Chicdiff: a computational pipeline for detecting differential chromosomal interactions in Capture Hi-C data

Cairns, Jonathan; Orchard, William R.; Malysheva, Valeriya; Spivakov, Mikhail

doi:10.1093/bioinformatics/btz450

Cited by 22 publications

(22 citation statements)

References 15 publications

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“…Guided by the exploratory observations from cluster analysis, we next sought to define subsets of promoter interactions that are lost, maintained, or gained upon cohesin and CTCF depletion formally and with high confidence. For this, we additionally took advantage of our recently developed differential calling pipeline for PCHi-C data, Chicdiff ( Cairns et al., 2019 ). Integrating Chicdiff and clustering results, we defined 36,174 lost, 12,978 maintained, and 2,484 gained interactions upon cohesin depletion ( Figures 2 A–2C and S1 C).…”

Section: Resultsmentioning

confidence: 99%

“…Chicdiff ( Cairns et al., 2019 ) was used to detect differential promoter interactions between SCC1-AID control (Aux-) and depleted (Aux+) samples, and between CTCF-AID control (Aux-) and depleted (Aux+) samples. Chicdiff uses DESeq2 ( Love et al., 2014 ) differential interaction calling with custom feature selection, normalization and multiple testing correction procedures.…”

Section: Methodsmentioning

confidence: 99%

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Cohesin-Dependent and -Independent Mechanisms Mediate Chromosomal Contacts between Promoters and Enhancers

et al. 2020

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Summary It is currently assumed that 3D chromosomal organization plays a central role in transcriptional control. However, depletion of cohesin and CTCF affects the steady-state levels of only a minority of transcripts. Here, we use high-resolution Capture Hi-C to interrogate the dynamics of chromosomal contacts of all annotated human gene promoters upon degradation of cohesin and CTCF . We show that a majority of promoter-anchored contacts are lost in these conditions, but many contacts with distinct properties are maintained, and some new ones are gained. The rewiring of contacts between promoters and active enhancers upon cohesin degradation associates with rapid changes in target gene transcription as detected by SLAM sequencing (SLAM-seq). These results provide a mechanistic explanation for the limited, but consistent, effects of cohesin and CTCF depletion on steady-state transcription and suggest the existence of both cohesin-dependent and -independent mechanisms of enhancer-promoter pairing.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Cohesin-Dependent and -Independent Mechanisms Mediate Chromosomal Contacts between Promoters and Enhancers

et al. 2020

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“…We examined the statistically significant differential interactions in PCHC data between WT and DKO cells with Chicdiff [ 42 ]. We identified 131 differential interactions between MEF WT and DKO cells (Additional file 2 : Fig.…”

Section: Resultsmentioning

confidence: 99%

Multiple epigenetic factors co-localize with HMGN proteins in A-compartment chromatin

Zhu

Postnikov

et al. 2022

Epigenetics & Chromatin

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Background Nucleosomal binding proteins, HMGN, is a family of chromatin architectural proteins that are expressed in all vertebrate nuclei. Although previous studies have discovered that HMGN proteins have important roles in gene regulation and chromatin accessibility, whether and how HMGN proteins affect higher order chromatin status remains unknown. Results We examined the roles that HMGN1 and HMGN2 proteins play in higher order chromatin structures in three different cell types. We interrogated data generated in situ, using several techniques, including Hi–C, Promoter Capture Hi–C, ChIP-seq, and ChIP–MS. Our results show that HMGN proteins occupy the A compartment in the 3D nucleus space. In particular, HMGN proteins occupy genomic regions involved in cell-type-specific long-range promoter–enhancer interactions. Interestingly, depletion of HMGN proteins in the three different cell types does not cause structural changes in higher order chromatin, i.e., in topologically associated domains (TADs) and in A/B compartment scores. Using ChIP-seq combined with mass spectrometry, we discovered protein partners that are directly associated with or neighbors of HMGNs on nucleosomes. Conclusions We determined how HMGN chromatin architectural proteins are positioned within a 3D nucleus space, including the identification of their binding partners in mononucleosomes. Our research indicates that HMGN proteins localize to active chromatin compartments but do not have major effects on 3D higher order chromatin structure and that their binding to chromatin is not dependent on specific protein partners.

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“…In order to detect enrichment of features in the interactions obtained with CHiCAGO for each cell type, narrowPeak bed files of H3K4me3 and H3K27ac were obtained. Finally, Chicdiff v0.6 (27) was used to detect differential interactions between different conditions: CD4 + T cells vs CD14 + monocytes; SSc patients vs healthy controls CD4 + T cells; and SSc patients vs healthy controls CD14 + monocytes. For each comparison, only those interactions with CHiCAGO score > 5 in at least one condition were included in differential analysis.…”

Section: Promoter Capture Hi-c Sequencing and Processingmentioning

confidence: 99%

Functional genomics in primary T cells and monocytes identifies mechanisms by which genetic susceptibility loci influence systemic sclerosis risk

González‐Serna

Shi

Kerick

et al. 2022

Preprint

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ObjectivesSystemic sclerosis (SSc) is a complex autoimmune disease with a strong genetic component. However, most of the causal genes and variants are still unknown. The challenge in the post-GWAS era is to use functional genomics to translate genetic findings into patients’ benefit, particularly in disease-relevant cell types.MethodsPromoter capture Hi-C (pCHi-C) and RNA sequencing experiments were performed in a total of 30 samples corresponding to CD4+ T cells and CD14+ monocytes (15 samples each) from SSc patients and healthy controls to link SSc-associated variants with their target genes, followed by differential expression and differential interaction analyses between both cell types. We also aimed to identify potential drugs that could be repurposed for its use in SSc.ResultsWe linked SSc-associated loci to 39 new potential target genes, confirming 7 previously assigned genes. We highlight novel causal genes, such as CXCR5 as the most probable candidate gene for the DDX6 locus. Some SSc confirmed genes such as IRF8, STAT4, or CD247 interestingly showed cell type specific interactions. We also identified 15 potential drug targets already in use in other similar immune-mediated diseases that could be repurposed for SSc treatment. Furthermore, we observed that interactions are directly related with the expression of important genes implicated in cell type specific pathways.ConclusionsOur study reveals potential causal genes for SSc-associated loci, some of them acting in a cell type specific manner, suggesting novel biological mechanisms that may mediate SSc pathogenesis.

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Chicdiff: a computational pipeline for detecting differential chromosomal interactions in Capture Hi-C data

Cited by 22 publications

References 15 publications

Cohesin-Dependent and -Independent Mechanisms Mediate Chromosomal Contacts between Promoters and Enhancers

Cohesin-Dependent and -Independent Mechanisms Mediate Chromosomal Contacts between Promoters and Enhancers

Multiple epigenetic factors co-localize with HMGN proteins in A-compartment chromatin

Functional genomics in primary T cells and monocytes identifies mechanisms by which genetic susceptibility loci influence systemic sclerosis risk

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