Journal Article

Systematic Error in Seed Plant Phylogenomics

Bojian Zhong, Oliver Deusch, Vadim V. Goremykin, David Penny, Patrick J. Biggs, Robin A. Atherton, Svetlana V. Nikiforova and Peter James Lockhart

in Genome Biology and Evolution

Published on behalf of Society for Molecular Biology and Evolution

Volume 3, issue , pages 1340-1348
Published in print January 2011 |
Published online October 2011 | e-ISSN: 1759-6653 | DOI:

More Like This

Show all results sharing these subjects:

  • Bioinformatics and Computational Biology
  • Evolutionary Biology
  • Genetics and Genomics


Show Summary Details


Resolving the closest relatives of Gnetales has been an enigmatic problem in seed plant phylogeny. The problem is known to be difficult because of the extent of divergence between this diverse group of gymnosperms and their closest phylogenetic relatives. Here, we investigate the evolutionary properties of conifer chloroplast DNA sequences. To improve taxon sampling of Cupressophyta (non-Pinaceae conifers), we report sequences from three new chloroplast (cp) genomes of Southern Hemisphere conifers. We have applied a site pattern sorting criterion to study compositional heterogeneity, heterotachy, and the fit of conifer chloroplast genome sequences to a general time reversible + G substitution model. We show that non-time reversible properties of aligned sequence positions in the chloroplast genomes of Gnetales mislead phylogenetic reconstruction of these seed plants. When 2,250 of the most varied sites in our concatenated alignment are excluded, phylogenetic analyses favor a close evolutionary relationship between the Gnetales and Pinaceae—the Gnepine hypothesis. Our analytical protocol provides a useful approach for evaluating the robustness of phylogenomic inferences. Our findings highlight the importance of goodness of fit between substitution model and data for understanding seed plant phylogeny.

Keywords: compositional heterogeneity; heterotachy; Gnetales; systematic error

Journal Article.  4512 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology ; Evolutionary Biology ; Genetics and Genomics

Users without a subscription are not able to see the full content. Please, subscribe or login to access all content.