Geometric models for robust encoding of dynamical information into embryonic patterns

  1. Laurent Jutras-Dubé
  2. Ezzat El-Sherif  Is a corresponding author
  3. Paul François  Is a corresponding author
  1. McGill University, Canada
  2. Friedrich-Alexander Universität Erlangen-Nürnberg, Germany

Abstract

During development, cells gradually assume specialized fates via changes of transcriptional dynamics, sometimes even within the same developmental stage. For anterior-posterior (AP) patterning in metazoans, it has been suggested that the gradual transition from a dynamic genetic regime to a static one is encoded by different transcriptional modules. In that case, the static regime has an essential role in pattern formation in addition to its maintenance function. In this work, we introduce a geometric approach to study such transition. We exhibit two types of genetic regime transitions, respectively arising through local or global bifurcations. We find that the global bifurcation type is more generic, more robust, and better preserves dynamical information. This could parsimoniously explain common features of metazoan segmentation, such as changes of periods leading to waves of gene expressions, 'speed/frequency-gradient' dynamics, and changes of wave patterns. Geometric approaches appear as possible alternatives to gene regulatory networks to understand development.

Data availability

https://github.com/laurentjutrasdube/Dual-Regime_Geometry_for_Embryonic_Patterning

The following data sets were generated

Article and author information

Author details

  1. Laurent Jutras-Dubé

    Physics, McGill University, Montreal, Canada
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4323-2840
  2. Ezzat El-Sherif

    Department of Biology, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
    For correspondence
    ezzat.el-sherif@fau.de
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1738-8139
  3. Paul François

    Physics, McGill University, Montreal, Canada
    For correspondence
    paul.francois2@mcgill.ca
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2223-839X

Funding

Simons Foundation (MMLS)

  • Laurent Jutras-Dubé
  • Paul François

Natural Sciences and Engineering Research Council of Canada (CREATE in Complex Dynamics)

  • Laurent Jutras-Dubé

Deutsche Forschungsgemeinschaft (EL 870/2-1)

  • Ezzat El-Sherif

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2020, Jutras-Dubé et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 1,963
    views
  • 319
    downloads
  • 29
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Laurent Jutras-Dubé
  2. Ezzat El-Sherif
  3. Paul François
(2020)
Geometric models for robust encoding of dynamical information into embryonic patterns
eLife 9:e55778.
https://doi.org/10.7554/eLife.55778

Share this article

https://doi.org/10.7554/eLife.55778

Further reading

    1. Developmental Biology
    2. Evolutionary Biology
    Simon Rethemeier, Sonja Fritzsche ... Vera S Hunnekuhl
    Research Article

    The insect brain and the timing of its development underwent evolutionary adaptations. However, little is known about the underlying developmental processes. The central complex of the brain is an excellent model to understand neural development and divergence. It is produced in large parts by type II neuroblasts, which produce intermediate progenitors, another type of cycling precursor, to increase their neural progeny. Type II neuroblasts lineages are believed to be conserved among insects, but little is known on their molecular characteristics in insects other than flies. Tribolium castaneum has emerged as a model for brain development and evolution. However, type II neuroblasts have so far not been studied in this beetle. We created a fluorescent enhancer trap marking expression of Tc-fez/earmuff, a key marker for intermediate progenitors. Using combinatorial labeling of further markers, including Tc-pointed, we characterized embryonic type II neuroblast lineages. Intriguingly, we found nine lineages per hemisphere in the Tribolium embryo while Drosophila produces only eight per brain hemisphere. These embryonic lineages are significantly larger in Tribolium than they are in Drosophila and contain more intermediate progenitors. Finally, we mapped these lineages to the domains of head patterning genes. Notably, Tc-otd is absent from all type II neuroblasts and intermediate progenitors, whereas Tc-six3 marks an anterior subset of the type II lineages. Tc-six4 specifically marks the territory where anterior-medial type II neuroblasts differentiate. In conclusion, we identified a conserved pattern of gene expression in holometabolan central complex forming type II neuroblast lineages, and conserved head patterning genes emerged as new candidates for conferring spatial identity to individual lineages. The higher number and greater lineage size of the embryonic type II neuroblasts in the beetle correlate with a previously described embryonic phase of central complex formation. These findings stipulate further research on the link between stem cell activity and temporal and structural differences in central complex development.

    1. Cell Biology
    2. Developmental Biology
    Jeet H Patel, Mary C Mullins
    Insight

    Disease-causing mutations in the signaling protein BMP4 impair its secretion, but only when it is made as a homodimer.