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Analysis of the Development of a Morphological Phenotype as a Function of Protein Concentration in Budding Yeast

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Evolution in developmental phenotype space.

Marie-Anne Félix¹

¹Institute of Biology of the Ecole Normale Supérieure, CNRS UMR8197, Inserm U1024, Ecole Normale Supérieure, 46 rue d'Ulm, 75230 Paris cedex 05, France. felix@biologie.ens.fr

Current Opinion in Genetics & Development

|August 29, 2012

Summary

This summary is machine-generated.

Quantitative models reveal how variations in molecular and cellular activities drive diverse developmental patterns. Some genetic changes cause significant morphological evolution, while others lead to cryptic evolution without visible changes.

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Area of Science:

Developmental Biology
Evolutionary Developmental Biology
Systems Biology

Background:

Developmental systems exhibit diverse patterns and morphologies influenced by molecular and cellular activities.
Quantitative modeling offers a framework to explore the full range of phenotypic outputs in developmental systems.
Understanding the link between genetic variation and developmental parameters is crucial for evolutionary studies.

Purpose of the Study:

To review recent studies employing quantitative models to investigate developmental evolution.
To highlight how molecular signaling pathways and their interactions shape phenotypic outcomes.
To discuss the concepts of dramatic morphological change versus cryptic developmental evolution.

Main Methods:

Review of recent research integrating quantitative models with empirical data on molecular signaling pathways.
Exploration of model parameter space to assess the range of phenotypic outputs.
Analysis of how variations in signaling pathway evolution impact morphology.

Main Results:

Quantitative pathway evolution can lead to substantial morphological changes.
Many developmental systems display robustness, where phenotypic output remains stable despite parameter variations, resulting in cryptic evolution.
The relationship between genetic variation and developmental model parameters is an emerging area of research.

Conclusions:

Quantitative modeling is a powerful tool for studying developmental evolution, integrating molecular mechanisms with phenotypic outcomes.
Developmental evolution can manifest as either dramatic morphological shifts or cryptic changes, depending on system robustness.
Further formalization and measurement are needed to fully connect genetic variation to developmental model parameters.