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Related Experiment Video

Updated: Oct 7, 2025

Combining Magnetic Sorting of Mother Cells and Fluctuation Tests to Analyze Genome Instability During Mitotic Cell Aging in Saccharomyces cerevisiae

Combining Magnetic Sorting of Mother Cells and Fluctuation Tests to Analyze Genome Instability During Mitotic Cell Aging in Saccharomyces cerevisiae

Published on: October 16, 2014

Selection bias in mutation accumulation.

Lindi M Wahl¹, Deepa Agashe²

¹Mathematics, Western University, London, Canada.

Evolution; International Journal of Organic Evolution

|January 6, 2022

Summary

This summary is machine-generated.

Mutation accumulation (MA) experiments can be biased by selection. This study quanties selection effects and presents a correction method for accurate evolutionary parameter estimation in microbial evolution.

Keywords:

Fitness effects of mutations mathematical model microbial evolution mutation accumulation

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Last Updated: Oct 7, 2025

Combining Magnetic Sorting of Mother Cells and Fluctuation Tests to Analyze Genome Instability During Mitotic Cell Aging in Saccharomyces cerevisiae

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Published on: October 16, 2014

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Measuring Microbial Mutation Rates with the Fluctuation Assay

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Published on: November 28, 2019

Area of Science:

Evolutionary biology
Microbial evolution
Population genetics

Background:

Mutation accumulation (MA) experiments are crucial for studying evolutionary processes.
MA protocols involve microbial population growth between bottlenecks.
The influence of selection during growth phases is often assumed to be negligible.

Purpose of the Study:

To quantify the impact of positive and negative selection in MA studies.
To develop a correction for selection bias in MA experiments.
To improve the accuracy of estimating evolutionary parameters.

Main Methods:

Quantification of selection effects in MA experiments.
Development of a bias correction method for beneficial and deleterious mutations.
Use of simulated MA experiments to validate the correction.
Application of the correction to experimental data.

Main Results:

Selective effects significantly bias the distribution of fitness effects (DFE) and mutation rates in MA studies.
The proposed correction method accurately reconstructs the true DFE.
Positive selection in microbial MA experiments is not negligible and can be corrected.

Conclusions:

Selection bias can substantially affect MA experiment results.
A novel correction method allows for more accurate estimation of evolutionary parameters.
This work refines MA experimental protocols for a better understanding of evolution.