Topological Domains, Metagenes, and the Emergence of Pleiotropic Regulations at Hox Loci

Author(s):  
Fabrice Darbellay ◽  
Denis Duboule
Keyword(s):  
Genome ◽  
2013 ◽  
Vol 56 (7) ◽  
pp. 415-423 ◽  
Author(s):  
Jingjing Zhao ◽  
Hongbo Shi ◽  
Nadav Ahituv

Tissue-specific gene expression is thought to be one of the major forces shaping mammalian gene order. A recent study that used whole-genome chromosome conformation assays has shown that the mammalian genome is divided into specific topological domains that are shared between different tissues and organisms. Here, we wanted to assess whether gene expression and regulation are involved in shaping these domains and can be used to classify them. We analyzed gene expression and regulation levels in these domains by using RNA-seq and enhancer-associated ChIP-seq datasets for 17 different mouse tissues. We found 162 domains that are active (high gene expression and regulation) in all 17 tissues. These domains are significantly shorter, contain less repeats, and have more housekeeping genes. In contrast, we found 29 domains that are inactive (low gene expression and regulation) in all analyzed tissues and are significantly longer, have more repeats, and gene deserts. Tissue-specific active domains showed some correlation with tissue-type and gene ontology. Domain temporal gene regulation and expression differences also displayed some gene ontology terms fitting their temporal function. Combined, our results provide a catalog of shared and tissue-specific topological domains and suggest that gene expression and regulation could have a role in shaping them.


2015 ◽  
Vol 29 (14) ◽  
pp. 1507-1523 ◽  
Author(s):  
Artyom A. Alekseyenko ◽  
Erica M. Walsh ◽  
Xin Wang ◽  
Adlai R. Grayson ◽  
Peter T. Hsi ◽  
...  

Epigenomes ◽  
2019 ◽  
Vol 3 (2) ◽  
pp. 12 ◽  
Author(s):  
Miguel Vidal

The Polycomb system is made of an evolutionary ancient group of proteins, present throughout plants and animals. Known initially from developmental studies with the fly Drosophila melanogaster, they were associated with stable sustainment of gene repression and maintenance of cell identity. Acting as multiprotein assemblies with an ability to modify chromatin, through chemical additions to histones and organization of topological domains, they have been involved subsequently in control of developmental transitions and in cell homeostasis. Recent work has unveiled an association of Polycomb components with transcriptionally active loci and the promotion of gene expression, in clear contrast with conventional recognition as repressors. Focusing on mammalian models, I review here advances concerning roles in transcriptional control. Among new findings highlighted is the regulation of their catalytic properties, recruiting to targets, and activities in chromatin organization and compartmentalization. The need for a more integrated approach to the study of the Polycomb system, given its fundamental complexity and its adaptation to cell context, is discussed.


2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Minji Kim ◽  
Meizhen Zheng ◽  
Simon Zhongyuan Tian ◽  
Byoungkoo Lee ◽  
Jeffrey H. Chuang ◽  
...  

AbstractThe single-molecule multiplex chromatin interaction data are generated by emerging 3D genome mapping technologies such as GAM, SPRITE, and ChIA-Drop. These datasets provide insights into high-dimensional chromatin organization, yet introduce new computational challenges. Thus, we developed MIA-Sig, an algorithmic solution based on signal processing and information theory. We demonstrate its ability to de-noise the multiplex data, assess the statistical significance of chromatin complexes, and identify topological domains and frequent inter-domain contacts. On chromatin immunoprecipitation (ChIP)-enriched data, MIA-Sig can clearly distinguish the protein-associated interactions from the non-specific topological domains. Together, MIA-Sig represents a novel algorithmic framework for multiplex chromatin interaction analysis.


2000 ◽  
Vol 275 (30) ◽  
pp. 23295-23302 ◽  
Author(s):  
Michael L. Schlador ◽  
Robert D. Grubbs ◽  
Neil M. Nathanson

PLoS ONE ◽  
2017 ◽  
Vol 12 (3) ◽  
pp. e0172725 ◽  
Author(s):  
Sherif El-Sharnouby ◽  
Bettina Fischer ◽  
Jose Paolo Magbanua ◽  
Benjamin Umans ◽  
Rosalyn Flower ◽  
...  

Genes ◽  
2015 ◽  
Vol 6 (3) ◽  
pp. 734-750 ◽  
Author(s):  
Vuthy Ea ◽  
Marie-Odile Baudement ◽  
Annick Lesne ◽  
Thierry Forné

2017 ◽  
Vol 18 (1) ◽  
Author(s):  
Qingjiao Li ◽  
Harianto Tjong ◽  
Xiao Li ◽  
Ke Gong ◽  
Xianghong Jasmine Zhou ◽  
...  

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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