Understanding how animals generate and regenerate cell diversity: integrating live imaging, lineage tracking, deep learning and big image data visualization – DeepLineage
Understanding how animals generate and regenerate cell diversity
Integrating live imaging, lineage tracking and big image data visualization
Multicellular organisms are made of a wide diversity of cells, all generated from a single cell during development. These cells are generated in the context of a cell genealogy (lineage), which plays an important role in determining their ultimate fate and plasticity. Some animals can also regenerate their body throughout their lifetime, from progenitor cells whose identity/properties are largely unknown. Our goal is to provide a generalised framework for determining and analysing cell lineages, to reveal how cell genealogy impacts cell fate in embryos and regenerating adults.
On the experimental side, we developed genetic tools that help to visualise cell diversity and differentiation during embryonic development and regeneration, and live imaging approaches that allow us to track cell lineages, focusing on the crustacean Parhyale hawaiensis, an experimental model organism where regeneration occurs with exceptional fidelity. On the computational side, we have developed an integrated platform for tracing, visualising, and analysing cell lineages, serving the needs of the wider developmental biology research community.
Multicellular organisms are made of a wide diversity of cells, all generated from a single cell during development. These cells are generated in the context of a cell genealogy (lineage), which plays an important role in determining their ultimate fate and plasticity. Some animals can also regenerate their body throughout their lifetime, from progenitor cells whose identity/properties are largely unknown. Our goal is to provide a generalised framework for determining and analysing cell lineages, to reveal how cell genealogy impacts cell fate in embryos and regenerating adults. On the experimental side, we will develop genetic and live imaging approaches to record cell lineages, focusing on the crustacean Parhyale hawaiensis, an experimental model where regeneration occurs with exceptional fidelity. On the computational side, we will develop an integrated framework for cell tracking (including deep learning), visual rendering and analysis of cell lineages.
Project coordination
Michalis Averof (INSTITUT DE GENOMIQUE FONCTIONNELLE DE LYON)
The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.
Partnership
IGFL INSTITUT DE GENOMIQUE FONCTIONNELLE DE LYON
University of Technology, TU Dresden / DFG Cluster of Excellence 'Physics of Life'
Max Planck Society / Max Planck Institute of Molecular Cell Biology and Genetics (MPI-CBG)
Help of the ANR 399,836 euros
Beginning and duration of the scientific project:
December 2021
- 36 Months