Browse
Submit Data
Databases
API
Help

Dataset Information

20 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Three-dimensional reconstruction of single-cell chromosome structure using recurrence plots.

ABSTRACT: Single-cell analysis of the three-dimensional (3D) chromosome structure can reveal cell-to-cell variability in genome activities. Here, we propose to apply recurrence plots, a mathematical method of nonlinear time series analysis, to reconstruct the 3D chromosome structure of a single cell based on information of chromosomal contacts from genome-wide chromosome conformation capture (Hi-C) data. This recurrence plot-based reconstruction (RPR) method enables rapid reconstruction of a unique structure in single cells, even from incomplete Hi-C information.

SUBMITTER: Hirata Y

PROVIDER: S-EPMC5057099 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Three-dimensional reconstruction of single-cell chromosome structure using recurrence plots.

Hirata Yoshito Y Oda Arisa A Ohta Kunihiro K Aihara Kazuyuki K

Scientific reports 20161011

Single-cell analysis of the three-dimensional (3D) chromosome structure can reveal cell-to-cell variability in genome activities. Here, we propose to apply recurrence plots, a mathematical method of nonlinear time series analysis, to reconstruct the 3D chromosome structure of a single cell based on information of chromosomal contacts from genome-wide chromosome conformation capture (Hi-C) data. This recurrence plot-based reconstruction (RPR) method enables rapid reconstruction of a unique struct ...[more]

PMID: 27725694

Similar Datasets

Imaging Three-Dimensional Elemental Inhomogeneity in Pt-Ni Nanoparticles Using Spectroscopic Single Particle Reconstruction.

Project description:The properties of nanoparticles are known to critically depend on their local chemistry but characterizing three-dimensional (3D) elemental segregation at the nanometer scale is highly challenging. Scanning transmission electron microscope (STEM) tomographic imaging is one of the few techniques able to measure local chemistry for inorganic nanoparticles but conventional methodologies often fail due to the high electron dose imparted. Here, we demonstrate realization of a new spectroscopic single particle reconstruction approach built on a method developed by structural biologists. We apply this technique to the imaging of PtNi nanocatalysts and find new evidence of a complex inhomogeneous alloying with a Pt-rich core, a Ni-rich hollow octahedral intermediate shell and a Pt-rich rhombic dodecahedral skeleton framework with less Pt at ?100? vertices. The ability to gain evidence of local surface enrichment that varies with the crystallographic orientation of facets and vertices is expected to provide significant insight toward the development of nanoparticles for sensing, medical imaging, and catalysis.

| S-EPMC6378652 | biostudies-literature

Protein structure determination by electron diffraction using a single three-dimensional nanocrystal.

Project description:Three-dimensional nanometre-sized crystals of macromolecules currently resist structure elucidation by single-crystal X-ray crystallography. Here, a single nanocrystal with a diffracting volume of only 0.14 µm3, i.e. no more than 6 × 105 unit cells, provided sufficient information to determine the structure of a rare dimeric polymorph of hen egg-white lysozyme by electron crystallography. This is at least an order of magnitude smaller than was previously possible. The molecular-replacement solution, based on a monomeric polyalanine model, provided sufficient phasing power to show side-chain density, and automated model building was used to reconstruct the side chains. Diffraction data were acquired using the rotation method with parallel beam diffraction on a Titan Krios transmission electron microscope equipped with a novel in-house-designed 1024 × 1024 pixel Timepix hybrid pixel detector for low-dose diffraction data collection. Favourable detector characteristics include the ability to accurately discriminate single high-energy electrons from X-rays and count them, fast readout to finely sample reciprocal space and a high dynamic range. This work, together with other recent milestones, suggests that electron crystallography can provide an attractive alternative in determining biological structures.

| S-EPMC5586247 | biostudies-literature

Modeling Three-Dimensional Chromosome Structures Using Gene Expression Data.

Project description:Recent genomic studies have shown that significant chromosomal spatial correlation exists in gene expression of many organisms. Interestingly, coexpression has been observed among genes separated by a fixed interval in specific regions of a chromosome chain, which is likely caused by three-dimensional (3D) chromosome folding structures. Modeling such spatial correlation explicitly may lead to essential understandings of 3D chromosome structures and their roles in transcriptional regulation. In this paper, we explore chromosomal spatial correlation induced by 3D chromosome structures, and propose a hierarchical Bayesian method based on helical structures to formally model and incorporate the correlation into the analysis of gene expression microarray data. It is the first study to quantify and infer 3D chromosome structures in vivo using expression microarrays. Simulation studies show computing feasibility of the proposed method and that, under the assumption of helical chromosome structures, it can lead to precise estimation of structural parameters and gene expression levels. Real data applications demonstrate an intriguing biological phenomenon that functionally associated genes, which are far apart along the chromosome chain, are brought into physical proximity by chromosomal folding in 3D space to facilitate their coexpression. It leads to important biological insight into relationship between chromosome structure and function.

| S-EPMC3134274 | biostudies-literature

Three-dimensional reconstruction of the dynactin complex by single-particle image analysis.

Project description:Dynactin is a large complex of at least nine distinct proteins that co-complexes with cytoplasmic dynein within cells, where it plays a major role as a regulator of the motor's function. Owing to its large size and complexity, relatively little is known about dynactin's 3D structure or the structural basis of its function. Use of single-particle image analysis techniques has enabled us to produce the first 3D reconstruction of the dynactin complex, to a resolution of 3 nm. The actin-related protein (Arp) backbone of the filament has been clearly visualized. Fitting of models of the Arp backbone showed that it consists of 10 subunits. Additional mass, not part of the Arp backbone, was also seen. A preliminary fitting of the capping protein CapZ structure into our 3D reconstruction of the dynactin complex suggests that it is optimally placed to perform its proposed function as a stabilizer of the Arp1 backbone and gives clues as to likely interaction points between the capping protein and Arp subunits. The results provide the first detailed visualization of the dynactin complex and shed light on the mode of interaction between several of its constituent proteins and their possible functions.

| S-EPMC553325 | biostudies-literature

Bayesian Estimation of Three-Dimensional Chromosomal Structure from Single-Cell Hi-C Data.

Project description:The problem of three-dimensional (3D) chromosome structure inference from Hi-C data sets is important and challenging. While bulk Hi-C data sets contain contact information derived from millions of cells and can capture major structural features shared by the majority of cells in the sample, they do not provide information about local variability between cells. Single-cell Hi-C can overcome this problem, but contact matrices are generally very sparse, making structural inference more problematic. We have developed a Bayesian multiscale approach, named Structural Inference via Multiscale Bayesian Approach, to infer 3D structures of chromosomes from single-cell Hi-C while including the bulk Hi-C data and some regularization terms as a prior. We study the landscape of solutions for each single-cell Hi-C data set as a function of prior strength and demonstrate clustering of solutions using data from the same cell.

| S-EPMC6856950 | biostudies-literature

Three-dimensional reconstruction of soybean nodules provides an update on vascular structure.

Project description:PREMISE OF THE STUDY:In many cases, the functioning of a biological system cannot be correctly understood if its physical anatomy is incorrectly described. Accurate knowledge of the anatomy of soybean [Glycine max (L.) Merril] nodules and its connection with the root vasculature is important for understanding its function in supplying the plant with nitrogenous compounds. Previous two-dimensional anatomical observations of soybean nodules led to the assumption that vascular bundles terminate within the cortex of the nodule and that a single vascular bundle connects the nodule to the root. We wanted to see whether these anatomical assumptions would be verified by digitally reconstructing soybean nodules in three dimensions. METHODS:Nodules were dehydrated, embedded in paraffin, and cut into 15 ?m thick sections. Over 200 serial sections were stained with safranin and fast green, and then photographed using light microscopy. Images were digitally cleared, aligned, and assembled into a three-dimensional (3D) volume using the Adobe program After Effects. KEY RESULTS:In many cases, vascular bundles had a continuous connection around the nodules. The 3D reconstruction also revealed a dual vascular connection originating in the nodule and leading to the root in 22 of the 24 nodules. Of the 22 dual connections, 11 maintained two separate vascular bundles into the root with independent connections to the root vasculature. CONCLUSIONS:A more robust and complex anatomical pathway for vascular transport between nodules and root xylem in soybean plants is indicated by these observations and will contribute to a better understanding of the symbiotic relationship between soybean plants and nitrogen-fixing bacteria within the nodules.

| S-EPMC6850150 | biostudies-literature

Three-dimensional Reconstruction and Quantification of Proteins and mRNAs at the Single-cell Level in Cultured Cells.

Project description:Gene expression is often regulated by the abundance, localization, and translation of mRNAs in both space and time. Being able to visualize mRNAs and protein products in single cells is critical to understand this regulatory process. The development of single-molecule RNA fluorescence in situ hybridization (smFISH) allows the detection of individual RNA molecules at the single-molecule and single-cell levels. When combined with immunofluorescence (IF), both mRNAs and proteins in individual cells can be analyzed simultaneously. However, a precise and streamlined quantification method for the smFISH and IF combined dataset is scarce, as existing workflows mostly focus on quantifying the smFISH data alone. Here we detail a method for performing sequential IF and smFISH in cultured cells (as described in Sepulveda et al., 2018 ) and the subsequent statistical analysis of the smFISH and IF data via three-dimensional (3D) reconstruction in a semi-automatic image processing workflow. Although our method is based on analyzing centrosomally enriched mRNAs and proteins, the workflow can be readily adapted for performing and analyzing smFISH and IF data in other biological contexts.

| S-EPMC7854272 | biostudies-literature

Robust lineage reconstruction from high-dimensional single-cell data.

Project description:Single-cell gene expression data provide invaluable resources for systematic characterization of cellular hierarchy in multi-cellular organisms. However, cell lineage reconstruction is still often associated with significant uncertainty due to technological constraints. Such uncertainties have not been taken into account in current methods. We present ECLAIR (Ensemble Cell Lineage Analysis with Improved Robustness), a novel computational method for the statistical inference of cell lineage relationships from single-cell gene expression data. ECLAIR uses an ensemble approach to improve the robustness of lineage predictions, and provides a quantitative estimate of the uncertainty of lineage branchings. We show that the application of ECLAIR to published datasets successfully reconstructs known lineage relationships and significantly improves the robustness of predictions. ECLAIR is a powerful bioinformatics tool for single-cell data analysis. It can be used for robust lineage reconstruction with quantitative estimate of prediction accuracy.

| S-EPMC5001598 | biostudies-literature

Arthroscopic Superior Capsule Reconstruction Using Three-Dimensional Preoperative Planning: Technique Description.

Project description:We describe a technique using a fascia lata autograft with 3-dimensional (3D) printing to reconstruct the rotator cuff. Prototyping constitutes the construction of physical prototypes with high complexity after virtual studies. Such models increase the knowledge of the characteristics and size of rotator cuff injuries, thus improving the accuracy of determining the correct size of the graft to be used in superior capsule reconstruction. We present a case of superior capsule reconstruction using 3D printing for enhancing the accuracy of fascia lata allograft size and tension determination; 3D reconstruction has never been described in the literature for rotator cuff injuries.

| S-EPMC8252837 | biostudies-literature

Three-dimensional reconstruction of helical polymers.

Project description:The field of three-dimensional electron microscopy began more than 45years ago with a reconstruction of a helical phage tail, and helical polymers continue to be important objects for three-dimensional reconstruction due to the centrality of helical protein and nucleoprotein polymers in all aspects of biology. We are now witnessing a fundamental revolution in this area, made possible by direct electron detectors, which has led to near-atomic resolution for a number of important helical structures. Most importantly, the possibility of achieving such resolution routinely for a vast number of helical samples is within our reach. One of the main problems in helical reconstruction, ambiguities in assigning the helical symmetry, is overcome when one reaches a resolution where secondary structure is clearly visible. However, obstacles still exist due to the intrinsic variability within many helical filaments.

| S-EPMC4543434 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data