A dynamical model reveals gene co-localizations in nucleus.
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 subnuclea...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2011-07-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1002094&type=printable |
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| _version_ | 1849331195369750528 |
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| author | Jing Kang Bing Xu Ye Yao Wei Lin Conor Hennessy Peter Fraser Jianfeng Feng |
| author_facet | Jing Kang Bing Xu Ye Yao Wei Lin Conor Hennessy Peter Fraser Jianfeng Feng |
| author_sort | Jing Kang |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-e19c2736161b4c1a94794155d9c0d34b |
| institution | Kabale University |
| issn | 1553-734X 1553-7358 |
| language | English |
| publishDate | 2011-07-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj-art-e19c2736161b4c1a94794155d9c0d34b2025-08-20T03:46:42ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582011-07-0177e100209410.1371/journal.pcbi.1002094A dynamical model reveals gene co-localizations in nucleus.Jing KangBing XuYe YaoWei LinConor HennessyPeter FraserJianfeng FengCo-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.https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1002094&type=printable |
| spellingShingle | Jing Kang Bing Xu Ye Yao Wei Lin Conor Hennessy Peter Fraser Jianfeng Feng A dynamical model reveals gene co-localizations in nucleus. PLoS Computational Biology |
| title | A dynamical model reveals gene co-localizations in nucleus. |
| title_full | A dynamical model reveals gene co-localizations in nucleus. |
| title_fullStr | A dynamical model reveals gene co-localizations in nucleus. |
| title_full_unstemmed | A dynamical model reveals gene co-localizations in nucleus. |
| title_short | A dynamical model reveals gene co-localizations in nucleus. |
| title_sort | dynamical model reveals gene co localizations in nucleus |
| url | https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1002094&type=printable |
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