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Threshold response to stochasticity in morphogenesis
During development of biological organisms, multiple complex structures are formed. In many instances, these structures need to exhibit a high degree of order to be functional, although many of their constituents are intrinsically stochastic. Hence, it has been suggested that biological robustness u...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6353092/ https://www.ncbi.nlm.nih.gov/pubmed/30699125 http://dx.doi.org/10.1371/journal.pone.0210088 |
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author | Courcoubetis, George Ali, Sammi Nuzhdin, Sergey V. Marjoram, Paul Haas, Stephan |
author_facet | Courcoubetis, George Ali, Sammi Nuzhdin, Sergey V. Marjoram, Paul Haas, Stephan |
author_sort | Courcoubetis, George |
collection | PubMed |
description | During development of biological organisms, multiple complex structures are formed. In many instances, these structures need to exhibit a high degree of order to be functional, although many of their constituents are intrinsically stochastic. Hence, it has been suggested that biological robustness ultimately must rely on complex gene regulatory networks and clean-up mechanisms. Here we explore developmental processes that have evolved inherent robustness against stochasticity. In the context of the Drosophila eye disc, multiple optical units, ommatidia, develop into crystal-like patterns. During the larva-to-pupa stage of metamorphosis, the centers of the ommatidia are specified initially through the diffusion of morphogens, followed by the specification of R8 cells. Establishing the R8 cell is crucial in setting up the geometric, and functional, relationships of cells within an ommatidium and among neighboring ommatidia. Here we study an PDE mathematical model of these spatio-temporal processes in the presence of parametric stochasticity, defining and applying measures that quantify order within the resulting spatial patterns. We observe a universal sigmoidal response to increasing transcriptional noise. Ordered patterns persist up to a threshold noise level in the model parameters. In accordance with prior qualitative observations, as the noise is further increased past a threshold point of no return, these ordered patterns rapidly become disordered. Such robustness in development allows for the accumulation of genetic variation without any observable changes in phenotype. We argue that the observed sigmoidal dependence introduces robustness allowing for sizable amounts of genetic variation and transcriptional noise to be tolerated in natural populations without resulting in phenotype variation. |
format | Online Article Text |
id | pubmed-6353092 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-63530922019-02-15 Threshold response to stochasticity in morphogenesis Courcoubetis, George Ali, Sammi Nuzhdin, Sergey V. Marjoram, Paul Haas, Stephan PLoS One Research Article During development of biological organisms, multiple complex structures are formed. In many instances, these structures need to exhibit a high degree of order to be functional, although many of their constituents are intrinsically stochastic. Hence, it has been suggested that biological robustness ultimately must rely on complex gene regulatory networks and clean-up mechanisms. Here we explore developmental processes that have evolved inherent robustness against stochasticity. In the context of the Drosophila eye disc, multiple optical units, ommatidia, develop into crystal-like patterns. During the larva-to-pupa stage of metamorphosis, the centers of the ommatidia are specified initially through the diffusion of morphogens, followed by the specification of R8 cells. Establishing the R8 cell is crucial in setting up the geometric, and functional, relationships of cells within an ommatidium and among neighboring ommatidia. Here we study an PDE mathematical model of these spatio-temporal processes in the presence of parametric stochasticity, defining and applying measures that quantify order within the resulting spatial patterns. We observe a universal sigmoidal response to increasing transcriptional noise. Ordered patterns persist up to a threshold noise level in the model parameters. In accordance with prior qualitative observations, as the noise is further increased past a threshold point of no return, these ordered patterns rapidly become disordered. Such robustness in development allows for the accumulation of genetic variation without any observable changes in phenotype. We argue that the observed sigmoidal dependence introduces robustness allowing for sizable amounts of genetic variation and transcriptional noise to be tolerated in natural populations without resulting in phenotype variation. Public Library of Science 2019-01-30 /pmc/articles/PMC6353092/ /pubmed/30699125 http://dx.doi.org/10.1371/journal.pone.0210088 Text en © 2019 Courcoubetis et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Courcoubetis, George Ali, Sammi Nuzhdin, Sergey V. Marjoram, Paul Haas, Stephan Threshold response to stochasticity in morphogenesis |
title | Threshold response to stochasticity in morphogenesis |
title_full | Threshold response to stochasticity in morphogenesis |
title_fullStr | Threshold response to stochasticity in morphogenesis |
title_full_unstemmed | Threshold response to stochasticity in morphogenesis |
title_short | Threshold response to stochasticity in morphogenesis |
title_sort | threshold response to stochasticity in morphogenesis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6353092/ https://www.ncbi.nlm.nih.gov/pubmed/30699125 http://dx.doi.org/10.1371/journal.pone.0210088 |
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