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Updated: Jul 13, 2026
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Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
Published on: December 7, 2021
Innovation and robustness in complex regulatory gene networks
S Ciliberti1, O C Martin, A Wagner
1Unité Mixte Recherche 8565, Laboratoire de Physique Théorique et Modèles Statistiques, Université Paris-Sud and Centre National de la Recherche Scientifique, F-91405 Orsay, France.
Summary
Evolutionary innovation in gene expression patterns is facilitated by connected genotype networks. This robustness allows for significant evolutionary changes while maintaining viable phenotypes, enabling long-term biological innovation.
Area of Science:
- Evolutionary biology
- Systems biology
- Genetics
Background:
- Life's history is marked by evolutionary innovations driven by biological organization principles.
- Understanding the mechanisms behind evolutionary innovation, particularly in gene expression, remains a challenge.
Purpose of the Study:
- To investigate the principles of biological organization governing evolutionary innovation in gene expression patterns.
- To analyze how transcriptional regulation networks contribute to evolutionary novelty.
Main Methods:
- Studied a model of transcriptional regulation networks central to embryonic development.
- Represented genotypes as network topologies and phenotypes as steady-state gene expression patterns.
- Analyzed connectivity in genotype space for networks sharing the same phenotype.
Main Results:
- Networks with identical phenotypes form connected graphs in genotype space.
- Evolutionary search on these graphs can access genotypes as diverse as random selections.
- This allows for significant innovation while remaining near a viable phenotype.
Conclusions:
- Robustness to mutations, while potentially hindering short-term innovation, is crucial for long-term evolutionary advancements.
- Connected genotype graphs, providing robustness, are essential for sustained innovation in gene expression patterns.
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