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Updated: Jun 26, 2026
08:57
Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
Published on: August 14, 2018
How well do evolutionary trees describe genetic relationships among populations?
1Department of Ecology, Montana State University, Lewis Hall, Bozeman, MT 59717, USA. skalinowski@montana.edu
Heredity
|January 29, 2009
Summary
Bifurcating evolutionary trees accurately model hierarchical population splits but distort relationships in continuous gene flow models. The neighbor-joining (NJ) algorithm better represents diverse evolutionary histories compared to UPGMA.
Area of Science:
- Population Genetics
- Evolutionary Biology
- Bioinformatics
Background:
- Bifurcating evolutionary trees are standard for depicting population genetic relationships.
- Hierarchical models may not capture non-hierarchical evolutionary patterns like gene flow.
- Quantifying tree distortion is crucial for accurate evolutionary inference.
Purpose of the Study:
- To evaluate the accuracy of bifurcating tree methods (UPGMA and NJ) in representing population genetic structure under different evolutionary models.
- To quantify the distortion introduced by these tree-building methods when applied to non-hierarchical population histories.
- To identify the most robust tree-building algorithm for diverse evolutionary scenarios.
Main Methods:
- Computer simulations were employed to generate genetic distance data for populations under three distinct evolutionary models: hierarchical fragmentation, linear stepping-stone, and 2D stepping-stone gene flow.
- The unweighted pair group method with arithmetic mean (UPGMA) and neighbor-joining (NJ) algorithms were used to construct bifurcating trees from simulated genetic distance matrices.
- The goodness-of-fit was assessed using R(2), representing the proportion of variation in genetic distances explained by each tree.
Main Results:
- The UPGMA algorithm accurately depicted population structure for the hierarchical fragmentation model.
- UPGMA severely distorted genetic relationships under both linear and 2D stepping-stone models, indicating poor fit for continuous gene flow.
- The NJ algorithm demonstrated greater robustness, accurately representing population structure in the hierarchical model and performing well with the linear stepping-stone model.
Conclusions:
- Bifurcating trees, particularly UPGMA, are reliable for populations with a history of fragmentation but can be misleading for populations with continuous gene flow.
- The neighbor-joining algorithm offers a more versatile approach, better accommodating a wider range of population evolutionary histories.
- Software for calculating tree distortion (R(2)) is available, facilitating more accurate assessments of population genetic structure.
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