scholarly journals Hierarchical chromatin organization detected by TADpole

2019 ◽  
Author(s):  
Paula Soler-Vila ◽  
Pol Cuscó Pons ◽  
Irene Farabella ◽  
Marco Di Stefano ◽  
Marc A. Marti-Renom
Keyword(s):  
Rapid Development ◽  
Super Resolution ◽  
Region Of Interest ◽  
Principal Component ◽  
Genomic Region ◽  
Mouse Strains ◽  
Bioinformatics Analyses ◽  
Chromosome Conformation ◽  
Resolution Imaging ◽  
Interaction Matrices

ABSTRACTThe rapid development of chromosome conformation capture (3C-based) techniques as well as super-resolution imaging together with bioinformatics analyses has been fundamental for unveiling that chromosomes are organized into the so-called topologically associating domains or TADs. While these TADs appear as nested patterns in the 3C-based interaction matrices, the vast majority of available computational methods are based on the hypothesis that TADs are individual and unrelated chromatin structures. Here we introduce TADpole, a computational tool designed to identify and analyze the entire hierarchy of TADs in intra-chromosomal interaction matrices. TADpole combines principal component analysis and constrained hierarchical clustering to provide an unsupervised set of significant partitions in a genomic region of interest. TADpole identification of domains is robust to the data resolution, normalization strategy, and sequencing depth. TADpole domain borders are enriched in CTCF and cohesin binding proteins, while the domains are enriched in either H3K36me3 or H3k27me3 histone marks. We show TADpole usefulness by applying it to capture Hi-C experiments in wild-type and mutant mouse strains to pinpoint statistically significant differences in their topological structure.

scholarly journals Hierarchical chromatin organization detected by TADpole

2020 ◽  
Vol 48 (7) ◽  
pp. e39-e39
Author(s):  
Paula Soler-Vila ◽  
Pol Cuscó ◽  
Irene Farabella ◽  
Marco Di Stefano ◽  
Marc A Marti-Renom
Keyword(s):  
Rapid Development ◽  
Region Of Interest ◽  
Principal Component ◽  
Genomic Region ◽  
Genetically Engineered ◽  
Bioinformatics Analyses ◽  
Chromosome Conformation ◽  
Data Resolution ◽  
Architectural Proteins ◽  
Interaction Matrices

Abstract The rapid development of Chromosome Conformation Capture (3C-based techniques), as well as imaging together with bioinformatics analyses, has been fundamental for unveiling that chromosomes are organized into the so-called topologically associating domains or TADs. While TADs appear as nested patterns in the 3C-based interaction matrices, the vast majority of available TAD callers are based on the hypothesis that TADs are individual and unrelated chromatin structures. Here we introduce TADpole, a computational tool designed to identify and analyze the entire hierarchy of TADs in intra-chromosomal interaction matrices. TADpole combines principal component analysis and constrained hierarchical clustering to provide a set of significant hierarchical chromatin levels in a genomic region of interest. TADpole is robust to data resolution, normalization strategy and sequencing depth. Domain borders defined by TADpole are enriched in main architectural proteins (CTCF and cohesin complex subunits) and in the histone mark H3K4me3, while their domain bodies, depending on their activation-state, are enriched in either H3K36me3 or H3K27me3, highlighting that TADpole is able to distinguish functional TAD units. Additionally, we demonstrate that TADpole's hierarchical annotation, together with the new DiffT score, allows for detecting significant topological differences on Capture Hi-C maps between wild-type and genetically engineered mouse.

scholarly journals 3D reconstruction of genomic regions from sparse interaction data

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Julen Mendieta-Esteban ◽  
Marco Di Stefano ◽  
David Castillo ◽  
Irene Farabella ◽  
Marc A Marti-Renom
Keyword(s):  
3D Models ◽  
Genomic Region ◽  
Gene Promoters ◽  
Chromosome Conformation ◽  
The Matrix ◽  
Chromatin Structural ◽  
A Cell ◽  
Similar Accuracy ◽  
Genomic Regions ◽  
Interaction Matrices

Abstract Chromosome conformation capture (3C) technologies measure the interaction frequency between pairs of chromatin regions within the nucleus in a cell or a population of cells. Some of these 3C technologies retrieve interactions involving non-contiguous sets of loci, resulting in sparse interaction matrices. One of such 3C technologies is Promoter Capture Hi-C (pcHi-C) that is tailored to probe only interactions involving gene promoters. As such, pcHi-C provides sparse interaction matrices that are suitable to characterize short- and long-range enhancer–promoter interactions. Here, we introduce a new method to reconstruct the chromatin structural (3D) organization from sparse 3C-based datasets such as pcHi-C. Our method allows for data normalization, detection of significant interactions and reconstruction of the full 3D organization of the genomic region despite of the data sparseness. Specifically, it builds, with as low as the 2–3% of the data from the matrix, reliable 3D models of similar accuracy of those based on dense interaction matrices. Furthermore, the method is sensitive enough to detect cell-type-specific 3D organizational features such as the formation of different networks of active gene communities.

scholarly journals Shh and ZRS enhancer co-localisation is specific to the zone of polarizing activity

2016 ◽  
Author(s):  
Iain Williamson ◽  
Laura A. Lettice ◽  
Robert E. Hill ◽  
Wendy A. Bickmore
Keyword(s):  
Developmental Stages ◽  
In Situ Hybridisation ◽  
Super Resolution ◽  
Genomic Region ◽  
Limb Bud ◽  
Fluorescence In Situ Hybridisation ◽  
Chromosome Conformation ◽  
Active Enhancer ◽  
Mouse Limb ◽  
Zone Of Polarizing Activity

AbstractLimb-specific Shh expression is regulated by the (~1 Mb distant) ZRS enhancer. In the mouse, limb bud restricted spatiotemporal expression of Shh occurs from ~E10-E11.5 at the distal posterior margin and is essential for correct autopod formation. Here, we have analysed the higher-order chromatin conformation of Shh in expressing and non-expressing tissues, both by fluorescence in situ hybridisation (FISH) and by chromosome conformation capture (5C). Conventional and super-resolution light microscopy identified significantly elevated frequencies of Shh/ZRS co-localisation only in the Shh expressing regions of the limb bud. However, Shh-ZRS spatial distances were consistently shorter than intervening distances to a neural enhancer in all tissues and developmental stages analysed. 5C identified a topologically associating domain (TAD) over the Shh/ZRS genomic region and enriched interactions between Shh and ZRS throughout E11.5 embryos. Shh/ZRS co-localisation, therefore, correlates with the spatiotemporal domain of limb bud-specific Shh expression, but close Shh/ZRS proximity in the nucleus occurs regardless of whether the gene or enhancer is active. We suggest that this constrained chromatin configuration optimises the opportunity for the active enhancer to locate and instigate Shh expression.

scholarly journals Super-Resolution Imaging of Tight and Adherens Junctions: Challenges and Open Questions

2020 ◽  
Vol 21 (3) ◽  
pp. 744 ◽  
Author(s):  
Hannes Gonschior ◽  
Volker Haucke ◽  
Martin Lehmann
Keyword(s):  
Single Molecule ◽  
Imaging Techniques ◽  
Rapid Development ◽  
Ion Homeostasis ◽  
Super Resolution ◽  
Stimulated Emission ◽  
Molecular Architecture ◽  
Structured Illumination ◽  
Structured Illumination Microscopy ◽  
Resolution Imaging

The tight junction (TJ) and the adherens junction (AJ) bridge the paracellular cleft of epithelial and endothelial cells. In addition to their role as protective barriers against bacteria and their toxins they maintain ion homeostasis, cell polarity, and mechano-sensing. Their functional loss leads to pathological changes such as tissue inflammation, ion imbalance, and cancer. To better understand the consequences of such malfunctions, the junctional nanoarchitecture is of great importance since it remains so far largely unresolved, mainly because of major difficulties in dynamically imaging these structures at sufficient resolution and with molecular precision. The rapid development of super-resolution imaging techniques ranging from structured illumination microscopy (SIM), stimulated emission depletion (STED) microscopy, and single molecule localization microscopy (SMLM) has now enabled molecular imaging of biological specimens from cells to tissues with nanometer resolution. Here we summarize these techniques and their application to the dissection of the nanoscale molecular architecture of TJs and AJs. We propose that super-resolution imaging together with advances in genome engineering and functional analyses approaches will create a leap in our understanding of the composition, assembly, and function of TJs and AJs at the nanoscale and, thereby, enable a mechanistic understanding of their dysfunction in disease.

scholarly journals 3D reconstruction of genomic regions from sparse interaction data

2020 ◽  
Author(s):  
Julen Mendieta-Esteban ◽  
Marco Di Stefano ◽  
David Castillo ◽  
Irene Farabella ◽  
Marc A Marti-Renom
Keyword(s):  
Genomic Region ◽  
Gene Promoters ◽  
Chromosome Conformation ◽  
Data Sparseness ◽  
The Matrix ◽  
Chromatin Structural ◽  
A Cell ◽  
Cell Type Specific ◽  
Genomic Regions ◽  
Interaction Matrices

AbstractChromosome Conformation Capture (3C) technologies measure the interaction frequency between pairs of chromatin regions within the nucleus in a cell or a population of cells. Some of these 3C technologies retrieve interactions involving non-contiguous sets of loci, resulting in sparse interaction matrices. One of such 3C technologies is Promoter Capture Hi-C (pcHi-C) that is tailored to probe only interactions involving gene promoters. As such, pcHi-C provides sparse interaction matrices that are suitable to characterise short- and long-range enhancer-promoter interactions. Here, we introduce a new method to reconstruct the chromatin structural (3D) organisation from sparse 3C-based datasets such as pcHi-C. Our method allows for data normalisation, detection of significant interactions, and reconstruction of the full 3D organisation of the genomic region despite of the data sparseness. Specifically, it produces reliable reconstructions, in line with the ones obtained from dense interaction matrices, with as low as the 2-3% of the data from the matrix. Furthermore, the method is sensitive enough to detect cell-type-specific 3D organisational features such as the formation of different networks of active gene communities.

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