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Updated: May 16, 2026
12:02
Molecular Evolution of the Tre Recombinase
Published on: May 29, 2008
An exactly solvable model of random site-specific recombinations
1Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA. ywei@cshl.edu
Bulletin of Mathematical Biology
|November 16, 2012
Summary
This study models site-specific recombination (SSR) events, revealing how random inversions and excisions create genomic diversity. We found all possible sequences are equally probable after many inversions, with calculable probabilities over time.
Area of Science:
- Genetics
- Molecular Biology
- Computational Biology
Background:
- Site-specific recombination (SSR) systems like Cre-lox are crucial genetic tools.
- Clustered recombination sites can generate significant genomic diversity within cells.
- This diversity is vital for applications like neuronal connectomics (e.g., Brainbow).
Purpose of the Study:
- To develop an exactly solvable statistical model for SSR on clustered recombination sites.
- To analyze the genomic diversity generated by inversions and excisions.
- To provide experimentally testable predictions for SSR outcomes.
Main Methods:
- Developed a statistical model for site-specific recombination (SSR).
- Analyzed sequence generation through inversions and excisions.
- Derived the ergodicity theorem for inversion outcomes.
- Calculated the number of possible generated sequences.
- Modeled sequence probability over time with infrequent excisions.
Main Results:
- The ergodicity theorem describes all sequences producible by multiple inversions.
- The number of distinct sequences generated from an initial sequence is calculable and experimentally verifiable.
- With sufficient random inversions, all accessible sequences are generated with equal probability.
- Derived equations predict sequence probability over time, especially when excisions are rare.
Conclusions:
- The statistical model accurately describes genomic diversity generated by SSR.
- The findings offer testable hypotheses for understanding genetic diversity in biological systems.
- This work provides a quantitative framework for analyzing complex genomic rearrangements.
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