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Colocalization of Coregulated Genes: A Steered Molecular Dynamics Study of Human Chromosome 19

Overview of attention for article published in PLoS Computational Biology, March 2013
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Title
Colocalization of Coregulated Genes: A Steered Molecular Dynamics Study of Human Chromosome 19
Published in
PLoS Computational Biology, March 2013
DOI 10.1371/journal.pcbi.1003019
Pubmed ID
Authors

Marco Di Stefano, Angelo Rosa, Vincenzo Belcastro, Diego di Bernardo, Cristian Micheletti

Abstract

The connection between chromatin nuclear organization and gene activity is vividly illustrated by the observation that transcriptional coregulation of certain genes appears to be directly influenced by their spatial proximity. This fact poses the more general question of whether it is at all feasible that the numerous genes that are coregulated on a given chromosome, especially those at large genomic distances, might become proximate inside the nucleus. This problem is studied here using steered molecular dynamics simulations in order to enforce the colocalization of thousands of knowledge-based gene sequences on a model for the gene-rich human chromosome 19. Remarkably, it is found that most (≈ 88%) gene pairs can be brought simultaneously into contact. This is made possible by the low degree of intra-chromosome entanglement and the large number of cliques in the gene coregulatory network. A clique is a set of genes coregulated all together as a group. The constrained conformations for the model chromosome 19 are further shown to be organized in spatial macrodomains that are similar to those inferred from recent HiC measurements. The findings indicate that gene coregulation and colocalization are largely compatible and that this relationship can be exploited to draft the overall spatial organization of the chromosome in vivo. The more general validity and implications of these findings could be investigated by applying to other eukaryotic chromosomes the general and transferable computational strategy introduced here.

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Geographical breakdown

Country Count As %
Italy 3 3%
United Kingdom 1 <1%
United States 1 <1%
Spain 1 <1%
Unknown 102 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 30 28%
Student > Ph. D. Student 22 20%
Student > Master 9 8%
Professor > Associate Professor 8 7%
Professor 5 5%
Other 23 21%
Unknown 11 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 42 39%
Physics and Astronomy 20 19%
Biochemistry, Genetics and Molecular Biology 19 18%
Engineering 6 6%
Computer Science 5 5%
Other 4 4%
Unknown 12 11%