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Related Experiment Videos

Subtree power analysis and species selection for comparative genomics.

Jon D McAuliffe1, Michael I Jordan, Lior Pachter

  • 1Department of Statistics and Mathematics, University of California, Berkeley, CA 94720, USA.

Proceedings of the National Academy of Sciences of the United States of America
|May 25, 2005
PubMed
Summary

Selecting the right species for genome sequencing is key to finding regions under selection. Our study shows that the most evolutionarily diverged species are not always the best choice for detecting conserved sites.

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Area of Science:

  • Comparative genomics
  • Evolutionary biology
  • Bioinformatics

Background:

  • Sequence comparison across organisms helps identify regions under selection.
  • Genome sequencing is resource-intensive, necessitating strategic species selection.
  • Prioritization requires considering biological scope and optimal species for functional element detection.

Purpose of the Study:

  • To introduce a statistical framework for optimal species subset selection in comparative genomics.
  • To maximize the power for detecting conserved sites across selected species.
  • To guide genome sequencing prioritization for evolutionary studies.

Main Methods:

  • Developed a statistical framework for optimal species subset selection.
  • Analyzed a phylogenetic star topology to theoretically assess subset selection.

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  • Empirically tested the framework using a study of vertebrate species.

    • Main Results:

    • Theoretically demonstrated that the optimal species subset is not necessarily the most evolutionarily diverged.
    • Empirically validated this finding in a vertebrate species study.
    • Identified marsupials as highly valuable candidates for genome sequencing.

    Conclusions:

    • Optimal species selection for comparative genomics requires a nuanced approach beyond evolutionary divergence.
    • The proposed statistical framework provides a robust method for prioritizing genome sequencing.
    • Marsupials represent a promising group for future sequencing efforts to detect conserved functional elements.