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Spatial Proximity and Similarity of the Epigenetic State of Genome Domains

Overview of attention for article published in PLOS ONE, April 2012
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Title
Spatial Proximity and Similarity of the Epigenetic State of Genome Domains
Published in
PLOS ONE, April 2012
DOI 10.1371/journal.pone.0033947
Pubmed ID
Authors

Ekaterina E. Khrameeva, Andrey A. Mironov, Gennady G. Fedonin, Philipp Khaitovich, Mikhail S. Gelfand

Abstract

Recent studies demonstrate that the organization of the chromatin within the nuclear space might play a crucial role in the regulation of gene expression. The ongoing progress in determination of the 3D structure of the nuclear chromatin allows one to study correlations between spatial proximity of genome domains and their epigenetic state. We combined the data on three-dimensional architecture of the whole human genome with results of high-throughput studies of the chromatin functional state and observed that fragments of different chromosomes that are spatially close tend to have similar patterns of histone modifications, methylation state, DNAse sensitivity, expression level, and chromatin states in general. Moreover, clustering of genome regions by spatial proximity produced compact clusters characterized by the high level of histone modifications and DNAse sensitivity and low methylation level, and loose clusters with the opposite characteristics. We also associated the spatial proximity data with previously detected chimeric transcripts and the results of RNA-seq experiments and observed that the frequency of formation of chimeric transcripts from fragments of two different chromosomes is higher among spatially proximal genome domains. A fair fraction of these chimeric transcripts seems to arise post-transcriptionally via trans-splicing.

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Geographical breakdown

Country Count As %
United States 4 6%
United Kingdom 3 4%
Portugal 1 1%
Mexico 1 1%
Germany 1 1%
Russia 1 1%
Korea, Republic of 1 1%
Unknown 60 83%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 25%
Student > Ph. D. Student 17 24%
Professor > Associate Professor 7 10%
Student > Master 7 10%
Professor 6 8%
Other 14 19%
Unknown 3 4%
Readers by discipline Count As %
Agricultural and Biological Sciences 43 60%
Biochemistry, Genetics and Molecular Biology 10 14%
Computer Science 7 10%
Medicine and Dentistry 4 6%
Engineering 2 3%
Other 1 1%
Unknown 5 7%