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Genome-scale approaches to resolving incongruence in molecular phylogenies

Author

Listed:
  • Antonis Rokas

    (University of Wisconsin-Madison)

  • Barry L. Williams

    (University of Wisconsin-Madison)

  • Nicole King

    (University of Wisconsin-Madison)

  • Sean B. Carroll

    (University of Wisconsin-Madison)

Abstract

One of the most pervasive challenges in molecular phylogenetics is the incongruence between phylogenies obtained using different data sets, such as individual genes. To systematically investigate the degree of incongruence, and potential methods for resolving it, we screened the genome sequences of eight yeast species and selected 106 widely distributed orthologous genes for phylogenetic analyses, singly and by concatenation. Our results suggest that data sets consisting of single or a small number of concatenated genes have a significant probability of supporting conflicting topologies. By contrast, analyses of the entire data set of concatenated genes yielded a single, fully resolved species tree with maximum support. Comparable results were obtained with a concatenation of a minimum of 20 genes; substantially more genes than commonly used but a small fraction of any genome. These results have important implications for resolving branches of the tree of life.

Suggested Citation

  • Antonis Rokas & Barry L. Williams & Nicole King & Sean B. Carroll, 2003. "Genome-scale approaches to resolving incongruence in molecular phylogenies," Nature, Nature, vol. 425(6960), pages 798-804, October.
    • Handle: RePEc:nat:nature:v:425:y:2003:i:6960:d:10.1038_nature02053
    DOI: 10.1038/nature02053
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    Citations

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    Cited by:

    1. Wang Yuancheng & Degnan James H, 2011. "Performance of Matrix Representation with Parsimony for Inferring Species from Gene Trees," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 10(1), pages 1-39, May.
    2. Alexei J Drummond & Simon Y W Ho & Matthew J Phillips & Andrew Rambaut, 2006. "Relaxed Phylogenetics and Dating with Confidence," PLOS Biology, Public Library of Science, vol. 4(5), pages 1-1, March.
    3. David Peris & Emily J. Ubbelohde & Meihua Christina Kuang & Jacek Kominek & Quinn K. Langdon & Marie Adams & Justin A. Koshalek & Amanda Beth Hulfachor & Dana A. Opulente & David J. Hall & Katie Hyma , 2023. "Macroevolutionary diversity of traits and genomes in the model yeast genus Saccharomyces," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
    4. Martín Espariz & Federico A Zuljan & Luis Esteban & Christian Magni, 2016. "Taxonomic Identity Resolution of Highly Phylogenetically Related Strains and Selection of Phylogenetic Markers by Using Genome-Scale Methods: The Bacillus pumilus Group Case," PLOS ONE, Public Library of Science, vol. 11(9), pages 1-17, September.
    5. Roch, Sebastien & Steel, Mike, 2015. "Likelihood-based tree reconstruction on a concatenation of aligned sequence data sets can be statistically inconsistent," Theoretical Population Biology, Elsevier, vol. 100(C), pages 56-62.
    6. Sergio Consoli & Jan Korst & Steffen Pauws & Gijs Geleijnse, 2020. "Improved metaheuristics for the quartet method of hierarchical clustering," Journal of Global Optimization, Springer, vol. 78(2), pages 241-270, October.
    7. Haque Md Rejuan & Kubatko Laura, 2024. "A global test of hybrid ancestry from genome-scale data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 23(1), pages 1-18, January.
    8. Rahul Siddharthan & Eric D Siggia & Erik van Nimwegen, 2005. "PhyloGibbs: A Gibbs Sampling Motif Finder That Incorporates Phylogeny," PLOS Computational Biology, Public Library of Science, vol. 1(7), pages 1-23, December.
    9. Siewert Elizabeth A & Kechris Katerina J, 2009. "Prediction of Motifs Based on a Repeated-Measures Model for Integrating Cross-Species Sequence and Expression Data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 8(1), pages 1-36, September.

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