1
|
Xu Y, Das P, McCord RP, Shen T. Node features of chromosome structure networks and their connections to genome annotation. Comput Struct Biotechnol J 2024; 23:2240-2250. [PMID: 38827231 PMCID: PMC11140560 DOI: 10.1016/j.csbj.2024.05.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 05/14/2024] [Accepted: 05/15/2024] [Indexed: 06/04/2024] Open
Abstract
The 3D conformations of chromosomes can encode biological significance, and the implications of such structures have been increasingly appreciated recently. Certain chromosome structural features, such as A/B compartmentalization, are frequently extracted from Hi-C pairwise genome contact information (physical association between different regions of the genome) and compared with linear annotations of the genome, such as histone modifications and lamina association. We investigate how additional properties of chromosome structure can be deduced using an abstract graph representation of the contact heatmap, and describe specific network properties that can have a strong connection with some of these biological annotations. We constructed chromosome structure networks (CSNs) from bulk Hi-C data and calculated a set of site-resolved (node-based) network properties. These properties are useful for characterizing certain aspects of chromosomal structure. We examined the ability of network properties to differentiate several scenarios, such as haploid vs diploid cells, partially inverted nuclei vs conventional architecture, depletion of chromosome architectural proteins, and structural changes during cell development. We also examined the connection between network properties and a series of other linear annotations, such as histone modifications and chromatin states including poised promoter and enhancer labels. We found that semi-local network properties exhibit greater capability in characterizing genome annotations compared to diffusive or ultra-local node features. For example, the local square clustering coefficient can be a strong classifier of lamina-associated domains. We demonstrated that network properties can be useful for highlighting large-scale chromosome structure differences that emerge in different biological situations.
Collapse
Affiliation(s)
- Yingjie Xu
- Graduate School of Genome Science & Technology, University of Tennessee, Knoxville, TN 37996, USA
| | - Priyojit Das
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
- Department of Molecular Biology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Rachel Patton McCord
- Department of Biochemistry & Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37996, USA
| | - Tongye Shen
- Department of Biochemistry & Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37996, USA
| |
Collapse
|
2
|
Li H, Playter C, Das P, McCord RP. Chromosome compartmentalization: causes, changes, consequences, and conundrums. Trends Cell Biol 2024; 34:707-727. [PMID: 38395734 PMCID: PMC11339242 DOI: 10.1016/j.tcb.2024.01.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 01/12/2024] [Accepted: 01/22/2024] [Indexed: 02/25/2024]
Abstract
The spatial segregation of the genome into compartments is a major feature of 3D genome organization. New data on mammalian chromosome organization across different conditions reveal important information about how and why these compartments form and change. A combination of epigenetic state, nuclear body tethering, physical forces, gene expression, and replication timing (RT) can all influence the establishment and alteration of chromosome compartments. We review the causes and implications of genomic regions undergoing a 'compartment switch' that changes their physical associations and spatial location in the nucleus. About 20-30% of genomic regions change compartment during cell differentiation or cancer progression, whereas alterations in response to a stimulus within a cell type are usually much more limited. However, even a change in 1-2% of genomic bins may have biologically relevant implications. Finally, we review the effects of compartment changes on gene regulation, DNA damage repair, replication, and the physical state of the cell.
Collapse
Affiliation(s)
- Heng Li
- Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, TN, USA
| | - Christopher Playter
- Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, TN, USA
| | - Priyojit Das
- University of Tennessee-Oak Ridge National Laboratory (UT-ORNL) Graduate School of Genome Science and Technology, University of Tennessee, Knoxville, TN, USA
| | - Rachel Patton McCord
- Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, TN, USA.
| |
Collapse
|
3
|
Nolan B, Harris HL, Kalluchi A, Reznicek TE, Cummings CT, Rowley MJ. HiCrayon reveals distinct layers of multi-state 3D chromatin organization. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.11.579821. [PMID: 38405883 PMCID: PMC10888951 DOI: 10.1101/2024.02.11.579821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
The co-visualization of chromatin conformation with 1D 'omics data is key to the multi-omics driven data analysis of 3D genome organization. Chromatin contact maps are often shown as 2D heatmaps and visually compared to 1D genomic data by simple juxtaposition. While common, this strategy is imprecise, placing the onus on the reader to align features with each other. To remedy this, we developed HiCrayon, an interactive tool that facilitates the integration of 3D chromatin organization maps and 1D datasets. This visualization method integrates data from genomic assays directly into the chromatin contact map by coloring interactions according to 1D signal. HiCrayon is implemented using R shiny and python to create a graphical user interface (GUI) application, available in both web or containerized format to promote accessibility. HiCrayon is implemented in R, and includes a graphical user interface (GUI), as well as a slimmed-down web-based version that lets users quickly produce publication-ready images. We demonstrate the utility of HiCrayon in visualizing the effectiveness of compartment calling and the relationship between ChIP-seq and various features of chromatin organization. We also demonstrate the improved visualization of other 3D genomic phenomena, such as differences between loops associated with CTCF/cohesin vs. those associated with H3K27ac. We then demonstrate HiCrayon's visualization of organizational changes that occur during differentiation and use HiCrayon to detect compartment patterns that cannot be assigned to either A or B compartments, revealing a distinct 3rd chromatin compartment. Overall, we demonstrate the utility of co-visualizing 2D chromatin conformation with 1D genomic signals within the same matrix to reveal fundamental aspects of genome organization. Local version: https://github.com/JRowleyLab/HiCrayon Web version: https://jrowleylab.com/HiCrayon.
Collapse
Affiliation(s)
- Ben Nolan
- Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Emile St, Omaha, 68198, NE, USA
| | - Hannah L Harris
- Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Emile St, Omaha, 68198, NE, USA
| | - Achyuth Kalluchi
- Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Emile St, Omaha, 68198, NE, USA
| | - Timothy E Reznicek
- Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Emile St, Omaha, 68198, NE, USA
| | - Christopher T Cummings
- Department of Pediatrics, University of Nebraska Medical Center, Emile St, Omaha, 68198, NE, USA
| | - M Jordan Rowley
- Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Emile St, Omaha, 68198, NE, USA
| |
Collapse
|
4
|
Li K, Zhang P, Wang Z, Shen W, Sun W, Xu J, Wen Z, Li L. iEnhance: a multi-scale spatial projection encoding network for enhancing chromatin interaction data resolution. Brief Bioinform 2023; 24:bbad245. [PMID: 37381618 DOI: 10.1093/bib/bbad245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 06/06/2023] [Accepted: 06/12/2023] [Indexed: 06/30/2023] Open
Abstract
Although sequencing-based high-throughput chromatin interaction data are widely used to uncover genome-wide three-dimensional chromatin architecture, their sparseness and high signal-noise-ratio greatly restrict the precision of the obtained structural elements. To improve data quality, we here present iEnhance (chromatin interaction data resolution enhancement), a multi-scale spatial projection and encoding network, to predict high-resolution chromatin interaction matrices from low-resolution and noisy input data. Specifically, iEnhance projects the input data into matrix spaces to extract multi-scale global and local feature sets, then hierarchically fused these features by attention mechanism. After that, dense channel encoding and residual channel decoding are used to effectively infer robust chromatin interaction maps. iEnhance outperforms state-of-the-art Hi-C resolution enhancement tools in both visual and quantitative evaluation. Comprehensive analysis shows that unlike other tools, iEnhance can recover both short-range structural elements and long-range interaction patterns precisely. More importantly, iEnhance can be transferred to data enhancement of other tissues or cell lines of unknown resolution. Furthermore, iEnhance performs robustly in enhancement of diverse chromatin interaction data including those from single-cell Hi-C and Micro-C experiments.
Collapse
Affiliation(s)
- Kai Li
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Ping Zhang
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Zilin Wang
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Wei Shen
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Weicheng Sun
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Jinsheng Xu
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Zi Wen
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Li Li
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
- Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| |
Collapse
|
5
|
Kalluchi A, Harris HL, Reznicek TE, Rowley MJ. Considerations and caveats for analyzing chromatin compartments. Front Mol Biosci 2023; 10:1168562. [PMID: 37091873 PMCID: PMC10113542 DOI: 10.3389/fmolb.2023.1168562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 03/27/2023] [Indexed: 04/08/2023] Open
Abstract
Genomes are organized into nuclear compartments, separating active from inactive chromatin. Chromatin compartments are readily visible in a large number of species by experiments that map chromatin conformation genome-wide. When analyzing these maps, a common step is the identification of genomic intervals that interact within A (active) and B (inactive) compartments. It has also become increasingly common to identify and analyze subcompartments. We review different strategies to identify A/B and subcompartment intervals, including a discussion of various machine-learning approaches to predict these features. We then discuss the strengths and limitations of current strategies and examine how these aspects of analysis may have impacted our understanding of chromatin compartments.
Collapse
Affiliation(s)
| | | | | | - M. Jordan Rowley
- Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, NE, United States
| |
Collapse
|