Data-Driven Polymer Model for Mechanistic Exploration of Diploid Genome Organization
© 2020 Biophysical Society Chromosomes are positioned nonrandomly inside the nucleus to coordinate with their transcriptional activity. The molecular mechanisms that dictate the global genome organization and the nuclear localization of individual chromosomes are not fully understood. We introduce a...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier BV
2022
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| Online Access: | https://hdl.handle.net/1721.1/141342 |
| _version_ | 1826204481846509568 |
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| author | Qi, Yifeng Reyes, Alejandro Johnstone, Sarah E Aryee, Martin J Bernstein, Bradley E Zhang, Bin |
| author_facet | Qi, Yifeng Reyes, Alejandro Johnstone, Sarah E Aryee, Martin J Bernstein, Bradley E Zhang, Bin |
| author_sort | Qi, Yifeng |
| collection | MIT |
| description | © 2020 Biophysical Society Chromosomes are positioned nonrandomly inside the nucleus to coordinate with their transcriptional activity. The molecular mechanisms that dictate the global genome organization and the nuclear localization of individual chromosomes are not fully understood. We introduce a polymer model to study the organization of the diploid human genome. It is data-driven because all parameters can be derived from Hi-C data; it is also a mechanistic model because the energy function is explicitly written out based on a few biologically motivated hypotheses. These two features distinguish the model from existing approaches and make it useful both for reconstructing genome structures and for exploring the principles of genome organization. We carried out extensive validations to show that simulated genome structures reproduce a wide variety of experimental measurements, including chromosome radial positions and spatial distances between homologous pairs. Detailed mechanistic investigations support the importance of both specific interchromosomal interactions and centromere clustering for chromosome positioning. We anticipate the polymer model, when combined with Hi-C experiments, to be a powerful tool for investigating large-scale rearrangements in genome structure upon cell differentiation and tumor progression. |
| first_indexed | 2024-09-23T12:56:17Z |
| format | Article |
| id | mit-1721.1/141342 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T12:56:17Z |
| publishDate | 2022 |
| publisher | Elsevier BV |
| record_format | dspace |
| spelling | mit-1721.1/1413422022-03-24T03:20:16Z Data-Driven Polymer Model for Mechanistic Exploration of Diploid Genome Organization Qi, Yifeng Reyes, Alejandro Johnstone, Sarah E Aryee, Martin J Bernstein, Bradley E Zhang, Bin © 2020 Biophysical Society Chromosomes are positioned nonrandomly inside the nucleus to coordinate with their transcriptional activity. The molecular mechanisms that dictate the global genome organization and the nuclear localization of individual chromosomes are not fully understood. We introduce a polymer model to study the organization of the diploid human genome. It is data-driven because all parameters can be derived from Hi-C data; it is also a mechanistic model because the energy function is explicitly written out based on a few biologically motivated hypotheses. These two features distinguish the model from existing approaches and make it useful both for reconstructing genome structures and for exploring the principles of genome organization. We carried out extensive validations to show that simulated genome structures reproduce a wide variety of experimental measurements, including chromosome radial positions and spatial distances between homologous pairs. Detailed mechanistic investigations support the importance of both specific interchromosomal interactions and centromere clustering for chromosome positioning. We anticipate the polymer model, when combined with Hi-C experiments, to be a powerful tool for investigating large-scale rearrangements in genome structure upon cell differentiation and tumor progression. 2022-03-23T15:42:18Z 2022-03-23T15:42:18Z 2020 2022-03-23T15:36:53Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/141342 Qi, Yifeng, Reyes, Alejandro, Johnstone, Sarah E, Aryee, Martin J, Bernstein, Bradley E et al. 2020. "Data-Driven Polymer Model for Mechanistic Exploration of Diploid Genome Organization." Biophysical Journal, 119 (9). en 10.1016/J.BPJ.2020.09.009 Biophysical Journal Creative Commons Attribution-NonCommercial-NoDerivs License http://creativecommons.org/licenses/by-nc-nd/4.0/ application/pdf Elsevier BV Other repository |
| spellingShingle | Qi, Yifeng Reyes, Alejandro Johnstone, Sarah E Aryee, Martin J Bernstein, Bradley E Zhang, Bin Data-Driven Polymer Model for Mechanistic Exploration of Diploid Genome Organization |
| title | Data-Driven Polymer Model for Mechanistic Exploration of Diploid Genome Organization |
| title_full | Data-Driven Polymer Model for Mechanistic Exploration of Diploid Genome Organization |
| title_fullStr | Data-Driven Polymer Model for Mechanistic Exploration of Diploid Genome Organization |
| title_full_unstemmed | Data-Driven Polymer Model for Mechanistic Exploration of Diploid Genome Organization |
| title_short | Data-Driven Polymer Model for Mechanistic Exploration of Diploid Genome Organization |
| title_sort | data driven polymer model for mechanistic exploration of diploid genome organization |
| url | https://hdl.handle.net/1721.1/141342 |
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