Comprehensive mapping of long-range interactions reveals folding principles of the human genome.
Erez Lieberman Aiden,Nynke L. van Berkum,Louise Williams,Maxim Imakaev,Tobias Ragoczy,Tobias Ragoczy,Agnes Telling,Agnes Telling,Ido Amit,Bryan R. Lajoie,Peter J. Sabo,Michael O. Dorschner,Richard Sandstrom,Bradley E. Bernstein,Bradley E. Bernstein,Michaël Bender,Mark Groudine,Mark Groudine,Andreas Gnirke,John A. Stamatoyannopoulos,Leonid A. Mirny,Eric S. Lander,Eric S. Lander,Job Dekker +23 more
TLDR
Hi-C is described, a method that probes the three-dimensional architecture of whole genomes by coupling proximity-based ligation with massively parallel sequencing and demonstrates the power of Hi-C to map the dynamic conformations of entire genomes.Abstract:
We describe Hi-C, a method that probes the three-dimensional architecture of whole genomes by coupling proximity-based ligation with massively parallel sequencing. We constructed spatial proximity maps of the human genome with Hi-C at a resolution of 1 megabase. These maps confirm the presence of chromosome territories and the spatial proximity of small, gene-rich chromosomes. We identified an additional level of genome organization that is characterized by the spatial segregation of open and closed chromatin to form two genome-wide compartments. At the megabase scale, the chromatin conformation is consistent with a fractal globule, a knot-free, polymer conformation that enables maximally dense packing while preserving the ability to easily fold and unfold any genomic locus. The fractal globule is distinct from the more commonly used globular equilibrium model. Our results demonstrate the power of Hi-C to map the dynamic conformations of whole genomes.read more
Citations
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Journal ArticleDOI
Multi-scale coding of genomic information: From DNA sequence to genome structure and function
Alain Arneodo,Alain Arneodo,Cédric Vaillant,Cédric Vaillant,Benjamin Audit,Benjamin Audit,Françoise Argoul,Françoise Argoul,Yves d'Aubenton-Carafa,Claude Thermes +9 more
TL;DR: This review shows that when using concepts, methodologies, numerical and experimental techniques coming from statistical mechanics and nonlinear physics combined with wavelet-based multi-scale signal processing, this work is able to decipher the multi- scale sequence encoding of chromatin condensation–decondensation mechanisms that play a fundamental role in regulating many molecular processes involved in nuclear functions.
Journal ArticleDOI
Nuclear mechanics in disease.
TL;DR: Findings illustrate that the nucleus is tightly integrated into the surrounding cellular structure and changes in nuclear structure and composition are highly relevant to normal development and physiology and can contribute to many human diseases, such as muscular dystrophy, dilated cardiomyopathy, (premature) aging, and cancer.
Journal ArticleDOI
The epigenetic basis of cellular heterogeneity.
Benjamin Carter,Keji Zhao +1 more
TL;DR: Advances in single-cell epigenomic profiling methods are enabling high-resolution mapping of chromatin states in individual cells, providing evidence that variations in different aspects of Chromatin organization collectively define gene expression heterogeneity among otherwise highly similar cells.
Journal ArticleDOI
Dynamic epigenomic landscapes during early lineage specification in mouse embryos.
Yu Zhang,Yunlong Xiang,Qiangzong Yin,Zhenhai Du,Xu Peng,Qiujun Wang,Miguel Fidalgo,Weikun Xia,Yuanyuan Li,Zhen-Ao Zhao,Wen-Hao Zhang,Jing Ma,Feng Xu,Jianlong Wang,Lei Li,Wei Xie +15 more
TL;DR: Transcriptome, DNA methylome and Hi-C profiling of peri- and post-implantation mouse cell lineages identified allele- and lineage-specific methylation patterns that led to differential methylation between embryonic and extraembryonic lineages at promoters of lineage regulators, gene bodies, and DNA-methylation valleys.
Journal ArticleDOI
Enhancing Hi-C data resolution with deep convolutional neural network HiCPlus
TL;DR: It is demonstrated that HiCPlus can impute interaction matrices highly similar to the original ones, while only using 1/16 of the original sequencing reads, and it is shown that the models learned from one cell type can be applied to make predictions in other cell or tissue types.
References
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