scholarly journals Predicting three-dimensional genome organization with chromatin states

2018 ◽  
Author(s):  
Yifeng Qi ◽  
Bin Zhang
Keyword(s):  
Genome Organization ◽  
De Novo ◽  
Three Dimensional ◽  
Super Resolution ◽  
Cell Types ◽  
Quantitative Agreement ◽  
Chromosome Conformation ◽  
Chromatin Loops ◽  
Chromatin Folding ◽  
Super Resolution Microscopy

ABSTRACTWe introduce a computational model to simulate chromatin structure and dynamics. Starting from one-dimensional genomics and epigenomics data that are available for hundreds of cell types, this model enables de novo prediction of chromatin structures at five-kilo-base resolution. Simulated chromatin structures recapitulate known features of genome organization, including the formation of chromatin loops, topologically associating domains (TADs) and compartments, and are in quantitative agreement with chromosome conformation capture experiments and super-resolution microscopy measurements. Detailed characterization of the predicted structural ensemble reveals the dynamical flexibility of chromatin loops and the presence of cross-talk among neighboring TADs. Analysis of the model’s energy function uncovers distinct mechanisms for chromatin folding at various length scales.

A sequence-based deep learning approach to predict CTCF-mediated chromatin loop

2021 ◽  
Author(s):  
Hao Lv ◽  
Fu-Ying Dao ◽  
Hasan Zulfiqar ◽  
Wei Su ◽  
Hui Ding ◽  
...  
Keyword(s):  
Computational Models ◽  
Genomic Sequence ◽  
Three Dimensional ◽  
Scoring Function ◽  
Cell Types ◽  
Frequency Component ◽  
Chromatin Interaction ◽  
Chromosome Conformation ◽  
Chromatin Loops ◽  
3D Architecture

Abstract Three-dimensional (3D) architecture of the chromosomes is of crucial importance for transcription regulation and DNA replication. Various high-throughput chromosome conformation capture-based methods have revealed that CTCF-mediated chromatin loops are a major component of 3D architecture. However, CTCF-mediated chromatin loops are cell type specific, and most chromatin interaction capture techniques are time-consuming and labor-intensive, which restricts their usage on a very large number of cell types. Genomic sequence-based computational models are sophisticated enough to capture important features of chromatin architecture and help to identify chromatin loops. In this work, we develop Deep-loop, a convolutional neural network model, to integrate k-tuple nucleotide frequency component, nucleotide pair spectrum encoding, position conservation, position scoring function and natural vector features for the prediction of chromatin loops. By a series of examination based on cross-validation, Deep-loop shows excellent performance in the identification of the chromatin loops from different cell types. The source code of Deep-loop is freely available at the repository https://github.com/linDing-group/Deep-loop.

scholarly journals HP1 drives de novo 3D genome reorganization in early Drosophila embryos

Nature ◽  
2021 ◽  
Author(s):  
Fides Zenk ◽  
Yinxiu Zhan ◽  
Pavel Kos ◽  
Eva Löser ◽  
Nazerke Atinbayeva ◽  
...  
Keyword(s):  
Genome Organization ◽  
Molecular Mechanisms ◽  
High Throughput Sequencing ◽  
De Novo ◽  
Early Embryo ◽  
Heterochromatin Protein ◽  
Chromosome Conformation ◽  
3D Genome ◽  
Genome Reorganization

AbstractFundamental features of 3D genome organization are established de novo in the early embryo, including clustering of pericentromeric regions, the folding of chromosome arms and the segregation of chromosomes into active (A-) and inactive (B-) compartments. However, the molecular mechanisms that drive de novo organization remain unknown1,2. Here, by combining chromosome conformation capture (Hi-C), chromatin immunoprecipitation with high-throughput sequencing (ChIP–seq), 3D DNA fluorescence in situ hybridization (3D DNA FISH) and polymer simulations, we show that heterochromatin protein 1a (HP1a) is essential for de novo 3D genome organization during Drosophila early development. The binding of HP1a at pericentromeric heterochromatin is required to establish clustering of pericentromeric regions. Moreover, HP1a binding within chromosome arms is responsible for overall chromosome folding and has an important role in the formation of B-compartment regions. However, depletion of HP1a does not affect the A-compartment, which suggests that a different molecular mechanism segregates active chromosome regions. Our work identifies HP1a as an epigenetic regulator that is involved in establishing the global structure of the genome in the early embryo.

Cubic spline-based depth-dependent localization of mitochondria–endoplasmic reticulum contacts by three-dimensional light-sheet super-resolution microscopy

The Analyst ◽  
2021 ◽  
Author(s):  
Yucheng Sun ◽  
Seungah Lee ◽  
Seong Ho Kang
Keyword(s):  
Endoplasmic Reticulum ◽  
Calcium Homeostasis ◽  
Three Dimensional ◽  
Super Resolution ◽  
Light Sheet ◽  
Cubic Spline ◽  
Contact Distance ◽  
Super Resolution Microscopy

The contact distance between mitochondria (Mito) and endoplasmic reticulum (ER) has received considerable attention owing to their crucial function in maintaining lipid and calcium homeostasis. Herein, cubic spline algorithm-based depth-dependent...

scholarly journals Technologies to study spatial genome organization: beyond 3C

2019 ◽  
Author(s):  
Nadine Übelmesser ◽  
Argyris Papantonis
Keyword(s):  
Genome Organization ◽  
Nuclear Organization ◽  
Three Dimensional ◽  
Nuclear Space ◽  
Chromosome Conformation ◽  
Novel Variants ◽  
Cell Processes ◽  
Systematic Biases ◽  
And Function ◽  
Spatial Genome Organization

Abstract The way that chromatin is organized in three-dimensional nuclear space is now acknowledged as a factor critical for the major cell processes, like transcription, replication and cell division. Researchers have been armed with new molecular and imaging technologies to study this structure-to-function link of genomes, spearheaded by the introduction of the ‘chromosome conformation capture’ technology more than a decade ago. However, this technology is not without shortcomings, and novel variants and orthogonal approaches are being developed to overcome these. As a result, the field of nuclear organization is constantly fueled by methods of increasing resolution and/or throughput that strive to eliminate systematic biases and increase precision. In this review, we attempt to highlight the most recent advances in technology that promise to provide novel insights on how chromosomes fold and function.

DeepYY1: a deep learning approach to identify YY1-mediated chromatin loops

2020 ◽  
Author(s):  
Fu-Ying Dao ◽  
Hao Lv ◽  
Dan Zhang ◽  
Zi-Mei Zhang ◽  
Li Liu ◽  
...  
Keyword(s):  
Deep Learning ◽  
Computational Methods ◽  
Learning Algorithm ◽  
Cell Types ◽  
Chromatin Loops ◽  
Deep Learning Algorithm ◽  
Dna Elements ◽  
Chromatin Folding ◽  
User Friendly ◽  
Different Cell Types

Abstract The protein Yin Yang 1 (YY1) could form dimers that facilitate the interaction between active enhancers and promoter-proximal elements. YY1-mediated enhancer–promoter interaction is the general feature of mammalian gene control. Recently, some computational methods have been developed to characterize the interactions between DNA elements by elucidating important features of chromatin folding; however, no computational methods have been developed for identifying the YY1-mediated chromatin loops. In this study, we developed a deep learning algorithm named DeepYY1 based on word2vec to determine whether a pair of YY1 motifs would form a loop. The proposed models showed a high prediction performance (AUCs$\ge$0.93) on both training datasets and testing datasets in different cell types, demonstrating that DeepYY1 has an excellent performance in the identification of the YY1-mediated chromatin loops. Our study also suggested that sequences play an important role in the formation of YY1-mediated chromatin loops. Furthermore, we briefly discussed the distribution of the replication origin site in the loops. Finally, a user-friendly web server was established, and it can be freely accessed at http://lin-group.cn/server/DeepYY1.

scholarly journals The three-dimensional genome organization of Drosophila melanogaster through data integration

2017 ◽  
Vol 18 (1) ◽  
Author(s):  
Qingjiao Li ◽  
Harianto Tjong ◽  
Xiao Li ◽  
Ke Gong ◽  
Xianghong Jasmine Zhou ◽  
...  
Keyword(s):  
Drosophila Melanogaster ◽  
Data Integration ◽  
Genome Organization ◽  
Genome Structure ◽  
Three Dimensional ◽  
Structural Features ◽  
Embryonic Cells ◽  
Data Types ◽  
Chromosome Conformation ◽  
Topological Domains

Abstract Background Genome structures are dynamic and non-randomly organized in the nucleus of higher eukaryotes. To maximize the accuracy and coverage of three-dimensional genome structural models, it is important to integrate all available sources of experimental information about a genome’s organization. It remains a major challenge to integrate such data from various complementary experimental methods. Here, we present an approach for data integration to determine a population of complete three-dimensional genome structures that are statistically consistent with data from both genome-wide chromosome conformation capture (Hi-C) and lamina-DamID experiments. Results Our structures resolve the genome at the resolution of topological domains, and reproduce simultaneously both sets of experimental data. Importantly, this data deconvolution framework allows for structural heterogeneity between cells, and hence accounts for the expected plasticity of genome structures. As a case study we choose Drosophila melanogaster embryonic cells, for which both data types are available. Our three-dimensional genome structures have strong predictive power for structural features not directly visible in the initial data sets, and reproduce experimental hallmarks of the D. melanogaster genome organization from independent and our own imaging experiments. Also they reveal a number of new insights about genome organization and its functional relevance, including the preferred locations of heterochromatic satellites of different chromosomes, and observations about homologous pairing that cannot be directly observed in the original Hi-C or lamina-DamID data. Conclusions Our approach allows systematic integration of Hi-C and lamina-DamID data for complete three-dimensional genome structure calculation, while also explicitly considering genome structural variability.

scholarly journals Small-Molecule Labeling of Live Cell Surfaces for Three-Dimensional Super-Resolution Microscopy

2014 ◽  
Vol 136 (40) ◽  
pp. 14003-14006 ◽  
Author(s):  
Marissa K. Lee ◽  
Prabin Rai ◽  
Jarrod Williams ◽  
Robert J. Twieg ◽  
W. E. Moerner
Keyword(s):  
Small Molecule ◽  
Three Dimensional ◽  
Super Resolution ◽  
Live Cell ◽  
Cell Surfaces ◽  
Super Resolution Microscopy
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