Next Article in Journal
Protein-Related Circular RNAs in Human Pathologies
Next Article in Special Issue
Compete or Coexist? Why the Same Mechanisms of Symmetry Breaking Can Yield Distinct Outcomes
Previous Article in Journal
Discovery of Molecular DNA Methylation-Based Biomarkers through Genome-Wide Analysis of Response Patterns to BCG for Bladder Cancer
Previous Article in Special Issue
Symmetry Breaking during Cell Movement in the Context of Excitability, Kinetic Fine-Tuning and Memory of Pseudopod Formation
Review

A “Numerical Evo-Devo” Synthesis for the Identification of Pattern-Forming Factors

1
Developmental Biology & Cell Biology and Biophysics Units, European Molecular Biology Laboratory, Meyerhofstraße 1, 69117 Heidelberg, Germany
2
Centre for Interdisciplinary Research in Biology, CNRS UMR 7241, INSERM U1050, Collège de France, 75005 Paris, France
3
Department of Mathematics and Volen National Center for Complex Systems, Brandeis University, 415 South Street, Waltham, MA 02453, USA
*
Authors to whom correspondence should be addressed.
Cells 2020, 9(8), 1840; https://doi.org/10.3390/cells9081840
Received: 22 June 2020 / Revised: 22 July 2020 / Accepted: 23 July 2020 / Published: 5 August 2020
(This article belongs to the Special Issue Symmetry Breaking in Cells and Tissues)
Animals display extensive diversity in motifs adorning their coat, yet these patterns have reproducible orientation and periodicity within species or groups. Morphological variation has been traditionally used to dissect the genetic basis of evolutionary change, while pattern conservation and stability in both mathematical and organismal models has served to identify core developmental events. Two patterning theories, namely instruction and self-organisation, emerged from this work. Combined, they provide an appealing explanation for how natural patterns form and evolve, but in vivo factors underlying these mechanisms remain elusive. By bridging developmental biology and mathematics, novel frameworks recently allowed breakthroughs in our understanding of pattern establishment, unveiling how patterning strategies combine in space and time, or the importance of tissue morphogenesis in generating positional information. Adding results from surveys of natural variation to these empirical-modelling dialogues improves model inference, analysis, and in vivo testing. In this evo-devo-numerical synthesis, mathematical models have to reproduce not only given stable patterns but also the dynamics of their emergence, and the extent of inter-species variation in these dynamics through minimal parameter change. This integrative approach can help in disentangling molecular, cellular and mechanical interaction during pattern establishment. View Full-Text
Keywords: pattern formation; natural variation; modelling pattern formation; natural variation; modelling
Show Figures

Figure 1

MDPI and ACS Style

Bailleul, R.; Manceau, M.; Touboul, J. A “Numerical Evo-Devo” Synthesis for the Identification of Pattern-Forming Factors. Cells 2020, 9, 1840. https://doi.org/10.3390/cells9081840

AMA Style

Bailleul R, Manceau M, Touboul J. A “Numerical Evo-Devo” Synthesis for the Identification of Pattern-Forming Factors. Cells. 2020; 9(8):1840. https://doi.org/10.3390/cells9081840

Chicago/Turabian Style

Bailleul, Richard, Marie Manceau, and Jonathan Touboul. 2020. "A “Numerical Evo-Devo” Synthesis for the Identification of Pattern-Forming Factors" Cells 9, no. 8: 1840. https://doi.org/10.3390/cells9081840

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop