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Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
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Intragenic Conflict in Phylogenomic Data Sets.

Stephen A Smith1, Nathanael Walker-Hale2, Joseph F Walker3

  • 1Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI.

Molecular Biology and Evolution
|July 14, 2020
PubMed
Summary

Intragenic conflict, or conflicting evolutionary histories within a single gene, is common in phylogenomic data. This study found conflict varies widely, with alignment errors being a key contributor, necessitating new analysis methods.

Keywords:
intragenic conflictphylogenomicsrecombination

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Area of Science:

  • Evolutionary Biology
  • Genomics
  • Bioinformatics

Background:

  • Phylogenetic analyses typically assume a single evolutionary history per gene.
  • Intragenic conflict, arising from biological processes or errors, can challenge this assumption.
  • The prevalence and sources of intragenic conflict in empirical data are not well understood.

Purpose of the Study:

  • To investigate the extent of well-supported intragenic conflict in large phylogenomic data sets.
  • To identify potential sources of this conflict, such as alignment errors.
  • To advocate for the routine analysis of within-gene phylogenetic signal.

Main Methods:

  • Examination of multiple large phylogenomic data sets from diverse taxa.
  • Application of a rapid and straightforward method for detecting intragenic conflict.
  • Detailed analysis of four exemplar genes and simulation of data under various scenarios.

Main Results:

  • Intragenic conflict was found to be highly variable across data sets, ranging from 1% to over 92% of genes.
  • Alignment error was identified as a significant contributor to intragenic conflict.
  • Unexplained conflict suggests potential biological signal or other error sources.

Conclusions:

  • Intragenic conflict is a prevalent phenomenon in phylogenomic data.
  • Alignment quality is crucial, but other factors also contribute to conflict.
  • Analyzing within-gene phylogenetic signal should be integrated into standard data analysis pipelines and biological exploration.