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Clade size distributions under the coalescent diversification model.

Yexuan Song1, Caroline Colijn1, Ailene MacPherson2

  • 1Department of Mathematics, Simon Fraser University, 8888 University Dr., Burnaby, BC, V5A 1S6, Canada.

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Summary

Understanding clade size patterns is crucial for evolutionary biology and epidemiology. This study develops a general method to derive clade size distributions, revealing quantitative differences between models and counterintuitive findings in epidemic growth.

Keywords:
DiversificationEffective population sizeKingman coalescentPhylogenetic clusteringYule

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Area of Science:

  • Evolutionary biology
  • Macroevolution
  • Epidemiology

Background:

  • Characterizing biological diversity patterns is central to evolutionary biology.
  • Understanding clade size expectations (species number vs. age) is key for identifying outliers and testing diversification hypotheses.

Purpose of the Study:

  • Develop a general method for deriving closed-form expressions for clade size distributions under specified diversification models.
  • Apply this method to coalescent and Yule models.
  • Examine transmission cluster size distributions in epidemics.

Main Methods:

  • Developed a general method for deriving closed-form expressions for clade size distributions.
  • Applied the method to constant- and variable-size coalescent models and the Yule model.
  • Utilized the coalescent framework to analyze epidemic transmission cluster sizes.

Main Results:

  • Coalescent and Yule models show qualitatively similar but quantitatively different clade size patterns.
  • Slowly growing epidemics, counterintuitively, are more likely to generate large transmission clusters than rapidly growing ones.
  • Identified quantitative differences in clade size patterns between different diversification models.

Conclusions:

  • The developed method provides a general framework for analyzing clade size distributions.
  • Epidemic growth rate influences transmission cluster size distributions in non-intuitive ways.
  • Quantitative differences between diversification models have implications for evolutionary and epidemiological studies.