MyoD is a 3D genome structure organizer for muscle cell identity

AbstractThe genome exists as an organized, three-dimensional (3D) dynamic architecture, and each cell type has a unique 3D genome organization that determines its cell identity. An unresolved question is how cell type-specific 3D genome structures are established during development. Here, we analyzed 3D genome structures in muscle cells from mice lacking the muscle lineage transcription factor (TF), MyoD, versus wild-type mice. We show that MyoD functions as a “genome organizer” that specifies 3D genome architecture unique to muscle cell development, and that H3K27ac is insufficient for the establishment of MyoD-induced chromatin loops in muscle cells. Moreover, we present evidence that other cell lineage-specific TFs might also exert functional roles in orchestrating lineage-specific 3D genome organization during development.

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MyoD is a structure organizer of 3D genome architecture in muscle cells

10.1101/2020.08.29.273375 ◽

2020 ◽

Author(s):

Qian Chen ◽

Fengling Chen ◽

Ruiting Wang ◽

Minglei Shi ◽

Antony K. Chen ◽

...

Keyword(s):

Genome Organization ◽

Three Dimensional ◽

Muscle Cells ◽

Cell Types ◽

Linear Molecule ◽

Basic Question ◽

Genome Architecture ◽

Cell Type ◽

3D Genome ◽

A Genome

AbstractThe genome is not a linear molecule of DNA randomly folded in the nucleus, but exists as an organized, three-dimensional (3D) dynamic architecture. Intriguingly, it is now clear that each cell type has a unique and characteristic 3D genome organization that functions in determining cell identity during development. A currently challenging basic question is how cell-type specific 3D genome structures are established during development. Herein, we analyzed 3D genome structures in primary myoblasts and myocytes from MyoD knockout (MKO) and wild type (WT) mice and discovered that MyoD, a pioneer transcription factor (TF), can function as a “genome organizer” that specifies the proper 3D genome architecture unique to muscle cell development. Importantly, we genetically demonstrate that H3K27ac is insufficient for establishing MyoD-induced chromatin loops in muscle cells. The establishment of MyoD’s “architectural role” should have profound impacts on advancing understanding of other pioneer transcription factors in orchestrating lineage specific 3D genome organization during development in a potentially very large number of cell types in diverse organisms.

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GSDB: a database of 3D chromosome and genome structures reconstructed from Hi-C data

10.1101/692731 ◽

2019 ◽

Cited By ~ 1

Author(s):

Oluwatosin Oluwadare ◽

Max Highsmith ◽

Jianlin Cheng

Keyword(s):

Structure Prediction ◽

Biological Activities ◽

Genome Structure ◽

3D Structure ◽

Three Dimensional ◽

Chromosome Conformation ◽

3D Genome ◽

Reconstruction Methods ◽

A Genome ◽

Structure Reconstruction

ABSTRACTAdvances in the study of chromosome conformation capture (3C) technologies, such as Hi-C technique - capable of capturing chromosomal interactions in a genome-wide scale - have led to the development of three-dimensional (3D) chromosome and genome structure reconstruction methods from Hi-C data. The 3D genome structure is important because it plays a role in a variety of important biological activities such as DNA replication, gene regulation, genome interaction, and gene expression. In recent years, numerous Hi-C datasets have been generated, and likewise, a number of genome structure construction algorithms have been developed. However, until now, there has been no freely available repository for 3D chromosome structures. In this work, we outline the construction of a novel Genome Structure Database (GSDB) to create a comprehensive repository that contains 3D structures for Hi-C datasets constructed by a variety of 3D structure reconstruction tools. GSDB contains over 50,000 structures constructed by 12 state-of-the-art chromosome and genome structure prediction methods for publicly used Hi-C datasets with varying resolution. The database is useful for the community to study the function of genome from a 3D perspective. GSDB is accessible at http://sysbio.rnet.missouri.edu/3dgenome/GSDB

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ChromeBat: A Bio-Inspired Approach to 3D Genome Reconstruction

10.1101/2021.03.04.433995 ◽

2021 ◽

Author(s):

Brandon Collins ◽

Philip N. Brown ◽

Oluwatosin Oluwadare

Keyword(s):

Genome Structure ◽

Three Dimensional ◽

Genomic Analysis ◽

Bat Algorithm ◽

Empirical Measure ◽

Reconstruction Problem ◽

Genome Reconstruction ◽

3D Genome ◽

A Genome ◽

Contact Data

Background: With the advent of Next Generation Sequencing and the Hi-C experiment, high quality genome-wide contact data is becoming increasingly available. This data represents an empirical measure of how a genome interacts inside the nucleus. Genome conformation is of particular interest as it has been experimentally shown to be a driving force for many genomic functions from regulation to transcription. Thus, the Three-Dimensional Genome Reconstruction Problem seeks to take Hi-C data and produce the complete physical genome structure as it appears in the nucleus for genomic analysis. Results: We propose and develop a novel method to solve the Chromosome and Genome Reconstruction problem based on the Bat Algorithm which we called ChromeBat.We demonstrate on real Hi-C data that ChromeBat is capable of state of the art performance. Additionally, the domain of Genome Reconstruction has been criticized for lacking algorithmic diversity, and the bio-inspired nature of ChromeBat contributes algorithmic diversity to the problem domain. Conclusions: ChromeBat is an effective approach at solving the Genome Reconstruction Problem. The source code and usage guide can be found here: https://github.com/OluwadareLab/ChromeBat.

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Population-based 3D genome structure analysis reveals driving forces in spatial genome organization

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1512577113 ◽

2016 ◽

Vol 113 (12) ◽

pp. E1663-E1672 ◽

Cited By ~ 110

Author(s):

Harianto Tjong ◽

Wenyuan Li ◽

Reza Kalhor ◽

Chao Dai ◽

Shengli Hao ◽

...

Keyword(s):

Genome Organization ◽

Driving Forces ◽

Genome Structure ◽

Probabilistic Approach ◽

Population Based ◽

3D Genome ◽

Structural Variability ◽

Chromatin Interactions ◽

A Genome ◽

Spatial Genome Organization

Conformation capture technologies (e.g., Hi-C) chart physical interactions between chromatin regions on a genome-wide scale. However, the structural variability of the genome between cells poses a great challenge to interpreting ensemble-averaged Hi-C data, particularly for long-range and interchromosomal interactions. Here, we present a probabilistic approach for deconvoluting Hi-C data into a model population of distinct diploid 3D genome structures, which facilitates the detection of chromatin interactions likely to co-occur in individual cells. Our approach incorporates the stochastic nature of chromosome conformations and allows a detailed analysis of alternative chromatin structure states. For example, we predict and experimentally confirm the presence of large centromere clusters with distinct chromosome compositions varying between individual cells. The stability of these clusters varies greatly with their chromosome identities. We show that these chromosome-specific clusters can play a key role in the overall chromosome positioning in the nucleus and stabilizing specific chromatin interactions. By explicitly considering genome structural variability, our population-based method provides an important tool for revealing novel insights into the key factors shaping the spatial genome organization.

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ChromeBat: A Bio-Inspired Approach to 3D Genome Reconstruction

Genes ◽

10.3390/genes12111757 ◽

2021 ◽

Vol 12 (11) ◽

pp. 1757

Author(s):

Brandon Collins ◽

Oluwatosin Oluwadare ◽

Philip Brown

Keyword(s):

Genome Structure ◽

Three Dimensional ◽

Genomic Analysis ◽

Bat Algorithm ◽

Empirical Measure ◽

Reconstruction Problem ◽

Genome Reconstruction ◽

3D Genome ◽

A Genome ◽

Contact Data

With the advent of Next Generation Sequencing and the Hi-C experiment, high quality genome-wide contact data are becoming increasingly available. These data represents an empirical measure of how a genome interacts inside the nucleus. Genome conformation is of particular interest as it has been experimentally shown to be a driving force for many genomic functions from regulation to transcription. Thus, the Three Dimensional-Genome Reconstruction Problem (3D-GRP) seeks to take Hi-C data and produces a complete physical genome structure as it appears in the nucleus for genomic analysis. We propose and develop a novel method to solve the Chromosome and Genome Reconstruction problem based on the Bat Algorithm (BA) which we called ChromeBat. We demonstrate on real Hi-C data that ChromeBat is capable of state-of-the-art performance. Additionally, the domain of Genome Reconstruction has been criticized for lacking algorithmic diversity, and the bio-inspired nature of ChromeBat contributes algorithmic diversity to the problem domain. ChromeBat is an effective approach for solving the Genome Reconstruction Problem.

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Repeat elements organize 3D genome structure and mediate transcription in the filamentous fungusEpichloë festucae

10.1101/339010 ◽

2018 ◽

Cited By ~ 1

Author(s):

David J Winter ◽

Austen RD Ganley ◽

Carolyn A Young ◽

Ivan Liachko ◽

Christopher L Schardl ◽

...

Keyword(s):

Genome Structure ◽

Regulation Of Gene Expression ◽

Three Dimensional ◽

Structural Features ◽

Dimensional Structure ◽

In Planta ◽

Repeat Elements ◽

Symbiotic Relationships ◽

3D Genome ◽

Transcriptional Changes

AbstractStructural features of genomes, including the three-dimensional arrangement of DNA in the nucleus, are increasingly seen as key contributors to the regulation of gene expression. However, studies on how genome structure and nuclear organization influence transcription have so far been limited to a handful of model species. This narrow focus limits our ability to draw general conclusions about the ways in which three-dimensional structures are encoded, and to integrate information from three-dimensional data to address a broader gamut of biological questions. Here, we generate a complete and gapless genome sequence for the filamentous fungus,Epichloë festucae. Coupling it with RNAseq and HiC data, we investigate how the structure of the genome contributes to the suite of transcriptional changes that anEpichloëspecies needs to maintain symbiotic relationships with its grass host. Our results reveal a unique “patchwork” genome, in which repeat-rich blocks of DNA with discrete boundaries are interspersed by gene-rich sequences. In contrast to other species, the three-dimensional structure of the genome is anchored by these repeat blocks, which act to isolate transcription in neighbouring gene-rich regions. Genes that are differentially expressed in planta are enriched near the boundaries of these repeat-rich blocks, suggesting that their three-dimensional orientation partly encodes and regulates the symbiotic relationship formed by this organism.

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3D genome organization during lymphocyte development and activation

Briefings in Functional Genomics ◽

10.1093/bfgp/elz030 ◽

2019 ◽

Vol 19 (2) ◽

pp. 71-82 ◽

Cited By ~ 1

Author(s):

Anne van Schoonhoven ◽

Danny Huylebroeck ◽

Rudi W Hendriks ◽

Ralph Stadhouders

Keyword(s):

Genome Organization ◽

Transcriptional Control ◽

Molecular Mechanisms ◽

Current Knowledge ◽

Three Dimensional ◽

Lymphocyte Development ◽

Control Of Gene Expression ◽

3D Genome ◽

Wide Range ◽

3D Architecture

Abstract Chromosomes have a complex three-dimensional (3D) architecture comprising A/B compartments, topologically associating domains and promoter–enhancer interactions. At all these levels, the 3D genome has functional consequences for gene transcription and therefore for cellular identity. The development and activation of lymphocytes involves strict control of gene expression by transcription factors (TFs) operating in a three-dimensionally organized chromatin landscape. As lymphocytes are indispensable for tissue homeostasis and pathogen defense, and aberrant lymphocyte activity is involved in a wide range of human morbidities, acquiring an in-depth understanding of the molecular mechanisms that control lymphocyte identity is highly relevant. Here we review current knowledge of the interplay between 3D genome organization and transcriptional control during B and T lymphocyte development and antigen-dependent activation, placing special emphasis on the role of TFs.

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

Genome Biology ◽

10.1186/s13059-017-1264-5 ◽

2017 ◽

Vol 18 (1) ◽

Cited By ~ 38

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.

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PGS: a dynamic and automated population-based genome structure software

10.1101/103358 ◽

2017 ◽

Cited By ~ 1

Author(s):

Nan Hua ◽

Harianto Tjong ◽

Hanjun Shin ◽

Ke Gong ◽

Xianghong Jasmine Zhou ◽

...

Keyword(s):

High Performance ◽

Spatial Organization ◽

Genome Structure ◽

Probabilistic Approach ◽

Population Based ◽

Chromatin Interaction ◽

3D Analysis ◽

3D Genome ◽

A Genome ◽

Contact Frequency

ABSTRACTHi-C technologies are widely used to investigate the spatial organization of genomes. However, the structural variability of the genome is a great challenge to interpreting ensemble-averaged Hi-C data, particularly for long-range/interchromosomal interactions. We pioneered a probabilistic approach for generating a population of distinct diploid 3D genome structures consistent with all the chromatin-chromatin interaction probabilities from Hi-C experiments. Each structure in the population is a physical model of the genome in 3D. Analysis of these models yields new insights into the causes and the functional properties of the genome’s organization in space and time. We provide a user-friendly software package, called PGS, that runs on local machines and high-performance computing platforms. PGS takes a genome-wide Hi-C contact frequency matrix and produces an ensemble of 3D genome structures entirely consistent with the input. The software automatically generates an analysis report, and also provides tools to extract and analyze the 3D coordinates of specific domains.

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GEM: A manifold learning based framework for reconstructing spatial organizations of chromosomes

10.1101/161208 ◽

2017 ◽

Author(s):

Guangxiang Zhu ◽

Wenxuan Deng ◽

Hailin Hu ◽

Rui Ma ◽

Sai Zhang ◽

...

Keyword(s):

Manifold Learning ◽

Learning Strategy ◽

Genome Structure ◽

Three Dimensional ◽

Conformational Energy ◽

3D Genome ◽

Learning Framework ◽

Reconstruction Methods ◽

Eukaryotic Gene ◽

Validation Tests

AbstractDecoding the spatial organizations of chromosomes has crucial implications for studying eukaryotic gene regulation. Recently, Chromosomal conformation capture based technologies, such as Hi-C, have been widely used to uncover the interaction frequencies of genomic loci in high-throughput and genome-wide manner and provide new insights into the folding of three-dimensional (3D) genome structure. In this paper, we develop a novel manifold learning framework, called GEM (Genomic organization reconstructor based on conformational Energy and Manifold learning), to elucidate the underlying 3D spatial organizations of chromosomes from Hi-C data. Unlike previous chromatin structure reconstruction methods, which explicitly assume specific relationships between Hi-C interaction frequencies and spatial distances between distal genomic loci, GEM is able to reconstruct an ensemble of chromatin conformations by directly embedding the neigh-boring affinities from Hi-C space into 3D Euclidean space based on a manifold learning strategy that considers both the fitness of Hi-C data and the biophysical feasibility of the modeled structures, which are measured by the conformational energy derived from our current biophysical knowledge about the 3D polymer model. Extensive validation tests on both simulated interaction frequency data and experimental Hi-C data of yeast and human demonstrated that GEM not only greatly outperformed other state-of-art modeling methods but also reconstructed accurate chromatin structures that agreed well with the hold-out or independent Hi-C data and sparse geometric restraints derived from the previous fluorescence in situ hybridization (FISH) studies. In addition, as GEM can generate accurate spatial organizations of chromosomes by integrating both experimentally-derived spatial contacts and conformational energy, we for the first time extended our modeling method to recover long-range genomic interactions that are missing from the original Hi-C data. All these results indicated that GEM can provide a physically and physiologically valid 3D representations of the organizations of chromosomes and thus serve as an effective and useful genome structure reconstructor.

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