A multiscale computational framework for the development of spines in molluscan shells.

Area of Science:

• Multiscale modeling in developmental biology and biophysics.
• Computational biology and evolutionary developmental biology.

Background:

• Shell formation involves diverse models at molecular and tissue scales, but integrating them is challenging.
• Linking genotype (molecular) to phenotype (tissue mechanics) is crucial for understanding shell development.

Purpose of the Study:

• To propose a modular framework for combining molecular and tissue-level models of shell formation.
• To connect genotype-phenotype relationships with observable shell characteristics and population data.
• To facilitate the association of molecular parameters with distinct shell specimen populations.

Main Methods:

• Utilizing a Quality-Diversity algorithm to explore molecular model outputs (concentration profiles).
• Simulating a mechanical model with diverse growth patterns to generate a library of spine shapes.
• Matching real shell spine images to generated shapes to infer growth patterns and molecular parameters.

Main Results:

• A computational framework successfully integrates molecular and mechanical models for shell formation.
• A library of shell spine shapes was generated, linked to specific molecular parameters.
• The approach was demonstrated on three populations of Turbo sazae, evaluating spine characteristics.

Conclusions:

• The developed framework streamlines the integration of multiscale models in shell formation studies.
• This approach allows for the quantitative linking of molecular mechanisms to phenotypic traits in shell structures.
• The modular design permits easy adaptation and application to various shell formation research questions.