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Inferring somatic mutation rates using the stop-enhanced green fluorescent protein mouse
1Department of Medical Genetics, University of Alberta, Edmonton, Alberta T6G 2H7, Canada.
Genetics
|July 3, 2007
Summary
A novel method estimates somatic mutation rates in vivo using a stop-enhanced green fluorescent protein (EGFP) mouse model. This approach accurately detects mutagenicity, revealing a 200-2000 fold increase in mutation rates after exposure to N-ethyl-N-nitrosourea (ENU).
Area of Science:
- Toxicology
- Genetics
- Molecular Biology
Background:
- Estimating somatic mutation rates is crucial for understanding disease development and aging.
- Existing methods may lack sensitivity or precision for in vivo applications.
- Transgenic models offer controlled systems for studying mutation processes.
Purpose of the Study:
- To develop and validate a new method for quantifying in vivo somatic mutation rates.
- To assess the mutagenic potential of N-ethyl-N-nitrosourea (ENU) using this novel assay.
- To establish a sensitive test for detecting mutagenicity.
Main Methods:
- Utilized a stop-enhanced green fluorescent protein (EGFP) transgenic mouse model.
- Administered the mutagen N-ethyl-N-nitrosourea (ENU) or vehicle control to mice.
- Developed a stochastic model for mutation and gene expression, deriving maximum-likelihood estimators.
- Implemented a likelihood-ratio test (LRT) for mutagenicity detection, validated with parametric bootstrap simulations.
Main Results:
- The developed likelihood-ratio test (LRT) demonstrated high significance (alpha < 0.01) for detecting mutagenicity.
- A 95% confidence interval revealed a 200- to 2000-fold increase in mutation rate due to ENU exposure.
- The method effectively quantifies the relative effect of mutagens on somatic mutation rates in vivo.
Conclusions:
- The novel EGFP-based transgenic mouse assay provides a sensitive and quantitative method for assessing in vivo somatic mutation rates.
- This approach is effective in detecting and quantifying the mutagenic effects of chemicals like ENU.
- The developed stochastic model and LRT offer a robust framework for toxicological and genetic research.
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