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Using positional information to provide context for biological image analysis with MorphoGraphX 2.0.

Sören Strauss1, Adam Runions1, Brendan Lane1,2

  • 1Max Planck Institute for Plant Breeding Research, Department of Comparative Development and Genetics, Cologne, Germany.

Elife
|May 5, 2022
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Summary

This study introduces MorphoGraphX software updates to map local coordinate systems in developing organs. This allows precise quantification of gene expression and growth dynamics, aiding understanding of developmental biology.

Keywords:
A. thalianaconvolutional neural networksdevelopmental biologymorphogenesisplant biologypositional informationquantificationsegmentation

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Area of Science:

  • Developmental Biology
  • Computational Biology
  • Systems Biology

Background:

  • Positional information guides organ development through morphogen gradients.
  • Understanding gene expression and growth dynamics requires spatial context.

Purpose of the Study:

  • To present advances in MorphoGraphX software for annotating developing organs with local coordinate systems.
  • To enable quantification of gene expression and growth within these spatial contexts.

Main Methods:

  • Utilizing MorphoGraphX software for generalized framework implementation.
  • Annotating microscopy data with organ-centric local coordinate systems.

Main Results:

  • Introduction of a framework to define local coordinate systems within developing organs.
  • Enabling quantification of gene expression and growth relative to positional information.

Conclusions:

  • MorphoGraphX advances facilitate the study of how positional cues direct morphogenesis.
  • This provides a quantitative approach to link molecular networks with emergent organ forms.