Download or read book Modeling the 3D Conformation of Genomes written by Guido Tiana and published by CRC Press. This book was released on 2019-01-15 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a timely summary of physical modeling approaches applied to biological datasets that describe conformational properties of chromosomes in the cell nucleus. Chapters explain how to convert raw experimental data into 3D conformations, and how to use models to better understand biophysical mechanisms that control chromosome conformation. The coverage ranges from introductory chapters to modeling aspects related to polymer physics, and data-driven models for genomic domains, the entire human genome, epigenome folding, chromosome structure and dynamics, and predicting 3D genome structure.
Download or read book Modeling the 3D Conformation of Genomes written by Guido Tiana and published by CRC Press. This book was released on 2019-01-15 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a timely summary of physical modeling approaches applied to biological datasets that describe conformational properties of chromosomes in the cell nucleus. Chapters explain how to convert raw experimental data into 3D conformations, and how to use models to better understand biophysical mechanisms that control chromosome conformation. The coverage ranges from introductory chapters to modeling aspects related to polymer physics, and data-driven models for genomic domains, the entire human genome, epigenome folding, chromosome structure and dynamics, and predicting 3D genome structure.
Download or read book Data driven Mechanistic Modeling of 3D Human Genome written by Yifeng Qi (Scientist in chemistry) and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis is organized as follows. In the first chapter, we introduce a computational model to simulate chromatin structure and dynamics. The model defines chromatin states by taking one-dimensional genomics and epigenomics data as input and quantitatively learns interacting patterns between these states using experimental contact data. Once learned, the model is able to make de novo predictions of 3D chromatin structures at five-kilo-base resolution across different cell types. The manuscript associated with this study is published in PLoS Computational Biology, 15.6, e1007024 (2019).
Download or read book Iterative Reconstruction of Three dimensional Model of Human Genome from Chromosomal Contact Data written by Sharif Ahmed and published by . This book was released on 2014 with total page 63 pages. Available in PDF, EPUB and Kindle. Book excerpt: 3D genome structures are important because they help us understand spatial gene regulation, transcription efficiency, genome interpretation, function implication (ENCODE), disease diagnosis, treatments and drug design. Recent study suggests that the spatial arrangement of chromosomes helps chromosomes to interact with themselves. This phenomenon convinced many researchers of the value of understanding the 3D genome structure, drawing interest to the field of genome modeling. Here we constructed 3D conformations of genomes using chromosomal contact data acquired by using the Hi-C technique. This technique is designed to determine both intra- and inter-chromosomal contacts in an unbiased manner at the whole genome scale. To construct 3D structures of any chromosome we only consider intrachromosomal contacts or interactions. We can think of a chromosome as a necklace with beads threaded together on a string. Now in our case, we can cut the whole chromosome into chunks that are one megabase (1Mb) in size, which gives us loci that we can treat as beads. Using our approach we can construct 3D structures of genomes at 1Mb scale by plotting the 3D coordinates of each 1Mb region and then connecting them. In a 3D modeling problem, it is crucial to initialize the starting model before using any optimization technique. So at first we try to initialize the coordinates using growth step which provides a probabilistic approach in determining their location. Chromatin that is not compressed into the dense chromosome form still resides in a globular shaped nucleus, suggesting a spherical model as a starting model for the smaller chromosomes. For larger chromosomes, former initialization is used as they have more regions for a specific resolution (i.e. 1Mb). After initialization, we apply two widely known optimization techniques, simulated annealing and genetic algorithms. Our novel scoring function allows optimization procedures to satisfy more intra-chromosomal contacts and non-contacts as well as some additional constraints. To perturb the position of the regions, as is mandatory for modeling optimization algorithms, the adaptation technique is used. This technique tries to fix the position of each region with high contact or noncontact satisfaction. This approach is inspired by similar work for proteins and can generate an ensemble of structures very quickly. The models generated are then compared with the published results of the MCMC5C method. It is found that in all cases our method produces models that are superior to the MCMC5C models. We present some visualization techniques to show how many contacts/non-contacts are satisfied/unsatisfied and also derive some simple yet powerful scoring measurements to evaluate widely known long range contacts. The robustness of the method is measured by convergence testing and recovering capability. Finally, we examine our final model for compartment features that Lieberman et al. suggested exist in chromosomes 14 and 22. We found those features to exist in our models as well, which validates our method.
Download or read book Statistical Topology of Genome Analysis written by Maxime Guiffo Pouokam and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genomes from bacteria to eukaryotes are intricately organized by the mutual interplay between the three-dimensional (3D) folding of their genome and their functional cell activities. In this dissertation, we propose exhaustive computational and statistical approaches to analyze chromosome conformation capture (CCC) data to investigate the 3D structure of the genome at both the level of CCC interaction counts between genomic loci and that of the 3D physical reconstruction structure. In this work, we use the yeast Saccharomyces cerevisiae (S. cerevisiae) as a model system. Our first result identifies the Rabl configuration, an evolutionary conserved feature of the 3D nuclear organization, characterized by the clustering of centromeres on one side of the nuclear envelope and the telomeres at the antipodal side, as an essential player in the simplification of the entanglement of chromatin fibers. In our approach, we introduced a new geometrical invariant termed the linking proportion that can capture the entanglement between pairs of chromosomes. Next, we showcase a novel approach of statistical topology whereby agreement between chromatin configuration reconstructions, which includes reproducibility of chromatin con- figurations and evaluation of chromatin reconstruction algorithms, can be evaluated. Our proposed approach makes use of the linking proportion together with statistical methods in inference to reach the important conclusion that the multidimensional scaling methods fails to preserve chromosomal topology. Finally, we present Smooth3D, a novel approach of inferring the 3D genome configuration structure from the CCC interaction counts based on cubic spline approximation. Smooth3D produces the 3D chromosomal trajectory from the CCC interactions counts via B-spline curve fitting using a least-squares algorithm. Our method estimates both the parameter of the transfer counts to distance function and the 3D chromosomal trajectory.
Download or read book Chromatin Architecture written by Kirti Prakash and published by Springer. This book was released on 2017-02-20 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book sheds new light on the current state of knowledge concerning chromatin organization. Particular emphasis is given to the new imaging potential offered by super-resolution microscopy, which allows DNA imaging with a very high labeling density. From the early work on chromosomes by Walther Flemming in the nineteenth century to recent advances in genomics, the history of chromatin research now spans more than a century. The various milestones, such as the discovery of the double helix structure, the sequencing of the human genome, and the recent description of the genome in 3D space, show that understanding chromatin and chromosome function requires a clear understanding of its structure. Presenting cutting-edge data from super-resolution single molecule microscopy, the book demonstrates that chromatin manifests several levels of folding, from nucleosomes to chromosomes. Chromatin domains emerge as a new fundamental building block of chromatin architecture, with functions possibly related to gene regulation. A detailed description of chromatin folding in the pachytene stage of meiosis serves as a model for exploring this functionality, showing the apparent interplay between structure, function, and epigenetic regulation. Lastly, the book discusses possible new avenues of innovation to describe chromatin’s organization and functions. Gathering essential insights on chromatin architecture, the book offers students an introduction to microscopy and its application to chromatin organization, while also providing advanced readers with new ideas for future research.
Download or read book Improving the Accuracy of 3D Chromosome Structure Inference and Analyzing the Organization of Genome in Early Embryogenesis Using Single Cell Hi C Data written by Tarak Shisode and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation summarizes my graduate work on the structure and organization of mouse genome during preimplantation development. My research is divided into three different areas, which I will discuss in turn. To begin, I will discuss my collaborative work on parental-to-embryo switch of chromosome organization during critical stages of early development. Notably, both paternal and maternal epigenomes undergo significant modifications following fertilization. Recent epigenomic studies have revealed the extraordinary chromatin landscapes found in oocytes, sperm, and early preimplantation embryos, including atypical histone modification patterns and differences in chromosome organization and accessibility. However, these studies reached polar opposite conclusions: the global absence of local topological-associated domains (TADs) in gametes and their appearance in the embryo versus the zygote's pre-existence of TADs and loops. The issues of whether parental structures can be inherited in the newly formed embryo and how these structures may be related to allele-specific gene regulation remain unresolved. To address this question, we use an optimized single cell high-throughput chromosome conformation capture (HiC) protocol to map genomic interactions for each parental genome (including the X chromosome) during mouse preimplantation. We integrate chromosome organization with allelic expression states and chromatin marks and demonstrate that after fertilization, higher-order chromatin structure is associated with an allele specific enrichment of histone H3 lysine 27 methylation. These early parental-specific domains are associated with gene repression and contribute to parentally biased gene expression-including newly described transiently imprinted loci. Additionally, we observe that these domains emerge in a non-parental-specific manner during the second wave of genome assembly. Finally, we discover that these domains are lost as genes are silenced on the paternal X chromosome but persist in regions that are not inactivated by the X chromosome. These findings highlight the complexities of three-dimensional genome organization and gene expression dynamics during early development. Second, I will discuss my work on some common and cell type-specific themes of higher order chromatin arrangements during mouse preimplantation development. Mapping the spatial organization of the genome is critical for comprehending its regulatory function in health, disease, and development. Our findings demonstrate an extraordinary amount of parent-specific chromosome choreography during the concatenation of two genomes. After fertilization, we observe an abrupt emergence of a Rabl-like configuration and a high head-to-head and tail-to-tail alignment of the chromosomes, which are gradually lost by the 64-cell stage. Additionally, the characteristics and marks of active and inactive chromatin exhibit a distinct radial profile across developmental stages and the genome. Finally, in addition to the well-known hallmarks of genome organization, we observe a preferential organization of chromosome territories - which call the "Territome". We were able to distinguish cell types based on the radial and relative positioning of the chromosomes in the 3D reconstructions. This suggest that interchromosomal interactions are just as critical for defining chromatin architecture and cellular identity as intrachromosomal interactions. Our findings establish a novel criterion for classifying cells when other hallmarks are difficult to quantify or when transcriptomics data is unavailable, thus paving a whole new way of looking at cells and learning how they function. Finally, with advances in experimental and theoretical approaches for generating single cell chromatin conformation capture assays, elucidating the genome's structure-function relationship has become a highly active area of research. Numerous computational methods have been developed to infer the genome's three-dimensional organization using Hi-C data from single cells. This is referred to as the three-dimensional genome reconstruction problem in formal terms (3D-GRP). While numerous methods exist for predicting the three-dimensional structure of a single genomic region, chromosome, or genome, the reconstructed models do not satisfy all of the input constraints. To address this, we present CUT & GROW, a method for improving the accuracy of three-dimensional chromosome structure inference using an iterative importance sampling strategy. CUT & GROW refines the structure of a three-dimensional chromosome (or genome) model by regrowing fragments of varying sizes locally, satisfying the majority of input constraints and providing a more precise view of the structure-function relationship
Download or read book Long Range Control of Gene Expression written by Veronica van Heyningen and published by Academic Press. This book was released on 2011-09-02 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: Long-Range Control of Gene Expression covers the current progress in understanding the mechanisms for genomic control of gene expression, which has grown considerably in the last few years as insight into genome organization and chromatin regulation has advanced. Discusses the evolution of cis-regulatory sequences in drosophila Includes information on genomic imprinting and imprinting defects in humans Includes a chapter on epigenetic gene regulation in cancer
Download or read book Computational Methods for 3D Genome Analysis written by Ryuichiro Nakato and published by Humana. This book was released on 2024-10-30 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume covers the latest methods and analytical approaches used to study the computational analysis of three-dimensional (3D) genome structure. The chapters in this book are organized into six parts. Part One discusses different NGS assays and the regulatory mechanism of 3D genome folding by SMC complexes. Part Two presents analysis workflows for Hi-C and Micro-C in different species, including human, mouse, medaka, yeast, and prokaryotes. Part Three covers methods for chromatin loop detection, sub-compartment detection, and 3D feature visualization. Part Four explores single-cell Hi-C and the cell-to-cell variability of the dynamic 3D structure. Parts Five talks about the analysis of polymer modelling to simulate the dynamic behavior of the 3D genome structure, and Part Six looks at 3D structure analysis using other omics data, including prediction of 3D genome structure from the epigenome, double-strand break-associated structure, and imaging-based 3D analysis using seqFISH. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and tools, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and thorough, Computational Methods for 3D Genome Analysis: Methods and Protocols is a valuable resource for researchers interested in using computational methods to further their studies in the nature of 3D genome organization.
Download or read book Hi C Data Analysis written by Silvio Bicciato and published by Humana. This book was released on 2022-09-04 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume details a comprehensive set of methods and tools for Hi-C data processing, analysis, and interpretation. Chapters cover applications of Hi-C to address a variety of biological problems, with a specific focus on state-of-the-art computational procedures adopted for the data analysis. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Hi-C Data Analysis: Methods and Protocols aims to help computational and molecular biologists working in the field of chromatin 3D architecture and transcription regulation.
Download or read book Computational Methods for Analyzing and Modeling Gene Regulation and 3D Genome Organization written by Anastasiya Belyaeva and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Biological processes from differentiation to disease progression are governed by gene regulatory mechanisms. Currently large-scale omics and imaging data sets are being collected to characterize gene regulation at every level. Such data sets present new opportunities and challenges for extracting biological insights and elucidating the gene regulatory logic of cells. In this thesis, I present computational methods for the analysis and integration of various data types used for cell profiling. Specifically, I focus on analyzing and linking gene expression with the 3D organization of the genome. First, I describe methodologies for elucidating gene regulatory mechanisms by considering multiple data modalities. I design a computational framework for identifying colocalized and coregulated chromosome regions by integrating gene expression and epigenetic marks with 3D interactions using network analysis. Then, I provide a general framework for data integration using autoencoders and apply it for the integration and translation between gene expression and chromatin images of naive T-cells. Second, I describe methods for analyzing single modalities such as contact frequency data, which measures the spatial organization of the genome, and gene expression data. Given the important role of the 3D genome organization in gene regulation, I present a methodology for reconstructing the 3D diploid conformation of the genome from contact frequency data. Given the ubiquity of gene expression data and the recent advances in single-cell RNA-sequencing technologies as well as the need for causal modeling of gene regulatory mechanisms, I then describe an algorithm as well as a software tool, difference causal inference (DCI), for learning causal gene regulatory networks from gene expression data. DCI addresses the problem of directly learning differences between causal gene regulatory networks given gene expression data from two related conditions. Finally, I shift my focus from basic biology to drug discovery. Given the current COVID19 pandemic, I present a computational drug repurposing platform that enables the identification of FDA approved compounds for drug repurposing and investigation of potential causal drug mechanisms. This framework relies on identifying drugs that reverse the signature of the infection in the space learned by an autoencoder and then uses causal inference to identify putative drug mechanisms.
Download or read book Molecular Modeling and Simulation written by Tamar Schlick and published by Springer Science & Business Media. This book was released on 2013-04-18 with total page 669 pages. Available in PDF, EPUB and Kindle. Book excerpt: Very broad overview of the field intended for an interdisciplinary audience; Lively discussion of current challenges written in a colloquial style; Author is a rising star in this discipline; Suitably accessible for beginners and suitably rigorous for experts; Features extensive four-color illustrations; Appendices featuring homework assignments and reading lists complement the material in the main text
Download or read book The Barley Genome written by Nils Stein and published by Springer. This book was released on 2018-08-18 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents an overview of the state-of-the-art in barley genome analysis, covering all aspects of sequencing the genome and translating this important information into new knowledge in basic and applied crop plant biology and new tools for research and crop improvement. Unlimited access to a high-quality reference sequence is removing one of the major constraints in basic and applied research. This book summarizes the advanced knowledge of the composition of the barley genome, its genes and the much larger non-coding part of the genome, and how this information facilitates studying the specific characteristics of barley. One of the oldest domesticated crops, barley is the small grain cereal species that is best adapted to the highest altitudes and latitudes, and it exhibits the greatest tolerance to most abiotic stresses. With comprehensive access to the genome sequence, barley’s importance as a genetic model in comparative studies on crop species like wheat, rye, oats and even rice is likely to increase.
Download or read book HiC Pro an Optimized and Flexible Pipeline for Hi C Data Processing written by Oldenburg Oldenburg Press and published by . This book was released on 2016-01-29 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt: HiC-Pro is an optimized and flexible pipeline for processing Hi-C data from raw reads to normalized contact maps. HiC-Pro maps reads, detects valid ligation products, performs quality controls and generates intra- and inter-chromosomal contact maps. It includes a fast implementation of the iterative correction method and is based on a memory-efficient data format for Hi-C contact maps. In addition, HiC-Pro can use phased genotype data to build allele-specific contact maps. We applied HiC-Pro to different Hi-C datasets, demonstrating its ability to easily process large data in a reasonable time. Source code and documentation are available at http://github.com/nservant/HiC-Pro.
Download or read book Analysis of 3D Genome Structure in Single Cells written by Jingtian Zhou and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 3D genome structure plays an important role in gene regulation. However, the study of genome folding in the context of cell-type specificity is largely missing. Here, we developed a single-cell multiomic assay, snm3C-seq, to simultaneously profile chromosome architecture and DNA methylation in the same single cell, enabling the investigation of 3D genome contacts across a wide range of cell types in a complex tissue. Nevertheless, it remains challenging to identify 3D chromatin features and compare them between cell types with single-cell data, given the heterogeneity of genome structures across cells as well as the limited reads being detected within a cell. To handle this question, we developed scHiCluster, a comprehensive framework for single-cell chromosome conformation analysis. The framework calculates low-dimensional embedding of single cells for accurate cell type clustering based on chromatin contacts, followed by annotating cell type specific chromatin loops and domains. We applied snm3C-seq and scHiCluster to developing human brain samples to analyze 53,063 cells. We identified 139 cell populations organized into 10 major lineages in the datasets, as well as over 2.5 million putative regulatory elements from these populations. The regulatory elements at chromatin loop anchors are highly enriched for putative causal common genetic variations of schizophrenia. We also observed difference in developmental timing between DNA methylation and 3D genome structures, and chromatin conformation changes often prime CG methylation (mCG). Together, this thesis shows the development of experimental and computational workflows to investigate single cell 3D genome structures and how we apply the technologies to study the molecular dynamics during brain development.
Download or read book High resolution Computational Analysis of Chromatin Architecture and Function written by Christopher Cameron and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "Since sequencing the human genome in the early 2000s, researchers have been determined to define the genetic pathways that regulate cellular activity or lead to disease. With the recent advent of Chromosome Conformation Capture (3C) technologies, the ability to observe chromatin’s three-dimensional (3D) structure became a possibility. It quickly became apparent that the genome is not regulated in one-dimension, but in 3D where chromatin loops are formed between an enhancer(s) and promoter to regulate a gene’s transcription. While 3C technology is quite useful, most protocols are limited in their resolution and availability across cell types and genomes. This limited resolution is a common concern for many technologies that study the regulation of genomes, such as Chromatin Immunoprecipitation (ChIP), and typically results from low-coverage sequencing. The objective of this thesis is to develop computational and biochemical methodologies that provide accurate, high-resolution genomic data for deciphering the organization and regulation of genomes. The first contribution in this thesis is Hi-C Interaction Frequency Inference (HIFI), a collection of density estimation algorithms for High-throughput 3C (Hi-C) data. Hi-C is a particularly useful 3C technology that identifies chromatin contacts genome-wide. HIFI allows Hi-C data to be analyzed at the highest possible resolution (restriction fragments) while providing the most accurate estimation of chromatin contact frequency when compared to other techniques in the field. The higher resolution afforded by HIFI has lead to the discovery of a potential role for active promoters and enhancers at the boundaries of Topologically Associating Domains (TADs). Next, we developed machine learning approaches to predict chromatin interaction frequencies from the reference genome sequence alone. While some machine learning work has been done to predict Hi-C data, all these models rely on biochemical input to make their predictions, which makes them impossible to use in cases where this data is unavailable (e.g., computationally inferred ancestral genomes). By limiting model input to features derived from sequence only, their predictions enable us to identify sequence determinants of 3D genome organization. Finally, we present a targeted and affordable ChIP methodology, called ‘Carbon Copy-ChIP’ (2C-ChIP), that continues our foray into high-resolution chromatin assays. 2C-ChIP provides quantifiable measures of bound protein across the genome at a cost that makes it very attractive for studies involving multiple experimental conditions (e.g., drug design). We also describe a computational tool for processing 2C-ChIP products called the Ligation-mediated Amplified, Multiplexed Paired-end Sequence (LAMPS) analysis pipeline.Taken together, the work in this thesis provides new ways to study genome function and organization affordably and at high resolution"--
Download or read book Genome Data Analysis written by Ju Han Kim and published by Springer. This book was released on 2019-04-30 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook describes recent advances in genomics and bioinformatics and provides numerous examples of genome data analysis that illustrate its relevance to real world problems and will improve the reader’s bioinformatics skills. Basic data preprocessing with normalization and filtering, primary pattern analysis, and machine learning algorithms using R and Python are demonstrated for gene-expression microarrays, genotyping microarrays, next-generation sequencing data, epigenomic data, and biological network and semantic analyses. In addition, detailed attention is devoted to integrative genomic data analysis, including multivariate data projection, gene-metabolic pathway mapping, automated biomolecular annotation, text mining of factual and literature databases, and integrated management of biomolecular databases. The textbook is primarily intended for life scientists, medical scientists, statisticians, data processing researchers, engineers, and other beginners in bioinformatics who are experiencing difficulty in approaching the field. However, it will also serve as a simple guideline for experts unfamiliar with the new, developing subfield of genomic analysis within bioinformatics.