Estimating DNA-DNA interaction frequency from Hi-C data at restriction-fragment resolution

Cameron, Christopher J. F.; Dostie, Josée; Blanchette, Mathieu

doi:10.1101/377523

Cited by 4 publications

(4 citation statements)

References 56 publications

(46 reference statements)

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“…Based on the valid pairs which specify the number of reads for each interaction anchor pair, we binned the anchor coordinates to 8-fragment resolution and summarized the reads at this resolution. Reads were normalized to a distance-normalized interaction frequency (IFnorm) 73,74 according to:…”

Section: Compartment Analysismentioning

confidence: 99%

“…Original implementation of HiCCUPS was described in 73 . We used the fast C + + implementation described in HIFI 74 to speed up computation, here setting HIFI to use the fixed resolution binning approach: -method=fixed and -fragmentPerBin=1. Significant loops were generated by comparing score(i,j) to those of distance-controlled randomly permuted IF matrix.…”

Section: Compartment Analysismentioning

confidence: 99%

“…Visualization of interaction matrix. Visualization of the IF-norm interaction matrix was provided by HIFI package 74 available at https://github.com/BlanchetteLab/ HIFI. We used the function plotHIFIoutput.py with vmin = 0 and vmax = 1.5.…”

Section: Compartment Analysismentioning

confidence: 99%

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Inner nuclear protein Matrin-3 coordinates cell differentiation by stabilizing chromatin architecture

Uyan

Kai

et al. 2021

Nat Commun

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Precise control of gene expression during differentiation relies on the interplay of chromatin and nuclear structure. Despite an established contribution of nuclear membrane proteins to developmental gene regulation, little is known regarding the role of inner nuclear proteins. Here we demonstrate that loss of the nuclear scaffolding protein Matrin-3 (Matr3) in erythroid cells leads to morphological and gene expression changes characteristic of accelerated maturation, as well as broad alterations in chromatin organization similar to those accompanying differentiation. Matr3 protein interacts with CTCF and the cohesin complex, and its loss perturbs their occupancy at a subset of sites. Destabilization of CTCF and cohesin binding correlates with altered transcription and accelerated differentiation. This association is conserved in embryonic stem cells. Our findings indicate Matr3 negatively affects cell fate transitions and demonstrate that a critical inner nuclear protein impacts occupancy of architectural factors, culminating in broad effects on chromatin organization and cell differentiation.

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Section: Compartment Analysismentioning

confidence: 99%

Section: Compartment Analysismentioning

confidence: 99%

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Inner nuclear protein Matrin-3 coordinates cell differentiation by stabilizing chromatin architecture

Uyan

Kai

et al. 2021

Nat Commun

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“…While this was shown to effectively smooth noisy Hi-C data up to a 10kb resolution, it was not shown to be effective at finer resolutions. Other strategies have been proposed to enhance the resolution of contact maps genome-wide directly from Hi-C data (Carron et al 2019;Cameron et al 2018), but they are inherently limited to achieving at best restriction fragment length resolution. Other methods have been proposed that incorporate TF binding and epigenomic data to predict Hi-C data directly (Farré et al 2018;S.…”

Section: Introductionmentioning

confidence: 99%

An Integrative Approach for Fine-Mapping Chromatin Interactions

Jaroszewicz

Ernst

2019

Preprint

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Chromatin interactions play an important role in genome architecture and regulation. The Hi-C assay generates such interactions maps genome-wide, but at relatively low resolutions (e.g., 5-25kb), which is substantially larger than the resolution of transcription factor binding sites or open chromatin sites that are potential sources of such interactions. To predict the sources of Hi-C identified interactions at a high resolution (e.g., 100bp), we developed a computational method that integrates ChIP-seq data of transcription factors and histone marks and DNase-seq data. Our method, c-SCNN, uses this data to first train a Siamese Convolutional Neural Network (SCNN) to discriminate between called Hi-C interactions and non-interactions. c-SCNN then predicts the high-resolution source of each Hi-C interaction using a feature attribution method. We show these predictions recover original Hi-C peaks after extending them to be coarser. We also show c-SCNN predictions enrich for evolutionarily conserved bases, eQTLs, and CTCF motifs, supporting their biological significance. c-SCNN provides an approach for analyzing important aspects of genome architecture and regulation at a higher resolution than previously possible.c-SCNN software is available on GitHub (https://github.com/ernstlab/X-SCNN).

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Reference panel guided topological structure annotation of Hi-C data

Zhang

Blanchette

2022

Nat Commun

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Accurately annotating topological structures (e.g., loops and topologically associating domains) from Hi-C data is critical for understanding the role of 3D genome organization in gene regulation. This is a challenging task, especially at high resolution, in part due to the limited sequencing coverage of Hi-C data. Current approaches focus on the analysis of individual Hi-C data sets of interest, without taking advantage of the facts that (i) several hundred Hi-C contact maps are publicly available, and (ii) the vast majority of topological structures are conserved across multiple cell types. Here, we present RefHiC, an attention-based deep learning framework that uses a reference panel of Hi-C datasets to facilitate topological structure annotation from a given study sample. We compare RefHiC against tools that do not use reference samples and find that RefHiC outperforms other programs at both topological associating domain and loop annotation across different cell types, species, and sequencing depths.

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Estimating DNA-DNA interaction frequency from Hi-C data at restriction-fragment resolution

Cited by 4 publications

References 56 publications

Inner nuclear protein Matrin-3 coordinates cell differentiation by stabilizing chromatin architecture

Inner nuclear protein Matrin-3 coordinates cell differentiation by stabilizing chromatin architecture

An Integrative Approach for Fine-Mapping Chromatin Interactions

Reference panel guided topological structure annotation of Hi-C data

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