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Detecting and overcoming systematic errors in genome-scale phylogenies.

Naiara Rodríguez-Ezpeleta1, Henner Brinkmann, Béatrice Roure

  • 1Canadian Institute for Advanced Research, Centre Robert Cedergren, Département de Biochimie, Université de Montréal, 2900 Boulevard Edouard-Montpetit, Montréal, Québec, H3T 1J4, Canada.

Systematic Biology
|May 24, 2007
PubMed
Summary
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Genome-scale phylogenetics can be misled by systematic errors, causing conflicting signals. This study identifies methods like removing fast-evolving sites and using site-heterogeneous models to improve the accuracy of eukaryotic phylogenetic trees.

Area of Science:

  • Evolutionary biology
  • Bioinformatics
  • Phylogenetics

Background:

  • Genome-scale data enhance phylogenetic inference by reducing stochastic errors.
  • However, systematic errors from model violations can lead to inaccurate phylogenies.
  • Conflicting signals in large datasets can reduce statistical support for phylogenetic branches.

Purpose of the Study:

  • To investigate the impact of systematic errors on eukaryotic phylogeny resolution.
  • To identify methods for mitigating systematic errors and improving phylogenetic accuracy.
  • To provide guidelines for robust genome-scale phylogenetic analyses.

Main Methods:

  • Analysis of 143 nuclear-encoded proteins from 37 eukaryotic species.
  • Creation of data subsets with varied taxon sampling to reveal conflicting signals.

Related Experiment Videos

  • Application of methods including removal of fast-evolving sites, amino acid recoding, and site-heterogeneous mixture models (CAT).

    • Main Results:

    • Data subsets with altered taxon sampling produced strongly supported but conflicting phylogenetic trees.
    • Conflicting phylogenetic and non-phylogenetic signals were confirmed in the original dataset.
    • Removing fast-evolving sites, recoding amino acids, and using CAT models effectively increased the phylogenetic signal-to-noise ratio.

    Conclusions:

    • Systematic errors significantly impact genome-scale phylogenetic inference, leading to artefacts.
    • Specific methods can effectively reduce systematic errors and enhance phylogenetic resolution.
    • Guidelines are proposed for detecting and overcoming phylogenetic artefacts in large-scale analyses.