Combining sea urchin embryo cell lineages by error-tolerant graph matching

Area of Science:

• Developmental Biology
• Computational Biology
• Bioimaging

Background:

• Mapping complete cell lineage trees is crucial for understanding embryonic development.
• Current imaging technologies limit capturing the entire embryogenesis of specimens like sea urchin embryos.
• Partial lineage trees from overlapping time frames necessitate novel combination strategies.

Purpose of the Study:

• To develop a method for concatenating cell lineage trees from two different embryos.
• To create a single, comprehensive lineage tree covering extended developmental periods.
• To overcome imaging limitations in capturing full embryogenesis.

Main Methods:

• Utilized an error-tolerant graph matching strategy.
• Represented cell information at overlapping time points as graphs (nodes=cells, edges=neighborhood relationships).
• Calculated minimal-cost correspondence between cells of different specimens for lineage combination.

Main Results:

• Successfully demonstrated a method for combining partial cell lineage trees.
• Enabled the creation of a more complete cell lineage tree than obtainable from single embryo imaging.
• The graph matching approach effectively identified correspondences between cells across embryos.

Conclusions:

• Concatenating partial cell lineage trees is feasible using graph matching techniques.
• This method extends the temporal coverage of developmental lineage reconstruction.
• Advances in imaging and computational methods are crucial for achieving complete cell lineage mapping.