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Spatial modeling of biological patterns shows multiscale organization of Arabidopsis thaliana heterochromatin
The spatial organization in the cell nucleus is tightly linked to genome functions such as gene regulation. Similarly, specific spatial arrangements of biological components such as macromolecular complexes, organelles and cells are involved in many biological functions. Spatial interactions among e...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7801681/ https://www.ncbi.nlm.nih.gov/pubmed/33431919 http://dx.doi.org/10.1038/s41598-020-79158-5 |
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author | Arpòn, Javier Sakai, Kaori Gaudin, Valérie Andrey, Philippe |
author_facet | Arpòn, Javier Sakai, Kaori Gaudin, Valérie Andrey, Philippe |
author_sort | Arpòn, Javier |
collection | PubMed |
description | The spatial organization in the cell nucleus is tightly linked to genome functions such as gene regulation. Similarly, specific spatial arrangements of biological components such as macromolecular complexes, organelles and cells are involved in many biological functions. Spatial interactions among elementary components of biological systems define their relative positioning and are key determinants of spatial patterns. However, biological variability and the lack of appropriate spatial statistical methods and models limit our current ability to analyze these interactions. Here, we developed a framework to dissect spatial interactions and organization principles by combining unbiased statistical tests, multiple spatial descriptors and new spatial models. We used plant constitutive heterochromatin as a model system to demonstrate the potential of our framework. Our results challenge the common view of a peripheral organization of chromocenters, showing that chromocenters are arranged along both radial and lateral directions in the nuclear space and obey a multiscale organization with scale-dependent antagonistic effects. The proposed generic framework will be useful to identify determinants of spatial organizations and to question their interplay with biological functions. |
format | Online Article Text |
id | pubmed-7801681 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-78016812021-01-13 Spatial modeling of biological patterns shows multiscale organization of Arabidopsis thaliana heterochromatin Arpòn, Javier Sakai, Kaori Gaudin, Valérie Andrey, Philippe Sci Rep Article The spatial organization in the cell nucleus is tightly linked to genome functions such as gene regulation. Similarly, specific spatial arrangements of biological components such as macromolecular complexes, organelles and cells are involved in many biological functions. Spatial interactions among elementary components of biological systems define their relative positioning and are key determinants of spatial patterns. However, biological variability and the lack of appropriate spatial statistical methods and models limit our current ability to analyze these interactions. Here, we developed a framework to dissect spatial interactions and organization principles by combining unbiased statistical tests, multiple spatial descriptors and new spatial models. We used plant constitutive heterochromatin as a model system to demonstrate the potential of our framework. Our results challenge the common view of a peripheral organization of chromocenters, showing that chromocenters are arranged along both radial and lateral directions in the nuclear space and obey a multiscale organization with scale-dependent antagonistic effects. The proposed generic framework will be useful to identify determinants of spatial organizations and to question their interplay with biological functions. Nature Publishing Group UK 2021-01-11 /pmc/articles/PMC7801681/ /pubmed/33431919 http://dx.doi.org/10.1038/s41598-020-79158-5 Text en © The Author(s) 2021, corrected publication 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Arpòn, Javier Sakai, Kaori Gaudin, Valérie Andrey, Philippe Spatial modeling of biological patterns shows multiscale organization of Arabidopsis thaliana heterochromatin |
title | Spatial modeling of biological patterns shows multiscale organization of Arabidopsis thaliana heterochromatin |
title_full | Spatial modeling of biological patterns shows multiscale organization of Arabidopsis thaliana heterochromatin |
title_fullStr | Spatial modeling of biological patterns shows multiscale organization of Arabidopsis thaliana heterochromatin |
title_full_unstemmed | Spatial modeling of biological patterns shows multiscale organization of Arabidopsis thaliana heterochromatin |
title_short | Spatial modeling of biological patterns shows multiscale organization of Arabidopsis thaliana heterochromatin |
title_sort | spatial modeling of biological patterns shows multiscale organization of arabidopsis thaliana heterochromatin |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7801681/ https://www.ncbi.nlm.nih.gov/pubmed/33431919 http://dx.doi.org/10.1038/s41598-020-79158-5 |
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