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Updated: Jul 18, 2026
08:57
Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
Published on: August 14, 2018
Bayesian estimation of concordance among gene trees.
Cécile Ané1, Bret Larget, David A Baum
1Department of Statistics, University of Wisconsin, USA. ane@wisc.edu
Molecular Biology and Evolution
|November 11, 2006
Summary
This study introduces a new statistical method to model gene tree concordance using multi-gene sequence data. The approach enhances evolutionary inference by accounting for shared phylogenetic signals across genes.
Area of Science:
- Evolutionary biology
- Phylogenetics
- Bioinformatics
Background:
- Statistical methods for analyzing multigene sequence data are limited.
- Gene trees can have different histories, but the number of distinct topologies is often small.
- Understanding concordance among gene trees is crucial for accurate evolutionary inference.
Purpose of the Study:
- To develop a novel approach for modeling and estimating concordance among gene trees.
- To improve inferences of evolutionary relationships using multigene sequence data.
- To estimate the proportion of genes supporting a specific clade at both sample-wide and genome-wide levels.
Main Methods:
- A one-parameter probability distribution for prior concordance among gene trees.
- A two-stage Markov chain Monte Carlo (MCMC) method.
- Estimating gene-to-tree maps (GTMs) and concordance factors.
Main Results:
- The method provides revised posterior probability distributions for gene trees, incorporating concordance.
- It allows estimation of sample-wide and genome-wide concordance factors with credibility intervals.
- Demonstrated on 106 genes from 8 yeast species.
Conclusions:
- The developed method effectively models and estimates gene tree concordance.
- This approach enhances the accuracy of phylogenetic inference from multigene sequence data.
- It offers a robust framework for analyzing evolutionary processes across the genome.
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