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Exon Recombination02:32

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The evolution of new genes is critical for speciation. Exon recombination, also known as exon shuffling or domain shuffling, is an important means of new gene formation. It is observed across vertebrates, invertebrates, and in some plants such as potatoes and sunflowers. During exon recombination, exons from the same or different genes recombine and produce new exon-intron combinations, which might evolve into new genes. 
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Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
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Published on: December 7, 2021

Extinction and resurrection in gene networks.

Daniel Schultz1, Aleksandra M Walczak, José N Onuchic

  • 1Center for Theoretical Biological Physics, University of California at San Diego, La Jolla, CA 92093-0374, USA.

Proceedings of the National Academy of Sciences of the United States of America
|November 27, 2008
PubMed
Summary

Small molecule numbers in gene regulatory networks lead to extinction and resurrection events, creating stable stochastic attractors not predicted by deterministic models. This impacts understanding of gene switches and phage lysogeny.

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Area of Science:

  • Systems Biology
  • Molecular Biology
  • Biophysics

Background:

  • Gene regulatory networks (GRNs) govern cellular functions.
  • Stochasticity in GRNs becomes significant at low molecular counts.
  • Deterministic models fail to capture extinction-driven dynamics.

Purpose of the Study:

  • Investigate the impact of molecular extinction and resurrection on attractor landscapes in GRNs.
  • Explore how cooperative binding and bursting protein production influence these dynamics.
  • Assess the relevance of these phenomena to biological systems like lambda-phage lysogeny.

Main Methods:

  • Analysis of stochastic dynamics in gene regulatory models.
  • Comparison of deterministic and stochastic approaches.
  • Focus on toggle switch and exclusive switch models.

Main Results:

  • Extinction and resurrection events create novel stable stochastic attractors.
  • These attractors are absent in deterministic models.
  • Cooperative binding and bursting production modify attractor stability.

Conclusions:

  • Stochastic extinction-resurrection cycles are crucial for understanding GRN dynamics at low molecule numbers.
  • Deterministic models are insufficient for regimes near molecular extinction.
  • These findings may explain the stability of lysogeny in lambda-phage.