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A dynamical model reveals gene co-localizations in nucleus
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Kang, Jing, Ph.D., Xu, Bing, Yao, Ye, Lin, Wei, Hennessy, Conor, Fraser, Peter and Feng, Jianfeng (2011) A dynamical model reveals gene co-localizations in nucleus. PLoS Computational Biology, Vol.7 (No.7). e1002094. doi:10.1371/journal.pcbi.1002094 ISSN 1553-734X.
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Official URL: http://dx.doi.org/10.1371/journal.pcbi.1002094
Abstract
Co-localization of networks of genes in the nucleus is thought to play an important role in determining gene expression patterns. Based upon experimental data, we built a dynamical model to test whether pure diffusion could account for the observed co-localization of genes within a defined subnuclear region. A simple standard Brownian motion model in two and three dimensions shows that preferential co-localization is possible for co-regulated genes without any direct interaction, and suggests the occurrence may be due to a limitation in the number of available transcription factors. Experimental data of chromatin movements demonstrates that fractional rather than standard Brownian motion is more appropriate to model gene mobilizations, and we tested our dynamical model against recent static experimental data, using a sub-diffusion process by which the genes tend to colocalize more easily. Moreover, in order to compare our model with recently obtained experimental data, we studied the association level between genes and factors, and presented data supporting the validation of this dynamic model. As further applications of our model, we applied it to test against more biological observations. We found that increasing transcription factor number, rather than factory number and nucleus size, might be the reason for decreasing gene co-localization. In the scenario of frequency-or amplitude-modulation of transcription factors, our model predicted that frequency-modulation may increase the co-localization between its targeted genes.
Item Type: | Journal Article | ||||
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Subjects: | Q Science > QA Mathematics Q Science > QH Natural history > QH426 Genetics |
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science Faculty of Science, Engineering and Medicine > Science > Centre for Scientific Computing |
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Library of Congress Subject Headings (LCSH): | Genes -- Mathematical models, Cell nuclei -- Mathematical models, Genetic transcription | ||||
Journal or Publication Title: | PLoS Computational Biology | ||||
Publisher: | Public Library of Science | ||||
ISSN: | 1553-734X | ||||
Official Date: | July 2011 | ||||
Dates: |
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Volume: | Vol.7 | ||||
Number: | No.7 | ||||
Page Range: | e1002094 | ||||
DOI: | 10.1371/journal.pcbi.1002094 | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Access rights to Published version: | Open Access (Creative Commons) | ||||
Date of first compliant deposit: | 18 December 2015 | ||||
Date of first compliant Open Access: | 18 December 2015 | ||||
Funder: | European Union (EU), Engineering and Physical Sciences Research Council (EPSRC), Biotechnology and Biological Sciences Research Council (Great Britain) (BBSRC), Medical Research Council (Great Britain) (MRC) |
Data sourced from Thomson Reuters' Web of Knowledge
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