Model sub-cellular transcript patterns with topology

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Topological Data Analysis to characterize transcriptomic spatial distributions

Erik Amézquita1,2     

Sutton Tennant1, Sandra Thibivillers1, Sai Subhash3, Samik Bhattacharya4, Jasper Kläver4, Benjamin Smith5, Marc Libault1

1. Division of Plant Sciences & Technology, University of Missouri, Columbia, MO
2. Department of Mathematics, University of Missouri, Columbia, MO
3. Complex Biosystems Program, University of Nebraska, Lincoln, NE
4. Resolve Biosciences GmbH, Monheim am Rhein, Germany
5. Vision Science group, University of California, Berkeley, CA


Molecular Cartography™

  • Soybean nodule 10µm thick cross-sections.
  • (X,Y,Z) coordinates for 3.7M+ cytosolic transcripts.
  • 97 genes (including 10 bacterial ones).
  • 2938 cells → 918 infected ones.

TDA: A framework that can compare all kinds of spatial distributions and patterns regardless of different cell sizes, shapes, orientations, and transcript number.

Kernel Density Estimation (KDE)

Sub-level set persistence


Persistence diagrams (H1 and H2)

Persistence Images

Relate back to the nodule

  • Senescent cells exhibit a distinct transcriptomic spatial pattern compared to the rest of population.
  • Loss of mRNA localization may be a lesser known contributor to cell senescence.

Acknowledgements

This research was supported by Mizzou Forward and NSF (Awards #2127485 and #1854326). Registration and travel support for this presentation was provided by the National Science Foundation and NSF Project 00087298.