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  • 1SUPA, School of Physics and Astronomy, University of Edinburgh, Edinburgh, EH9 3FD, UK.

Genetics
|May 25, 2023
PubMed
Summary

We developed a robust method to estimate evolutionary parameters from time-series data using the Wright-Fisher model. This approach accurately tracks changes in allele frequencies in biological and cultural evolution, even in challenging scenarios.

Keywords:
Wright–Fisher modeleffective population sizeselection strengthtime-series analysis

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Area of Science:

  • Evolutionary biology
  • Computational biology
  • Quantitative genetics

Background:

  • The Wright-Fisher model is fundamental for understanding allele frequency dynamics driven by selection and genetic drift.
  • Time-series data from biological populations and cultural evolution offer valuable insights into evolutionary processes.
  • Existing methods for parameter estimation in the Wright-Fisher model face limitations, particularly in strong selection or near-extinction scenarios.

Purpose of the Study:

  • To develop a reliable and robust estimation method for evolutionary parameters within the Wright-Fisher model using time-series data.
  • To address limitations of previous approaches in estimating parameters under strong selection and near-extinction.
  • To apply the developed method to real-world biological and cultural evolutionary data.

Main Methods:

  • Construction of a reliable estimation method based on a Beta-with-Spikes approximation to the Wright-Fisher model's allele frequency distribution.
  • Development of a self-contained scheme for parameter estimation within the approximation.
  • Validation using synthetic data, including scenarios with strong selection and near-extinction.

Main Results:

  • The method demonstrates robustness with synthetic data, outperforming previous approaches in challenging evolutionary regimes.
  • Application to baker's yeast (Saccharomyces cerevisiae) allele frequency data revealed significant signals of selection where independently supported.
  • Successfully detected evolutionary parameter changes, exemplified by analyzing a Spanish language spelling reform.

Conclusions:

  • The developed method provides a reliable tool for estimating evolutionary parameters from time-series data in both biological and cultural evolution.
  • The approach enhances the analysis of evolutionary dynamics, particularly in scenarios previously difficult to model.
  • This work offers new possibilities for detecting evolutionary shifts and understanding selection pressures in diverse systems.