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Updated: Aug 14, 2026
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Following the Dynamics of Structural Variants in Experimentally Evolved Populations
Published on: February 3, 2023
Quantifying the predictability of evolution by analysis of coalescent rate variation
1MRC Centre for Global Infectious Disease Analysis and the Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Molecular Biology and Evolution
|August 12, 2026
Summary
Evolutionary predictability is enhanced by new coalescent models that track lineage growth. These models use coalescent odds ratios to quantify natural selection, aiding in the analysis of microbial populations like Neisseria gonorrhoeae and SARS-CoV-2.
Area of Science:
- Evolutionary biology
- Population genetics
- Phylogenetics
Background:
- Understanding evolutionary predictability is crucial for tracking lineage diversification.
- Traditional coalescent models often assume neutrality, limiting their ability to capture selection dynamics.
- Variation in lineage coalescence rates can reflect heritable traits influenced by natural selection.
Purpose of the Study:
- To develop novel coalescent models that incorporate heritable variation in coalescence rates.
- To introduce coalescent odds ratios as a metric for lineage growth and natural selection.
- To create statistical methods for analyzing phylogenetic data under relaxed neutrality.
Main Methods:
- Developed a class of coalescent models allowing continuous heritable variation in coalescence rates.
- Defined coalescent odds ratios based on pairwise lineage propensities.
- Implemented statistical techniques for sampling bias correction, hyperparameter calibration, and phylogenetic clustering.
- Utilized simulations to assess method sensitivity and robustness.
Main Results:
- Coalescent odds provide a statistic informative about lineage growth and natural selection strength.
- Methods demonstrated sensitivity to small selective effects and robustness to imbalanced sampling.
- Analysis of Neisseria gonorrhoeae revealed antibiotic resistance patterns linked to high coalescent odds.
- SARS-CoV-2 data analysis showed coalescent odds as a proxy for variant fitness.
Conclusions:
- Coalescent odds offer a powerful tool for inferring evolutionary dynamics and selection pressures.
- The developed methods enhance the predictability of evolution by analyzing phylogenetic relationships.
- These approaches are valuable for studying microbial evolution, including antibiotic resistance and viral variant fitness.
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