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Likelihood-based tree reconstruction on a concatenation of aligned sequence data sets can be statistically

Sebastien Roch1, Mike Steel2

  • 1Department of Mathematics, University of Wisconsin-Madison, Madison, WI, USA.

Theoretical Population Biology
|December 30, 2014
PubMed
Summary

Reconstructing species trees from genomic data is challenging due to gene tree differences and imperfect sequence data. Concatenating gene data and assuming independent evolution leads to statistically inconsistent species tree estimation.

Keywords:
ConsistencyIncomplete lineage sortingMaximum likelihoodPhylogenetic reconstruction

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Area of Science:

  • Phylogenetics
  • Computational Biology
  • Genomics

Background:

  • Reconstructing species trees from genomic data is complex.
  • Gene trees can differ from species trees due to incomplete lineage sorting.
  • Genetic sequence data provides an imperfect estimate of gene tree topology.

Purpose of the Study:

  • To formally demonstrate statistical issues with the concatenation approach in species tree reconstruction.
  • To analyze the impact of ignoring incomplete lineage sorting and sequence estimation errors.
  • To provide theoretical justification for simulation findings.

Main Methods:

  • Formal statistical analysis under the multispecies coalescent model.
  • Maximum likelihood estimation on concatenated sequence data.
  • Investigating the assumption of independent and identically distributed sites on a fixed tree.

Main Results:

  • Concatenation of gene data with incorrect assumptions leads to statistically inconsistent species tree estimation.
  • The multispecies coalescent model highlights the limitations of the concatenation approach.
  • Inconsistency arises when assuming independent site evolution across concatenated genes.

Conclusions:

  • The concatenation approach is statistically inconsistent for species tree reconstruction under the multispecies coalescent model.
  • Ignoring biological processes like incomplete lineage sorting leads to estimation errors.
  • This work provides formal theoretical backing for previous simulation studies and complements existing research.