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Related Experiment Videos

Incorporating gene-specific variation when inferring and evaluating optimal evolutionary tree topologies from

Tae-Kun Seo1, Hirohisa Kishino, Jeffrey L Thorne

  • 1Bioinformatics Research Center, North Carolina State University, Box 7566, Raleigh, NC 27695-7566, USA. seo@iu.a.u-tokyo.ac.jp

Proceedings of the National Academy of Sciences of the United States of America
|March 15, 2005
PubMed
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This study introduces novel criteria for inferring optimal phylogenetic trees from multigene data. These methods effectively account for gene-specific evolutionary features, improving upon simple sequence concatenation for phylogenetic inference.

Area of Science:

  • Genomics
  • Phylogenetics
  • Bioinformatics

Background:

  • Increasing genomic data necessitates advanced methods for phylogenetic inference.
  • Concatenating sequences from multiple genes can overlook crucial gene-specific evolutionary characteristics.
  • Existing methods may not adequately address the complexity of multigene datasets.

Purpose of the Study:

  • To propose and evaluate new criteria for inferring optimal phylogenetic tree topologies from multigene sequence data.
  • To develop methods that account for gene-specific evolutionary features in phylogenetic analysis.
  • To introduce a robust statistical framework for testing the significance of inferred phylogenetic relationships.

Main Methods:

  • Developed two criteria for optimal tree inference: sum of log-likelihoods and mean of log-likelihood ratios per gene.

Related Experiment Videos

  • Proposed a two-stage bootstrap procedure involving resampling genes and alignment columns.
  • Applied these methods within a two-stage hierarchical framework considering gene-specific and site-specific features.

    • Main Results:

    • The proposed criteria offer improved phylogenetic inference by acknowledging gene-specific evolutionary patterns.
    • The two-stage bootstrap procedure effectively accounts for gene-specific evolutionary features, outperforming simple concatenation.
    • The framework is adaptable to statistical tests like the Kishino-Hasegawa and Shimodaira-Hasegawa tests.

    Conclusions:

    • Novel criteria and a two-stage bootstrap method provide a more accurate approach to phylogenetic inference with multigene data.
    • These methods are essential for handling the complexity of gene-specific evolutionary processes in large genomic datasets.
    • The study advances the field of phylogenetics by offering a more nuanced and statistically sound methodology.