| Abstract Detail
Kaplan Memorial Lecture - Dan Chitwood Chitwood, Dan [1]. Persistent homology and organismal theory: quantifying the branching topologies of plants. Morphology in plants arises at the organismal level, rather than as an emergent property from the collective behavior of cells. Some siphonous algae developed convergent morphologies with land plants, but dramatically uncouple morphology from cell division. The green alga Caulerpa is arguably the largest single celled organism in the world yet is differentiated into leaf, stem, and root analogs. I will present results of a de novo assembled intra-cellular transcriptomic atlas of the giant coenocyte Caulepra taxifolia. Gene expression patterns are organized along an apical-basal gradient from the frond tip to the stolon and holdfasts that roughly corresponds to the flow of genetic information in the cell, from transcription to translation. I will also present evidence that similar cohorts of transcripts have been recruited to form organs between Caulerpa and the land plants. An organismal theory of plants emphasizes the overall plant form—rather than cells and histogenesis—as the focus of plant morphology. I will end with a discussion of a promising new topological technique, persistent homology, which unlike traditional morphometric approaches can capture the branching architectures of plants. I will describe the application of persistent homology to leaf shape, leaflet serrations, and root architecture in the same plants that reveals a shared genetic basis for these diverse features in tomato introgression lines. I will end with a preview of applying persistent homology to predict plant family and location independently of each other in >170,000 leaves, and quantifying the complex, 3D branching architectures of roots and inflorescences using X-ray Computed Tomography.
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1 - Independent Researcher
Keywords:
none specified
Presentation Type: Special Presentation
Session: S5, Kaplan Memorial Lecture
Location: Sundance 2/Omni Hotel
Date: Tuesday, June 27th, 2017
Time: 3:30 PM
Number: S5001
Abstract ID:730
Candidate for Awards:None |
