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Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
Published on: August 14, 2018
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An improved approximate-Bayesian model-choice method for estimating shared evolutionary history.
1Department of Ecology and Evolutionary Biology, University of Kansas, 1200 Sunnyside Avenue, Lawrence Kansas 66045, USA. joaks1@gmail.com.
BMC Evolutionary Biology
|July 5, 2014
Summary
This study introduces a new Bayesian method to estimate species divergence times using genetic data. The improved method enhances accuracy in understanding evolutionary history and biological diversification.
Area of Science:
- Evolutionary Biology
- Population Genetics
- Phylogeography
Background:
- Understanding biological diversification requires analyzing large-scale evolutionary processes impacting co-distributed populations.
- Temporally clustered divergence times, indicative of such events, can be estimated using genetic data from co-distributed species.
Purpose of the Study:
- Introduce a novel approximate-Bayesian method for comparative phylogeographical model-choice.
- Estimate the temporal distribution of divergences across taxa using multi-locus DNA sequence data.
Main Methods:
- Extended the msBayes model with reparameterized parameters and more flexible priors.
- Implemented a non-parametric Dirichlet-process prior for divergence models.
- Utilized multi-locus DNA sequence data for comparative phylogeography.
Main Results:
- Improved robustness, accuracy, and power in estimating shared evolutionary history.
- Enhanced performance attributed to appropriate priors and a flexible Dirichlet-process prior.
- Reduced tendency for incorrect model estimation with strong support.
Conclusions:
- The new method provides more robust estimates of posterior uncertainty.
- Flexible priors prevent overly penalizing models with intermediate divergence events.
- Facilitates more accurate reconstruction of evolutionary histories and diversification patterns.
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