scholarly journals In silico prediction of high-resolution Hi-C interaction matrices

2018 ◽  
Author(s):  
Shilu Zhang ◽  
Deborah Chasman ◽  
Sara Knaack ◽  
Sushmita Roy
Keyword(s):  
High Resolution ◽  
Cell Lines ◽  
Regulatory Protein ◽  
Three Dimensional ◽  
Predictive Performance ◽  
Computational Prediction ◽  
Range Interaction ◽  
Novel Approach ◽  
Sequence Elements ◽  
Topologically Associated Domains

AbstractThe three-dimensional organization of the genome plays an important role in gene regulation by enabling distal sequence elements to control the expression level of genes hundreds of kilobases away. Hi-C is a powerful genome-wide technique to measure the contact count of pairs of genomic loci needed to study three-dimensional organization. Due to experimental costs high resolution Hi-C datasets are available only for a handful of cell lines. Computational prediction of Hi-C contact counts can offer a scalable and inexpensive approach to examine three-dimensional genome organization across many cellular contexts. Here we present HiC-Reg, a novel approach to predict contact counts from one-dimensional regulatory signals such as epigenetic marks and regulatory protein binding. HiC-Reg exploits the signal from the region spanning two interacting regions and from across multiple cell lines to generalize to new contexts. Using existing feature importance measures and a new matrix factorization based approach, we found CTCF and chromatin marks, especially repressive and elongation marks, as important for predictive performance. Predicted counts from HiC-Reg identify topologically associated domains as well as significant interactions that are enriched for CTCF bi-directional motifs and agree well with interactions identified from complementary long-range interaction assays. Taken together, HiC-Reg provides a powerful framework to generate high-resolution profiles of contact counts that can be used to study individual locus level interactions as well as higher-order organizational units of the genome.

scholarly journals In silico prediction of high-resolution Hi-C interaction matrices

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Shilu Zhang ◽  
Deborah Chasman ◽  
Sara Knaack ◽  
Sushmita Roy
Keyword(s):  
High Resolution ◽  
Genome Organization ◽  
Three Dimensional ◽  
Predictive Performance ◽  
Computational Prediction ◽  
3D Genome ◽  
Genome Wide ◽  
Binding Factor ◽  
Sequence Elements ◽  
Individual Locus

AbstractThe three-dimensional (3D) organization of the genome plays an important role in gene regulation bringing distal sequence elements in 3D proximity to genes hundreds of kilobases away. Hi-C is a powerful genome-wide technique to study 3D genome organization. Owing to experimental costs, high resolution Hi-C datasets are limited to a few cell lines. Computational prediction of Hi-C counts can offer a scalable and inexpensive approach to examine 3D genome organization across multiple cellular contexts. Here we present HiC-Reg, an approach to predict contact counts from one-dimensional regulatory signals. HiC-Reg predictions identify topologically associating domains and significant interactions that are enriched for CCCTC-binding factor (CTCF) bidirectional motifs and interactions identified from complementary sources. CTCF and chromatin marks, especially repressive and elongation marks, are most important for HiC-Reg’s predictive performance. Taken together, HiC-Reg provides a powerful framework to generate high-resolution profiles of contact counts that can be used to study individual locus level interactions and higher-order organizational units of the genome.

scholarly journals Identification of the conserved long non-coding RNAs in myogenesis

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Anupam Bhattacharya ◽  
Simang Champramary ◽  
Tanya Tripathi ◽  
Debajit Thakur ◽  
Ilya Ioshikhes ◽  
...  
Keyword(s):  
Gene Regulation ◽  
Muscle Development ◽  
Three Dimensional ◽  
C2c12 Cells ◽  
Mouse Muscle ◽  
Rna Molecules ◽  
Expression Of Genes ◽  
Novel Approach ◽  
Non Coding Rna ◽  
Topologically Associated Domains

Abstract Background Our understanding of genome regulation is ever-evolving with the continuous discovery of new modes of gene regulation, and transcriptomic studies of mammalian genomes have revealed the presence of a considerable population of non-coding RNA molecules among the transcripts expressed. One such non-coding RNA molecule is long non-coding RNA (lncRNA). However, the function of lncRNAs in gene regulation is not well understood; moreover, finding conserved lncRNA across species is a challenging task. Therefore, we propose a novel approach to identify conserved lncRNAs and functionally annotate these molecules. Results In this study, we exploited existing myogenic transcriptome data and identified conserved lncRNAs in mice and humans. We identified the lncRNAs expressing differentially between the early and later stages of muscle development. Differential expression of these lncRNAs was confirmed experimentally in cultured mouse muscle C2C12 cells. We utilized the three-dimensional architecture of the genome and identified topologically associated domains for these lncRNAs. Additionally, we correlated the expression of genes in domains for functional annotation of these trans-lncRNAs in myogenesis. Using this approach, we identified conserved lncRNAs in myogenesis and functionally annotated them. Conclusions With this novel approach, we identified the conserved lncRNAs in myogenesis in humans and mice and functionally annotated them. The method identified a large number of lncRNAs are involved in myogenesis. Further studies are required to investigate the reason for the conservation of the lncRNAs in human and mouse while their sequences are dissimilar. Our approach can be used to identify novel lncRNAs conserved in different species and functionally annotated them.

High-Resolution Seismic Hazard Analysis in a Complex Geological Configuration: The Case of the Sulmona Basin in Central Italy

2014 ◽  
Vol 30 (4) ◽  
pp. 1801-1824 ◽  
Author(s):  
Manuela Villani ◽  
Ezio Faccioli ◽  
Mario Ordaz ◽  
Marco Stupazzini
Keyword(s):  
High Resolution ◽  
Seismic Hazard ◽  
Ground Motion ◽  
Hazard Analysis ◽  
Near Field ◽  
Central Italy ◽  
Three Dimensional ◽  
Spectral Element ◽  
Seismic Wave Propagation ◽  
Novel Approach

This work proposes a novel approach for probabilistic seismic hazard analyses (PSHA) in the near field of active earthquake faults, in which deterministically computed ground motion scenarios, replacing empirically predicted ground motion values, are introduced. In fact, the databases of most ground motion prediction equations (GMPEs) tend to be insufficiently constrained at short distances and data may only partially account for the rupture process, seismic wave propagation and three-dimensional (3-D) complex configurations. Hence, herein, 3-D numerical simulations of a Mw = 6.4 earthquake rupture of the Sulmona fault in Central Italy, are carried out through the spectral element code GeoELSE ( f < 2.5 Hz), and the results are introduced in a PSHA, exploiting the capabilities of CRISIS2008 code. The SH results obtained highlight the combined effects of site, basin, and topographic features, and provide a “high-resolution” representation of the hazard in the Sulmona Basin, particularly at long periods. Such representation is expected to be more realistic than those based simply on a GMPE.

Visualization and stereological characterization of individual rat lung acini by high-resolution X-ray tomographic microscopy

2013 ◽  
Vol 115 (9) ◽  
pp. 1379-1387 ◽  
Author(s):  
David Haberthür ◽  
Sébastien F. Barré ◽  
Stefan A. Tschanz ◽  
Eveline Yao ◽  
Marco Stampanoni ◽  
...  
Keyword(s):  
High Resolution ◽  
Surface Area ◽  
Particle Deposition ◽  
Three Dimensional ◽  
Rat Lung ◽  
X Ray ◽  
Novel Approach ◽  
Pulmonary Airways ◽  
Conducting Airways

The small trees of gas-exchanging pulmonary airways, which are fed by the most distal purely conducting airways, are called acini and represent the functional gas-exchanging units. The three-dimensional architecture of the acini has a strong influence on ventilation and particle deposition. Due to the difficulty in identifying individual acini on microscopic lung sections, the knowledge about the number of acini and their biological parameters, like volume, surface area, and number of alveoli per acinus, are limited. We developed a method to extract individual acini from lungs imaged by high-resolution synchrotron radiation-based X-ray tomographic microscopy and estimated their volume, surface area, and number of alveoli. Rat acini were isolated by semiautomatically closing the airways at the transition from conducting to gas-exchanging airways. We estimated a mean internal acinar volume of 1.148 mm3, a mean acinar surface area of 73.9 mm2, and a mean of 8,470 alveoli/acinus. Assuming that the acini are similarly sized throughout different regions of the lung, we calculated that a rat lung contains 5,470 ± 833 acini. We conclude that our novel approach is well suited for the fast and reliable characterization of a large number of individual acini in healthy, diseased, or transgenic lungs of different species, including humans.

scholarly journals Accurate prediction of boundaries of high resolution topologically associated domains (TADs) in fruit flies using deep learning

2019 ◽  
Vol 47 (13) ◽  
pp. e78-e78 ◽  
Author(s):  
John Henderson ◽  
Vi Ly ◽  
Shawn Olichwier ◽  
Pranik Chainani ◽  
Yu Liu ◽  
...  
Keyword(s):  
Deep Learning ◽  
High Resolution ◽  
Short Term Memory ◽  
Computational Prediction ◽  
Cell Types ◽  
Learning Model ◽  
Fruit Flies ◽  
Topologically Associated Domains ◽  
Multiple Cell ◽  
Deep Learning Model

Abstract Genomes are organized into self-interacting chromatin regions called topologically associated domains (TADs). A significant number of TAD boundaries are shared across multiple cell types and conserved across species. Disruption of TAD boundaries may affect the expression of nearby genes and could lead to several diseases. Even though detection of TAD boundaries is important and useful, there are experimental challenges in obtaining high resolution TAD locations. Here, we present computational prediction of TAD boundaries from high resolution Hi-C data in fruit flies. By extensive exploration and testing of several deep learning model architectures with hyperparameter optimization, we show that a unique deep learning model consisting of three convolution layers followed by a long short-term-memory layer achieves an accuracy of 96%. This outperforms feature-based models’ accuracy of 91% and an existing method's accuracy of 73–78% based on motif TRAP scores. Our method also detects previously reported motifs such as Beaf-32 that are enriched in TAD boundaries in fruit flies and also several unreported motifs.

High Resolution Microscopy of Multi-Layered Biological Crystals

1982 ◽  
Vol 40 ◽  
pp. 80-83
Author(s):  
H.A. Cohen ◽  
T.W. Jeng ◽  
W. Chiu
Keyword(s):  
High Resolution ◽  
Low Dose ◽  
Three Dimensional ◽  
Data Interpretation ◽  
Two Dimensional ◽  
Biological Objects ◽  
Density Maps ◽  
Density Map ◽  
Complex Crystal ◽  
High Resolution Microscopy

This tutorial will discuss the methodology of low dose electron diffraction and imaging of crystalline biological objects, the problems of data interpretation for two-dimensional projected density maps of glucose embedded protein crystals, the factors to be considered in combining tilt data from three-dimensional crystals, and finally, the prospects of achieving a high resolution three-dimensional density map of a biological crystal. This methodology will be illustrated using two proteins under investigation in our laboratory, the T4 DNA helix destabilizing protein gp32*I and the crotoxin complex crystal.

Electron crystallographic determination of the 3-D structure of staurolite at atomic resolution

1991 ◽  
Vol 49 ◽  
pp. 540-541
Author(s):  
Kenneth H. Downing ◽  
Hu Meisheng ◽  
Hans-Rudolf Went ◽  
Michael A. O'Keefe
Keyword(s):  
High Resolution ◽  
Three Dimensional ◽  
High Resolution Electron Microscopy ◽  
Atomic Resolution ◽  
Dimensional Structure ◽  
Structure Information ◽  
Resolution Electron ◽  
Scattering Effects ◽  
High Resolution Images ◽  
Effects Of Radiation

With current advances in electron microscope design, high resolution electron microscopy has become routine, and point resolutions of better than 2Å have been obtained in images of many inorganic crystals. Although this resolution is sufficient to resolve interatomic spacings, interpretation generally requires comparison of experimental images with calculations. Since the images are two-dimensional representations of projections of the full three-dimensional structure, information is invariably lost in the overlapping images of atoms at various heights. The technique of electron crystallography, in which information from several views of a crystal is combined, has been developed to obtain three-dimensional information on proteins. The resolution in images of proteins is severely limited by effects of radiation damage. In principle, atomic-resolution, 3D reconstructions should be obtainable from specimens that are resistant to damage. The most serious problem would appear to be in obtaining high-resolution images from areas that are thin enough that dynamical scattering effects can be ignored.

Three-Dimensional Immunoelectron Microscopy of Yeast Cells by a New High-Resolution Replica Method

1985 ◽  
Vol 43 ◽  
pp. 562-563
Author(s):  
Hirano T. ◽  
M. Yamaguchi ◽  
M. Hayashi ◽  
Y. Sekiguchi ◽  
A. Tanaka
Keyword(s):  
High Resolution ◽  
Plasma Polymerization ◽  
Three Dimensional ◽  
Freeze Fracture ◽  
Replica Method ◽  
Yeast Cells ◽  
Dynamic Aspect ◽  
Replica Technique ◽  
Gaseous Hydrocarbon ◽  
Transmission Electron

A plasma polymerization film replica method is a new high resolution replica technique devised by Tanaka et al. in 1978. It has been developed for investigation of the three dimensional ultrastructure in biological or nonbiological specimens with the transmission electron microscope. This method is based on direct observation of the single-stage replica film, which was obtained by directly coating on the specimen surface. A plasma polymerization film was deposited by gaseous hydrocarbon monomer in a glow discharge.The present study further developed the freeze fracture method by means of a plasma polymerization film produces a three dimensional replica of chemically untreated cells and provides a clear evidence of fine structure of the yeast plasma membrane, especially the dynamic aspect of the structure of invagination (Figure 1).

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