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Regeneration is the process of restoring injured or lost tissues, organs, or body parts. While simpler organisms generally show greater ability to regenerate their whole body, few complex animals show similarly exceptional regeneration. For example, planarian flatworms have a unique regenerative potential making them a popular study organism among biologists to understand the mechanisms of whole body regeneration. Other organisms, such as hydra, also show extreme regeneration potential;...
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Surgical Ablation Assay for Studying Eye Regeneration in Planarians
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Curation and annotation of planarian gene expression patterns with segmented reference morphologies.

Joy Roy1, Eric Cheung1, Junaid Bhatti1

  • 1Department of Biological Sciences, University of Maryland, Baltimore County, Baltimore, MD 21250, USA.

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|January 18, 2020
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Summary

We developed a computational method and software (PlanGexQ) to standardize and analyze spatial gene expression and morphology data in planarian worms. This approach facilitates knowledge extraction and mechanistic model development in regenerative biology.

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Area of Science:

  • Developmental Biology
  • Regenerative Biology
  • Computational Biology

Background:

  • Large-scale morphological and gene expression data are rapidly generated in developmental and regenerative biology.
  • Extracting knowledge from these datasets is challenging due to a lack of formalization methods and tools.
  • Formalizing spatial phenotypes and gene expression is particularly difficult in organisms with variable morphologies like planarians.

Purpose of the Study:

  • To present a computational methodology and mathematical formalism for encoding and curating spatial phenotypes and gene expression patterns in planaria.
  • To enable the centralized, standardized annotation and analysis of complex experimental data in planarians.
  • To facilitate the extraction of knowledge and reverse-engineering of mechanistic models in regenerative organisms.

Main Methods:

  • Encoding planarian morphologies using mathematical graphs based on anatomical ontology terms to generate reference morphologies.
  • Registering gene expression patterns to standard reference morphologies.
  • Automatic annotation of spatial expression patterns and textual descriptions with anatomical ontology terms.

Main Results:

  • A standardized computational methodology and mathematical formalism for planarian data.
  • A user-friendly graphical software tool, PlanGexQ, implementing the methodology.
  • A centralized, standardized dataset enabling knowledge extraction and mechanistic model development.

Conclusions:

  • The presented methodology and tool standardize the analysis of complex morphological and gene expression data in planaria.
  • This approach overcomes limitations in formalizing spatial phenotypes and gene expression in highly regenerative organisms.
  • Enables advanced data-driven insights and mechanistic model development in planarian research and other regenerative systems.