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Gene Tree Estimation Error with Ultraconserved Elements: An Empirical Study on Pseudapis Bees.

Silas Bossert1,2,3, Elizabeth A Murray2,3, Alain Pauly4

  • 1Department of Entomology, Cornell University, Comstock Hall, Ithaca, NY 14853, USA.

Systematic Biology
|December 28, 2020
PubMed
Summary
This summary is machine-generated.

Gene tree estimation methods significantly impact species phylogenies in phylogenomics. IQ-Tree with automated model selection yielded the most accurate species trees, outperforming other programs like MrBayes and RAxML when using coalescent-based summary methods.

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Area of Science:

  • Phylogenomics
  • Evolutionary Biology
  • Bioinformatics

Background:

  • Phylogenomic analyses commonly use two-step coalescent methods to infer species phylogenies from gene trees.
  • Gene tree estimation error, stemming from biological and analytical factors, can compromise downstream species tree accuracy.
  • The impact of different gene tree inference methods on empirical data remains understudied.

Purpose of the Study:

  • To evaluate the influence of gene tree inference methods on species tree accuracy within a phylogenomic framework.
  • To compare the performance of four widely used gene tree inference programs (PhyloBayes, MrBayes, IQ-Tree, RAxML) using empirical data from bees.
  • To provide practical recommendations for gene tree estimation in summary-based phylogenomic analyses.

Main Methods:

  • Phylogenetic analysis of over 800 ultraconserved elements from the bee subfamily Nomiinae, focusing on the genus Pseudapis.
  • Gene tree inference using PhyloBayes, MrBayes, IQ-Tree, and RAxML under various model-selection criteria.
  • Assessment of gene tree topological accuracy and branch length (stemminess) and summarization using ASTRAL to infer species phylogenies.

Main Results:

  • Bayesian methods (MrBayes, PhyloBayes) produced more concordant gene trees with better stemminess values compared to RAxML.
  • IQ-Tree, when utilizing automated model selection (ModelFinder), generated ASTRAL summary trees that consistently reflected the most accurate species phylogeny.
  • Gene tree estimation method choice significantly affects species tree reconstruction, with IQ-Tree demonstrating superior performance in this study.

Conclusions:

  • The selection of gene tree inference software and model-selection strategy is critical for accurate species tree reconstruction in phylogenomics.
  • Automated model selection, as implemented in IQ-Tree's ModelFinder, is recommended for robust gene tree estimation when using coalescent-based summary methods like ASTRAL.
  • This study establishes the first phylogeny-informed classification for the genus Pseudapis and highlights the importance of accurate phylogenetics for taxonomic revisions.