence: 99%

“…Significant loops (q-value <= 0.05) and differential loops (log2FC cut-off = 1, p-value < 0.05) across conditions were identified using HiC-DC+ with raw HiC-Pro matrices and bed files of two AS replicates and two GFP replicates at 10 Kb resolution (Sahin et al ., 2021). To filter biases in denser genomic regions in close proximity and noise in sparser regions that are more far apart, only loops between 50 Kb and 2 Mb were called.…”

Section: Star Methodsmentioning

confidence: 99%

Role of theEGR2promoter antisense RNA in modulating chromatin accessibility and spatial genome organization

Moreno

Karambizi

Hwang

et al. 2022

Preprint

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The EGR2 promoter antisense RNA (AS-RNA) recruits chromatin remodeling complexes to inhibit EGR2 transcription following peripheral nerve injury. Here we show that the EGR2-AS-RNA modulates chromatin accessibility and serves as scaffold for two distinct histone modification complexes. It binds to EZH2 and WDR5 and enables coordinate targeting of H3K27me3 and H3K4me3 to promoters of EGR2and C-JUN. Expression of the AS-RNA results in reorganization of the global chromatin landscape and quantitative changes in loop formation and in contact frequency at domain boundaries exhibiting enrichment for AP-1 genes. In addition, the EGR2-AS-RNA induces changes in hierarchical TADs and increases transcriptional activity on an inter-TAD loop between a super-enhancer regulatory hub and the promoter of mTOR. Our results show that the EGR2-AS-RNA may serve as regulator of coordinate chromatin remodeling and spatial genome organization to regulate cellular plasticity-associated transcription in Schwann cells.

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HiC-DC+ enables systematic 3D interaction calls and differential analysis for Hi-C and HiChIP

Cited by 28 publications

References 35 publications

Nucleome programming is required for the foundation of totipotency in mammalian germline development

Nucleome programming is required for the foundation of totipotency in mammalian germline development

MaxHiC: A robust background correction model to identify biologically relevant chromatin interactions in Hi-C and capture Hi-C experiments

Role of theEGR2promoter antisense RNA in modulating chromatin accessibility and spatial genome organization

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