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This study investigates methods for establishing cell-to-cell correspondence in Drosophila embryos, focusing on the optimization of correlations based on gene expression levels. We highlight advantages like treating cells as discrete units and preserving expression discontinuities. Approaches discussed include coarse registration and mesh generation techniques, leveraging computer graphics tools for effective segmentation and model building. By establishing detailed correspondences, we aim to address biological variations and enhance developmental understanding through detailed optimization frameworks.
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Finding correspondences between drosophila embryo Charless Fowlkes, Jitendra Malik UCB Computer Sciences
% egg length coordinate system 10% strip Warp x-axis to align peak features Myasnikova et al (2001)
Advantages: Treats cells as discrete units Discontinuities in expression levels between cells are preserved Given a correspondence, it is easy to find a global coordinate system Cell-to-Cell Correspondence • Cell lineage gives “ground-truth” correspondence
Sources of Variation • Not so interesting: • Staining • Shrinking • Spinning • Squashing • Staging • Interesting: • Biological Variation
Correspondence as Optimzation • Of all possible correspondences between two embryos, find the one which pairs cells with similar expression levels.
Correspondence as Optimzation • Of all possible correspondences between two embryos, find the one which pairs cells with similar expression levels.
Correspondence as Optimzation • Of all possible correspondences between two embryos, find the one which pairs cells with similar expression levels and results in a smooth transformation
Correspondence Overview Nuclear Segmentation Coarse Registration X Y Z Sna Ftz 220.3 40.2 31.0 0.28 0.99 182.4 30.1 44.9 0.22 0.77 . . Detailed Correspondence and Model Building Mesh Generation Feature Extraction
Coarse Registration • Align the center of masses of two embryos • Scale along AP axis in order to match length • Sphere perpendicular to AP axis in order to remove squashing • Rotate along AP axis to align SNA expression pattern
Coarse Registration Scale and Rotate
Correspondence Overview Nuclear Segmentation Coarse Registration X Y Z Sna Ftz 220.3 40.2 31.0 0.28 0.99 182.4 30.1 44.9 0.22 0.77 . . Detailed Correspondence and Model Building Mesh Generation Feature Extraction
Mesh generation • Point cloud doesn’t capture the blastoderm topology. Locally, it is a 2D sheet of cells
Mesh generation • Utilize standard tools from computer graphics and computational geometry
Feedback Mesh Information to Segmentation ? Nuclear Segmentation X Y Z Sna Ftz 220.3 40.2 31.0 0.28 0.99 182.4 30.1 44.9 0.22 0.77 . . Mesh Generation
Correspondence Overview Nuclear Segmentation Coarse Registration X Y Z Sna Ftz 220.3 40.2 31.0 0.28 0.99 182.4 30.1 44.9 0.22 0.77 . . Detailed Correspondence and Model Building Mesh Generation Feature Extraction
Feature Extraction • Extract expression levels in the neighborhood of a given cell by flattening the sheet.
Correspondence Overview Nuclear Segmentation Coarse Registration X Y Z Sna Ftz 220.3 40.2 31.0 0.28 0.99 182.4 30.1 44.9 0.22 0.77 . . Detailed Correspondence and Model Building Mesh Generation Feature Extraction
Detailed Correspondence • Set up quadratic optimzation problem which includes matching and smoothness terms • only considers correspondences between points which are nearby after the coarse registration • 100 fold reduction in potential matches • utilize features extracted from the mesh • much better match accuracy • further pruning • Results…soon
Conclusion • Techniques aimed at cellular correspondence between multiple embroys • Utilize knowledge of embryo topology along with rough alignment to make detailed correspondence tractable