Digital Embryos: A quantitative geometric analysis of ascidian morphogenesis and its evolution
Informations
- Funding country
France- Acronym
- Dig-Em
- URL
- -
- Start date
- 10/1/2014
- End date
- -
- Budget
- 507,508 EUR
Fundings
| Name | Role | Start | End | Amount |
|---|---|---|---|---|
| AAPG - Generic call for proposals [Appel à projets générique] 2014 | Grant | 10/1/2014 | - | 507,508 EUR |
Abstract
Biodiversity on Earth results from the evolution of two types of developmental programs. Cell patterning and differentiation defines the cell types that are present in an organism. Morphogenesis controls the proper spatial organization of the various cell types. While patterning and cell differentiation have received considerable attention, the genetic and evolutionary drivers of morphogenesis are much less understood. In particular, we very poorly understand why some morphogenetic processes show remarkable evolutionary stability, while others evolve very rapidly. In this project, we will use advanced ligh-sheet imaging of live embryos to quantitatively describe embryonic morphogenesis in ascidians, a class of animals that undergo very rapid genomic divergence, yet show an extraordinary stasis of embryonic morphologies, based on invariant early cell lineages shared by all studied species. The global aims of the proposal, which will bridge micro- and macroevolutionary scales of analysis, are: 1. To provide a global systems-level description at cellular resolution of an animal embryonic program 2. To use this description to characterize intra-specific and inter-specific patterns of morphogenetic variations 3. To analyze possible molecular mechanisms explaining the unusual robustness of this program to environmental and genetic perturbations. To achieve these aims, we will combine advanced live light-sheet microscopy, computational biology, functional gene assays and evolutionary approaches. The project is presented by a team of developmental biologists and two teams of computer scientists. A central part of this research program will be the development of a high-throughput computational framework to analyze and formalize high-throughput 4D imaging data into digital embryos, in order to quantify and formally represent with cellular resolution the average development of an organism and its variations within and between species. In addition to its biological interest, a major output of the project will thus be the development of robust general computational methods for the analysis, visualization and representation of massive high-throughput light-sheet datasets.